Holocene climate evolution in NW Morocco as recorded in aragonitic speleothems:

Significance of the North Atlantic Oscillation

Kef Chaara (2011)

Dissertationzur Erlangung des akademischen Grades eines

Doktors der Naturwissenschaftenan der Fakultät für Geowissenschaften der Ruhr-Universität Bochum

vorgelegt von

Jasper Wassenburg

geboren am 04.07.1982 in Leiden (Niederlande)

Erklärung

Ich erkläre hiermit an Eides statt, dass ich die vorliegende Arbeit selbstständig angefertigt sowie die benutzten Quellen und Hilfsmittel vollständig angegeben habe. Soweit Zitate oder Abbildungen an-derer Werke im Wortlaut oder dem Sinn nach entnommen wurden, wurden diese in jedem Einzelfall als Entlehnung kenntlich gemacht. Die vorliegende Dissertation wurde in dieser oder ähnlicher Form bei keiner anderen Fakultät oder Hochschule zur Prüfung vorgelegt.

Bochum, Januar 2013

Jasper Wassenburg

I

ABSTRACT

At present, future climate development under influence of anthropogenic greenhouse gasses like CO2 and CH4 remains difficult to predict. Therefore, it is essential to assess the natural climate variability beyond the period where instrumental weather data existed (i.e., the last 11.500 years: The Holocene). This is the only possibility to place recent climate change into its context. The North Atlantic/European winter climate is affected by the North Atlantic Oscillation (NAO), which represents the dominating sea level pressure mode of the North Atlantic/European area. Especially the western Mediterranean Realm (i.e. Iberian Peninsula and Morocco) is sensitive to the NAO because this region receives most of its rainfall during the winter season, whereas summers are very dry. The evolution of the NAO during the Holocene is, however, still largely unknown.

In this thesis, the main aim was to reconstruct the Holocene climate for northwest Morocco by using speleothems (cave carbonate deposits) and to place this reconstruction in the context of earlier published climate records from the North Atlantic area. A major advantage of speleothems is that they are suitable for radiometric dating (U-Th) as they act as “closed systems”. The accuracy and precision of this technique depends largely on the U concentration of the samples. In calcite speleothems, this is often a limiting factor, aragonite speleothems, however, do have high U concentrations, which is related to their different crystallographic system. Aragonite speleothems are still underexplored for their applicability as climate archives, additionally various factors may be important for inducing aragonite precipitation in cave environments. Therefore, a large part of this thesis has focused on the reasons for aragonite precipitation in cave environments and on the (climate related) processes which affect their trace element concentrations.

In two caves in the Middle Atlas Mountain range of Morocco, the Grotte Prison de Chien and Grotte de Piste, Pleistocene and Holocene speleothems with stratigraphical transitions from calcite to aragonite and from aragonite to calcite were encountered. By analyzing the stratigraphical transitions at 100 µm resolution for carbon and oxygen isotopes and trace element concentrations (Mg, Sr, Ba, P, Y, U, Pb, Al, Ti, Th), it was possible to demonstrate that Prior Calcite Precipitation (PCP: the precipitation of calcite within the karst aquifer or at the cave ceiling from the stalagmite precipitating fluid) was a major process inducing the precipitation of aragonite by increasing the drip water Mg/Ca ratio and decreasing the drip water CaCO3 saturation state. Once a threshold (a certain drip water Mg/Ca ratio and CaCO3 saturation state) was reached, aragonite precipitation started to occur at the stalagmite surface and potentially in the karst aquifer. In that case PCP was joined by Prior Aragonite Precipitation (PAP, a process similar to PCP, but then involving aragonite precipitation). Here PCP occurred as a consequence of increasing aridity and reached a maximum just before the transition, therefore the transitions from calcite to aragonite were climatically forced.

The interpretation of trace element concentrations in calcite speleothems cannot be simply extrapolated to aragonite speleothems due to their different crystallographic systems. Aragonite preferably takes up Sr over Ca but prefers Ca over Mg, whereas calcite prefers Ca over Sr and Mg. Therefore enhanced PAP decreases the drip water Sr/Ca ratio but increases the drip water Mg/Ca ratio, whereas enhanced PCP would increase both the drip water Sr/Ca and Mg/Ca ratios. Analysis of Mg, Sr and Ba concentrations from cave drip waters from nine visits to Grotte de Piste equally distributed

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over a two year interval, combined with a comparison between a Sr record from an actively growing aragonite stalagmite and a tree-ring based drought reconstruction has demonstrated for the first time the existence of PAP. The Sr record showed that the Medieval Warm Period was dry compared to the Little Ice Age confirming the tree ring based drought reconstruction. The application of trace element concentrations (Sr) in aragonite speleothems may thus provide useful climate information. A detailed comparison between the Mg and Sr record, however, indicated that the PAP dominated period (the dry Medieval Warm Period) was interrupted by short intervals when PCP dominated. This has a large effect on the interpretation of Sr. Strontium should thus always be combined with Mg in order to identify whether PCP or PAP is the dominating process.

Additionally a Holocene oxygen isotope record from an aragonite stalagmite from Grotte de Piste was constructed and shown to be related to rainfall. This record was compared to Holocene climate reconstructions from NAO sensitive areas. From these comparisons it was possible to show that the NAO induced a negative correlation in terms of rainfall between Western Germany and northwest Morocco for most of the Middle and Late Holocene. In the Early Holocene, a positive correlation existed. Climate modeling data demonstrated that this was caused by a different configuration of the typical NAO sea level pressure zones related to a non linear climate response to the presence and melting of the Laurentide Ice Sheet.

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KURZFASSUNG

Derzeit ist es schwierig die kommende klimatische Entwicklung unter dem Einfluss von anthropogenen Treibhausgasen wie CO2 und CH4 vorherzusagen. Daher ist es notwendig die natürlichen klimatischen Veränderungen, die über die Periode der Wetteraufzeichnungen hinausgehen, abzuschätzen (zum Beispiel die letzten 11.500 Jahre: das Holozän). Dies ist die einzige Möglichkeit die rezenten Klimaveränderungen in ihren Kontext zu setzten. Das nordatlantische/ europäische Klima des Winters steht unter dem Einfluss der Nordatlantischen Oszillation (NAO). Die NAO ist das dominierende atmosphärische Drucksystem des Nordatlantiks und Europas. Besonders der westliche Mittelmeerraum (Iberische Halbinsel und Marokko) wird davon beeinflusst, da diese Region generell durch humide Winter und aride Sommer gekennzeichnet ist.

Das Hauptziel dieser Arbeit ist es, das Holozäne Klima von Nordwest-Marokko anhand von Speläothemen (Karbonatablagerungen aus Höhlen) zu rekonstruieren. Diese Rekonstruktion wird mit bereits veröffentlichten Klimaarchiven des Nordatlantiks in einen größeren Kontext gesetzt. Speläotheme fungieren als „geschlossenes System“ und bieten somit einen großen Vorteil, da sie besonders geeignet sind für radiometrische Datierung (U-Th). Die Genauigkeit und Präzision dieser Technik basiert hauptsächlich auf den Urankonzentrationen der Proben. Während aragonitische Speläotheme eine hohe Urankonzentration aufweisen, ist dies in kalzitischen Speläothemen häufig ein limitierender Faktor. Von entscheidender Bedeutung sind dabei die unterschiedlichen Kristallsysteme von Kalzit und Aragonit. Aragonitische Speläotheme sind immer noch relativ wenig erforscht vor allem in Bezug auf ihre Verwendung als Klimaarchive. Für den komplexen Prozess der Aragonitausfällung in Höhlen spielen verschiedene Faktoren eine wichtige Rolle. Aus diesem Grund befasst sich ein großer Teil dieser Arbeit mit den Ursachen der Aragonitausfällung in Höhlensystemen. Weiterhin werden (klimabezogene) Prozesse untersucht, die Spurenelement-konzentrationen in aragonitischen Speläothemen beeinflussen.

Aus zwei Höhlen des mittleren Atlasgebirge in Marokko, der Grotte Prison de Chien und der Grotte de Piste, wurden zwei Pleistozäner und zwei Holozäner Speläothem entnommen. Diese Speläotheme weisen einen stratigraphischen und lateralen Übergang von Kalzit zu Aragonit und vice versa auf. Durch hochauflösende Analysen (100µm) dieses stratigraphischen Übergangs mittels Kohlenstoff-, Sauerstoffisotopie und den Spurenelementkonzentrationen (Mg, Sr, Ba, P, Y, U, Pb, Al, Ti, Th) war es möglich Prior Calcite Precipitation (PCP: die Ausfällung von Calcit aus dem Fällungsfluid des Stalagmits im Karstgrundwasserleiter oder an der Höhlendecke) als Hauptprozess für das Herbeiführen der Aragonitausfällung zu identifizieren. Prior Calcite Precipitation (PCP) führt generell zu einer Erhöhung des Mg/Ca Tropfwasserverhältnisses und einer Verringerung des CaCO3 Tropfwasser-Sättigungsgrades. Dies hat auch zur Folge, dass Pior Aragonite Precipitation (PAP, ein ähnlicher Prozess wie PCP, der aber Aragonitausfällung zur Folge hat) statt PCP auftritt, wenn die Grenze zur Aragonitausfällung erreicht ist. In den hier untersuchten Speläothemen trat Prior Calcite Precipitation als eine Konsequenz von zunehmender Trockenheit auf und erreichte genau vor dem Übergang zur Aragonitausfällung sein Maximum. Als Schlussfolgerung dieses Prozesses zeigt sich, dass der Übergang von Kalzit zu Aragonit klimatisch gesteuert ist.

Die Interpretation der Spurenelementkonzentrationen von kalzitischen Speläothemen kann

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nicht grundsätzlich für aragonitische Speläotheme übernommen werden, da ihre Kristallsysteme unterschiedlich sind. Denn Aragonit nimmt vorzugsweise Strontium statt Kalzium auf aber bevorzugt Kalzium vor Magnesium. Im Gegensatz dazu bevorzugt Kalzit Kalzium statt Strontium und Magnesium. Während gesteigerte Prior Calcite Precipitation (PCP) sowohl das Sr/Ca Verhältnis als auch das Mg/Ca Verhältnis erhöht, verringert eine erhöhte Prior Aragonite Precipitation das Sr/Ca Tropfwasserverhältnis und steigert das Mg/Ca Tropfwasserverhältnis.

Grundlage der Analysen von Mg, Sr und Barium Konzentrationen von Höhlentropfwässern waren neun Exkursionen in die Grotte de Piste, die in einem Zeitraum von zwei Jahren durchgeführt wurden. Die Ergebnisse der Analysen wurden mit einem Vergleich kombiniert. Dieser Vergleich umfasst einen Sr- Rekord eines aktiven (wachsenden) aragonitischen Stalagmiten und einer auf Baumringen basierenden Rekonstruktion von Dürreperioden. Diese Kombination hat zum ersten Mal die Existenz der PAP bewiesen. Der Sr-Rekord zeigte, dass die Mittelalterliche Warmzeit im Gegensatz zur Kleinen Eiszeit trocken war, was durch die Baumringrekonstruktion bestätigt wurde. Die Anwendung der Strontiumelementkonzentration in aragonitischen Speläothemen liefert nützliche Informationen fürs Klima. Jedoch zeigt ein detaillierter Vergleich zwischen dem Mg- und Sr-Rekord, dass die PAP dominierte Periode (die trockene Mittelalterliche Warmzeit) von kurzen Intervallen unterbrochen wurden, in denen dann PCP vorherrschte. Dies hat einen großen Effekt auf die Interpretation von Strontium. Die Analyse der Strontiumelementkonzentrationen sollte also immer mit der Magnesiumelementkonzentration kombiniert werden, um herauszufinden ob PCP oder PAP der dominierende Prozess ist.

Die Sauerstoffisotopie wurde an einem Holozänen aragonitischen Stalagmiten der Grotte de Piste gemessen. Dabei wurde gezeigt, dass diese mit dem Niederschlagssignal in Beziehung steht. Dieser Sauerstoffisotopen-Rekord wurde mit verschiedenen Klimaarchiven aus dem Holozän verglichen. Die Klimaarchive befinden sich in Gebiete, die von NAO beeinflusst wurden. Durch diesen Vergleich war es möglich zu zeigen, dass die NAO eine negative Korrelation in Bezug auf Niederschlag zwischen Westdeutschland und Nordwest-Marokko während des Mittleren und späten Holozän hervorrief. Während im Frühen Holozän eine positive Korrelation existierte. Die Auswertung der verwendeten Klimamodelle zeigte, dass die positive Korrelation durch die unterschiedlichen Konfigurationen der NAO Meeresoberflächen-Druckgebiete verursacht wurde. Die unterschiedliche Konfiguration der NAO Meeresoberflächen-Druckgebiete ist eine nicht-linearen Reaktion auf Klima-veränderungen. Weiterhin steht diese Korrelation im Zusammenhang mit der Präsenz und dem Schmelzen des Laurentidischen Eisschilds.

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ACKNOWLEDGEMENTS:

First of all, I would like to thank you Adrian for your supervision and many many funny moments. I will never forget my first cave fieldtrip to Morocco with you and Herr Richter. Especially Grotte Mouilier was interesting, because Herr Richter started to explain you about „CO2 höhle“, where I disappeared with Houcine and Tarik for at least 1.5 hour and you started to get worried whether you had lost your PhD student. And then there was the unforgettable trip to Argentina. I would really like to thank you that I could always talk to you whenever I had problems making decisions and that you always kept the overview on the project. I’m glad that you compiled your „Jasper manual“, otherwise it would not have worked out so well! I really learned a lot from you, THANKS!.

I would also like to give a special thanks to Herr Richter, who was always there as well. You organized so many nice cave trips in Germany (although B7 cave is still missing…). It was really great to have you as a supervisor especially concerning thin sections from speleothems. Also I enjoyed Krakau very much, I even got my first (and only) poster award on a poster without data! I hope to drink some more beers with you in the future!

I would like to thank Conny and Sabine for being the best (and funny) secretaries we could wish for, even if it wasn’t related to work you were both there to help me out. Our department really needs you!

I also like to acknowledge all the people working in the Bochum labs. Without them it would never have been possible to create the amount of data we did: Ulrike S, Beate, Rolf, Noushin, Kathrin, H.-J. Bernard, Herr Reinecke, Matthias, Andreas. Special thanks go to Dieter who always had good ideas for sampling approaches and for taking nice pictures from my stalagmites. Furthermore thank you Andrea N. for the many discussions on calcite, aragonite and their trace element concentrations.

Many thanks go to my direct colleagues which whom I had countless nice parties, Christmas markets, bowling, barbecues and beergarten moments, without you Bochum would have been a lot less interesting: Ariane, Susanne, Anthony, Francois, Nico, Stefan, Juan, Anna, Sylvia, Stéphane, Ulli, René, Mohammad, Mohammad, Mélanie T., Mélodie, Philip, Dana, Sabine, Baris, Christian, Niels. Special thanks goes to Sabine my office “mate”. Adrian could not have placed two persons in one room who are more different then the two of us in terms of organization! I really enjoyed it to share my office with you.

I would like to acknowledge the work that has been done by my HIWI’s and bachelor students: Ann-Christine, Manuela and Christian K.

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I had many people joining me on the numerous (I think 10!) fieldtrips to Morocco. Especially Melanie, you were essential to make the fieldtrips a success, even though my German hampered the communication now and then… The overall atmosphere created by the Morocco group has truly been fantastic, I always felt completely relaxed, and still we got the work done. Houcine and Tarik you were both really reliable, thanks for the many truly great moments in the field. I would really like to give a very special thanks to the Berber family near Grotte de Piste, who where extremely nice, friendly and prepared so many nice dinners for us. Additionaly I would like to thank Houcine and Mileud for taking rain water samples every day it had rained and not to forget Mélanie T., Nico, Christian R. and Lea. Last but definitely not least Abdellah and his family, I’m really happy that I got to know you! I would like to give the people that I collaborated with, big thanks: Denis, Andrea S., Klaus Peter, Jan F., Jan E., Stephan D., Jens F., Gerrit Lohmann, Wei Wei, Lea, Dana, Abdellah.

Additionaly I would like to thank Dominik Fleitmann, Christoph Spötl and Andrea Borsato for the time that they were willing to spent with me for very helpful and essential discussions on several topics related to my PhD.

Finally (and I’ll do this one in Dutch) en zeker niet de minste, wil ik graag mijn vader, zus, Jacek, oma’s (opa’s in nagedachtenis) en vrienden in Nederland bedanken voor hun ondersteuning. Zeer speciale gedachten gaan naar mijn moeder (Ida) die inmiddels al meer dan acht jaar geleden is overleden. Bedankt dat je altijd in mij hebt geloofd, ik mis je.

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TABLE OF CONTENTS

ABSTRACT I

KURZFASSUNG V

ACKNOWLEDGEMENTS: IX

1. INTRODUCTION 11.1. Scope and aims 11.2. Speleothems as climate archives 3

1.2.1 Speleothem formation 31.2.2. U-Th dating 41.2.3. Understanding speleothem proxies 51.2.4. Calcite versus aragonite speleothems 5

1.3. Climate forcing mechanisms 61.3.1. External forcing mechanisms 71.3.2. Feedback mechanisms 8

1.4. Morocco: Physiography and present day climate 111.5. North Atlantic Oscillation 111.6. Holocene Moroccan Climate 131.7. Research questions, approach and general outline 14

1.7.1. General outline 15References 16

2. GEOLOGICAL SETTING 272.1. Grotte Prison de Chien 272.2. Grotte de Piste 27References 28

3. MATERIALS AND METHODS 313.1. Petrography 313.2. Trace element concentrations soil 313.3. Dating and age depth modeling 323.4. Carbon and oxygen isotopes 333.5. Trace element analysis CaCO3 33

3.5.1. LA-ICP-MS 333.5.2. ICP-OES 34

3.6. Cave monitoring 353.7. Statistical treatment of the data 35References 36

4. CLIMATE AND CAVE CONTROL ON PLEISTOCENE/HOLOCENE CALCITE-TO-ARAGONITE TRANSITIONS IN SPELEOTHEMS FROM MOROCCO: ELEMENTAL AND ISOTOPIC EVIDENCE 39

Abstract 39

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4.1. Introduction 394.2. Case setting 41

4.2.1. Present day climate 414.2.2. Cave parameters 41

4.3. Materials and methods 434.4. Results 48

4.4.1. 230Th/U-dating 484.4.2. Soil mineralogy and trace element composition 484.4.3. Stalagmites HK1 and HK3 (Grotte Prison de Chien) 494.4.4. Stalagmite GP2 (Grotte de Piste) 58

4.5. Interpretation and discussion 594.5.1. Aragonite diagenesis 594.5.2. Climate forcing of alternating calcite and aragonite precipitation? 634.5.3. Interpretation of trace element abundances in speleothem aragonite 72

4.6. Conclusions 74Acknowledgements 75References 75SUPPLEMENTARY MATERIAL CHAPTER 4 83

Methods 83Reproducibility of trace element results 87Effects on trace element concentrations of 0-10% primary calcite in aragonite 88

5. MEDIEVAL PRECIPITATION VARIABILITY IN MOROCCO REFLECTED BY SPELEOTHEM AND TREE-RING PROXIES* 91

Abstract 915.1. Introduction 915.2. Case setting 93

5.2.1. Present day climate of the Middle Atlas 935.2.2 Cave setting 94

5.3. Material and methods 955.4. Results 97

5.4.1. Cave monitoring 975.4.2. Age-depth model 985.4.3. Petrography 995.4.4. Geochemistry 995.4.5. Updated tree-ring self-calibrating Palmer Drought Severity Index reconstruction 102

5.5. Discussion and climatic interpretation 1025.5.1. Prior Calcite Precipitation versus Prior Aragonite Precipitation 1025.5.2. Interpretation of Strontium data from stalagmite GP5 1065.5.3. Climatic implications 109

5.6. Conclusions 110Acknowledgements 111References 111SUPPLEMENTARY MATERIAL CHAPTER 5 119

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Methods 119Supplementary figures 119References 121

6. THE NORTH ATLANTIC OSCILLATION: EVOLUTION THROUGHOUT THE HOLOCENE* 123

Abstract 1236.1. Introduction 1236.2. Results and interpretation* 1256.3. Discussion and conclusions 130Acknowledgements 139References 139SUPPLEMENTARY MATERIAL CHAPTER 6 145

Methods 145Supplementary figures 147References 150

7. SYNTHESIS AND OUTLOOK 1537.1. Calcite versus aragonite 153

7.1.1. Presence of aragonite in caves: An indication for climate aridity? 1537.1.2. Interpretation of trace element variations in aragonite speleothems 155

7.2. The evolution of the North Atlantic Oscillation through the Holocene 1567.3. Outlook 157References 158

CURRICULUM VITAE 161

APPENDIX 163

Introduction

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Fig. 1.1. Atmospheric concentration of greenhouse gasses for the last 20,000 years and its radiative forcing (Jansen et al. 2007 and references therein). (A) CO2. (B) N2O. (C) CH4. (D) rate of change.

1. INTRODUCTION

1.1. Scope and aims

The term “climate” can be defined as the average weather conditions for a specific region for a period of typically 30 years (Le Treut et al., 2007). Climate change is often associated with the anthropogenic increase in atmospheric greenhouse gas concentrations (CO2, CH4 and N2O), of which CO2 has the largest radiative forcing (Forster et al., 2007). Mean pre-industrial CO2 concentrations during the Holocene (i.e. 11,500 years BP* until present) were approximately 280 ppm as based on air bubbles trapped in ice (Monnin et al., 2004). Since 1750 AD this increased exponentially to 380 ppm today (Fig. 1.1; Jansen et al., 2007). The observed warming trend during the last century (Mann and Jones, 2003; Mann et al., 2008) has at the very least partly been assigned to this increase in atmospheric CO2 (Hansen et al., 1981). Possible impacts of warming (among others) are sea level rise due to increasing sea surface temperatures and melting of the ice sheets (Bindoff et al., 2007; Carlson et al., 2008), a freshening of the surface ocean water potentially affecting the formation of

deep water in the North Atlantic and therefore the strength of the thermohaline circulation (THC; Alley and Agustsdottir, 2005; Bamberg et al., 2010; see section 1.3.2; Fig. 1.6 for an explanation) and increasing ocean bottom water temperatures and surface temperatures, which in turn could destabilize

Chapter 1

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CH4 hydrates (i.e., frozen CH4) stored beneath the ocean floor and in permafrost areas (Archer, 2007) amplifying the greenhouse effect. However, in order to be able to predict the impact of increasing greenhouse gas concentrations it is essential to assess and understand Holocene natural climate variability, especially on a regional scale. Therefore:

The first aim of this thesis is to reconstruct the Holocene climate of NW Morocco by using speleothem archive data and to place the climate reconstruction in a climate dynamical context with respect to earlier published reconstructions from the North Atlantic area.

In geosciences, climate can be reconstructed by using many different types of climate archives. In these archives climate proxy data is reflecting certain processes which are controlled by climate parameters like temperature or precipitation amounts. Changes in proxy data with time (i.e., along the direction of growth of a coral) may thus reflect a change in a climate parameter. However, each type of archive has its strengths and weaknesses depending on the possibilities for absolute dating, achievable resolution (seasonal up to 1000’s of years), potential time interval, which can be reconstructed, possibility for multi-proxy approaches, the understanding of the processes behind the proxies and its geographical distribution. A few examples of continental climate archives are: ice cores, which can go back in time up to 800,000 years (i.e. EPICA Dome C ice core from Antarctica; Lambert et al., 2008), but they are restricted to cold and stable areas (Rasmussen et al., 2007). Tree chronologies, which have annual resolution and typically represent a specific growth season depending on their geographic location (i.e., tree rings and late wood density are able to record summer temperatures or winter precipitation; Esper et al., 2007; 2012). Lake records, which may provide information on paleo-vegetation through pollen assemblages and may be used to reconstruct surface temperature and precipitation from different seasons (Cheddadi et al., 1998; Dormoy et al., 2009; Magny et al., 2011). Many more climate archives and proxies exist, which have not been listed above for sake of brevity. However, speleothems (i.e. continental cave carbonate (CaCO3) deposits) are especially interesting because: they form over extensive time periods (hundreds of 1000’s of years), can be accurately dated with the U-Th dating technique (Cheng et al., 1998; Dorale et al., 2004), may provide up to seasonal resolution records (Johnson et al., 2006; Borsato et al., 2007), have a large array of climate proxies (Gascoyne, 1992) and have a wide geographical distribution. The understanding of processes, which affect the climate proxies in speleothems has tremendously increased in recent decades (Gascoyne, 1992; McDermott, 2004; Fairchild and Treble, 2009; Lachniet, 2009; Fairchild and Baker, 2012). Nowadays speleothems are well established as continental climate archives (Cruz et al., 2005; Wang et al., 2008; Zhang et al., 2008; Drysdale et al., 2009; Kanner et al., 2012; Kennett et al., 2012).

Speleothems are dominated by two types of CaCO3 polymorphs being the minerals calcite and aragonite, where calcite is the most abundant one. Research on aragonitic speleothems is still limited (Finch et al., 2001; Bertaux et al., 2002; Frisia et al., 2002; Finch et al., 2003; McMillan et al., 2005), but a large advantage of aragonite speleothems in comparison to its calcitic counterparts is its relatively high U-contents (see section 1.2.4). Therefore they can be very precisely dated with the U-Th dating technique. In Grotte Prison de Chien (Dog’s Prison Cave) and Grotte de Piste (Gravel Road Cave) in the NW part of the Middle Atlas of Morocco (Fig. 1.2) we encountered many aragonite

Introduction

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Fig. 1.2. (A) Location Morocco as indicated by the red box. (B) Regional climate zones of Morocco and location of study area as indicated by the red star (map modified after Sadalmelik: http://commons.wikimedia.org/wiki/File:Morocco_Topography.png). The main mountain ridges the Rif, Middle Atlas (MA), High Atlas (HA) and Anti Atlas (AA) subdivide Morocco into three regions: the Atlantic region (ATL), the Mediterranean region (MED) and a region south of the Atlas (SOA; Knippertz et al., 2003). (C) Long term precipitation characteristics of the three regions (Schulz and Judex, 2008), note the similar long term precipitation decline after the 1970’s for the MED and ATL region. This has been related to a shift towards more dominant positive North Atlantic Oscillation conditions.

speleothems, which provided an excellent opportunity to test whether they are suitable climate archives. As a consequence:

The second aim of this thesis is to explore and to document the high potential of aragonite speleothems as climate archives.

1.2. Speleothems as climate archives

A speleothem is generally referred to as a cave carbonate (CaCO3) deposit and includes many different types of morphologies, including (not limited to) stalagmites (i.e. growing upward), macaronis and stalactites (i.e. growing downward), flowstones, eccentrics and cryogenic calcites (Hill and Forti, 1997; Richter and Riechelmann, 2008). Most studies use stalagmites for climate reconstructions because of their regular and sometimes layered growth structures. Stalagmites have a large range of climate proxies which can be measured from subsamples taken along the stalagmite growth axis. In the following sections the formation of speleothems and the differences between its CaCO3 polymorphs (calcite and aragonite) will be introduced and explained. Subsequently a small summary of how the proxies can be used to reconstruct climate is presented.

1.2.1 Speleothem formation

Chapter 1

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A soil, epikarst, cave system may be subdivided into two geochemically different regions: a dissolution region and a precipitation region (Fig. 1.3; Fairchild et al., 2006). In the dissolution region rainwater infiltrates into a soil and takes up CO2 derived from root respiration and microbial activity, which forms carbonic acid (Fig. 1.3; H2CO3). The carbonic acid dissolves the host rock CaCO3, such that the water contains the free ions Ca2+ and 2HCO3

-. Precipitation of CaCO3 occurs when the water encounters a gas phase with a pCO2 (CO2 partial pressure) smaller than the pCO2 of the water forcing the water to degas CO2 (Fig. 1.3). This can occur in the epikarst above the cave or in the cave itself in the form of a speleothem. Speleothem growth rate may thus be controlled by CO2 production in the soil or epikarst and cave air pCO2 (Frisia and Borsato, 2010), although other factors may play a role as well (Kaufmann, 2003; Banner et al., 2007 and references therein).

(1)

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CarbonateHostrock

Fig. 1.3. Speleothem formation. Dissolution and CaCO3 precipitation regimes are indicated on the left. Carbonic acid forms within the soil zone from H2O and CO2 (1), after infiltration it starts to dissolve CaCO3 (2). When the water encounters a gas phase with lower pCO2 it starts to degas and precipitate CaCO3 (3). Modified after Fairchild et al. (2006).

1.2.2. U-Th dating

One of the big advantages of speleothems is the possibility for “absolute” (radiometric) dating with the U-Th dating technique (Chen et al., 1986). 238Uranium is decaying over time to 230Th via 234U. Uranium and Th have different physical properties, which fractionate them from each other, i.e. U is highly soluble in water and can be easily transported, whereas Th is highly insoluble. When water bearing U infiltrates the cave and is incorporated into the speleothem calcite or aragonite it starts to decay to 230Th. As the minerals calcite or aragonite can be regarded as a closed system, the 230Th accumulates within the speleothem, whereas 234U decreases. As the half-lives of 238U, 234U and

Introduction

5

230Th are known, the age of deposition can be calculated by measurements of 238U, 234U and 230Th of the speleothem. Generally the precision and accuracy of this method depends on the U concentration of the sample, measurement precision and the initial 234U/238U activity ratio. For more details on the U-Th dating method and complications the reader is referred to (Cheng et al., 2000; Dorale et al., 2004).

1.2.3. Understanding speleothem proxies

Climate proxies used in this study are carbon and oxygen isotopes and trace element concentrations (Mg, Sr, Ba, P, Pb, U, Ti, Th, Y and Al). Oxygen isotopes may be controlled by both local processes like evaporation and temperature and by the processes which determine the oxygen isotope composition of the rainfall (Lachniet, 2009; Dayem et al., 2010). Trace elements and carbon isotopes mainly represent local processes taking place in the soil, epikarst and cave environment, whereas different processes may affect different trace elements. For example P, Y, Pb and U have been interpreted as proxies for organic matter decay (Treble et al., 2003; Borsato et al., 2007), Mg, Sr and Ba on the other hand may be linked to the precipitation of calcite within the epikarst (i.e., prior to reaching the stalagmite surface; Fairchild et al., 2000). The presence of Al in stalagmites is often related to Al-silicates, whereas Th is an indicator for clay minerals (Dorale et al., 2004). However, some proxies may be affected by several processes, thus interpreting geochemical proxy data from stalagmites is not straightforward (McDermott, 2004; Fairchild and Treble, 2009; Lachniet, 2009; Baker et al., In Press). Other indications for speleothem growth conditions may come from the crystal fabric of the speleothem (Frisia et al., 2000; 2002; Frisia and Borsato, 2010), which is related to the morphology and arrangements of the crystals the speleothem is built from. Generally, in order to reconstruct climate parameters with speleothems multiple proxies have to be considered. Other methods to increase the understanding of proxies include calibration studies, i.e. a direct comparison of proxy data from actively growing stalagmites with instrumental climate data from weather stations (Finch et al., 2003; Treble et al., 2003) or cave monitoring. Where drip waters may be analyzed for their isotopic C and O composition and elemental concentrations, which may be compared to precipitates collected on glass plates or watch glasses from the same drip sites (Spötl et al., 2005; Mattey et al., 2010; Riechelmann et al., 2011; Baldini et al., 2012). These data may then be compared to weather station data providing a link between the proxy data and exterior climate.

1.2.4. Calcite versus aragonite speleothems

The two dominating mineralogies encountered in speleothems are calcite and aragonite of which calcite is the most abundant one (Hill and Forti, 1997). Calcite and aragonite are polymorphs, meaning that they have the same chemical composition (CaCO3) but a different crystallography. Calcite is characterized by a trigonal crystal system whereas aragonite is characterized by an orthorhombic crystal system. The difference between the two systems is the way the CO3

2- and the Ca2+ ions are arranged with respect to each other (Fig. 1.4). In calcite the cation (Ca2+) is connected to 6 anions (CO3

2-), therefore calcite is characterized by a 6-fold coordination. Aragonite is characterized by a

Chapter 1

6

= Calcium = Oxygen = Carbon

a b

Fig. 1.4. Calcite and aragonite structure. (A) Calcite unit cell. (B) aragonite unit cell (modified after Ruiz Hernandez et al., 2010). Note the different arrangements of the CO3

2- ions.

9-fold coordination, which has important implications for the available space within the crystal lattice for the cation. Typically in aragonite there is more space available for the cation compared to calcite. Aragonite is therefore more likely to incorporate larger cations like Sr2+ and Ba2+ or cation complexes like uranyl ions (UO2

2+) but only incorporates very little Mg2+ as this cation is much smaller compared to Ca2+. As a consequence the interpretation of elemental concentrations in aragonite speleothems cannot be simply extrapolated from interpretations in calcite speleothems. Another effect is that aragonite contains much more U and is thus an ideal candidate for high precision dating.

A disadvantage of aragonite with respect to calcite is that it is thermodynamically less stable, because it is usually formed under high pressure conditions at a depth below the earth’s surface of several kilometers. Screening for diagenesis before using aragonite speleothems is thus a prerequisite (Frisia et al., 2002; Martin-Garcia et al., 2009). It also raises the question why aragonite occurs in cave systems (Hill and Forti, 1997). Literature on aragonite precipitation experiments is extensive and suggests that only specific conditions are able to induce aragonite precipitation under atmospheric pressure. One of the most important aspects seems to be a high fluid Mg/Ca ratio, although as mentioned a range of factors play a role (Fernández-Díaz et al., 1996; Zuddas and Mucci, 1998; Davis et al., 2000; De Choudens-Sanchez and Gonzalez, 2009; Wassenburg et al., 2012).

1.3. Climate forcing mechanisms

Important external climate forcing mechanisms, which may have played a role during the Holocene, include orbital forcing, solar forcing and volcanic activity (Wanner et al., 2008). In addition many climate feedback mechanisms within earth’s climate system are of importance. These together with the interaction between its different components (atmosphere, land, sea, ice and vegetation) make the climate system inherently complex (Ruddiman, 2001). Below a small overview of which

Introduction

7

climate forcing and feedback mechanisms play a role is presented.

1.3.1. External forcing mechanisms

Orbital forcing consisting of the well known Milankovitch cycles (eccentricity, precession and obliquity, reviewed in Berger, 1980) has a major control on the insolation of the sun on earth at multi-millennial timescales including the occurrence of glacial and interglacials. Typical known cyclicity patterns are 400 and 100 kilo years (ka) related to the eccentricity of the earth’s orbit around the sun (determining the distance of the earth to the sun at aphelion and perihelion), 41 ka related to the obliquity of the earth’s axis with respect to the sun (determining seasonality) and 23 ka related to the spinning of the earth’s axis (determining the timing of the solstices and equinoxes; Ruddiman, 2001). The present interglacial (Holocene) commenced approximately 11.5 ka BP and coincided with the highest summer insolation due to orbital forcing (Fig. 1.5). Since 6 ka BP until present, Northern Hemisphere summer insolation and seasonality has decreased, whereas winter insolation increased although changes are relatively small compared to summer (Wanner et al., 2008).

Fig. 1.5. Evolution of the major external forcing mechanisms through the Holocene. (A-B) Orbital forcing for northern and southern hemisphere for the summer season (Berger, A. L., 1978; Laskar et al. 2004). (C) Solar forcing derived from the production of the cosmogenic nuclide 10Be in ice cores (Steinhilber et al. 2009). (D) Volcanic sulphate concentrations from the GISP2 ice core (Zielinski et al. 1997).

Centennial to millennial climate events have occurred throughout the Holocene (Mayewski et al., 2004; Wanner et al., 2008; Wanner et al., 2011; Fletcher and Zielhofer, In Press). Solar forcing (Fig. 1.5) has often been suggested to be the driver of these climate events (Bond et al., 1997; Bond et al., 2001; Neff et al., 2001; Mangini et al., 2005; Jackson et al., 2008; Springer et al., 2008). Typical

Chapter 1

8

frequencies of solar activity (among others) are the 11 year Schwabe and 22 year Hale cycle (Peristykh and Damon, 1998), the 88 year Gleissberg cycle (Peristykh and Damon, 2003), the 205 year Suess (De Vries) cycle (Wagner et al., 2001), a 400 year cycle (Knudsen et al., 2009) and the 2300 year Halstatt cycle (Steinhilber et al., 2010). It is however acknowledged that the forcing factor of solar variability alone is too small to explain the observed climate events (Shindell et al., 1999; Bond et al., 2001; Rind, 2002). A potential amplifier of solar forcing could be stratospheric ozone production at low latitudes and ozone destruction at polar latitudes (Gray et al., 2010 and references therein). It has also been suggested that the flux of Galactic Cosmic Rays may affect cloudiness by the generation of sulphate aerosols as a consequence of increased atmospheric ion production (Dickinson, 1975), although quantification of its effects has just begun (Gray et al., 2010). Oceanic feedbacks may be involved as well, like changes in the strength of the thermo haline circulation (THC; Fig. 1.6; Bond et al., 2001; Renssen et al., 2006).

Volcanic activity represents the third external forcing mechanism (Fig. 1.5). Especially large eruptive events are able to emit up to 1 Tg of tephra and gases to 20-25 km altitudes (Wanner et al., 2008). Volcanic aerosols in the stratosphere are not washed out by rain and have a longer residence time compared to their brothers and sisters in the troposphere. They are good absorbers of incoming solar radiation and thus have a general cooling effect at the earth’s surface (Crowley, 2000). Probably the best example of the effects of volcanic activity is the Little Ice Age, which is a well studied time interval (Wanner et al., 2008; Mann et al., 2009; Graham et al., 2011; Fletcher and Zielhofer, In Press) characterized by overall cooling in the extratropical Northern Hemisphere (Mann et al., 2009). Although the exact timing differs per region, recently Wanner et al. (2011) showed that on a more global scale the Little Ice Age is represented by the time interval 1200-1800 AD, a period which encompasses clusters of volcanic activity together with periods of low solar activity, including the Maunder Minimum (Wanner et al., 2011).

1.3.2. Feedback mechanisms

On centennial to millennial timescales ice sheets, sea ice, surface ocean currents (Fig. 1.6), vegetation and large scale atmospheric circulation (Fig. 1.7) patterns all interact with each other. Therefore a change in the earth’s heat budget as a consequence of one of the external forcing mechanisms described above may trigger a range of effects. Please note that for a basic explanation of large scale atmospheric circulation patterns and ocean circulation the reader is referred to Fig. 1.6 and Fig. 1.7.

Ice sheets are able to affect regional climate through their high albedo, this induces a local cooling effect and may affect atmospheric circulation patterns (Magnusdottir et al., 2004; Chiang and Bitz, 2005). The effect of sea ice in terms of albedo is even larger, because water has a lower albedo compared to land surface, which enhances regional cooling. The formation of sea ice makes the underlying surface ocean water increasingly saline by the rejection of salts, which may strengthen the formation of North Atlantic deepwater. However, the presence of sea ice could also have a stratiphication effect on the water column as it prevents the surface ocean to release heat to the atmosphere, which may reduce North Atlantic deepwater formation (Levermann et al.,

Introduction

9

Subtropicalgyre

Subpolargyre

LCNC

NAC

NEC

CC

IC

EGC

2007). In addition the introduction of melt water into regions of North Atlantic deep water formation reduces northward heat transport through the North Atlantic Current (Curry and Mauritzen, 2005; Renssen et al., 2009; Bamberg et al., 2010). Whereas the North Atlantic Current is responsible for the relatively warm and humid climate in North-Western Europe. A slow down of the THC thus has a general cooling effect on the north-(eastern) part of the North Atlantic area, in addition sea surface temperatures across the North Atlantic basin are affected through a propagation along the North Atlantic subtropical gyre (deMenocal et al., 2000b; Lohmann, 2003; Kim et al., 2007). These changes in sea surface conditions may also play an important role in determining moisture availability and land sea pressure differences in for example monsoonal regions (Kutzbach and Liu, 1997; Texier et al., 2000; Zhao and Harrison, 2012).

Land surface albedo is lower when occupied by vegetation, which has a large impact on land temperatures. This forces an ascending motion of the air and thus lowering sea level pressures and potentially increasing precipitation (Kutzbach et al., 1996; Knorr and Schnitzler, 2006). Vegetation

Fig. 1.6. Simplified overview of surface ocean currents in the North Atlantic and the subtropical and subpolar gyre systems. Red arrows represent warm surface currents, blue arrows represent cool surface currents; map modified after Bamberg et al. (2010). The Thermo Haline Circulation (THC) refers to the water density driven ocean circulation, which consists of surface ocean currents and deep sea ocean currents. In the North Atlantic warm saline surface waters flow northwards and cool down (i.e. the Northern Equatorial Current (NEC), the North Atlantic Current (NAC), the Irminger Current (IC) and the Norwegian Current (NC)). This cooling increases the water density, which causes it to sink (i.e. “deep water formation”). As a consequence surface waters are drawn towards the position where the deep water is formed. Deep water formation is thus considered as a major driver for ocean circulation. The green dashed circles indicate the two main positions of deep water formation in the Labrador Sea (West of Greenland) and the Greenland Sea (east of Greenland). The warm currents are essential for keeping the European climate temperate. Cool surface currents are indicated: Labrador Current (LC), East Greenland Current (EGC) and the Canary Current (CC).

Chapter 1

10

Polar cell

Ferrell cell

Hadley cell

Hadley cell

Ferrell cell

Polar cellPolar easterlies

Polar front

Subtropical high

Subtropical high

ITCZ

NE Trades

Westerlies

SE Trades

Westerlies

Polar easterlies

30°

60°

0°

30°

60°

Fig. 1.7. Simplified overview of general atmospheric circulation patterns. Air rises at low latitudes due to surface heating, which creates low surface pressures (Intertropical Convergence Zone; ITCZ) and descends in the subtropics due to cooling, which is causing the subtropical high pressure zone. At the earth’s surface at the position of the subtropical high the air flows southwards in the form of the Northeast tradewinds and northwards in the form of the Westerlies. The Hadley cell consists of the air circulation between the ITCZ and the subtropical high. In addition a 2nd and 3rd cell exist, the Ferrell and the polar cells. The ascending branch of the polar and Ferrell cell is mainly forced by frontal weather systems where cool polar air meets warmer air from the south. Main surface wind directions are a consequence of the distribution of the high and low pressure zones and induce the trade winds, mid-latitude westerlies and polar easterlies. Note that these zones shift in north-south direction with the seasons, Morocco is located near the northern subtropical high pressure zone as indicated by the red star. A more detailed explanation can be found in textbooks like Ruddiman et al. (2001). Modified after: http://www.hovanitz.com/ChapterNotesGarrison/Chapter08.html

also plays an important role in the local hydrology through moisture recycling as it prevents the water from being drained through groundwater or via surface runoff (Texier et al., 2000). Liu et al. (2010) also suggests that there is an indirect vegetation feedback through changes in soil moisture contents, which itself have an impact on surface albedo and evaporation. They stated that the net feedback effect depends on the interaction between vegetation, soil and climate (Liu et al., 2010). A good example of a positive vegetation feedback on precipitation is the African Humid Period during the Early to Middle Holocene which was characterized by a “Green” Sahara (Lezine et al., 1990; Gasse and Vancampo, 1994; deMenocal et al., 2000a; 2000b). The African Humid Period was initially forced by orbitally induced higher summer insolation, but amplified by the vegetation feedback, in

Introduction

11

addition to positive oceanic feedbacks and the presence of wetlands and lakes (Kutzbach and Liu, 1997; Krinner et al., 2012).

1.4. Morocco: Physiography and present day climate

Morocco (approx. 33°N 6°W; Fig. 1.2) represents a very interesting geographical position as it is under influence of the Azores subtropical high pressure zone, which is the descending branch of the Ferrell and Hadley cell (Fig. 1.7). Moroccan climate is therefore under influence of the North Atlantic Oscillation (NAO; Ward et al., 1999; Glueck and Stockton, 2001; Trouet et al., 2009), which is the dominating atmospheric pressure mode of the Northern Hemisphere (Hurrell, 1995).

Climatically, Morocco can be subdivided into three regions: a region dominated by the Atlantic, a region dominated by the Mediterranean and a region south of the Atlas (Knippertz et al., 2003). This subdivision follows the topography of Morocco with the Rif Mountains in the north and the west-south-west east-north-east trending Atlas mountain range. The Atlas Mountains can be subdivided into the Middle Atlas in the north-east, the High Atlas in the south-west and the Anti-Atlas in the south (Fig. 1.2).

In summer Morocco is under direct influence of the Azores subtropical high which causes hot and dry conditions. During winter (December-February) Morocco is located at the southern edge of the westerly zone when it receives most of its rainfall originating above the North Atlantic. This however, especially accounts for the Atlantic and Mediterranean regions, the region south of the Atlas is located in the rain shadow of the Atlas mountains and receives most of its rainfall during summer due to local convection (Knippertz et al., 2003). The Mediterranean and Atlantic dominated regions show very similar long term precipitation trends, with a strong decrease in annual precipitation after the 1970’s (Fig. 1.2). This trend has largely been assigned to dominating positive NAO conditions (Hurrell and Van Loon, 1997; Ward et al., 1999; Glueck and Stockton, 2001). Because of its importance for Moroccan climate, in section 1.5 the characteristics and forcing mechanisms of the NAO are described.

1.5. North Atlantic Oscillation

The general importance of understanding the dynamics behind the North Atlantic Oscillation (NAO) is well expressed simply by searching for papers with “North Atlantic Oscillation” in the title on ISI Web of Knowledge (572 hits). In addition many reviews have been written on its impact on Northern Hemisphere climate (Hurrell and Van Loon, 1997; Marshall et al., 2001; Hurrell et al., 2003; Hurrell and Deser, 2009; Pinto and Raible, 2012; Trouet et al., 2012). More precise, the NAO may be considered as the regional expression of the Northern Hemisphere annular mode also called the Arctic Oscillation (Wallace, 2000). Therefore the term AO/NAO is often found in the literature.

The main characteristics of the NAO are related to the sea level pressure gradient between its centers of action: the Icelandic low and the Azores subtropical high (Fig. 1.8). The NAO can simply be expressed as an index based on the difference between the normalized sea level pressure data from Lisbon (Portugal) and Stykkisholmur (Iceland; (Hurrell, 1995). A disadvantage of this

Chapter 1

12

NAO- NAO+

Wet

ColdairCold

air- +

DeepConvect.- Deep

Convect.+

Sea ice+ Sea ice-

Dry

Runoff+Runoff-

Dry

Wet

Cool

Warm

Warm- Trades

-Westerlies

Warm

Cool

Cool+Westerlies

+Trades

Fig. 1.8. General features of the North Atlantic Oscillation (NAO). The Icelandic low pressure zone is indicated by L, high pressure zones are indicated by a red H. Negative NAO conditions (NAO-, left) coincide with wet conditions in Morocco (indicated by the red star) and dry conditions in North-West Europe, a decrease in deepwater formation in the Labrador Sea, warming in West Greenland and southward extending sea ice east of Greenland. Positive NAO conditions (NAO+, right) are characterized by opposite conditions. Modified after Wanner et al. (2001).

type of expression is that neither spatial variability nor seasonal variability is captured, however the advantage over other methods like Principal Component Analysis and Cluster Analysis of sea level pressure data (Hurrell and Deser, 2009) is that the NAO-index can be extended further back in time as it is only based on two geographical positions (Marshall et al., 2001 and references therein). Although the NAO sea level pressure pattern may be present throughout the year, it is most pronounced during the winter season (Wanner et al., 2001). The strength of the westerly winds in the mid-latitudes over the North Atlantic depends on the NAO. During negative NAO conditions (NAO-index < 0) the pressure difference between the Icelandic low and the Azores subtropical high is relatively small which causes the western winds to be weakened and shifted south together with the jet stream. This coincides with increasing winter rainfall in Central-Southern Europe (including the Alps), Greenland, Northern Africa and the Mediterranean, whereas Northern Europe and Scandinavia experience decreasing winter rainfall (Hurrell and Van Loon, 1997; Fig. 1.8). During positive NAO conditions the situation is typically reversed due to stronger and northward shifted western winds and jet stream.

The NAO also plays an important role in surface temperatures (Fig. 1.8) as indicated by the fact that since 1970 31% of the variance of extra-tropical Northern Hemisphere winter surface temperature can be explained by the NAO (Hurrell, 1996). Marshall et al. (2001) and Visbeck et al. (2001) calculated correlations between the NAO-index and surface temperatures and showed positive correlations for Europe, Scandinavia and large parts of Eurasia. Negative correlations

Introduction

13

(although not strong) were observed for the North-Eastern United States and Northern Africa. Sea surface temperatures (SST) typically show a tripole pattern with warm (cold) SST’s in the subpolar and subtropical North Atlantic and cold (warm) SST’s in the centre during negative (positive) NAO conditions (Rodwell et al., 1999). The NAO also affects the regional distribution of sea ice. During a positive NAO, sea ice in the Labrador sea extends further south during winter due to stronger northern winds in this area, whereas east of Greenland sea ice is forced north due to stronger southern winds (Wanner et al., 2001; Bader et al., 2011). Atlantic deep water formation in the Labrador Sea is increased during positive NAO conditions which may feedback on the strength of the THC (Dickson et al., 1996; Hurrell et al., 2003; Ortega et al., 2012).

Potential forcing mechanisms for specific NAO states have been examined but are still a matter of debate (Hurrell and Deser, 2009). An increase in sea ice extend in the Labrador sea combined with a reduction of sea ice east of Greenland may induce increasingly negative NAO conditions (Magnusdottir et al., 2004). North Atlantic SST patterns seem to re-inforce the NAO pressure patterns by affecting evaporation, precipitation and surface heating (Rodwell et al., 1999). Tropical SST’s in the Pacific and Indian oceans have also been suggested to force NAO conditions (Hoerling et al., 2001; Hurrell et al., 2004; Bader and Latif, 2005), whereas Sutton and Hodson (2003) suggested that different time intervals may have had different oceanic SST forcing patterns. According to Timmermann et al. (1998) a strengthened THC may force the NAO towards positive conditions. As a consequence warmer ocean waters may be transported towards the positions of North Atlantic deep water formation which may reduce the THC and completes a phase reversal (Timmermann et al., 1998). Finally, Gong et al. (2002) suggested a connection between snow cover in North America and Eurasia during autumn which may produce a feedback on AO/NAO through the Siberian high pressure zone. Overall many forcing mechanisms may thus play a role and apparently the NAO is both forced by specific SST patterns but also affects SST patterns itself. It has also been suggested that the memory or the slower response of the ocean and the persistence of SST patterns throughout the year forces recurrent NAO patterns in subsequent years (Cassou et al., 2007). Timescales at which the NAO typically acts may vary from 6-10 years (Hurrell et al., 2003) to multi-decadal timescales as evidenced by the recently dominating positive NAO conditions (1980-2000). Variability of the NAO on centennial to millennial timescales is still largely unknown and requires extensive research (Kim et al., 2007; Trouet et al., 2009; 2012).

1.6. Holocene Moroccan Climate

In Morocco several records covering (parts of) the Holocene have been published (Lamb et al., 1995; Cheddadi et al., 1998; Lamb et al., 1999; Esper et al., 2007; Détriché et al., 2009; Rhoujjati et al., 2010). Apart from the tree ring chronology from Esper et al. (2007) they all represent lake records. Based on a pollen record from Lake Tigalmamine, Cheddadi et al. (1998) suggested that the early Holocene was characterized by dry and warm conditions (11.7-7.5 ka BP), followed by an intermediate period with more humid and cooler conditions (7.5-2.6 ka BP) and a Late Holocene characterized by increasing aridity. The relation with the African Humid Period (14.9-5.6 ka BP; deMenocal et al., 2000a) was discussed, and the contrast in rainfall (i.e. high rainfall in the Sahara

Chapter 1

14

and lower rainfall in NW Morocco in the Early Holocene) was explained by the position of Morocco with respect to the Azores subtropical high, whereas the Sahara was affected by the North African monsoon. A subsequent southward shift of the monsoonal regime together with the Azores subtropical high as a consequence of precessional forcing from the middle to late Holocene explained the more humid conditions in NW Morocco (i.e. NW Morocco was under influence of the westerly winds in winter) versus the more arid conditions in the Sahara region (i.e. stronger influence from the Azores subtropical high) (Cheddadi et al., 1998). Multiple centennial climate events were recognized in the Lake Tigalmamine record (Lamb et al., 1995) with relatively arid intervals at 12.5-10.3, 7.9-7.6, 5.1-4.9, 3.1-2.9 and 1.9-1.7 ka BP. Other records from Lake Sidi Ali (Lamb et al., 1999), and Lake Ifrah (Rhoujjati et al., 2010) do not have a straightforward data interpretation, may be affected by anthropogenically induced features, lack a robust age model, or do not cover the entire Holocene (Détriché et al., 2009).

During the Holocene many centennial to millenial climate events have been recognized (Bond et al., 2001; Mayewski et al., 2004; Wanner et al., 2008; Wanner et al., 2011). A general issue is to constrain the exact timing of climatic transitions / events. At present, the Moroccan records lack a high resolution chronostratigraphy (less than one age per 1000 years) and sampling resolution (approximately 100 years). This is especially important when correlations have to be established between proxy records separated by large distances (over 1000 km) in order to determine whether climate teleconnections exist and whether climate transitions occur in or out of phase. An excellent example of this is the NAO reconstruction for the last millennium from Trouet et al. (2009). These authors used the mentioned tree ring chronology from NW Morocco (Esper et al., 2007) and an annual lamineae thickness record from a Scottish speleothem (Proctor et al., 2000). Both records were interpreted as reflecting variations in rainfall, and both have a perfect age model due to the annual layers. The records showed negative correlations in terms of rainfall which has been related to the North Atlantic Oscillation (NAO). The authors were able to suggest that the Little Ice Age was dominated by more negative NAO conditions, whereas the Medieval Warm Period was dominated by more positive NAO conditions.

1.7. Research questions, approach and general outline

I would first like to recall the aims of this thesis in order to place these research questions in their conceptual context:

1) To reconstruct the Holocene climate of NW Morocco by using speleothem archives and to place the climate reconstruction in a climate dynamical context with respect to earlier published reconstructions from the North Atlantic domain.

2) To explore and document the high potential of aragonitic speleothems as climate archives.

Mainly aragonite speleothems were encountered in Grotte Prison de Chien (Dog’s Prison Cave) and Grotte de Piste (Gravel Road Cave) in the NW Middle Atlas of Morocco (Fig. 1.2).

Introduction

15

Therefore, it is a prerequisite to know why aragonite is precipitating before it is possible to test whether they are suitable as climate archives, and before we can use them to reconstruct the Holocene climate of NW Morocco. As such the first research questions which have to be answered are:

1. What processes control the precipitation of aragonite in these cave systems?2. Can the presence of aragonite in speleothems be regarded as a climate signal itself?

Although the carbon and oxygen isotope systematics in aragonite speleothems are fairly well known, literature on trace elements in aragonite is still very limited (see section 1.1 and 1.2). As explained in section 1.2.3 it is necessary to apply multi proxy approaches in order to derive climate reconstructions from speleothem proxy data. Therefore it is essential to gain knowledge on which trace elements in aragonite speleothems are most sensitive to climate parameters in order to support any interpretation from carbon and oxygen isotopes. As a consequence the third and fourth research questions which have to be answered are:

3. Which trace elements in aragonite speleothems are most sensitive to climate change?4. What processes are affecting these trace elements?

Once these questions are answered it is possible to start reconstructing climate parameters with aragonite speleothems. As explained the lack of high resolution well dated climate reconstructions from Morocco has prevented to correlate centennial climate events with other regions from the North Atlantic. As Moroccan climate is influenced by the position and strength of the Azores subtropical high its climate is related to the North Atlantic Oscillation (NAO). Therefore, the last two research questions are:

5. Can we find a NAO signature in NW Morocco during the Holocene?6. If so, how has the NAO developed during the Holocene?

1.7.1. General outline

Chapter 1: Introduction to the scope and aims of this thesis followed by a general description of speleothems as climate archives, the modern Moroccan climate, climate forcing mechanisms, the North Atlantic Oscillation and the Holocene climate of Morocco.

Chapter 2: Description of the geological setting of Grotte Prison de Chien and Grotte de Piste.

Chapter 3: Description of the methodology.

Chapter 4: A study of lateral and stratigraphical calcite-to-aragonite transitions in speleothems from two different cave systems. General focus is on the processes which induce the presence of aragonite and whether the occurrence of aragonite can be used as a

Chapter 1

16

climate signal itself. In addition these transitions created the opportunity to study the different behavior of trace elements within calcite and aragonite.

Chapter 5: A study focusing on the validation of aragonite speleothem trace element concentrations as a climate proxy, including cave monitoring data and a comparison with an updated tree ring chronology from the Middle Atlas covering the last 1000 years.

Chapter 6: A study focusing on the Holocene North Atlantic climate, which aims to reconstruct the North Atlantic Oscillation over the complete Holocene, by correlating records from Greenland, Scotland, Germany and Morocco.

References

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Archer, D., 2007. Methane hydrate stability and anthropogenic climate change. Biogeosciences 4, 521-544.

Bader, J., Latif, M., 2005. North Atlantic oscillation response to anomalous Indian Ocean SST in a coupled GCM. Journal of Climate 18, 5382-5389.

Bader, J., Mesquita, M.D.S., Hodges, K.I., Keenlyside, N., Osterhus, S., Miles, M., 2011. A review on Northern Hemisphere sea-ice, storminess and the North Atlantic Oscillation: Observations and projected changes. Atmospheric Research 101, 809-834.

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Trouet, V., Esper, J., Graham, N.E., Baker, A., Scourse, J.D., Frank, D.C., 2009. Persistent Positive North Atlantic Oscillation Mode Dominated the Medieval Climate Anomaly. Science 324, 78-80.

Trouet, V., Scourse, J.D., Raible, C.C., 2012. North Atlantic storminess and Atlantic Meridional Overturning Circulation during the last Millennium: Reconciling contradictory proxy records of NAO variability. Global and Planetary Change 84-85, 48-55.

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Wagner, G., Beer, J., Masarik, J., Muscheler, R., Kubik, P.W., Mende, W., Laj, C., Raisbeck, G.M., Yiou, F., 2001. Presence of the solar de Vries cycle (similar to 205 years) during the last ice age. Geophysical Research Letters 28, 303-306.

Introduction

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Wallace, J.M., 2000. North Atlantic Oscillation/annular mode: Two paradigms - one phenomenon. Quarterly Journal of the Royal Meteorological Society 126, 791-805.

Wang, Y.J., Cheng, H., Edwards, R.L., Kong, X.G., Shao, X.H., Chen, S.T., Wu, J.Y., Jiang, X.Y., Wang, X.F., An, Z.S., 2008. Millennial- and orbital-scale changes in the East Asian monsoon over the past 224,000 years. Nature 451, 1090-1093.

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Zielinski, G. A., Mershon, G. R., 1999. GISP2 Volcanic markers. doi:10.1594/PANGAEA.56074

Chapter 2

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Geological setting

27

1Ta

zekk

a

5000 m

10 km

SE

Tanger

RabatCasablanca

Fes

ErrachidiaMarrakech

Ouarzazate

AA

HA

MA

Rif0

2000

NWTahla

Massifde Tazekka Maghraoua J. Ouadda

21

MaghraouaTahla

4°

34°2

1b

ca

Taza

2 3 4 5 6 7 8119 10

4000

0 100 200 300

3000

2000

1000

0

m

Fig. 2.1. Geological setting of Grotte Prison de Chien and Grotte de Piste. (A) Location of the study area in the Northwestern part of the Middle Atlas in Morocco (map modified after Sadalmelik: http://commons.wikimedia.org/wiki/File:Morocco_Topography.png). (B) Geological map modified after Taous et al. (2009), stars indicate location of caves. 1 = Grotte Prison de Chien; 2 = Grotte de Piste. (C) Geological cross section modified after Taous et al. (2009) with indication of relative cave positions. Key to colour scheme in panels B and C: 1 = Palaeozoic schists and sandstones; 2 = Permian, Triassic clays and basalts; 3 = Lower Jurassic dolostones and limestones; 4 = Middle and Upper Jurassic limestones and marls; 5 = Middle Jurassic marls; 6 = Miocene units; 7 = Pliocene/Quaternary units; 8 = Quaternary basalts; 9 = Quaternary and recent units; 10 = fault structures.

2. GEOLOGICAL SETTING

The stalagmites used in this study were retrieved from two caves in the NW part of the Middle Atlas. These caves are referred to as “Grotte Prison de Chien” (Dog’s prison cave), situated at 360 m above sea level (Fig. 2.1), and “Grotte de Piste” (Gravel road cave), situated at 1260 m above sea level (Fig. 2.1).

2.1. Grotte Prison de Chien

Grotte Prison de Chien lies within a predominantly limestone (subordinate dolostone) host rock - as based on XRD analysis - and is formed within Liassic brecciated marine limestones (Fig. 2.1; Sabaoui et al., 2009; Taous et al., 2009). The cave is overlain by about 20 m of host rock and has several open connections with the outside atmosphere (Fig. 2.2). The vegetation is restricted to small shrubs, locally small trees and grasses. Approximately 50% of the land surface above the cave is covered by up to 30 cm of lateritic soil; Elsewhere, the limestone host rock is exposed at the land surface. 2.2. Grotte de Piste

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100 m

Main entrance

2nd entrance

3rd entrance

a

GP2GP5

Entrance

2nd level

20 m

b

c

GP2GP5

10 m 2nd level Entrance

GC Map

GP Map

GP Cross section

HK3

HK1

Fig. 2.2. Cave morphologies of Grotte Prison de Chien and Grotte de Piste. (A) Cave map Grotte Prison de Chien, entrances and sample locations of stalagmites HK1 and HK3 are indicated. (B-C) Cave cross section and map of Grotte de Piste, entrance and sample locations of stalagmites GP2 and GP5 are indicated.

Grotte de Piste lies within a Lower Jurassic south-east dipping, dominantly dolomitic host rock with spatially limited limestone intervals (Fig. 2.1; Sabaoui et al., 2009; Taous et al., 2009).The vegetation above the cave consists of small (i.e., <2 m tall) oak trees, shrubs and grasses. About 60% of the surface is covered by up to 20 cm of soil, elsewhere the dolomite host rock is exposed at the land surface. The drip water entering the cave is of local origin due to the surface morphology above the cave, forming a topographic high, and the elevated position of the cave at the slope. The entrance of the cave is about 3 m in diameter and has a steep downward gradient (Fig. 2.2). Grotte de Piste has a second level, approximately 20 meters above the cave bottom (Fig. 2.2).

References

Sabaoui, A., Obda, K., Laaouane, M., 2009. Potentialites geologiques du developpement local du Moyen Atlas septentrional: structures, paysages et histoire geologique. Geomaghreb 5, 9-39.

Taous, A., Tribak, A., Obda, K., Baena, R., Lopez Lara, E., Miranda Bonilla, J., 2009. Karst et resources en eau au Moyen Atlas nord-oriental. Geomaghreb 5, 41-59.

Geological setting

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Chapter 3

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Materials and methods

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3. MATERIALS AND METHODS

This thesis focuses on stalagmites HK1 and HK3 (Fig. 3.1) from Grotte Prison de Chien and stalagmites GP2 and GP5 (Fig. 3.1) from Grotte de Piste, which were collected during several field campaigns in 2009 and 2010. Stalagmite HK1 exhibits lateral calcite – aragonite transitions, whereas stalagmites HK3 and GP2 exhibit stratigraphical calcite – aragonite transitions and aragonite – calcite transitions (Fig. 3.1). For more details on stalagmites HK1, HK3 and GP2 see chapter 4 and 6, for stalagmite GP5 see chapter 5.

3.1. Petrography

Polished thin sections were first examined under a polarisation microscope and thereafter sputtered with gold and examined under a cathodoluminescence microscope at the Ruhr University Bochum, Germany. The cathodoluminescence microscope is equipped with a hot cathode (Neuser et al., 1996). Beam current densities were between 5 and 10 μA/mm2, with an acceleration potential of 14 kV. Carbonate detrital material containing traces of Mn range in color from yellow to red under the cathodoluminescence microscope, therefore it can easily be distinguished from the low-Mn speleothem calcite (dark blue) and the green aragonite (Richter et al., 2003). Other types of inclusions like organic material or clay minerals cannot be distinguished with this method. Important to distinguish from each other is the intercrystalline calcite within an aragonite layer which is formed in situ, and carbonate detrital material, which is derived from an allochthonous source. It is difficult to distinguish the mineralogy of the carbonate detrital material, therefore we will continue to use the term carbonate detrital material.

Mineralogies of cave hostrock and speleothems were determined by X-ray diffraction (XRD) at the Ruhr University Bochum, Germany. Approximately 20 mg of sample powder was drilled for XRD. Ten percent of quartz was added to the sample powder as a standard in order to derive offsets in the 104 calcite peaks, and estimate the Mg content within the crystal lattice in mol% (Füchtbauer and Richter, 1988). Subsequently the samples were homogenised in an agate mortar before being analysed. X-ray diffraction patterns were recorded with a Pananalytical MPD diffractometer, equipped with a copper tube, 0.5° divergent and antiscatter slits, a 0.2-mm high receiving slit, incident and diffracted beam 0.04 rad soller slits, and a secondary graphite monochromator as documented in Miao et al. (2009). In the terminology applied here, speleothem fabrics are referred to as “calcitic” if they contain ≥99 % calcite. Conversely, the term “aragonitic” implies ≥98 % aragonite with the remaining bulk fabric dominated by calcite. Cave host rocks are referred to as “limestone” if they are formed by at least 70 % calcite, whereas the label “dolostone” is used for a host rock containing at least 96 % dolomite.

3.2. Trace element concentrations soil

Soil trace element concentrations were analysed from compressed powders consisting of 8 gram of sample material and 1 gram of ELVACITE resin. Analysis was performed on a wavelength dispersive X-ray fluorescence spectrometer (WD-XRF; Philips PW 2404) with a Rh-tube. Two soil

Chapter 3

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GP5

HK3

HK1GP250 mm 50 mm 50 mm

50 mm

Cc

ArAr Ar

Ar

CcCcAr

Cc

Cc

Cc

Cc

Ar

Fig. 3.1. Pictures of cross sections of stalagmites GP2, GP5, HK1 and HK3. Calcite (Cc) and aragonite (Ar) sections are separated by red dashed lines.

samples were analysed for Grotte de Piste and one soil sample was analysed for Grotte Prison de Chien.

3.3. Dating and age depth modeling

U-series dating of the speleothems was conducted at IFM GEOMAR, Kiel, Germany, with

Materials and methods

33

an AXIOM MIC-ICP-MS (multiple ion counting inductively coupled plasma mass spectrometer). Further methodological details can be found in Fietzke et al. (2005).

Additional dating was performed with the radiocarbon method in order to find the mid 20th century atmospheric 14C anomaly (“bomb-peak”) to document recent growth of stalagmite GP5 (Mattey et al., 2008; Hodge et al., 2011; Fohlmeister et al., 2012). Samples were drilled with a hand held dental burr (1 mm). Calcite powder was acidified in vacuum with HCl. The emerging CO2 was combusted to C with H2 and an iron catalyst at 575°C (Fohlmeister et al., 2011). Measurements were performed with a MICASAS AMS system (Synal et al., 2007) in the Klaus-Tschirra laboratory Mannheim. The age-depth model was calculated using the StalAge algorithm designed by Scholz and Hoffmannn (2011), which gives 95%-confidence limits for the age model.

3.4. Carbon and oxygen isotopes

Carbon and oxygen isotope analyses were performed at the Ruhr University Bochum, Germany, with a Gasbench coupled to a Finnigan MAT 253 mass spectrometer. For sampling a micromill (Merchantek, Esi-New Wave) equipped with a flat-tipped, 0.5 mm diameter dentist drill was used in addition to a hand held drill (Dremel) and a CAM 100 drilling system equipped with a 1 mm drill bit. Carbon and oxygen isotope values are expressed in ‰ with respect to the Vienna PDB (VPDB) standard. Sample aliquots weighing between 0.27 and 0.33 mg were dried in an oven at 105°C for 48 hours. The vials were flushed with He in order to avoid atmospheric contamination. Phosphoric acid (104%) was added to the sample. CO1 and CO8 carbonate standards were used for correction, whereas the NBS19 and the RUB internal carbonate standards were used as a quality control. Four duplicates were analyzed for every sample batch of 48 samples, in order to check for sample homogeneity. Adding the averaged internal standard deviations derived from the analysis of 9 peaks per sample, to the averaged difference of each duplicate, suggests a precision of ± 0.04‰ for δ13C and ± 0.14‰ for δ18O.

3.5. Trace element analysis CaCO3

3.5.1. LA-ICP-MS

Elemental abundances were analysed with a Thermo Finnigan Element 2 ICP-MS (Inductively Coupled Plasma – Mass Spectrometry) at the Max Planck Institute for Chemistry, Mainz, Germany. The analysis is accurate as proved by Jochum et al. (2012), who focussed on LA-ICP-MS (Laser Ablation – Inductively Coupled Plasma – Mass Spectometry) analysis on carbonates including speleothems. Samples were ablated with a New Wave UP213 laser with an energy of 15.7 J/cm2. A round, 100 μm diameter spot was used for all measurements. The relatively large spot size was necessary to average out heterogeneities within a given growth increment (Finch et al., 2003; McMillan et al., 2005). In order to avoid an effect of surface contamination the first two to five scans of every single spot analysis were discarded. Total measurement time per spot analysis was between 100 and 105 seconds. Intensities or “counts per second” were corrected for background noise, therefore all data shown

Chapter 3

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were significantly elevated above the background value and therefore above the detection limit. The NIST-612 glass reference material and the MACS3 and MACS1 carbonate reference material were measured 9-15 times equally distributed in the sequence in blocks of three individual spot analyses. The MACS1 reference material was not included in the sequence with stalagmite HK3. An averaged relative sensitivity factor (Jochum et al., 2007) from the NIST612 and MACS3 was used to derive absolute concentrations with the newest reference values (Jochum et al., 2011).

Detection limits (Jochum et al., 2012) and relative uncertainties are shown in Table 3.1. The relative uncertainty is derived from the MACS1 elemental abundances, and is hereby defined as the relative standard deviation in percent. The detection limits as published in Jochum et al. (2012) are here used as a reference value. If elemental concentrations are close to the referenced detection limit (concentration < 10 times the detection limit; Jochum et al., 2012), we assumed a relative uncertainty of 20%, unless the MACS1 values are close to the detection limit and can provide a fundament for a more solid estimate. It has to be stated that detection limits may vary by a factor of three or four per sequence depending on the measurement conditions. Note that for chalcophile/siderophile elements with low boiling points, a matrix matched calibration is necessary to avoid matrix effects (Jochum et al., 2012). Lead was therefore only corrected with the MACS3 carbonate reference material. For more information on the method, accuracy and precision the reader is referred to Jochum et al. (2007; 2011; 2012) and Mertz-Kraus et al. (2009).

Element Detection limit (ppm)*

ConcentrationMACS1

Uncertainty(1 Standard

deviation SD)

Relativeuncertainty(1RSD)**

Al 1 27.1 ± 3.5 13%Ba 0.02 106 ± 6 6%Mg 0.2 10.5 ± 0.7 7%P** 4 2.5 ± 0.2 8%Pb 0.003 102 ± 7 7%Sr 0.5 196 ± 13 7%Th 0.0002 0.01 ± 0.002 20%Ti 0.5 - ± - 20%U 0.0002 0.003 ± 0.0007 23%Y 0.01 0.06 ± 0.01 17%

Table 3.1. LA-ICP-MS detection limits, and relative uncertainty

**For elements which are close to the referenced detection limits we assumed a relative uncertainty of 20%, unless the MACS1 can provide a fundament for an estimation (for example P).

*Detection limits may vary by a factor of three or four depending on the measurement conditions, the values here were derived from Jochum et al. (2012).

3.5.2. ICP-OES

In addition to LA-ICP-MS, ICP-OES (Inductively Coupled Plasma – Optical Emission spectrometry; iCap 6500 from Thermo Electron Corporation) was conducted at the Ruhr University Bochum,

Materials and methods

35

Germany. Larger sample sizes (drilled with a 1 mm drill bit) were sampled from the same stratigraphic position as the 100 µm LA-ICP-MS spots. This in order to show that sample heterogeneity did not have an effect on the measured concentrations of Ca, Mg and Sr (chapter 4 supplement). For preparation 1.5 mg of carbonate sample material is dissolved in one ml concentrated nitric acid (suprapure, 65%), which is diluted after 24 hours by adding two ml of high-purity water. Additionally the international standard reference materials CRM 915 and CRM 916 are prepared with the same procedure. At least 8 of these standard reference materials are added to each ICP-OES run to verify the quality of the measurement.

3.6. Cave monitoring

Cave monitoring of Grotte de Piste and Grotte Prison de Chien was conducted between March 2010 and March 2012 with sampling intervals of three months (i.e., spring, summer, fall, winter). Drip sites were monitored for drip rates and drip water Mg, Sr, Ba concentrations. Drip rates were measured manually for all drip sites and continuously using an automatic drip counter (Stalagmate; Collister and Mattey, 2005). Drip water was sampled over a two day period and stored in a fridge in Morocco for the duration of the monitoring trips. Upon return to Germany, water samples for the cation analysis were acidified with 100 µl 65% HNO3 per 10 ml of water sample. Drip water was analysed for Ca, Mg, Ba, and Sr concentrations using a Vista MPX ICP-OES (Varian) at the institute for Geosciences, Heidelberg University, Germany. NIST 1643e and SPS SW2 are used as standards, the long term 1σ reproducibility is 2-3%.

Cave air CO2 concentrations were measured at fixed positions at the ceiling and at the bottom of the cave during monitoring visits in order to deduce information on cave air circulation (Bourges et al., 2006; Kowalczk and Froelich, 2010; Frisia et al., 2011). CO2 was measured with a portable Vaisala GMP 222 probe (0-2000 ppmv) coupled to a Vaisala MI 70. Typical uncertainties are ±20 ppmv plus 2% between 0 and 2000 ppmv. At CO2 concentrations >2000 ppmv the values were corrected for the offset from the “real” value. In addition, cave air temperature was measured every twelve hours using permanently installed temperature loggers (I-Buttons; DS1923#F5 and DS1922#L5), which have an uncertainty of ± 0.5°.

3.7. Statistical treatment of the data

Pearson correlation coefficients (r) have been calculated. Correlations are referred to as significant on the 1 % significance level (p-value <0.01) and r >0.5, unless stated otherwise. In addition, “Principal Component Analyses” (PCA) has been performed in chapter four (von Storch and Zwiers, 2002; Navarra and Simoncini, 2010).

A PCA identifies patterns of simultaneous variations between (in this case) different trace element time series and finds a small subspace that contains most of the variability of the complete dataset. This small subspace is formed by the principal components, which explain most of the total variance of the data. Whereas total variance is defined as the cumulative of the variance from the individual trace element time series and can thus be regarded as the total variation of the complete

Chapter 3

36

dataset. The principal components can be regarded as new time series derived from a combination of different trace element time series. A single principal component may represent a single forcing mechanism (e.g. climate aridity). Principal components are independent from each other, and are ordered in a way, such that the 1st principal component explains most of the total variance and the 2nd principal component explains the 2nd most of the total variance (von Storch and Zwiers, 2002; Navarra and Simoncini, 2010). Therefore, the higher the explained total variance by the 1st and 2nd principal components the more dominant the forcing mechanisms become. Note, there are as many principal components as dimensions in the multi-dimensional data space (e.g., the number of different trace elements). For more information on the specific application of PCA in this study see chapter four.

References

Bourges, F., Genthon, P., Mangin, A., D’Hulst, D., 2006. Microclimates of L’Aven d’Orgnac and other French limestone caves (Chauvet, Esparros, Marsoulas). International Journal of Climatology 26, 1651-1670.

Collister, C., Mattey, D., High resolution measurement of water drip rates in caves using an acoustic drip counter, American Geophysical Union Fall Meeting 2005, Abstract # PP31A-1496, 2005.

Fietzke, J., Liebetrau, V., Eisenhauer, A., Dullo, C., 2005. Determination of uranium isotope ratios by multi-static MIC-ICP-MS: method and implementation for precise U- and Th-series isotope measurements. Journal of Analytical Atomic Spectrometry 20, 395-401.

Finch, A.A., Shaw, P.A., Holmgren, K., Lee-Thorp, J., 2003. Corroborated rainfall records from aragonitic stalagmites. Earth and Planetary Science Letters 215, 265-273.

Fohlmeister, J., Kromer, B., Mangini, A., 2011. The influence of soil organic matter age spectrum on the reconstruction of atmospheric C-14 levels via stalagmites. Radiocarbon 53, 99-115.

Fohlmeister, J., Schroder-Ritzrau, A., Scholz, D., Riechelmann, D.F.C., Mudelsee, M., Wackerbarth, A., Gerdes, A., Riechelmann, S., Immenhauser, A., Richter, D.K., Mangini, A., 2012. Bunker Cave stalagmites: an archive for central European Holocene climate variability. Climate of the Past 8, 1751-1764.

Frisia, S., Fairchild, I.J., Fohlmeister, J., Miorandi, R., Spötl, C., Borsato, A., 2011. Carbon mass-balance modelling and carbon isotope exchange processes in dynamic caves. Geochimica Et Cosmochimica Acta 75, 380-400.

Füchtbauer, H., Richter, D.K., 1988. Karbonatgesteine, in: H. Füchtbauer (Eds), Sedimente und Sedimentgesteine. Schweizerbart’sche Verlagsbuchhandlung, Stuttgart, pp. 233-434.

Hodge, E., McDonald, J., Fischer, M., Redwood, D., Hua, Q., Levchenko, V., Drysdale, R., Waring, C., Fink, D., 2011. Using the (14)C bomb pulse to date young speleothems. Radiocarbon 53, 345-357.

Jochum, K.P., Stoll, B., Herwig, K., Willbold, M., 2007. Validation of LA-ICP-MS trace element analysis of geological glasses using a new solid-state 193 nm Nd : YAG laser and matrix-matched calibration. Journal of Analytical Atomic Spectrometry 22, 112-121.

Jochum, K.P., Weis, U., Stoll, B., Kuzmin, D., Yang, Q., Raczek, I., Jacob, D.E., Stracke, A., Birbaum, K., Frick, D.A., Günther, D., Enzweiler, J., 2011. Determination of Reference Values for

Materials and methods

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NIST SRM 610--617 Glasses Following ISO Guidelines. Geostandards and Geoanalytical Research doi: 10.1111/j.1751-908X.2011.00120.x,

Jochum, K.P., Scholz, D., Stoll, B., Weis, U., Wilson, S.A., Yang, Q., Schwalb, A., Börner, N., Jacob, D.E., Andreae, M.O., 2012. Accurate trace element analysis of speleothems and biogenic calcium carbonates by LA-ICP-MS. Chemical Geology 318, 31-44.

Kowalczk, A.J., Froelich, P.N., 2010. Cave air ventilation and CO2 outgassing by radon-222 modeling: How fast do caves breathe? Earth and Planetary Science Letters 289, 209-219.

Mattey, D., Lowry, D., Duffet, J., Fisher, R., Hodge, E., Frisia, S., 2008. A 53 year seasonally resolved oxygen and carbon isotope record from a modem Gibraltar speleothem: Reconstructed drip water and relationship to local precipitation. Earth and Planetary Science Letters 269, 80-95.

McMillan, E.A., Fairchild, I.J., Frisia, S., Borsato, A., McDermott, F., 2005. Annual trace element cycles in calcite-aragonite speleothems: evidence of drought in the western Mediterranean 1200-1100 yr BP. Journal of Quaternary Science 20, 423-433.

Mertz-Kraus, R., Brachert, T.C., Jochum, K.P., Reuter, M., Stoll, B., 2009. LA-ICP-MS analyses on coral growth increments reveal heavy winter rain in the Eastern Mediterranean at 9 Ma. Palaeogeography Palaeoclimatology Palaeoecology 273, 25-40.

Miao, S.J., d’Alnoncourt, R.N., Reinecke, T., Kasatkin, I., Behrens, M., Schlögl, R., Muhler, M., 2009. A Study of the Influence of Composition on the Microstructural Properties of ZnO/Al(2)O(3) Mixed Oxides. European Journal of Inorganic Chemistry 910-921.

Navarra, A. and Simoncini, V., 2010. A Guide to Empirical Orthogonal Functions for Climate Data Analysis, Springer Sciecne+Business Media.

Neuser, R.D., Bruhn, F., Götze, J., Habermann, D., Richter, D.K., 1996. Kathodolumineszenz: Methodik und Andwendung. Zeitblad Geologie Paläontologie 287-306.

Richter, D.K., Götte, T., Götze, J., Neuser, R.D., 2003. Progress in application of cathodoluminescence (CL) in sedimentary petrology. Mineralogy and Petrology 79, 127-166.

Scholz, D., Hoffmann, D.L., 2011. StalAge - An algorithm designed for construction of speleothem age models. Quaternary Geochronology 6, 369-382.

Synal, H.A., Stocker, M., Suter, M., 2007. MICADAS: A new compact radiocarbon AMS system. Nuclear Instruments & Methods in Physics Research Section B-Beam Interactions with Materials and Atoms 259, 7-13.

von Storch, H. and Zwiers, F. W., 2002. Statistical Analysis in Climate Research, 293 pp, Cambridge University Press, Cambridge, UK.

Chapter 4

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Calcite Aragonite Transitions

39

4. CLIMATE AND CAVE CONTROL ON PLEISTOCENE/HOLOCENE CALCITE-TO-ARAGONITE TRANSITIONS IN SPELEOTHEMS FROM MOROCCO: ELEMENTAL AND ISOTOPIC EVIDENCE

Jasper A. Wassenburg, Adrian Immenhauser, Detlev K. Richter, Klaus Peter Jochum, Jan Fietzke, Michael Deininger, Manuela Goos, Denis Scholz and Abdellah Sabaoui

This chapter has been published in Geochimica et Cosmochimica Acta, 92 (2012), 23-47

DOI: 10.1016/j.gca.2012.06.002

Abstract

The occurrence of aragonite in speleothems has commonly been related to high drip water Mg/Ca ratios, because Mg is known to be a growth inhibitor for calcite. Laboratory aragonite precipitation experiments, however, suggested a more complex array of controlling factors. Here, we present data from Pleistocene to Holocene speleothems collected from both a dolostone and a limestone cave in northern Morocco. These stalagmites exhibit both lateral and stratigraphic calcite-to-aragonite transitions. Aragonite fabrics are well-preserved and represent primary features. In order to shed light on the factors that control alternating calcite and aragonite precipitation, elemental (Mg, Sr, Ba, U, P, Y, Pb, Al, Ti and Th) abundances were measured using LA-ICP-MS, and analysed with Principal Component Analysis. Samples were analyzed at 100–200 µm resolution across stratigraphic and lateral transitions. Carbon and oxygen isotope ratios were analysed at 100 µm resolution covering stratigraphic calcite-to-aragonite transitions. Results show that the precipitation of aragonite was driven by a decrease in effective rainfall, which enhanced prior calcite precipitation. Different geochemical patterns are observed between calcite and aragonite when comparing data from the Grotte de Piste and Grotte Prison de Chien. This may be explained by the increased drip water Mg/Ca ratio and enhanced prior aragonite precipitation in the dolostone cave versus lower drip water Mg/Ca ratio and prior calcite precipitation in the limestone cave. A full understanding for the presence of lateral calciteto-aragonite transitions is not reached. Trace elemental analysis, however, does suggest that different crystallographic parameters (ionic radius, amount of crystal defect sites, adsorption potential) may have a direct effect on the incorporation of Sr, Mg, Ba, Al, Ti, Th, U and possibly Y and P.

4.1. Introduction

Speleothems – particularly stalagmites and flowstones - are established archives of continental climate change (Dorale et al., 1992; Neff et al., 2001; Johnson et al., 2006). Processes determining their isotopic and elemental composition, however, are complex (Fairchild and Treble, 2009; Lachniet, 2009). Whereas most stalagmites currently used for palaeo-climate reconstruction are calcitic, detailed studies using aragonitic stalagmites are less abundant (Holmgren et al., 2003).

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40

Aragonitic stalagmites or flowstones are often avoided because aragonite is thermodynamically instable and subject to post-depositional alteration to calcite (Frisia et al., 2002; Martin-Garcia et al., 2009). Climate proxy data from aragonite archives yield promising results, however, when screening for geochemical and petrographical alteration documents well-preserved aragonite fabrics (Finch et al., 2003; Cosford et al., 2008; Li et al., 2011).

Nevertheless, poor knowledge of the controls on aragonite precipitation in cave depositional environments remains a significant obstacle in aragonite archive research. The processes involved are complex and the controlling factors may change over time between different caves, within a single cave and even for an individual drip site (Railsback et al., 1994; Frisia et al., 2002; McMillan et al., 2005). From field studies and laboratory experiments, it is suggested that high drip water Mg/Ca ratios (molar Mg/Ca ratio > 1.1) are an important factor in inducing aragonite precipitation (Frisia et al., 2002; McMillan et al., 2005; Fairchild and Treble, 2009) by inhibiting the formation of calcite (Fernández-Díaz et al., 1996; Davis et al., 2000). Other controlling factors include (i) evaporation within the cave combined with elevated cave air temperatures (Railsback et al., 1994); (ii) crystal nucleation parameters combined with air temperature (Kawano et al., 2009); (iii) CO2 degassing rates (Fernández-Díaz et al., 1996); (iv) low CaCO3 fluid saturation states combined with high fluid Mg/Ca ratios (De Choudens-Sanchez and Gonzalez, 2009); or (v) CO3

2- controlled kinetic effects (Zuddas and Mucci, 1998).

Processes affecting drip water Mg/Ca ratio include prior calcite precipitation (PCP), karst water residence times, incongruent dissolution of dolomite and selective leaching of Mg with respect to Ca (Fairchild et al., 2000). Prior calcite precipitation occurs when the water encounters a gas phase with a lower pCO2. Within the karst aquifer, the space occupied by gas increases under more arid conditions, and thus enhances PCP. Increased water residence times potentially affect the amount of dissolution of Mg-rich dolomite, whilst saturation with respect to calcite is reached earlier compared to dolomite. Therefore, increasing water residence times increases the ratio of dolomite to calcite dissolution. Although incongruent dissolution of dolomite and selective leaching may affect drip water Mg/Ca ratios as well, the potential effects of the former two processes has lead many authors to interpret the presence of aragonite in caves as a consequence of more arid climatic conditions or seasonal aridity (Railsback et al., 1994; McMillan et al., 2005). This may also result in increased evaporation rates of the thin water film on a stalagmite surface. As shown by Frisia et al. (2002), the local karst hydrology plays an important role as well. For example, changes in the aquifer water pathway may affect the encountered amount of gas filled voids, affecting PCP and the amount of encountered dolomite.

Specific elemental patterns in speleothems have the potential to shed light on these complex processes and pathways (Fairchild et al., 2000; Treble et al., 2003; Borsato et al., 2007). A positive correlation between Mg, Sr and Ba might indicate the existence of PCP in the karst aquifer or at the ceiling of the cave (Tooth and Fairchild, 2003; McMillan et al., 2005; Wong et al., 2011), whereas P, Y, Pb and possibly U indicate organic material, which could be flushed into the cave system from the soil (Treble et al., 2003; Borsato et al., 2007; Zhou et al., 2008b). These trace elements have the potential to shed light on microbial activity in the soil zone and or the amount of vegetation decay (Fairchild et al., 2001). It has also been noted that different transport mechanisms may play a role (colloidal,

Calcite Aragonite Transitions

41

particles, free ions) and that this affects the way these elements are incorporated into the stalagmite (Borsato et al., 2007; Hartland et al., 2012). Furthermore, clay minerals may be detected by high peak concentrations of Al, whereas clay minerals can adsorb a range of trace elements including Th (Dorale et al., 2004) and may therefore obscure the climate signal inferred from other trace elements.

Here, we present, discuss and interpret a wide range of elemental data including Mg, Sr, Ba, U, Al, Ti, Th, Pb, P and Y as well as carbon and oxygen isotope ratios from three Pleistocene to Holocene stalagmites. The stalagmites were collected in different caves in the Middle Atlas range of Morocco and are characterized by well-preserved, aragonite-to-calcite (Ar-Cc), and calcite-to-aragonite (Cc-Ar) transitions within individual speleothems. The aim of this study is threefold: first, to present high-resolution elemental and isotope transects across aragonite-to-calcite transitions; second, to provide tentative interpretations of speleothem aragonite data in a process-oriented context; third to assess the significance of Ar-Cc and Cc-Ar transitions as archives of past climate change.

4.2. Case setting

4.2.1. Present day climate

With respect to its climatic setting, Morocco represents a complex and interesting study area as it is bordered by the North Atlantic to the west, the Mediterranean Sea to the north-east and the Sahara desert to the south-east. Morocco is characterized by the west-south-west to east-north-east trending Atlas mountain range subdivided in the Middle Atlas to the north-east, the High Atlas to the south-west and the Anti-Atlas to the south. The three speleothems discussed here are from caves located in the north-west of the Middle Atlas (Fig. 4.1a), according to Knippertz et al. (2003) this area falls within the Atlantic domain of Morocco. The present-day climate in the Middle Atlas region is characterized by dry summers and wet winters, related to the strength and position of the Azores subtropical high. Annual rainfall depends on altitude, with mountain ranges being wetter relative to lowlands. For the period 1999-2008, average annual rainfall in the city of Taza, situated at 450 m above sea level and located in the vicinity of Grotte Prison de Chien (Fig. 4.1b), was 468 mm. Data were collected by the weather station in Taza and made available by the Institute for Geophysics and Meteorology, University of Cologne, Germany. At Bab Bou Idir, situated at an altitude of 1500 m and located near the second cave site (Fig. 4.1b), an annual average 711 mm of rainfall was measured for the period 1999-2008. On decadal timescales, the North Atlantic Oscillation (NAO) plays an important role on the amount of winter rainfall (Ward et al., 1999). Decreasing rainfall amounts in the Atlantic and Mediterranean domains of Morocco after the 1970’s were related to a dominant positive NAO mode (Ward et al., 1999).

4.2.2. Cave parameters

The stalagmites were retrieved from two caves in the Middle Atlas. These caves are referred to as “Grotte Prison de Chien” (Dog’s prison cave), situated at 360 m above sea level (Fig. 4.1b-c and 2a), and “Grotte de Piste” (Gravel road cave), situated at 1260 m above sea level (Fig. 4.1b-c and 4.2b-c).

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1

Taze

kka

5000 m

10 km

SE

Tanger

RabatCasablanca

Fes

ErrachidiaMarrakech

Ouarzazate

AA

HA

MA

Rif0

2000

NWTahla

Massifde Tazekka Maghraoua J. Ouadda

21

MaghraouaTahla

4°

34°2

1b

ca

Taza

2 3 4 5 6 7 89 10

Bab Bou Idir

4000

0 100 200 300

3000

2000

1000

0

m

Fig. 4.1. Regional setting of Northern Morocco bordered by the North Atlantic to the west and the Mediterranean Sea to the north. MA =Middle Atlas; HA = High Atlas; AA = Anti Atlas. (A) Map modified after I. Sadalmelik. Location of study area indicated by square. (B) Geological map modified after Taous et al. (2009), stars indicate location of caves. 1 = Grotte Prison de Chien; 2 = Grotte de Piste. (C) Geological cross section modified after Taous et al. (2009) with indication of relative cave positions. Key to colour scheme in panels B and C: 1 = Palaeozoic schists and sandstones; 2 = Permian, Triassic clays and basalts; 3 = Lower Jurassic dolostones and limestones; 4 = Middle and Upper Jurassic limestones and marls; 5 = Middle Jurassic marls; 6 = Miocene units; 7 = Pliocene/Quaternary units; 8 = Quaternary basalts; 9 = Quaternary and recent units; 10 = fault structures.

Grotte Prison de Chien lies within a predominantly calcitic (subordinate dolomite content) host rock - as based on XRD analysis - and is formed within Liassic brecciated marine limestones (Fig. 4.1b-c; (Sabaoui et al., 2009; Taous et al., 2009). The cave is overlain by ca. 20 m of host rock and has several open connections with the outside atmosphere (Fig. 4.2a). The vegetation is restricted to small shrubs, locally small trees and grasses. Approximately 50% of the land surface above the cave is covered by up to 30 cm of lateritic soil; Elsewhere, the limestone host rock is exposed at the land surface. The cave has a steeply downward sloping entrance that is approximately 7 m in diameter. During winter, a noticeable draft of incoming air is present. Cave air temperature varies on a seasonal scale between 12.2 °C in winter to 15.7 °C in summer, as based on one year of temperature measurements with a resolution of 12 h. These data suggest that the cave is dynamically ventilated.

Grotte de Piste lies within a Lower Jurassic south-east dipping, dominantly dolomitic host rock with spatially limited limestone intervals (Fig. 4.1b-c; (Sabaoui et al., 2009; Taous et al., 2009). The vegetation above the cave consists of small (i.e., <2 m tall) oak trees, shrubs and grasses. About 60% of the surface is covered by up to 20 cm of soil, elsewhere the dolomite host rock is exposed at the land surface. The drip water entering the cave is of local origin due to the surface morphology above the cave, forming a topographic high, and the elevated position of the cave at the slope. The entrance of the cave is about 3 m in diameter and has a steep downward gradient (Fig. 4.2b). Cave

Calcite Aragonite Transitions

43

100 m

HK3

Main entrance

2nd entrance

3rd entrance

a

HK1

GP2Entrance

2nd level

20 m

b

c GP2

10 m 2nd level Entrance

GC Map

GP Map

GP Cross section

Fig. 4.2. Cave maps and cross sections. (A) Map view of Grotte Prison de Chien (GC). (B) Cross section view of Grotte de Piste (GP). (C) Map view of Grotte de Piste. Sampling locations of stalagmites HK3, HK1 and GP2 are indicated.

ventilation is evident from the seasonally varying cave air temperature, which ranges between 10.7 (winter) and 12. 3°C (summer) at the bottom of the cave and between 11.8 °C (winter) and 13.3 °C (summer) at the 2nd cave level (Fig. 4.2b-c).

4.3. Materials and methods

Mineralogies of cave hostrock and speleothems were determined by X-ray diffraction (XRD) at the Ruhr University Bochum, Germany. Approximately 20 mg of sample powder was drilled for XRD. Ten percent of quartz was added to the sample powder as a standard in order to derive offsets in the 104 calcite peaks, and estimate the Mg content within the crystal lattice in mol % (Füchtbauer and Richter, 1988). Subsequently the samples were homogenised in an agate mortar before being analysed. X-ray diffraction patterns were recorded with a Pananalytical MPD diffractometer, equipped with a copper tube, 0.5° divergent and antiscatter slits, a 0.2-mm high receiving slit, incident and diffracted beam 0.04 rad soller slits, and a secondary graphite monochromator as documented in Miao et al. (2009). In the terminology applied here, speleothem fabrics are referred to as “calcitic” if they contain ≥99 % calcite with the remaining bulk fabric being formed by aragonite and subordinate amounts of clay minerals. Conversely, the term “aragonitic” implies ≥98 % aragonite with the remaining bulk fabric being formed by calcite and subordinate amounts of clay minerals. Similar to this, cave host rocks are referred to as “limestone” if they are formed by at least 70 % calcite, whereas the label “dolostone” is used for a host rock containing at least 96 % dolomite.

The three stalagmites examined in this study were sampled during a field campaign in March 2009, and were not active at the time of collection. Stalagmite HK1 was collected from Grotte Prison de Chien (Fig. 4.2a). HK1 is 56 cm long and 13 cm wide at its base (Fig. 4.3a). The stalagmite exhibits a mainly calcitic core with laterally increasing amounts of aragonite towards the flanks of the

Chapter 4

44

HK3-ACHK3-CA

5 mm

Trace element transectTrench for C and O isotopes

XRD

MIS 2

Stalagmite HK3

23.5 ± 0.2ka BP

b

100 mm

10 mm

Stalagmite GP2

Ar

Cc

Trace element transectTrench for C and O isotopes

XRD

HoloceneHiatus

11.5 ± 0.2ka BP

11.1 ± 0.1ka BP

cTrace elementtransect

CA2

CA1

Stalagmite HK1

36.5 ± 0.3 Ka BP

33.4 ± 0.3Ka BP

XRD50 mm

Ar

Cc

Ar

Cc

2 mm

2 mm

a

Cc

Ar

Cc

Ar

Ar

Cc

Cc

CcAr

20 mm27.5 ± 0.2ka BP

HoloceneHiatus

14.4 ± 0.1ka BP

Fig. 4.3. Images of cut and polished speleothems. Positions of geochemical sampling transects for elemental abundances (black lines), isotope ratios (grey shading), XRD analysis (star), and 230Th/U data (arrows) are indicated. (A) Stalagmite HK1. (B) Stalagmite HK3. (C) Stalagmite GP2.

stalagmite. Therefore, this speleothem allows for the study of lateral changes in calcite and aragonite within single growth layers.

Stalagmite HK3 was also collected from Grotte Prison de Chien, but from a different locality (Fig. 4.2a). HK3 is 26 cm long and 6 cm wide at its base (Fig. 4.3b). The stalagmite exhibits four aragonite layers alternating stratigraphically with calcite intervals. Two transitions were studied here, one Ar-Cc transition (27.4-17.5 mm) and one Cc-Ar transition (10.1-0.2 mm).Stalagmite GP2 formed part of a column and was collected from Grotte de Piste, at the 2nd level of the cave (Fig. 4.2b-c). This speleothem is approximately 100 cm long and 8 cm wide at the base and exhibits one stratigraphic transition from calcite to aragonite.

The three stalagmites were cut longitudinally and surfaces were polished. Macroscopically, calcite intervals appear darker whereas aragonite intervals are whitish in appearance (Fig. 4.3), Cc-Ar and Ar-Cc mineralogical transitions are sharp (i.e. take place over distances of some tens of microns only; Fig. 4.3).

U-series dating of the speleothems was conducted at the IFM GEOMAR, Kiel, Germany, with an AXIOM MIC-ICP-MS (multiple ion counting inductively coupled plasma mass spectrometer). Further methodological details can be found in Fietzke et al (2005).

Polished thin sections were first examined under a polarisation microscope and thereafter sputtered with gold and examined under a cathodoluminescence microscope at the Ruhr University Bochum, Germany. The cathodoluminescence microscope is equipped with a hot cathode (Neuser et al., 1996). Beam current densities were between 5 and 10 μA/mm2, with an acceleration potential of 14 kV. Carbonate detrital material containing traces of Mn range in color from yellow to red under the cathodoluminescence microscope, therefore it can easily be distinguished from the low-Mn speleothem calcite (dark blue) and the green aragonite (Richter et al., 2003). Other types of

Calcite Aragonite Transitions

45

inclusions like organic material or clay minerals cannot be distinguished with this method. Important to distinguish from each other is the intercrystalline calcite within an aragonite layer which is formed in situ, and carbonate detrital material, which is derived from an allochthonous source. It is difficult to distuinguish the mineralogy of the carbonate detrital material, therefore we will continue to use the term carbonate detrital material.

Carbon and oxygen isotope analyses were performed at the Ruhr University Bochum, Germany, with a Gasbench coupled to a Finnigan MAT 253 mass spectrometer. For sampling of the stratigraphical Cc-Ar and Ar-Cc transitions, a micromill (Merchantek, Esi-New Wave) equipped with a flat-tipped, 0.5 mm diameter dentist drill was used. Two 1-mm-deep trenches were drilled with a width of 5 mm (HK3) and 10 mm (GP2). The Ar-Cc and Cc-Ar transitions in stalagmite HK3 (Fig. 4.3b) were each sampled at a resolution of 100-200 µm over a 4 mm traverse. Sampling of these intervals was extended to both older and younger growth at 500 µm resolution. In stalagmite GP2, the interval 3 mm beneath to 1 mm above the transition was sampled at 100 µm resolution (Fig. 4.3c). This sampling transect was extended with a hand-held drill at 1 mm resolution in order to cover the same interval analysed for the trace elements.

Carbon and oxygen isotope values are expressed in ‰ with respect to the Vienna PDB (VPDB) standard. Sample aliquots weighing between 0.27 and 0.33 mg were dried in an oven at 105 °C for 48 hours. The vials were flushed with He in order to avoid atmospheric contamination. Phosphoric acid (104%) was added to the sample. CO1 and CO8 carbonate standards were used for correction, whereas the NBS19 and the RUB internal carbonate standards were used as a quality control. Four duplicates were analyzed for every sample batch of 48 samples, in order to check for sample homogeneity. Adding the averaged internal standard deviations derived from the analysis of nine peaks per sample, to the averaged difference of each duplicate, suggests a precision of ±0.08‰ for δ13C in both stalagmites and ±0.09‰ (stalagmite GP2) and ±0.13‰ (stalagmite HK3) for δ18O.

Elemental abundances (Mg, Sr, Ba, P, Y, Pb, U, Th, Al, Ti) were analysed with a Thermo Finnigan Element 2 ICP-MS at the Max Planck Institute for Chemistry, Mainz, Germany. The analysis is accurate as proved by Jochum et al. (2012), who focussed on LA-ICP-MS analysis on carbonates including speleothems. Samples were ablated with a New Wave UP213 laser with an energy of 15.7 J/cm2. A round, 100 μm diameter spot was used for all measurements. The relatively large spot size was necessary to average out heterogeneities within a given growth increment (Finch et al., 2003; McMillan et al., 2005). In order to avoid an effect of surface contamination the first two to five scans of every single spot analysis were discarded. Total measurement time per spot analysis was between 100 and 105 seconds. Intensities or “counts per second” were corrected for background noise, therefore all data shown were significantly elevated above the background value and therefore above the detection limit. The NIST-612 glass reference material and the MACS3 and MACS1 carbonate reference material were measured 9-15 times equally distributed in the sequence in blocks of three individual spot analyses. The MACS1 reference material was not included in the sequence with stalagmite HK3. An averaged relative sensitivity factor (Jochum et al., 2007) from the NIST612 and MACS3 was used to derive absolute concentrations with the newest reference values (Jochum et al., 2011).

Detection limits (Jochum et al., 2012) and relative uncertainties are shown in Table 4.1. The

Chapter 4

46

relative uncertainty is derived from the MACS1 elemental abundances, and is hereby defined as the relative standard deviation in percent (Table 4.1). The detection limits as published in Jochum et al. (2012) are here used as a reference value. If elemental concentrations are close to the referenced detection limit (concentration <10 times the detection limit; Jochum et al., 2012), we assumed a relative uncertainty of 20%, unless the MACS1 values are close to the detection limit and can provide a fundament for a more solid estimate. It has to be stated that detection limits may vary by a factor of three or four per sequence depending on the measurement conditions. In addition, the measured MACS1 elemental concentrations and uncertainties were very similar to earlier published MACS1 values (Munksgaard et al., 2004; Mertz-Kraus et al., 2009; Table S4.1 in supplementary material). A comparison between parallel tracks of ICP-OES and LA-ICP-MS trace element data across the Cc-Ar transition in stalagmite GP2 shows that potential sample heterogeneity does not play a role (see Fig. S4.1 in supplementary material). Note that for chalcophile/siderophile elements with low boiling points, a matrix matched calibration is necessary to avoid matrix effects (Jochum et al., 2012). Lead was therefore only corrected with the MACS3 carbonate reference material. For more information on the method, accuracy and precision the reader is referred to Jochum et al. (2007; 2011; 2012) and Mertz-Kraus et al. (2009).

Element Detection limit (ppm)*

ConcentrationMACS1

Uncertainty(1 Standard

deviation SD)

Relativeuncertainty(1RSD)**

Al 1 27.1 ± 3.5 13%Ba 0.02 106 ± 6 6%Mg 0.2 10.5 ± 0.7 7%P** 4 2.5 ± 0.2 8%Pb 0.003 102 ± 7 7%Sr 0.5 196 ± 13 7%Th 0.0002 0.01 ± 0.002 20%Ti 0.5 - ± - 20%U 0.0002 0.003 ± 0.0007 23%Y 0.01 0.06 ± 0.01 17%

Table 4.1. LA-ICP-MS detection limits, and relative uncertainty

**For elements which are close to the referenced detection limits we assumed a relative uncertainty of 20%, unless the MACS1 can provide a fundament for an estimation (for example P).

*Detection limits may vary by a factor of three or four depending on the measurement conditions, the values here were derived from Jochum et al. (2012).

In order to compare trace element transects with C and O isotope transects, the exact position of each Cc-Ar and Ar-Cc transition was used as a datum. For stalagmite GP2, the position of the trace elemental transect was parallel to the isotopic transect at a distance within 5 mm (Fig. 4.3c). For stalagmite HK3, the trace element transects were measured in the same traverse as the isotope data (Fig. 4.3b).

Soil trace element concentrations were analysed from compressed powders consisting of 8 g

Calcite Aragonite Transitions

47

of sample material and 1 g of ELVACITE resin. Analysis was performed on a wavelength dispersive X-ray fluorescence spectrometer (WD-XRF; Philips PW 2404) with a Rh-tube. Two soil samples were analysed for Grotte de Piste and one soil sample was analysed for Grotte Prison de Chien.

Pearson correlation coefficients (r) have been calculated between all individual elements to identify similar properties of the trace element time series. Correlations are referred to as significant on the 1 % significance level (p-value<0.01) and r > 0.5, unless stated otherwise. For an overview of all correlation coefficients and significance levels, the reader is referred to Table S4.2-S4.6 in the supplementary material. In addition, “Principal Component Analyses” (PCA) has been performed (von Storch and Zwiers, 2002; Navarra and Simoncini, 2010). It is acknowledged that PCA represents a non-trivial and abstract statistical method. Therefore a basic explanation of the significance of PCA for the research shown here is given below.

A PCA identifies patterns of simultaneous variations between (in this case) different trace element time series and finds a small subspace that contains most of the variability of the complete dataset. This small subspace is formed by the principal components, which explain most of the total variance of the data. Whereas total variance is defined as the cumulative of the variance from the individual trace element time series and can thus be regarded as the total variation of the complete dataset. The principal components can be regarded as new time series derived from a combination of different trace element time series. A single principal component may represent a single forcing mechanism (e.g. climate aridity). Principal components are independent from each other, and are ordered in a way, such that the 1st principal component explains most of the total variance and the 2nd principal component explains the 2nd most of the total variance (von Storch and Zwiers, 2002; Navarra and Simoncini, 2010). Therefore, the higher the explained total variance by the 1st and 2nd principal components the more dominant the forcing mechanisms become. Note, there are as many principal components as dimensions in the multi-dimensional data space (e.g., the number of different trace elements).

In this study PCA has been used to visualize correlation patterns between different groups of trace elements by plotting the correlation coefficients of the individual trace element time series with respect to the first and second principal components. In these plots trace elements that are close to each other are in general positively correlated. When trace elements plot on opposite sites, they are generally negatively correlated to each other. In addition PCA has been used to identify the dominant forcing mechanisms affecting the trace element composition of the stalagmites. The advantage of studying PCA in addition to Pearson Correlation Coefficients is that the shape of each principal component versus distance (i.e., time) can be examined. Thus, if a principal component is identified as a dominant forcing mechanism (e.g., climate aridity or effective rainfall) higher values of the principal component represent higher climate aridity or lower effective rainfall.

In order to be able to compare the trace element time series, and to account for the different amplitudes in their variability, the data was normalized in a way that the average of each trace element time series is 0 and the standard deviation of each trace element time series is 1 (Navarra and Simoncini, 2010). The PCA in this study was performed using MATLAB.

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48

4.4. Results

4.4.1. 230Th/U-dating

Table 4.2 presents all relevant 230Th/U ages. For dating, most of the sample material was collected from the aragonitic portion of the stalagmites. Since the aragonite contains relatively high amounts of the parent nuclide U (in the order of ppm’s), this results in small analytical errors. For all samples, the 230Th/232Th activity ratio is relatively high, indicating a minimum amount of initial detrital Th in the samples (Table 4.2).

The base of stalagmite HK3 is dated at 27.5 ka BP, the top revealed an age of 4.2 ka BP. This stalagmite has a hiatus between 23.5 and 7.7 ka BP (Table 4.2; Fig. 4.3b). The four aragonite layers occur in a time window between 27.5 and 23.5 ka BP. The average precipitation rate in this interval is 17 μm/a. Therefore, a 100 μm spot size corresponds to on average 5.7 years per sample.

The base of stalagmite HK1 revealed an age of 36.5 ka, the top was dated 18.9 ka BP. The lateral calcite-to-aragonite transitions studied here were dated 36.5 (base) and 33.4 (top) ka BP (Table 4.2).

Stalagmite GP2 has been dated between 97.7 ka (base) and 2.5 ka (top) BP, a hiatus exists between 44.8 and 11.5 ka BP. At around 2.5 ka BP, the upward growing stalagmite and the downward growing stalactite connected. The calcite-to-aragonite transition was dated between 11.5 (base) and 11.1 (top) ka BP (Table 4.2). During this time period, the average growth rate was 40 μm/year, thus a 100 μm spot size corresponds to ~2.5 years.

Sample Mineralogy Depth (mm) Initial (234U/238U)

GP2U3.1 Aragonite 7 1.485 ± 0.002 5345 ± 48 6.000 ± 0.012 6.04 2.78 ± 0.02GP2U1.3 Aragonite 582 1.374 ± 0.002 74688 ± 2131 7.000 ± 0.010 7.19 11.11 ± 0.06GP2U1.2 Calcite 597 0.013 ± 0.000 380 ± 6 7.050 ± 0.030 7.25 11.49 ± 0.17GP2U1.1 Calcite* 613 0.047 ± 0.000 828 ± 4 5.127 ± 0.011 6.25 44.77 ± 0.57GP2U1 Calcite 987 0.029 ± 0.000 9636 ± 1104 5.624 ± 0.025 6.44 97.74 ± 0.98HK3U7 Calcite 6 0.234 ± 0.000 82 ± 1 1.313 ± 0.003 1.32 4.24 ± 0.05HK3U3 Calcite 95 0.239 ± 0.000 52 ± 0 1.430 ± 0.002 1.44 7.66 ± 0.07HK3U2 Aragonite 156 6.340 ± 0.010 3710 ± 19 1.358 ± 0.003 1.38 23.53 ± 0.17

HK3U1.1 Aragonite 186 36.996 ± 0.068 3255 ± 11 1.020 ± 0.003 1.02 14.36 ± 0.09HK3U1 Aragonite 224 10.169 ± 0.020 13363 ± 107 1.326 ± 0.003 1.35 27.48 ± 0.20HK1U6 Aragonite 16 12.536 ± 0.025 15662 ± 165 1.260 ± 0.003 1.27 18.87 ± 0.14HK1U2 Aragonite 444 11.041 ± 0.025 261630 ± 29276 1.200 ± 0.003 1.22 33.41 ± 0.29HK1U1 Calcite 531 0.353 ± 0.000 3088 ± 118 1.250 ± 0.003 1.28 36.47 ± 0.26

*Based on macroscopic observation

Table 4.2. Results from U/Th dating

Age (ka)

For the correction of detrital Th230 a Th230/Th232 activity ratio of 0Decay constants used: λ230 = 9.158 X 10-6 y-1, λ232 = 4.9475 X 10-11 y-1, λ234 = 2.8263 X 10-6 y

238U (ppm) (230Th/232Th) (234U/238U)

4.4.2. Soil mineralogy and trace element composition

At present, the soil above Grotte Prison de Chien consists of organic plant debris with mineral components of muscovite, kaolinite in which quartz is volumetrically dominant. Trace element concentrations of the soil are shown in Table 4.3. Both muscovite (alkaline earths) and kaolinite

Calcite Aragonite Transitions

49

(alkalis, alkaline earths) may act as a source material for a range of trace elements, suggesting that the soil is an important source in addition to the cave host rock. For Grotte de Piste, the main mineral composition of the soil consists of quartz, muscovite, chlorite, albite, kaolinite and unspecified Fe-oxides/hydroxides. This mineralogical composition again suggests that trace elements in speleothems could be provided by the soil in addition to the cave host rock. Table 4.3 lists trace element concentrations of the soil above Grotte de Piste. It is acknowledged that mass balance calculations of soil-derived versus cave host rock-derived elements might provide useful insights. Given the lack of quantitative data from leaching experiments tailored to the specific geological conditions found in the study areas, however we conclude that this approach is beyond the scope of our work.

Table 4.3. Soil trace element concentrationsGrotte Prison de Chien

Element SGC 1 SGP1 SGP2

Al2O3 (%) 19.82 19.43 19.15TiO2 (%) 1.73 2.16 2.16MgO (%) 1.12 3.46 3.06P2O5 (%) 0.99 0.48 0.28Pb (ppm) 63 102 73Th (ppm) 16 19 15Y (ppm) 54 48 47U (ppm) 3 7 7Sr (ppm) 82 75 66Ba (ppm) 349 292 256

Grotte de Piste

4.4.3. Stalagmites HK1 and HK3 (Grotte Prison de Chien)

4.4.3.1. Petrography

In speleothem HK1, both calcite and aragonite was identified by XRD. Calcite layers contain up to 1.9 mol-% MgCO3, whereas intercrystalline calcite within the aragonite contains up to 1.3 mol-% MgCO3. Examination from a thin section of a lateral calcite-to-aragonite transition revealed that (i) the mineralogy of both carbonate phases is primary and (ii) no petrographic evidence for secondary dissolution or calcitization of aragonite fabrics was found (Fig. 4.4a-b). Within the calcite crystals relict aragonite needles cannot be identified, note that the thin section was taken from a position off the growth axis, therefore a dominant growth direction cannot be observed in this thin section.

In speleothem HK3, both calcite and aragonite were identified by XRD (Fig. 4.3b). The calcite layers contain up to 3.25 mol-% MgCO3, whereas the intercrystalline calcite within the aragonite layers contains up to 4 mol-% MgCO3. Thin sections across Ar-Cc and Cc-Ar transitions reveal a fibrous morphology of aragonite. The fibres have a length-to-width ratio >6. Furthermore, a sweeping extinction across several crystals is observed under the microscope with crossed nichols. This is in agreement with acicular fabrics as described in Frisia and Borsato (2010). Figure 4c-j gives an overview of the observed fabrics. Inclusions of carbonate detrital material are evenly distributed in the aragonite and increase in abundance close to the flank of the stalagmite (Fig. 4.4j) as evidenced by the yellowish to red spots under cathodoluminescence microscopy (Fig. 4.4d; f and j). Solid inclusions forming layers were not observed. Near the Ar-Cc transition, the abundance of intercrystalline calcite

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Fig. 4.4. Stalagmite HK1 and HK3. Thin section petrography. Red arrows indicate transitions. Calcite is blue, aragonite is green under cathodoluminescence. (A and B) Lateral calcite (Cc) to aragonite (Ar) transition stalagmite HK1. (A) View under plane polarized light. (B) As A under crossed nichols. Thin section was taken from a position off the growth axis of stalagmite HK1, therefore calcite does not show a clear growth direction. (C–J) Petrography stalagmite HK3. (C) Overview of aragonite (dark; Ar) to calcite (light; Cc) transition under plane polarized light. (D) Same as in C, under cathodoluminescence. In the transition interval from aragonite (Ar) towards calcite (Cc) increasing abundance of carbonate detrital material is indicated by increased abundance of yellowish to red spots. (E) Overview of calcite (Cc) to aragonite (Ar) transition under plane polarized light. Porosity (light brown) in calcite is visible. (F) Same section as in E under cathodoluminescence. Porosity (grey; Pr) in calcite is visible. (G) Horizontal layering in calcitic portion under plane polarized light. Red line indicates a distinct transition. (H) As G but under cathodoluminescence. Layering is formed by luminescent detrital carbonate particles and micro- and macro-pores (Pr) and possibly non luminescent material. (I) Columnar to elongated columnar calcite crystals with high undulosity under crossed nichols (Un). Undulosity points to primary nature of the calcite. (J) Cathodoluminescence image taken close to the flank of stalagmite HK3 showing the increased abundance of carbonate detrital material (yellowish to red spots) with slower growth.

Calcite Aragonite Transitions

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between aragonite fibres and the amount of carbonate detrital material both increase (Fig. 4.4d). Under the cathodoluminescence microscope, the carbonate detrital material appears as yellowish to red spots respectively (Richter et al., 2003; Fig. 4.4d; f; h and j).

The calcite crystals forming speleothem HK3 are characterized by columnar to elongated columnar fabric (Frisia and Borsato, 2010). A sweeping extinction across multiple crystals and within every individual crystal (undulosity) is observed under crossed nichols (Fig. 4.4i). Based on their characteristic extinction pattern, these calcites represent radiaxial fibrous fabrics, which are characterized by crystals with converging C-axes in the direction of growth (Neuser and Richter, 2007; Richter et al., 2011). The radiaxial calcites in sample HK3 contains carbonate detrital material as evidenced by the yellowish to red spots under the cathodoluminescence microscopy (Fig. 4.4h) and are characterized by layers of macro- and micro-pores (Fig. 4.4g; h). Neither crystals with round features, nor relicts of aragonite needles within calcite crystals, nor blocky calcite lacking a dominant growth direction has been observed (Fig. 4.4). Therefore, evidence for dissolution or recrystallisation of aragonite is lacking, which is considered solid evidence that the aragonite represents a primary fabric.

4.4.3.2. Geochemistry

Two lateral Cc-Ar transitions within individual growth increments in stalagmite HK1 were analysed in order to assess differences in geochemical concentrations across these intervals. Analytical results are presented in Fig. 4.5. Trends within the calcite or aragonite intervals may be induced by the fact that the trace element transect was not entirely perpendicular to the growth axis. Across the lateral Cc-Ar transitions, however, Mg concentrations decrease approximately by a factor of 60-90, Ba by a factor of 4-5, Sr by a factor of 7-9 and U by a factor of 40-60. In addition, P and Y increase as well, whereas Pb and Al concentrations remain similar (Fig. 4.5). The elements Ti, and Th were not significantly elevated above background level during measurement. Therefore, Ti and Th are not shown in figure 4.5.

Stalagmite HK3 exhibits four aragonite layers alternating with calcitic intervals that range in age between 27.5 and 23.5 ka BP. Barium, Sr, U (Fig. 4.6), Al and Ti (Fig. 4.7) display a distinct change within only 100s of μm across the transitions. With regard to P, Y (Fig. 4.6) and Pb (Fig. 4.7) shifts in elemental abundance are only present across Ar-Cc transitions. Magnesium shows a gradually increasing concentration at the Ar-Cc transition, but a very pronounced shift at the Cc-Ar transition. Carbon and oxygen isotope ratios decrease across the Ar-Cc transition, whereas especially carbon isotope ratios increase at the Cc-Ar transition (Fig. 4.6).

In the aragonite section of the Ar-Cc transition, the total variation in the data explained by the first two principal components is 64%. The 1st principal component is made up by Al, Pb, Mg and Sr and U and the 2nd principal component is made up by P and Y (Fig. 4.8a). Aluminium and Pb are strongly correlated to each other, but only weakly correlated to Mg. Strontium is positively correlated to U and weakly correlated to P (Fig. 4.8a). Negative correlations exist between U and Al and Pb. Phosphorus and Y are not correlated to each other. Carbon and oxygen isotope values lack a consistent co-variation with elemental patterns (Fig. 4.6). Titanium and Th are mainly below the

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Fig. 4.5. Stalagmite HK1, trace elemental concentration in lateral calcite-to-aragonite transitions. From core to flank is to the left, as indicated by the arrow. Horizontal scale indicates distance in mm from aragonite-to-calcite transition. Transect HK1-CA1 is indicated by triangles, HK1-CA2 is indicated by open circles. Aragonite is shown by light grey, calcite by dark grey shading. Calcite is present in the core portions of the stalagmite, aragonite at the flanks. Note, U and Mg are plotted on logarithmic scales in order to reveal the lowest concentrations. Relative uncertainty is not shown in order to be able to compare the two transects.

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Fig. 4.6. Stalagmite HK3: trace elemental data of Mg, Ba, Sr, Y, P, U and carbon and oxygen isotope ratios. Stratigraphic top is to the right, as indicated by the arrow. Aragonite is shown by light grey, calcite by dark grey shading, white refers to transition zone (as based on Mg, and U concentrations). Note, that Mg, Ba, Sr, U and Y are plotted on logarithmic scales, whereas P, carbon and oxygen isotope ratios are plotted on linear scales. Relative uncertainty is indicated by grey shading.

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Fig. 4.7. Stalagmite HK3: trace elemental data of Th, Pb, Ti and Al. Stratigraphic top is to the right, as indicated by the arrow. Thorium and Ti values marked by the transparent grey bar were not significantly elevated above the background. Aragonite is shown by light grey, calcite by dark grey shading, white refers to the transition zone (as based on Mg, and U concentrations). Relative uncertainty is indicated by grey shading.

detection limits and are therefore not further discussed.In the calcitic section, close to the Cc-Ar transition, Mg, Ba and Sr display an increasing

trend towards aragonite, similar to carbon and oxygen isotopes, whereas P and Y show a decreasing trend (Fig. 4.9). The total variation in the data explained by the first two principal components is 77%. Whereas the 1st principal component is made up by Mg, Ba, Sr, P and Y and the 2nd principal component is made up by Al, Ti, Th and Pb (Fig. 4.8b). Magnesium, Ba, Sr and P and Y show a strong positive correlation to each other, whereas P and Y are both negatively correlated to Mg, Ba and Sr (Fig. 4.8b). Aluminium, Ti, Th and Pb are strongly positively correlated to each other (Fig. 4.8b).

In the aragonitic section from the Cc-Ar transition, δ13C, Mg, Sr and Ba co-vary (Fig. 4.10), Ba is positively correlated to Mg and Sr. The total variation in the data explained by the first two principal components is 60% (Fig. 4.8c). In general, correlations between elements are low. The 1st principal component is made up by Mg, Sr, Y, Ba, Pb and Al. Phosphorus and U make up the 2nd principal component and show a weak positive correlation to each other. Titanium and Th are mainly below the detection limits and are therefore not discussed (Fig. 4.7).

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Fig. 4.8. Correlation plots between trace element time series and the 1st and 2nd principal components from stalagmite HK3 and GP2. The percentage of total data variation explained by the respective principal component is indicated. Trace elements which plot close to each other are generally positively correlated. (A) Aragonite from the aragonite-to-calcite transition stalagmite HK3. (B) Calcite stalagmite HK3. (C) Aragonite from the calcite-to-aragonite transition stalagmite HK3. (D) Calcite stalagmite GP2. (E) Aragonite stalagmite GP2. The specific intervals analysed by the PCA were defined by the Mg and U concentrations in order to avoid data representing an admixture of calcite and aragonite.

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Fig. 4.9. Stalagmite HK3 calcite from calcite-to-aragonite transition: trace elemental data of Mg, Ba, Sr, Y, P, U and carbon and oxygen isotope ratios. Stratigraphic up is to the right as indicated by the arrow. Aragonite is shown by light grey, calcite by dark grey shading, white refers to the transition zone (as based on Mg, and U concentrations). Relative uncertainty is indicated by grey shading. Note, Y is plotted on a logarithmic scale. Note the strong covarying patterns between Mg, Ba, Sr and d13C, which is interpreted as a prior calcite precipitation effect, see text Section 5.2.1 for discussion.

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Fig. 4.10. Stalagmite HK3 aragonite from calcite-to-aragonite transition: trace elemental data of Mg, Ba, Sr, Y, P, U and carbon and oxygen isotope ratios. Stratigraphic up is to the right as indicated by the arrow. Aragonite is shown by light grey, calcite by dark grey shading, white refers to the transition zone (as based on Mg and U concentrations). Relative uncertainty is indicated by grey shading.

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4.4.4. Stalagmite GP2 (Grotte de Piste)

4.4.4.1. Petrography

In speleothem GP2, both calcite and aragonite were identified by XRD for those intervals that were later sampled for trace elemental and isotope analyses. The calcite layer contains up to 4.65 mol-% MgCO3, whereas the intercrystalline calcite within the aragonite contains up to 3 mol-% MgCO3. Figure 4.11a-b provides an overview on the spatial distribution of the different carbonate mineralogies. After the transition from calcite to aragonite, the mineralogy remains aragonitic up to the tip of the stalagmite. The columnar to elongated columnar calcite crystals (Frisia and Borsato, 2010) show a sweeping extinction over several crystals (Fig. 4.11c). Undulosity is observed for individual calcite crystals (Fig. 4.11c). This is evidence for their radiaxial fibrous fabrics with converging C-axes in the direction of growth as previously described from speleothems in Germany (Neuser and Richter, 2007; Richter et al., 2011). The calcite is characterized by low porosity and minor amounts of detrital material, as evidenced by the lack of yellowish to red spots under the CL-microscope as well as the lack of non light transmissive inclusions within the calcite crystals (Fig. 4.11a-c).

The change in mineralogy from calcite to aragonite takes place over a distance of some tens of microns only. The fibrous aragonitic fabric is organised in fans characterized by a sweeping extinction pattern extending over several crystal fibres (Fig. 4.11a-b). Following Frisia and Borsato (2010) this fabric is classified as acicular. Porosity in the aragonitic fabric is most common between clusters of fans.

Fig. 4.11. Stalagmite GP2, thin section petrography. Stratigraphic up is to the top. (A) Image of calcite-to-aragonite transition under plane polarized light. Note fan-like texture of aragonite (Ar) fibres and clear calcite (Cc) crystal shape at the black arrow oriented in the growth direction, which indicates that this calcite is a primary calcite. Red arrows indicate position of transition. Porosity is indicated (Pr). (B) Same as A under cathodoluminescence. (C) Image of undulous (Un), columnar to elongated columnar calcite crystals under crossed polarized light. Undulosity is evidence for the primary nature of the calcite.

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4.4.4.2. Geochemistry

The transition from calcite to aragonite in stalagmite GP2 occurred between 11.5 and 11.1 ka BP. At the transition from calcite to aragonite, Ba, Sr, U, P, Y and Pb show a strong increase in concentration, whereas Mg and Al display a strong decrease (Fig. 4.12). Especially carbon isotope ratios increase across the Cc-Ar transition, oxygen isotope ratios show a more continuous increase.

In the calcite interval, δ13C values display a trend towards more negative values (a decrease of 2‰) followed by a minor increase near the transition to aragonite (Fig. 4.13). Oxygen isotope ratios show a small variation. Magnesium, Ba and Sr show an increasing trend towards the Cc-Ar transition, whereas Y, P, Pb, U and Al show a decreasing trend (Fig. 4.13). The total variation explained by the first two principal components is 83% (Fig. 4.8d). The 1st principal component is made up by P, Y, Pb, Al and Mg, Ba and Sr. The 2nd principal component is made up by Al and U (Fig. 4.8d). Phosphorus, Y, Pb, and Mg, Ba and Sr are positively correlated to each other, whereas Mg, Ba, Sr are negatively correlated to P, Y and Pb (Mg versus Pb: r = -0.49; Fig. 4.8d).

In the aragonite interval, Sr, P, Y, Pb and U show a decreasing trend after the transition (Fig. 4.14). Magnesium, Ba and Al show no consistent co-variation with any other elements described here. Carbon and oxygen isotope ratios co-vary and shift towards more positive values after the calcite-to-aragonite transition. Above a sampling depth of 583 mm both δ13C and δ18O become more negative. The total variation explained by the first two principal components is 74% (Fig. 4.8e). The 1st principal component is made up by Sr, P, Y, Pb and U. The 2nd principal component is made up by P and Ba (Fig. 4.8e). Aluminium is not incorporated in the PCA, because it is not correlated to any of the other trace elements. Strontium is positively correlated to P, Y, Pb and U (Fig. 4.8e).

4.5. Interpretation and discussion

4.5.1. Aragonite diagenesis

Aragonite is thermodynamically unstable under atmospheric pressure and surface temperature conditions. Therefore, aragonite may be dissolved or re-crystallised to calcite or another, more stable carbonate mineralogy (Frisia et al., 2002; Martin-Garcia et al., 2009). Any study of fossil aragonitic speleothems must, thus, assess the degree of post-depositional diagenetic alteration. The most powerful screening tool for the detection of diagenetic aragonite alteration is careful thin section petrography. Acicular fibres of aragonite can be affected by diagenetic calcitization and micritization. Both of these features are recognizable in thin sections. In the case of the Moroccan speleothems examined here, none of the thin sections show the above-mentioned petrographic evidence for diagenetic alteration of aragonite (Figs. 4.4; 4.11). More complex and far more difficult to trace, however, is fabric-preserving diagenetic remobilization of specific elements and isotopes. Detailed investigation of fossil aragonitic corals has shown that the U-series system is more sensitive to post-depositional diagenetic change than any other petrographic or general geochemical parameter (e.g., Chen et al., 1991; Fruijtier et al., 2000; Scholz and Mangini, 2007). A spatially localized example for fabric-preserving geochemical

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Fig. 4.12. Stalagmite GP2, trace elemental data of Mg, Ba, Sr, U, P, Y, Pb, Al and carbon and oxygen isotope ratios. Stratigraphic up is to the right as indicated by the arrow. Horizontal scale is distance in mm from top of speleothem. Aragonite is shown by light grey, calcite by dark grey shading, white refers to the transition zone (as based on Mg, and U concentrations). Note, that P and carbon and oxygen isotope ratios are plotted on linear scales, whereas Mg, Ba, Sr, U, Y, Pb, and Al are plotted on logarithmic scales in order to reveal the lowest concentrations. Relative uncertainty is indicated by grey shading surrounding the plots, except for the isotope ratios where relative uncertainties are very small.

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Fig. 4.13. Stalagmite GP2 calcite: trace elemental data of Mg, Ba, Sr, Y, P, Pb, U, Al and carbon and oxygen isotope ratios. Aragonite is shown by light grey, calcite by dark grey shading, white refers to the transition zone (as based on Mg, and U concentrations). Note that Y and Pb are plotted on logarithmic scales. Relative uncertainty is indicated by grey shading.

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Fig. 4.14. Stalagmite GP2 aragonite, trace elemental data of Mg, Ba, Sr, U, P, Y, Pb, Al and carbon and oxygen isotope ratios. Aragonite is shown by light grey, calcite by dark grey shading, white refers to the transition zone (as based on Mg, and U concentrations). Note that Y and Pb are plotted on logarithmic scales. Relative uncertainty is indicated by grey shading surrounding the plots.

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remobilization of U and/or Th isotopes is found in stalagmite HK3. 230Th/U-dating of the aragonite at one of the aragonite-to-calcite transitions resulted in an age that was - in comparison to nearby age data - apparently 10 ka too young (Table 4.2). Interestingly, the U concentration of this specific interval is 37 ppm, which is four times higher than the average U concentration in HK3 aragonite based on LA-ICP-MS analysis. This may be evidence for post-depositional U-redistribution, which has been observed in fossil reef corals (Scholz et al., 2007).

Apart from this localized feature, no further geochemical or petrographic evidence for diagenesis was observed in any of the speleothems studied here. Moreover, the very sharp boundary of the transitions in the trace element concentrations serves as an additional argument against fabric preserving remobilization. In addition, the amount of inter-crystalline calcite within the aragonite intervals is below 2%. Assuming calcite and aragonite end member values for elemental abundances based on the observed difference at the lateral and stratigraphic Cc-Ar and Ar-Cc transitions, simple mass balance calculations suggest that 2 % of primary calcite within an aragonitic fabric may affect Mg and U but the effect on other elements is minimal (see supplementary material for calculations and Fig. S4.2). If the 2 % calcite represents calcitized aragonite, then the effect on the elemental abundances is very small as the composition of this calcite is most likely close to that from the original aragonite.

Calcitized aragonite is characterized by low Mg calcite (0.6-1.6 mol-% MgCO3; XRD; Niggemann and Richter, 2006). In the stalagmites studied here, inter-crystalline calcite in aragonite layers probably represent a mixture of both primary and secondary calcite as XRD analysis indicated a range of 0.5-4.6 mol % of MgCO3 for the inter-crystalline calcite. The samples analysed with XRD suggest that the amount of inter-crystalline calcite does not exceed 2%. Therefore, it can be concluded that aragonite in the Moroccan speleothems discussed here is well preserved both with respect to its fabric and geochemistry. Small-scale, spatially localized geochemical remobilization cannot be excluded but is not considered significant for the intervals analysed here.

4.5.2. Climate forcing of alternating calcite and aragonite precipitation?

The key to understand the reason for aragonite precipitation lies in the calcitic section just before the occurrence of the aragonite. Thus, we focus here on the calcite from the Cc-Ar transitions. Trace elements correlated and grouped by Principal Component Analysis (Fig. 4.8), are assumed to reflect a common process. Therefore, the following clusters of elements will be discussed and placed in the context of their suggested drivers: (i) Mg, Sr, Ba in the context of PCP; (ii) P and Y in the context of vegetation decay; and (iii) Al, Th, Ti, Pb in the context of clay minerals.

4.5.2.1. Magnesium Strontium and Barium, relation to prior calcite precipitation

Prior calcite precipitation refers to the process of calcite precipitation from groundwater prior to reaching the stalagmite. This includes precipitation of stalactites at the cave ceiling. Prior calcite precipitation takes place if the soil and aquifer water encounters a gas phase with lower pCO2, which causes CO2 degassing that in turn leads to fluid super-saturation with respect to CaCO3 and

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precipitation of calcite from the liquid phase (Fairchild and Treble, 2009). As a consequence, PCP affects the CaCO3 saturation state of the drip water. Furthermore, since the partition coefficients of Mg, Sr and Ba are smaller compared to that of Ca during calcite precipitation, PCP will increase the Mg/Ca, Sr/Ca and the Ba/Ca ratios of the drip water. Thus, a pronounced positive correlation between speleothem Mg, Sr and Ba concentrations has been interpreted in terms of variable amounts of PCP (Tooth and Fairchild, 2003; McMillan et al., 2005; Wong et al., 2011). Since PCP affects the Mg/Ca ratio and the CaCO3 saturation state of the drip water, PCP may be an essential process for inducing aragonite precipitation. Prior calcite precipitation may occur as a consequence of increasingly arid climate (Fairchild et al., 2000) resulting in reduced drip rates. Increasing air temperatures, however, may increase soil CO2 production (Pinol et al., 1995), which could enhance PCP as well. Finally, the effect of re-dissolving carbonate formed during PCP on drip water chemistry remains difficult to quantify.

Prior calcite precipitation also affects the δ13C value of the dissolved inorganic carbon of the drip water (Johnson et al., 2006; Scholz et al., 2009; Dreybrodt and Scholz, 2011). Drip water δ13C, however, may also be influenced by several other processes including relative changes between C3 and C4 type vegetation above the cave (Dorale et al., 1992; McDermott, 2004), (micro-) biological activity in the soil zone and the carbonate aquifer (Genty et al., 2006), kinetic effects modulated by changes in drip rate (Mühlinghaus et al., 2007; 2009) and cave ventilation (Spötl et al., 2005; Frisia et al., 2011). Enhanced PCP due to increasing aridity likely coincides with longer water residence time in the aquifer, higher evaporation rates, decreasing drip rates and soil zone activity as well as an increase of C4 type vegetation relative to C3 type vegetation (Fairchild et al., 2000; McMillan et al., 2005; Fairchild and Treble, 2009). All these processes commonly result in increasing δ13C values of the drip water.

The calcitic portion of speleothem HK3 is characterized by a strong co-variation between the elements Mg, Sr, Ba and the carbon isotope ratios (Fig. 4.9). This pattern is considered evidence for PCP. Following the above considerations, the observation that the highest Mg, Sr and Ba concentrations as well as high δ13C values occur just before the transition of calcite to aragonite (Fig. 4.9) suggests that enhanced PCP was of major significance for the onset of aragonite precipitation in stalagmite HK3 (Fig. 4.15b).

A similar relation is observed for the elements Mg, Sr and Ba in the calcitic sections of stalagmite GP2 (Fig. 4.13). Applying the previous lines of evidence, the presence of aragonite in stalagmite GP2 is probably also related to enhanced PCP. Stalagmites HK3 and GP2, however, differ from each other in one significant aspect. δ13C values do not co-vary with Mg, Sr and Ba in stalagmite GP2 (Fig. 4.13). This may imply that, in the case of stalagmite GP2, PCP is not the dominant process affecting drip water carbon isotope ratios. Furthermore, the amount of PCP required to induce aragonite precipitation is probably smaller in Grotte de Piste compared to Grotte Prison de Chien. This is because of the different host rocks, which is a Mg-rich dolomite in the case of the Grotte de Piste (speleothem GP2) and low-Mg limestone in the case of the Grotte Prison de Chien (speleothem HK3). In addition, the concentrations of Mg in the calcite just before the Cc-Ar transition are for both stalagmites approximately 8500-9500 ppm (Fig. 4.9; 4.13). This may imply that a certain drip water Mg/Ca ratio threshold has to be reached in order to precipitate aragonite. This threshold may

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Fig. 4.15. Schematic graphic summary of geochemical patterns in Moroccan speleothems across calcite-to-aragonite transitions and their respective drivers. Stratigraphic up is to the right. Summary is based on the observed first order trends in stalagmite HK3 and GP2. Prior calcite precipitation = PCP; Prior aragonite precipitation = PAP. (A) Carbon and oxygen isotope ratios in stalagmite HK3. (B) Magnesium, Ba and Sr concentrations in stalagmite HK3. (C) Phosphporus, Y and Sr abundances in stalagmite HK3. (D) Carbon and oxygen isotope ratios in stalagmite GP2. (E) Magnesium, Ba, and Sr abundances in stalagmite GP2. (F) Phosphorus, Y and Sr abundances in stalagmite GP2.

be calculated assuming a partition coefficient for Mg in calcite of 0.019 at 15°C, or 0.031 at 25°C (Huang and Fairchild, 2001). Calcite containing 9000 ppm Mg could therefore be precipitated from drip water with a molar Mg/Ca ratio of 2.1 or 1.3, respectively. In particular the calculated drip water Mg/Ca ratio at 25°C is in good agreement with monitoring data from Frisia et al., (2002). Given the fact that paleo-temperature data for the caves investigated are not well constrained, the correct

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partition coefficient remains difficult to assess.In summary, Mg, Sr, and Ba elemental data provide strong evidence that enhanced PCP induced

aragonite precipitation in both stalagmites. In order to assess whether the amount of PCP is related to changes in (i) aridity, (ii) temperature related CO2 production or (iii) changes in local hydrology, other trace elements not affected by PCP (e.g. P and Y), may provide important information.

4.5.2.2. Phosphorus and Yttrium, relation to vegetation decay

Fairchild et al. (2001) and Treble et al. (2003) suggested that speleothem P concentrations and vegetation decay are related. Treble et al. (2003) observed that for regions, where vegetation productivity is stressed by water availability, speleothem P concentrations decreased in years with lower rainfall. Furthermore, Borsato et al. (2007) concluded that at Grotta di Ernesto (Italy) elevated speleothem P and Y concentrations are related to enhanced transport of (organic) colloids from the soil during the infiltration season, where P most likely originates from microbial breakdown of organic matter. Borsato et al. (2007, pp. 1507) also noted that the “…incorporation of P into calcite depends on the relative proportions of free ion versus inorganic and organic colloidal forms…” Furthermore, Huang et al. (2001) suggested that P was available as phosphate ions. In the view of the authors, it therefore remains an open question how P is actually transported and incorporated into calcite or aragonite (de Kanel and Morse, 1978; Huang et al., 2001; Millero et al., 2001). This may be different between different cave sites. Finally, Treble et al. (2005) identified growth rate related annual patterns of Na, Sr, Ba and U in a stalagmite from Moondyne Cave. Phosphorus did not show annual banding, which may suggest that the incorporation of P into speleothem calcite is not related to changes in speleothem growth rates. It must be noted, however, that P can be transported and incorporated through several mechanisms, and that for example the amount of defect sites under high growth rates could increase, whereas the adsorption potential may remain similar. This still requires more research.

The source of Y differs from that of P but has similar chemical properties and atomic structure compared to the rare earth elements (Zhou et al., 2008b), which have the tendency to become adsorbed to organic matter (McCarthy et al., 1998; Tyler, 2004). Therefore, a positive correlation between P and Y in speleothems is indicative of soil-derived organics in cave drip water (Borsato et al., 2007; Zhou et al., 2008b). Note that the unspecific label “organics” is used here because it remains unclear whether P is transported in form of organic colloids or as organic matter. The source of these organics is, as indicated above, most likely decaying plant remains in the soil zone above the cave. Table 4.3 provides evidence that the soil above a cave may act as a source for Y.

Phosphorus and Y are positively correlated in calcitic intervals of stalagmite HK3 (Fig. 4.8b). Following the above discussion, we propose that these elements reflect the incorporation of organics in the crystal lattice or inter-crystalline organics. In the calcite interval, near the calcite-to-aragonite transition, both P and Y concentrations are decreasing towards the aragonite interval (Fig. 4.9). A possible interpretation for this feature may be related to decreasing microbial break down of organic matter in the soil zone. This potentially reflects an effect of decreasing temperature or a decrease in effective rainfall. It must be emphasized here that increasing temperatures could increase both the microbial breakdown of organic matter (thus increasing stalagmite P concentrations) and soil

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CO2 concentrations (thus enhancing PCP), provided that the available amount of moisture in the soil is sufficient to sustain microbial activity and soil zone CO2 production. Because of the negative correlation between P and Y with Mg, Sr and Ba (Fig. 4.8b), it is suggested that PCP was induced by increasingly drier climatic conditions rather than changes in local hydrology or increasing temperatures (Fig. 4.15a-c). The 1st principal component in the calcite section of HK3 made up by Mg, Ba, Sr and P, and Y is therefore representing effective rainfall. Higher values represent lower effective rainfall and vice versa, because the highest values occur just before the Cc-Ar transition, aragonite started to precipitate at the moment effective rainfall was low (Fig. 4.16). Similar to stalagmite HK3, a negative correlation between P, Y and Mg, Sr and Ba is observed in the calcite layer for stalagmite GP2 (Fig. 4.8d). This recurrent pattern, combined with low P and Y concentrations in the calcitic speleothem close to the calcite-to-aragonite transition, is indicative of enhanced PCP driven by increasing aridity (Fig. 4.13; 4.15d-f). It can therefore be concluded that the 1st principal component in the calcite section of stalagmite GP2 made up by P, Y, Pb, Mg, Sr, and Ba is, similar to stalagmite HK3, representing effective rainfall. Lower values indicate lower effective rainfall and vice versa. The lowest values occur just before the Cc-Ar transition, indicating that aragonite started to precipitate at the moment that effective rainfall was relatively low (Fig. 4.16). The forcing mechanism behind the 2nd principal component and the negative correlation between Mg and U remains unclear.

Due to the differences in the host rock mineralogies in the two caves in Morocco, we suggest that – in the case of stalagmite GP2 – only a moderate decrease in effective rainfall was required to induce aragonite precipitation. This is due to the considerably higher Mg content of the dolomite host rock of Grotte de Piste. Evidence for this comes from the observation that speleothem GP2 δ13C values lack a co-variation with Mg, Sr, Ba, P or Y (Fig. 4.13; 4.15d-f), showing that changes in mean drip rates were not sufficient to induce a significant additional amount of CO2 degassing. Instead speleothem GP2 δ13C values must have been dominated by other processes.

Across the transition from calcite to aragonite in stalagmite GP2, P, Y and Pb concentrations increase with increasing aragonite content (Fig. 4.12). This was also observed for P and Y in the lateral calcite-to-aragonite transitions in stalagmite HK1 (Fig. 4.5), but not in stalagmite HK3 (Fig. 4.6). This observation suggests a crystallographic forcing on P and Y. It can, however, not be explained by simple substitution for Ca, due to the different valence of P (3+ or 5+) and Y (3+) compared to Ca (2+), and for P its smaller ionic radius. Therefore the shift to higher P and Y concentrations at the transition from calcite to aragonite may be related to differences in adsorption potential between calcite and aragonite, the amount of defect sites available for organics or competition effects. The reason why this pattern is not observed in stalagmite HK3 may be related to differences in the relative proportions of P available as free ions versus inorganic and organic colloidal material (Borsato et al., 2007) in the drip water between the two caves. Furthermore, the correlation between P and Y (indicative for organics) is much weaker in the aragonite compared to calcite. This indicates that P is indeed not only available as organic material but may also be transported and incorporated through other mechanisms. These considerations must be the scope of further research and are not addressed here.

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Fig. 4.16. 1st and 2nd principal components versus distance (time). Aragonite is indicated by light grey shading, calcite (Cc) is indicated by dark grey shading. (A) 1st principal component from GP2 calcite section, high values indicate higher effective rainfall and vice versa. (B) 2nd principal component from GP2 calcite section (unknown forcing mechanism). (C) 1st principal component from the GP2 aragonite section, higher values indicate higher effective rainfall and vice versa. (D) 2nd principal component from GP2 aragonite section (unknown forcing mechanism). (E) 1st principal component from HK3 aragonite section from aragonite-to-calcite transition (unknown forcing mechanism). (F) 2nd principal component from HK3 aragonite section from aragonite-to-calcite transition (unknown forcing mechanism). (G) 1st principal component from the HK3 calcite section, high values indicate lower effective rainfall. (H) 2nd principal component from HK3 calcite section, possibly reflecting a transport mechanism for clay minerals. (I) 1st principal component from HK3 aragonite section from calcite-to-aragonite transition (unknown forcing mechanism). (J) 2nd principal component from HK3 aragonite section from calcite-to-aragonite transition (unknown forcing mechanism).

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4.5.2.3. Aluminium, Titanium, Lead and Thorium, relation to clay minerals

Higher concentrations of Th are associated with non-carbonate phases (Fairchild et al., 2006). This is because Th is transported as adsorbed phase on detrital materials such as clay minerals (Dorale et al., 2004). Aluminium is also a major constituent of clay minerals, such as kaolinite or montmorillonite and is transported both in colloidal and particulate form (Zhou et al., 2008a; Fairchild and Treble, 2009). Elemental abundances of Al, Ti, Pb and Th in stalagmite HK3 are positively correlated and together make up the 2nd principal component in the calcitic section of stalagmite HK3 (Fig. 4.8b). The most likely interpretation of this pattern is a similar source and similar transport mechanism for these elements. Clay minerals are rich in Al and can easily adsorb a range of trace elements including Th (Dorale et al., 2004). They can be transported as colloidal material and as particles (Fairchild and Treble, 2009). Therefore, the Al, Ti, Pb and Th elemental maxima may be related to an increased abundance of colloidal clay material or larger clay particles.

At the stratigraphic mineralogical transitions of stalagmite HK3 and stalagmite GP2 a clear shift from higher concentrations in calcite to lower concentrations in aragonite is observed for Al, Ti, Th and Pb (Fig. 4.7; 4.12). Considering the abrupt shift in elemental abundances at the transitions, it is here suggested that this pattern is crystallographically forced. This may be related to different adsorption potentials between calcite and aragonite or competition effects for crystal defect sites. Interestingly the suggested crystallographic forcing on Y and P showed an opposite effect. This indicates that organics may be differently incorporated or are directly competing for crystal defect sites with clay minerals in these stalagmites. Once more, this topic requires much more attention, but is beyond the scope of this paper.

An interesting feature of the 2nd principal component is the trend towards more negative values approaching the Cc-Ar transition (Fig. 4.16). This is not directly visible in Fig. 4.7, showing the additional value of PCA. Whereas the 1st principal component was interpreted as representing effective rainfall, the 2nd principal component could represent transport mechanisms that may be related to effective rainfall as well, but with a different type of response compared to the 1st principal component. Other potential interpretations could be a gradual increase in aragonite abundance approaching the Cc-Ar transition, because the aragonite is characterized by very low Al, Ti, Pb and Th concentrations, or a temperature induced weathering signal (cooling). Neither of the latter two interpretations is, however, supported by petrographic evidence or other proxies. For this reason, the authors consider effective rainfall as the most likely forcing mechanism.

4.5.2.4. Detrital layers and hiatus surfaces

Under increasingly arid conditions, drip sites may dry out and hiatus surfaces cap speleothems. Hiatus surfaces in speleothems are often marked by detrital material that is delivered as aerosols in cave air or in the drip water itself. Alternatively, detrital material may accumulate on crystal surfaces due to overall decreasing precipitation rates, which eventually results in a hiatus surface characterized by detrital material (Immenhauser et al., 2007). A third option is that the thin and only temporarily present water film on a speleothem beneath an increasingly dry drip site may be insufficient to remove

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detrital material from the speleothem surface. These mechanisms might occur in combination or separately.

In the aragonite layer from the Ar-Cc transition in stalagmite HK3, it was observed that silt-sized carbonate detrital material increased in abundance at the upper boundary of the aragonite layer (Fig. 4.4d). This material might represent insoluble residue from the carbonate host rock or the soil above the cave. At the flank of the stalagmite where growth is slow the abundance of carbonate detrital material increased as well (Fig. 4.4j). Therefore, the fine silt probably accumulated in the inter-fibre pore space on top of the aragonite surface from the Ar-Cc transition during time intervals when speleothem growth ceased. Additional evidence for the presence of a hiatus at the top of the aragonite layer comes from the strong shift to higher concentrations in P and Y at the Ar-Cc transition and the absence of such a shift at the Cc-Ar transition (Fig. 4.6). Therefore, it can be concluded that this shift is not crystallographically forced, but rather indicates the onset of increased soil activity after a relatively dry period.

The increasing amounts of calcite observed towards the upper limit of aragonite layers can be explained by the re-initiation of speleothem growth and, thus, more humid climate. Calcite precipitation on top of the aragonite hiatal surfaces occluded pore space between aragonite fibres and encased detrital material on top of the aragonite speleothem surface. This is supported by geochemical evidence based on the Mg concentrations across the Ar-Cc and Cc-Ar transitions. The Ar-Cc transition is much more gradual compared to the Cc-Ar transition (Fig. 4.6). XRD data from this aragonite layer indicates that the calcite contains 4 mol % MgCO3 an observation that suggests that the calcite at the transition qualifies as a moderately high Mg calcite rather than calcitized aragonite that would form low-Mg calcite. Although the effect of the carbonate detrital material on the Mg concentrations cannot be excluded, we consider it very likely that the increase of calcite with an elevated Mg content contributed to the more gradual Ar-Cc transition.

4.5.2.5. Climatic context of stratigraphic calcite-to-aragonite transitions

Only a few climate reconstructions from Morocco cover the Holocene and the late glacial (Lamb et al., 1995; Cheddadi et al., 1998; 2009). Lake Tigalmamine is the best studied lake record and is located in the Middle Atlas at an altitude of 1628 meters above sea level. Cheddadi et al. (1998) suggested that during the early Holocene, the region of Lake Tigalmamine was characterized by increasing January temperatures and a decrease in annual precipitation from 900 mm at approximately 12 ka BP to 700 mm around 11 ka BP (14C ages were calibrated using the online calibration http://www.calpal-online.de/, accessed 2011-11-29; Weninger and Jöris, 2008). It must be noted, that these annual precipitation rates were probably lower than 700 mm at the site of Grotte de Piste due to its lower altitude (1260 m) compared to Lake Tigalmamine (1628 m) and the general altitude-to-rainfall amount relation in Morocco. Acknowledging some degree of error in the age model of these climate reconstructions, the warmest and driest period of the Holocene seems to coincide in time with the stratigraphic Cc-Ar transition in stalagmite GP2. This might imply that the occurrence of aragonite in stalagmite GP2 is probably induced by decreasing rainfall amounts. Increasing average air temperatures might have played a role too.

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The climate context of calcite-to-aragonite transitions in stalagmite HK3 is more difficult to assess, whilst climate reconstructions from Morocco for marine isotope stage 2 and 3 are limited to a record from Lake Ifrah (Rhoujjati et al., 2010). The age model of the Lake Ifrah record does not allow for a comparison of the age of aragonite layers with the marine isotope stage 2 and 3 climate reconstruction in Morocco. Heinrich event 2 (H2) was recorded by several marine cores surrounding the Iberian Peninsula and Morocco (Turon et al., 2003; Bout-Roumazeilles et al., 2007; Fletcher and Goni, 2008; Nebout et al., 2009; Penaud et al., 2010). Fletcher and Goni (2008) and Nebout et al. (2009) suggested that H2 was characterized by overall dry conditions in the Western Mediterranean. Bout-Roumazeilles et al. (2007) used Artemisia and Ephedra pollen data to reconstruct the % of semi-dessert vegetation combined with the palygorskite content from a marine core in the Alboran Sea (ODP 976), which reflects vegetation cover in Western Morocco. This reconstruction suggests that Western Morocco was characterized by several dry/humid phases between 26.5 and 21.5 ka BP (Bout-Roumazeilles et al., 2007).

Stalagmite HK3 commences to grow (aragonite) around 27.5 ka BP. This time interval coincides with Greenland Interstadial 3 as recognized in the Greenland ice cores (Rasmussen et al., 2008). At present, our attempt to date the transition from aragonite to calcite was unsuccessful. Linear interpolation between the two datings suggests that the timing of the more humid calcite phase is centred around 24.5 ka BP. In contrast, the subsequent dry aragonite phase is centred around 23.7 ka BP, although it has to be noted that the presence of the hiatus at the top of the aragonite layer induces uncertainties in the age model. The age of the aragonite phase centred around 23.7 ka BP is, however, robust, as the sample for dating was drilled from this layer. This may confirm Fletcher and Goni (2008) and Nebout et al. (2009) who suggested that dry conditions occurred during H2. The calcite phase, however, indicates a more humid period too that may coincide with one of the more humid phases reconstructed by Bout-Roumazeilles et al. (2007) for the period between 26.5 and 21.5 ka BP.

4.5.2.6. Lateral calcite-to-aragonite transitions in stalagmite HK1 (Grotte Prison de Chien)

In the above discussion, evidence has been presented that stratigraphic transitions from calcite to aragonite may be driven by, amongst other factors, effective rainfall. In the case of lateral calcite-to-aragonite transitions, similar processes inducing aragonite precipitation might have been active. Obviously, the main difference between lateral relative to stratigraphic transitions is that both, calcite and aragonite are precipitated pene-contemporaneously within one growth increment. Precipitation of calcite and aragonite must not, however, be from the same fluid. Alternatively, the physico-chemical properties of the water film on the stalagmite surface may have changed over short distances. This implies that boundary conditions were initially in a calcite mode but very close to the threshold of the aragonite mode. In the case of lateral transitions of calcite (stalagmite core) to aragonite (stalagmite flanks), relevant parameters of drip water chemistry include CaCO3 saturation state, drip water Mg/Ca ratio and CO3

2- controlled kinetics. Relevant environmental conditions include temperature and evaporation potential (Railsback et al., 1994; Fernández-Díaz et al., 1996; Zuddas and Mucci, 1998; Frisia et al., 2002; Kawano et al., 2009). Possibly, the occurrence of both calcite and aragonite within a single growth layer has some implication as climate proxy. This hypothesis may be verified or

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falsified by analyzing stratigraphic changes in geochemistry.

4.5.3. Interpretation of trace element abundances in speleothem aragonite

Prior calcite precipitation was the main process to induce aragonite precipitation in Grotte Prison de Chien and Grotte de Piste speleothems. In the calcitic portions of stalagmites HK3 and GP2, no difference in the behaviour of Mg, Sr and Ba was observed. Conversely, Mg, Sr and Ba do show a different behaviour in the aragonitic portions of the two stalagmites. In addition the total amount of variance explained by the first two principal components in the aragonite sections are lower compared to the calcitic sections. These differences merit discussion. The number of previous studies focussing on trace elements (particularly Ba and Sr) in speleothem aragonite is indeed limited (Finch et al., 2001; 2003; McMillan et al., 2005). Finch and co-workers proposed a possible relation of Ba and Sr concentrations to rainfall amount, with higher concentrations of Ba and Sr corresponding to higher rainfall. A mechanistic model for Ba and Sr incorporation into speleothem aragonite, however, has not yet been brought forward. We consider PCP an unlikely mechanism, because higher rainfall amounts should result in a decrease of PCP and thus, lower speleothem Ba and Sr concentrations. Aragonitic stalagmites as discussed in previous studies were mainly retrieved from caves with a dolomitic host rock. Examples include the Cold Air Cave in South Africa (Holmgren et al., 1999; Finch et al., 2003), the Lianhua cave in China (Cosford et al., 2008), the João Arruda Cave in Brazil (Bertaux et al., 2002) and the B7 cave in Germany (Niggemann and Richter, 2006). This fundamental pattern emphasizes the role of Mg in aragonite precipitation. An aspect that has not been given sufficient consideration is “prior aragonite precipitation” (PAP) rather than prior calcite precipitation. This process may be important where Mg concentrations in the drip water of dolomitic host rock caves are high. Differences between PAP and PCP exist because the partition coefficients of Ba and Sr for aragonite precipitation are closer to unity compared to partition coefficients for calcite precipitation (Fairchild and Treble, 2009). The relation between the drip water Ba/Ca and Sr/Ca ratios, however, depends on whether the partition coefficients are smaller or larger than one. Trace element partition coefficients depend on several environmental factors such as temperature and precipitation rate (Huang and Fairchild, 2001; Treble et al., 2005). Cave analogue experiments focussing on partition coefficients in aragonite do not exist to our knowledge. It is therefore only emphasized that PAP will have a different signature on the speleothem Ba and Sr concentrations compared to PCP. This feature may explain the absence of a negative correlation between Ba, Sr and annual rainfall at Cold Air Cave in South Africa (Finch et al., 2003). In addition, Sr concentrations in dolomite are relatively low compared to limestone due to the lower amount of Ca-sites available for substitution by Sr (Jacobson and Usdowski, 1976). This implies that in caves with a dolomite host rock, soil-derived Sr is likely to be more significant relative to limestone host rock caves.

The interpretation of Mg in aragonite speleothems also differs from that of calcite speleothems. This is because Mg is not likely incorporated into the crystal lattice of aragonite due to differences in ionic radius between Ca and Mg (1Ǻ versus 0.72Ǻ). Magnesium/Ca ratios of the drip water will, therefore, increase faster in the case of PAP compared to PCP. Magnesium concentrations in aragonite

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speleothems potentially indicate differences in the amounts of PAP. However, Mg could also be an indicator for co-precipitating magnesian calcite, shown by the Mg concentrations across the more gradual Ar-Cc transition in stalagmite HK3 (Fig. 4.6) discussed in section 5.2.4. Alternatively, Mg is associated with colloidal material, organic matter or particles. Organic matter may be incorporated in the aragonite crystal lattice or be present as inter-crystalline phase. Thus, variations in Mg, Sr and Ba in aragonitic speleothems must not be compared with those in calcitic speleothems and may reflect very different processes.

4.5.3.1. Aragonitic portion of speleothem GP2

Stalagmite GP2 was collected in Grotte de Piste characterized by a dolomitic host rock mineralogy similar to that of the Cold Air Cave (Holmgren et al., 1999). In contrast to the calcitic portions of speleothem GP2, the aragonitic portion lacks a clear positive correlation between Mg, Sr and Ba elemental values. Instead, Sr is positively correlated with P, Y, Pb and U, which together make up the 1st principal component (Fig. 4.8e). Magnesium does not significantly correlate with any element and Ba is only negatively correlated with Pb. Following the discussion above, the decoupling of Sr, Mg and Ba in aragonite is probably due to the absence of PCP, whereas PAP may have taken over in the karst aquifer (Fig. 4.15).

Strontium, Y, P, U and Pb all show decreasing trends across the aragonite portion of speleothem GP2 (Fig. 4.14). Acknowledging that the correlation between P and Y is weaker compared to the calcite section, this positive correlation still indicates that organics play a role in determining the P concentrations in the aragonite from speleothem GP2. This is confirmed by the similar trends of U, Y and Pb, elements that are strongly linked to organics (Treble et al., 2003; Borsato et al., 2007). Therefore, it can be concluded that Sr variations observed in aragonite may be related to the presence of organics (Fig. 4.15) and that the 1st principal component represents effective rainfall, with lower values representing lower effective rainfall and higher values representing higher effective rainfall (Fig. 4.16). Following this line of evidence, it is suggested that rainfall amounts continued to decrease after the initiation of aragonite precipitation (Fig. 4.16). It remains, however, unclear why Mg and U show a weak positive correlation. Similarly, the main driver of the 2nd principal component remains poorly constrained too. 4.5.3.2. Aragonitic portions of speleothem HK3

When comparing the outcome of the PCA from both individual aragonite layers in speleothem HK3, similarities in elemental grouping are not obvious (Fig. 4.8a; c). In the aragonite section beneath the Ar-Cc transition, a correlation between Mg, Sr and Ba is lacking. This implies that PCP is not a dominant factor. A correlation between Sr, P, U, Y and Pb, as observed for speleothem GP2, is not visible in speleothem HK3. Nevertheless, a positive correlation between Sr and P as well as Sr and U exists. This might indicate the influence of organics. Furthermore, compared to speleothem GP2, higher Al concentrations in speleothem HK3 suggest a stronger influence of clay minerals, because Al is positively correlated with Mg, Pb and Y (p < 0.03, r = 0.47; Fig. 4.8). However, the low total data

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variation explained by the first two principal components in the aragonite from the Ar-Cc transition suggests, that it is difficult to identify a dominant forcing mechanism for the trace elements in this aragonite interval in contrast to the calcite interval.

A positive correlation between Mg and Ba as well as Ba and Sr was observed in the aragonitic section that directly follows the Cc-Ar transition (Fig. 4.8c). These elements co-vary with δ13C, suggesting an influence of PCP (Fig. 4.10). If enhanced PCP is interpreted in terms of lower effective rainfall, however, a negative correlation of Mg, Sr and Ba with P and Y is expected. This is not the case. Therefore, the interpretation of this set of elements is not straightforward, a conclusion that is also reflected in the Principal Component Analysis. This is because the first two principal components only account for 60% of the total data variation (Fig. 4.8c), an outcome that contrasts with the calcite interval. This suggests that various environmental and kinetic factors are relevant, which may include different incorporation, transport mechanisms and possibly competition effects for crystal defect sites (Borsato et al., 2007).

4.6. Conclusions

Three Pleistocene/Holocene speleothems from two caves in Morocco were investigated for their petrography as well as their elemental and isotope geochemistry across lateral and stratigraphic calcite-to-aragonite transitions. By using Principle Component Analysis the overall complexity of the dataset was reduced and dominant forcing mechanisms were identified. The 1st principle component in the calcitic sections of stalagmites HK3 and GP2 is coupled to the vegetation-related input of organics and prior calcite precipitation and is reflecting effective rainfall. The 2nd principle component in stalagmite HK3 reflects transport mechanisms of clay minerals (colloidal or particle) that shows a different response to effective rainfall compared to the 1st principal component. The 1st principal component in the aragonite section of stalagmite GP2 reflects the vegetation-related input of organics and is coupled to effective rainfall. In stalagmite HK3, the total data variation explained by the first two principal components was very low in the aragonite. This indicates that trace elemental abundances were not dominated by one or two forcing mechanisms.

Aragonite precipitation in stalagmites HK3 and GP2 is predominantly controlled by climate forcing. Particularly, the change from more humid to more arid climate is of importance. Arguments for this relation include: (i) The vegetation-related input of organics as documented by speleothem P and Y concentrations reaches a minimum before and during the precipitation of a given aragonite interval. (ii) Prior calcite precipitation was at a maximum just before the presence of aragonite as evidenced from the relatively high Mg, Sr and Ba concentrations in the calcite directly before the aragonite interval. (iii) On top of the aragonite layer from the aragonite-to-calcite transition in stalagmite HK3 the increased abundance of carbonate detrital material is possibly linked to a hiatal surface. Evidence comes from the strong increase in the P and Y concentrations across the aragonite-to-calcite transition and the absence of such a shift across the calcite-to-aragonite transition.

The transition from calcite to aragonite in stalagmite GP2 is less significant in terms of climate change compared to that of speleothem HK3. This is mainly due to the dolomitic host rock mineralogy of Grotte de Piste (GP2) resulting in elevated background Mg/Ca ratio in Grotte de Piste drip water,

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which in turn decreases the rate of calcite precipitation and enhances aragonite precipitation.The interpretation of trace element abundances in aragonitic speleothems differs substantially

from that of calcitic speleothems. Major differences include the absence of prior calcite precipitation and the possible presence of prior aragonite precipitation within caves with mainly dolomitic host rock versus prior calcite precipitation within caves with mainly limestone host rock mineralogies. This is obvious from the decoupling of the positive correlation between Mg, Sr and Ba in the aragonite of stalagmite GP2. Difficulties in the interpretation of trace elements in aragonite may occur as a consequence of small scale dissolution and recrystallization features. In well-preserved aragonitic speleothems, Mg is likely an indicator for the co-precipitation of calcite or detrital material. Conversely, Sr most likely reflects the flux of soil-derived organics evidenced by the positive correlation between Sr, P, U, Y and Pb in the aragonite from stalagmite GP2.

The data shown here, clearly document the value of well-preserved speleothem aragonite fabrics. Specifically, speleothems characterized by stratigraphic and/or lateral changes from aragonite to calcite represent sensitive, albeit highly complex, archives of past climate change.

Acknowledgements

This work was financed by the Deutsche Forschungsgemeinschaft (DFG; project IM 44/1). We would like to thank the following people for fruitful discussions: A. Borsato, S. Frisia, C. Spötl, D. Fleitmann and A. Niedermayr. In addition the staff in the isotope laboratories at Bochum and Mainz (U. Weis, B. Stoll, D. Buhl and B. Gehnen) is acknowledged for their help with sample preparations and measurements. C. Kirchmann is thanked for his help with the drilling of isotope samples. Furthermore, we would like to thank R. Neuser for the help with the cathodoluminescence microscope, T. Reinecke for the X-Ray diffraction measurements, the thin section lab at Bochum, our local speleoguides El Houcine El Mansouri and Tarik Echchibi for their help in the field and A. Fink (Institute for Geophysics and Meteorology, University of Cologne) and Mileud (weather station Bab Bou Idir) for providing rainfall data. Sadalmelik is thanked for making the Morocco map (Fig. 1A) available.We greatly acknowledge the very detailed and constructive comments by three GCA reviewers: R. Martín-García and two anonymous colleagues. We also acknowledge the comments and the editorial handling of this paper by Miryam Bar-Matthews.

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Chapter 4

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Supplement

83

SUPPLEMENTARY MATERIAL CHAPTER 4

Methods

Element

Al 110 ± 16 31 ± 4 27.1 ± 3.5Ba 114 ± 8 115 ± 6 105.4 ± 6Br 18.7 ± 21.2Ce 123 ± 10 121 ± 11Cu 124 ± 5 90 ± 8Dy 135 ± 12 138 ± 16Er 128 ± 11 136 ± 17Eu 0.0049 ± 0.0009 0.004 ± 0.001Fe 130 ± 8Gd 128 ± 11 134 ± 16Ho 0.0052 ± 0.0005 0.006 ± 0.001La 126 ± 12 125 ± 12 129 ± 12Lu 0.0026 ± 0.0003 0.002 ± 0.0004Mg 10 ± 10 11.8 ± 0.6 10.6 ± 0.7Mn 118 ± 12 122 ± 9 120 ± 10.2Na 36.2 ± 6Nd 135 ± 12 134 ± 13P 2.5 ± 0.2

Pb 115 ± 5 102 ± 7Pr 0.0063 ± 0.0008 0.006 ± 0.001Rb 0.065 ± 0.03 0.08 ± 0.02Sm 134 ± 12 133 ± 14Sr 219 ± 20 215 ± 7 196 ± 13Tb 0.021 ± 0.002 0.03 ± 0.006Th 0.011 ± 0.001 0.01 ± 0.002Tm 0.0039 ± 0.0006 0.004 ± 0.001U 0.004 ± 0.001 0.003 ± 0.0007Y 0.054 ± 0.004 0.06 ± 0.01

Yb 132 ± 10 130 ± 17Zn 123 ± 16 98 ± 5 109 ± 12

Recommended by S. Wilsona Mertz-Kraus 2009 This study

Table S4.1. Elemental concentrations (ppm) MACS1 standard

Chapter 4

84

Mg Al P Sr Y Ba) Pb UMg 1.00 0.54 -0.24 -0.49 0.33 0.35 0.53 -0.32Al 0.54 1.00 -0.04 -0.33 0.47 -0.21 0.88 -0.57P -0.24 -0.04 1.00 0.54 0.20 0.04 -0.19 0.26Sr -0.49 -0.33 0.54 1.00 -0.06 0.07 -0.41 0.63Y 0.33 0.47 0.20 -0.06 1.00 -0.32 0.35 0.11Ba 0.35 -0.21 0.04 0.07 -0.32 1.00 -0.22 0.15Pb 0.53 0.88 -0.19 -0.41 0.35 -0.22 1.00 -0.64U -0.32 -0.57 0.26 0.63 0.11 0.15 -0.64 1.00

Mg -- 0.01 0.16 0.01 0.05 0.04 0.01 0.06Al 0.01 -- 0.80 0.05 0.01 0.20 0.01 0.01P 0.16 0.80 -- 0.01 0.22 0.81 0.27 0.12Sr 0.01 0.05 0.01 -- 0.70 0.67 0.01 0.01Y 0.05 0.01 0.22 0.70 -- 0.05 0.03 0.50Ba 0.04 0.20 0.81 0.67 0.05 -- 0.20 0.37Pb 0.01 0.01 0.27 0.01 0.03 0.20 -- 0.01U 0.06 0.01 0.12 0.01 0.50 0.37 0.01 --

Table S4.2. Aragonite from the aragonite-to-calcite transitionPearson correlation coefficients between all elements with significance levels. All correlation coefficients 0.5 and p-value 0.01 are considered significant. Correlations considered significant are bold, for clarity reasons p-values 0.01 are indicated as 0.01.

PearsonCorrelationcoefficients

P-values

Supplement

85

Mg

Al

PT

iSr

YB

a)Pb

Th

UM

g1.

00-0

.13

-0.8

1-0

.02

0.71

-0.5

20.

80-0

.14

-0.1

60.

13A

l-0

.13

1.00

0.34

0.85

-0.2

50.

17-0

.08

0.75

0.81

0.02

P-0

.81

0.34

1.00

0.17

-0.7

00.

74-0

.84

0.29

0.33

-0.2

3T

i-0

.02

0.85

0.17

1.00

-0.0

80.

060.

020.

780.

810.

02Sr

0.71

-0.2

5-0

.70

-0.0

81.

00-0

.58

0.84

0.00

-0.0

40.

47Y

-0.5

20.

170.

740.

06-0

.58

1.00

-0.7

10.

110.

16-0

.32

Ba

0.80

-0.0

8-0

.84

0.02

0.84

-0.7

11.

000.

100.

020.

47Pb

-0.1

40.

750.

290.

780.

000.

110.

101.

000.

930.

21T

h-0

.16

0.81

0.33

0.81

-0.0

40.

160.

020.

931.

000.

10U

0.13

0.02

-0.2

30.

020.

47-0

.32

0.47

0.21

0.10

1.00

Mg

--0.

190.

010.

880.

010.

000.

010.

180.

140.

21A

l0.

19--

0.01

0.01

0.02

0.11

0.42

0.01

0.01

0.86

P0.

010.

01--

0.12

0.01

0.01

0.01

0.01

0.01

0.02

Ti

0.88

0.01

0.12

--0.

450.

610.

860.

010.

010.

84Sr

0.01

0.02

0.01

0.45

--0.

010.

010.

980.

690.

01Y

0.01

0.11

0.01

0.61

0.01

--0.

010.

270.

140.

01B

a0.

010.

420.

010.

860.

010.

01--

0.34

0.86

0.01

Pb0.

180.

010.

010.

010.

980.

270.

34--

0.01

0.04

Th

0.14

0.01

0.01

0.01

0.69

0.14

0.86

0.01

--0.

37U

0.21

0.86

0.02

0.84

0.01

0.01

0.01

0.04

0.37

--

Tabl

e S4

.3. H

K3

Cal

cite

Pear

son

corr

elat

ion

coef

ficie

nts b

etw

een

all e

lem

ents

with

sign

ifica

nce

leve

ls. A

ll co

rrel

atio

n co

effic

ient

s 0

.5 a

nd

p-va

lue

0.0

1 ar

e co

nsid

ered

sign

ifica

nt. C

orre

latio

ns c

onsi

dere

d si

gnifi

cant

are

bol

d, fo

r cla

rity

reas

ons p

-val

ues

0.

01 a

re in

dica

ted

as 0

.01.

Pear

son

Cor

rela

tion

coef

ficie

nts

P-va

lues

Chapter 4

86

Mg Al P Sr Y Ba) Pb UMg 1.00 0.39 -0.24 0.39 0.24 0.64 0.27 0.01Al 0.39 1.00 0.20 0.23 0.70 0.45 0.48 -0.02P -0.24 0.20 1.00 0.18 -0.04 0.20 -0.02 0.53Sr 0.39 0.23 0.18 1.00 0.21 0.57 0.24 0.32Y 0.24 0.70 -0.04 0.21 1.00 0.16 0.49 -0.07Ba 0.64 0.45 0.20 0.57 0.16 1.00 0.28 0.40Pb 0.27 0.48 -0.02 0.24 0.49 0.28 1.00 -0.08U 0.01 -0.02 0.53 0.32 -0.07 0.40 -0.08 1.00

Mg -- 0.01 0.11 0.01 0.11 0.01 0.07 0.96Al 0.01 -- 0.18 0.12 0.01 0.01 0.01 0.90P 0.11 0.18 -- 0.22 0.80 0.19 0.91 0.01Sr 0.01 0.12 0.22 -- 0.16 0.01 0.11 0.03Y 0.11 0.01 0.80 0.16 -- 0.30 0.01 0.64Ba 0.01 0.01 0.19 0.01 0.30 -- 0.06 0.01Pb 0.07 0.01 0.91 0.11 0.01 0.06 -- 0.60U 0.96 0.90 0.01 0.03 0.64 0.01 0.60 --

Table S4.4. HK3 Aragonite from the calcite-to-aragoPearson correlation coefficients between all elements with significance levels. All correlation coefficients 0.5 and p-value 0.01 are considered significant. Correlations considered significant are bold, for clarity reasons p-values 0.01 are indicated as 0.01.

PearsonCorrelationcoefficients

P-values

Table S4.5. GP2 Calcite

Mg Al P Sr Y Ba) Pb UMg 1.00 -0.54 -0.73 0.66 -0.58 0.71 -0.49 -0.68Al -0.54 1.00 0.47 -0.52 0.43 -0.66 0.26 -0.03P -0.73 0.47 1.00 0.95 0.86 -0.93 0.71 0.22Sr 0.66 -0.52 -0.95 1.00 -0.78 0.96 -0.69 0.22Y -0.58 0.43 0.86 -0.78 1.00 -0.72 0.58 0.05Ba 0.71 -0.66 -0.93 0.96 -0.72 1.00 -0.63 -0.39Pb -0.49 0.26 0.71 -0.69 0.58 -0.63 1.00 0.05U -0.68 -0.03 0.22 -0.22 -0.05 -0.39 0.05 1.00

Mg -- 0.01 0.01 0.01 0.01 0.01 0.01 0.01Al 0.01 -- 0.01 0.01 0.01 0.01 0.07 0.84P 0.01 0.01 -- 0.01 0.01 0.01 0.01 0.14Sr 0.01 0.01 0.01 -- 0.01 0.01 0.01 0.14Y 0.01 0.01 0.01 0.01 -- 0.01 0.01 0.75Ba 0.01 0.01 0.01 0.01 0.01 -- 0.01 0.01Pb 0.01 0.07 0.01 0.01 0.01 0.01 -- 0.72U 0.01 0.84 0.14 0.14 0.75 0.01 0.72 --

Pearson correlation coefficients between all elements with significance levels. All correlation coefficients 0.5 and p-value 0.01 are considered significant. Correlations considered

PearsonCorrelationcoefficients

P-values

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Table S6. GP2 Aragonite

Mg Al P Sr Y Ba Pb UMg 1.00 0.13 -0.08 0.07 0.20 0.10 0.30 0.54Al 0.13 1.00 0.33 0.08 -0.05 0.12 -0.01 0.04P -0.08 0.33 1.00 0.67 0.50 0.19 0.26 0.42Sr 0.07 0.08 0.67 1.00 0.67 -0.11 0.54 0.81Y 0.20 -0.05 0.50 0.67 1.00 -0.29 0.82 0.56Ba 0.10 0.12 0.19 -0.11 -0.29 1.00 -0.60 -0.07Pb 0.30 -0.01 0.26 0.54 0.82 -0.60 1.00 0.56U 0.54 0.04 0.42 0.81 0.56 -0.07 0.56 1.00

Mg -- 0.37 0.60 0.61 0.17 0.51 0.04 0.01Al 0.37 -- 0.02 0.56 0.74 0.41 0.96 0.78P 0.60 0.02 -- 0.01 0.01 0.19 0.07 0.01Sr 0.61 0.56 0.01 -- 0.01 0.45 0.01 0.01Y 0.17 0.74 0.01 0.01 -- 0.05 0.01 0.01Ba 0.51 0.41 0.19 0.45 0.05 -- 0.01 0.64Pb 0.04 0.96 0.07 0.01 0.01 0.01 -- 0.01U 0.01 0.78 0.01 0.01 0.01 0.64 0.01 --

Pearson correlation coefficients between all elements with significance levels. All correlation coefficients 0.5 and p-value 0.01 are considered significant. Correlations considered significant are bold, for clarity reasons p-values 0.01 are indicates as 0.01.

PearsonCorrelationcoefficients

P-values

Reproducibility of trace element results

Fig. S4.1 Comparison between LA-ICP-MS and ICP-OES trace element data. Red lines represent Mg, and Sr (ppm) measured with LA-ICP-MS. Black lines represent Mg/Ca and Sr/Ca ratio’s measured with ICP-OES. Calcite interval is indicated by bar shaded dark grey. Aragonite interval is indicated by bar shaded light grey. Note the very similar trends in the Mg/Ca ratio and the Mg concentration. The transition to aragonite coincides with a strong increase in the Sr/Ca ratio and the Sr concentration, and a strong decrease in the Mg/Ca ratio and the Mg concentration. This is considered evidence that the results can be reproduced, and are not affected by sample inhomogenities.

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Effects on trace element concentrations of 0-10% primary calcite in aragonite

The lateral and stratigraphical Ar-Cc, and Cc-Ar transitions provide solid evidence that close to the transitions Sr concentrations fluctuate around 60 ppm for calcite and 600 ppm for aragonite, Mg concentrations fluctuated around 9000 ppm in calcite and 40 ppm in aragonite, wherea Ba concentrations fluctuated around 12 ppm in calcite and 35 ppm in aragonite. Fig. S4.2 plots Mg and Sr concentrations for different calcite aragonite mixtures varying from 100% aragonite to 90% aragonite. Different Sr aragonite end member values (300, 600, and 900 ppm) were used, while Mg in the pure calcite end member value was given as 10000 ppm. A 2% increase in primary calcite, may increase the Mg concentration by approximately 150 ppm, the overall effect on Sr is small (below 10 ppm), this does not depend on the Sr aragonite endmember (Fig. S4.2). Uranium, which is not shown here, may be affected similarly to Mg, as the differences in the concentrations across the Ar-Cc, and Cc-Ar transitions are in a similar range.

Fig. S4.2 Calcite aragonite mixture effects.

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Prior Aragonite Precipitation

5. MEDIEVAL PRECIPITATION VARIABILITY IN MOROCCO REFLECTED BY SPELEOTHEM AND TREE-RING PROXIES*

This chapter is in revision and to be resubmitted to Earth and Planetatry Science Letters

Abstract

Speleothem-based climate reconstructions are mostly based on calcitic stalagmites as aragonite is thermodynamically less stable. Unaltered aragonite speleothems, however, contain high amounts of U and allow for particularly well dated paleoclimate reconstructions. The effects of prior calcite precipitation on Mg, Ba and Sr concentrations in calcitic speleothems are thoroughly discussed in literature. Prior aragonite precipitation, in contrast, has received little attention. Here, we present drip water Mg/Ca, Ba/Ca and Sr/Ca ratios from a two year monitoring program of Grotte de Piste in Morocco. Different drip sites indicate both, prior calcite and prior aragonite precipitation and a modelling approach is used to assess differences between prior calcite and aragonite precipitation. Results indicate that prior aragonite precipitation may explain negative correlations between Mg and Sr and Sr and Ba in aragonitic speleothems. Comparison between an aragonite stalagmite Sr record and an updated tree-ring based drought reconstruction from Morocco reveals substantial coherence on multi-centennial timescales. This indicates that especially Sr concentrations in aragonitic speleothems seem to be sensitive for variations in prior aragonite precipitation. However, short intervals of prior calcite precipitation (identified by positive correlations between Mg and Sr) may interrupt periods dominated by prior aragonite precipitation. This has a large impact on the interpretation of Sr, therefore Sr should be accompanied by Mg. Nevertheless, seven periods of relatively low effective rainfall just before and during the Medieval Warm Period were recognized. Six of these are most likely linked to positive North Atlantic Oscillation conditions. This suggests that the North Atlantic Oscillation has varied on multidecadal to centennial time scales just before and during the Medieval Warm Period.

5.1. Introduction

Speleothems are well established archives of continental paleoclimate (Cruz et al., 2005; Wang et al., 2008; Zhang et al., 2008; Drysdale et al., 2009; Kanner et al., 2012). To date, most studies rely on calcitic stalagmites and flowstones (Neff et al., 2001; Spötl et al., 2002; White, 2004; Cai et al., 2010). Aragonite speleothems are common in dolomite host rock caves and in (seasonally) arid settings (Railsback et al., 1994; Bertaux et al., 2002; Frisia et al., 2002; Wassenburg et al., 2012). In general, aragonite is diagenetically less stable compared to calcite and may, thus, recrystallize to calcite (Frisia et al., 2002; Martin-Garcia et al., 2009). Well preserved aragonitic speleothems provide excellent archives for climate reconstruction (Cosford et al., 2008; Li et al., 2011) because they are well suited for U-Th dating due to their often high U content. Whereas most aragonite-based studies focussed on oxygen isotopes (Holmgren et al., 1999; Cosford et al., 2008; Holzkämper et al., 2009; Li et al., 2011 and others), trace element compositions remain largely unexplored (Finch et al., 2001; 2003; McMillan et al., 2005; Wassenburg et al., 2012). Therefore, understanding the processes

* In collaboration with: A. Immenhauser, D. K. Richter, A. Niedermayr, J. Fietzke, D. Scholz, K. P. Jochum, J. Fohlmeister, A.Schröder-Ritzrau, A. Sabaoui, D. F. C. Riechelmann, L. Schneider and J. Esper

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affecting speleothem aragonite trace element abundances is a necessity in order to explore the full potential of aragonite speleothems.

Positive correlations between Mg, Sr and Ba in calcitic speleothems have repeatedly been interpreted in terms of Prior Calcite Precipitation (PCP). Prior calcite precipitation refers to the process of calcite precipitation from the fluid upflow of the stalagmite when CO2 degasses and water becomes supersaturated with respect to CaCO3 (Fairchild and Treble, 2009). This may be related to the amount of water infiltrating into the karst aquifer and thus rainfall (Johnson et al., 2006; Cruz Jr. et al., 2007).

The interpretation of trace element records from aragonite speleothems differs from calcite speleothems due to: i) the different crystallographic systems (orthorhombic versus trigonal), ii) the possible presence of secondary calcite (Frisia et al., 2002; Ortega et al., 2005; Martin-Garcia et al., 2009) or iii) co-precipitation of primary aragonite and calcite (Holzkämper et al., 2009; Wassenburg et al., 2012). Crystallographic parameters cause PCP to have a different effect on drip water trace element to Ca ratios compared to prior aragonite precipitation (PAP; Wassenburg et al., 2012).

Here, trace element compositions of an aragonitic speleothem from the north-western part of the Middle Atlas in Morocco have been investigated. The cave studied is located in an area sensitive to droughts and is affected by the dominating atmospheric pressure mode of the Northern Hemisphere, the North Atlantic Oscillation (NAO; Hurrell, 1995). This is evident from the strong decrease in the amount of winter rainfall after the 1970’s, which was linked to pre-dominantly positive NAO conditions (Ward et al., 1999). Instrumental rainfall data in north-western Africa are not available from before 1900 AD and 1940 AD for most regions. Thus, high resolution, precisely dated palaeo-climate records for this region covering the last hundred to thousand years are needed to place recent climate change in a long-term context (IPCC 2007).

Esper et al. (2007) used tree-ring width data to reconstruct the Palmer Drought Severity Index (PDSI; Dai et al., 2004) for Morocco back to 1049 AD and showed that the late Medieval Warm Period (MWP) was characterized by exceptionally dry conditions. In contrast, the Little Ice Age (LIA) was shown to have been relatively wet in NW Africa. More recently, Trouet et al. (2009) observed a relationship between climate in north-western Africa and Europe based on the Moroccan PDSI reconstruction (Esper et al., 2007) and a Scottish speleothem (Proctor et al., 2000) and related this pattern to the NAO. The long-term change from persistently positive to (modern state) fluctuating NAO patterns during the MWP-LIA transitions, as reconstructed by Trouet et al. (2009), can, however, not be reproduced by climate models (Lehner et al., 2012).

The aims of this study are: 1) to present and interpret a precisely dated Sr record from an aragonite speleothem from the Middle Atlas in Morocco, covering the 747-1962 AD period; 2) to compare the speleothem record to an updated version of the tree-ring based PDSI reconstruction from Esper et al. (2007) and 3) to reconstruct the climatic conditions during the MWP in Morocco, with a focus on effective rainfall.

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5.2. Case setting

5.2.1. Present day climate of the Middle Atlas

Morocco is bordered by the North Atlantic to the west, the Mediterranean Sea to the north-east and the Western Sahara to the south-east (Fig. 5.1). The cave investigated here is referred to as Grotte de Piste (Gravel road cave) and is located in the north-western part of the Middle Atlas of Morocco (Fig. 5.1). According to Knippertz et al. (2003), this region falls within the Atlantic climate domain. The climate of the Middle Atlas is characterized by very dry summers (<2% of mean annual rainfall) and relatively wet winters (>40% of mean annual rainfall). Annual precipitation measured in Bab Bou Idir (1500 m asl.) near Grotte de Piste, is 862 (± 506; 1 SD) mm (years defined according to the Oct-Sep rain season, 1999-2010 period).

Tanger

RabatCasablanca

Fes

ErrachidiaMarrakech

Ouarzazate

AA

HA

MA

Rif

b

a

Fig. 5.1. Regional setting. (A) Regional setting of Morocco at the boundary between North Atlantic and Mediterranean Sea. (B) Cave position (indicated by the white star), with respect to the Rif, the Middle Atlas (MA), the High Atlas (HA), and the Anti Atlas (AA) mountain belts. Map modified after Sadalmelik: http://commons.wikimedia.org/wiki/File:Morocco_Topography.png.

Rainfall patterns are related to the strength and position of the Azores subtropical high, and are therefore related to the NAO index (Hurrell, 1995). During negative NAO conditions, the meridional pressure gradient is relatively low, weakening and shifting the westerlies southward (Wanner et al., 2001). Negative (positive) NAO conditions induce wetter (dryer) conditions in Morocco and the Iberian Peninsula, whereas in (north) Western Europe, relatively cold (warm) and dry (wet) conditions prevail. The NAO has also been demonstrated to be an important forcing of decadal scale climate variability in Morocco (Hurrell and Van Loon, 1997; Ward et al., 1999; Glueck and Stockton, 2001).

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5.2.2 Cave setting

Speleothem GP5 was collected from Grotte de Piste (Fig. 5.2) that developed in dolomitic host rock with spatially limited limestone intervals (Wassenburg et al., 2012). Grotte de Piste is located at an altitude of 1260 m above sea level. The vegetation above the cave consists of small oak trees, shrubs and grasses. About 60% of the dolomite host rock surface is covered by clay-rich soil with a thickness of up to 20 cm. Due to the cave’s position close to the top of a crest; the drip water is of local origin. The cave’s entrance is about 3 m wide and is characterized by a steep downward gradient. Grotte de Piste has a lower and an upper level, which is located approximately 20 m above the cave floor (Fig. 5.2).

1417

1813

GP5

Entrance

Upper level

20 m

a

b GP5

Upper level Entrance

1417

1813

1413

18

17

20 m

Fig. 5.2. Cave map and cross section of Grotte de Piste (modified after Wassenburg et al. 2012), with positions of drip site 13, 14, 17 and 18. (A) Cave in cross section view. (B) Cave in map view. The sampling location of stalagmite GP5 is indicated.

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5.3. Material and methods

Stalagmite GP5, fed by a 27 cm long stalactite, has a total length of 78 cm and grew at the upper cave level at a distance of 50 meters from the entrance (Fig. 5.2). Here, data from the upper 20 cm of the stalagmite are presented (Fig. 5.3). GP5 is partly characterized by mm scale layering made up by alternating porous and less porous layers (Fig. 5.3). The mineralogy of GP5 was determined by X-ray diffraction analysis (XRD, Miao et al., 2009) of hand drilled samples (ca. 20 mg). Ten percent of quartz was added to the sample powder as a standard in order to derive offsets in the {104} calcite peaks and estimate the Mg content within the crystal lattice in mol-% (Füchtbauer and Richter, 1988). Samples were homogenised in an agate mortar before being analysed. Thin section petrography was used to examine the aragonite fabric for potential diagenetic features.

818 AD997 AD

619 AD 5 mm

1

2 3

1 mm

1 cm

619 AD

818 AD997 AD

1269 AD

1381 AD

1759 AD

1896 AD

a

b

dTrace element transectXRD sample

U/Th, 14C sample

200 μm

1964 AD c

Fig. 5.3. Overview stalagmite GP5 and sampling positions. (A) Stalagmite GP5 with U-Th and 14C derived years, X-ray Diffraction (XRD) sample positions and trace element transects indicated. (B) Sketch showing periods of discontinuous growth labelled 1-3. Changes in drip position caused changes in the growth directions indicated by black arrows. (C) Scan across hiatus surface. Black arrows indicate dense grey layers. (D) Thin section image under crossed nichols showing layering due to alternating low and high porosity layers. Black arrow indicates growth direction.

Cave monitoring of Grotte de Piste was performed between March 2010 and March 2012 with sampling intervals of three months (i.e., spring, summer, fall, winter). Four drip sites located on the upper cave level were monitored (Fig. 5.2) for drip rates and drip water Mg, Sr, Ba concentrations. Cave air CO2 concentrations were measured at fixed positions at the ceiling and at the bottom of

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the cave during monitoring visits in order to deduce information on cave air circulation (Bourges et al., 2006; Kowalczk and Froelich, 2010; Frisia et al., 2011). In addition, cave air temperature was measured every twelve hours using permanently installed temperature loggers (I-Buttons). For more details see supplement.

GP5 was dated using the U-Th dating method at the IFM-Geomar in Kiel, Germany. Eight samples (Fig. 5.3) were analysed with an AXIOM MIC-ICP-MS; (Fietzke et al., 2005). Additional dating was performed with the radiocarbon method in order to find the mid 20th century atmospheric 14C anomaly (“bomb-peak”) to document recent growth of the stalagmite (Mattey et al., 2008; Hodge et al., 2011; Fohlmeister et al., 2012). See supplement for more details. The age-depth model was calculated using the StalAge algorithm designed by Scholz and Hoffmann (2011), which gives 95%-confidence limits for the age model. Additional uncertainty exists due to the thickness of the sample hole (i.e., 2.5-4 mm), however this remains difficult to include quantitatively with StalAge. Sample positions are shown in Fig. 5.3.

Magnesium, Sr and Ba concentrations were analysed at 1 mm (5 year) resolution covering the complete top 20 cm of stalagmite GP5 and locally at 100 μm (sub-annual) resolution across very well defined layering. A Thermo Finnigan Element 2 ICP-MS at the Max Planck Institute for Chemistry, Mainz, Germany performed the analyses of 25Mg, 86Sr and 137Ba. Samples were ablated with a New Wave UP213 laser with energy of 15.7 J/cm2. NIST612 glass (Jochum et al., 2011) and MACS3 carbonate (Jochum et al., 2012) reference materials were used for correction of instrumental biases. The use of the MACS1 reference material as a quality control showed that Mg, Sr and Ba values were close to other published values (Jochum et al., 2012). Relative uncertainties for Mg, Sr and Ba derived from MACS1 measurements are approximately 7%. A relatively large spot size (100 μm) was used for all measurements to average out heterogeneities within growth increments (Finch et al., 2003; McMillan et al., 2005). Sample positions are indicated in Fig. 5.3. For further details about the method, the reader is referred to (Jochum et al., 2007; 2012).

Esper et al. (2007) reconstructed PDSI variations of the 1049-2001 AD period in Morocco. We here include an update of this reconstruction based on 22 new tree-ring samples collected in 2010 from some of the oldest Cedrus atlantica trees in Morocco, “Col du Zad” (Col) in the Middle Atlas. The re-sampling included cedar trees with a girth of > 4.5 m drilled with a 1 m long increment corer. The new samples were combined with the original collection of 326 tree-ring series detailed in Esper et al. (2007). A PDSI-reconstruction is derived from linear regression of a combined RCS and linear detrended tree-ring chronology against February-June sc (self-calibrating) PDSI data (van der Schrier et al., 2011) over the period of 1931-2008. Besides increasing replication during earlier periods, the updated scPDSI reconstruction is based on an extended calibration period (now 1931-2008) resulting in an (slightly) improved transfer model. Consideration of the scPDSI (instead of PDSI; Dai et al., (2004) for calibration has two major advantages: It is i) based on a finer grid, 0.5° x 0.5° instead 2.5° x 2.5°, and ii) calibrated with respect to the representative onsite conditions, i.e. reconstructed drought deviations can more directly be compared with variations from other, perhaps teleconnected regions (van der Schrier et al., 2011). For calibration 40 grid points north of the High Atlas were selected, which represent the synoptic climate setting of the investigated region. See Esper et al. (2007) for more detailed information on the sampling location and chronology construction.

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5.4. Results

5.4.1. Cave monitoring

At the bottom of the cave, pCO2 fluctuates between ~450 ppmv during winter and ~4000 ppmv during summer months. In addition, the temperature at the bottom of the cave ranges from 10.7 (winter) to 12.3°C (summer). Outside air temperature ranges from 7 (winter) to 22°C (summer). This is strong evidence for seasonally fluctuating cave air ventilation (Bourges et al., 2006; Kowalczk and Froelich, 2010). Speleothem GP5 was collected from the upper cave level (Fig. 5.2), which experiences a seasonal temperature range between 11.8°C (winter) and 13.3°C (summer). Cave air pCO2 has a mean of 666 ± 151 ppmv at the position of stalagmite GP5 and is rather constant throughout the year. Therefore, it is unlikely that variations in cave ventilation had a strong effect on the growth rate of stalagmite GP5.

Four drip sites have been monitored over a period of two years. This includes drip site 14, which fed stalagmite GP5. All drip sites are located on the upper level of the cave (Fig. 5.2) and display a clear response to the pronounced seasonality resulting in a cessation of dripping at drip sites 14 and 17 and a very slow drip interval (<0.1 drips per minute) for drip sites 13 and 18 in September. In February 2010, coinciding with a negative NAO index (Osborn, 2011), drip sites 13 and 14 showed the highest drip rates of the monitoring period (Fig S5.1). All drip sites show a strong relation between drip water Ca concentrations and drip rate (Fig. 5.4a). The drip water from drips 17 and 18 has Mg/Ca ratios <1, whereas drip water Mg/Ca ratios are generally >2 for drip sites 13 and 14, except for one sample (Fig. 5.4b). The elevated Mg/Ca ratios are one of the key factors that induce aragonite precipitation in Grotte de Piste (Wassenburg et al., 2012).

0 4 8 12Mg/Ca (mmol/mmol)

00.40.81.21.6

Ca

(mm

ol/l)

0 1 2 3Drip rate (dr/min)

00.40.81.21.6

Ca

(mm

ol/l)

0.1 0.3 0.5 0.7Sr/Ca (µmol/mmol)

00.40.81.21.6

Ca

(mm

ol/l)

0 0.3 0.6 0.9Ba/Ca (µmol/mmol)

00.40.81.21.6

Ca

(mm

ol/l)

a

c

b

d

Fig. 5.4. Drip water monitoring data. Orange circles represent drip site 13. Red rhombus indicate drip site 14. Dark blue triangles indicate drip site 17. Light blue crosses indicate drip site 18. (A) Calcium concentration versus drip rate. (B) Calcium concentration versus Mg/Ca ratio. (C) Calcium concentration versus 1000*Ba/Ca. (D) Calcium concentration versus 1000*Sr/Ca. The highlighted data points (dashed circles) represent the two fastest drips from drip site 14.

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Drip water Mg/Ca and Ba/Ca ratios display a clear trend towards higher values with decreasing drip water Ca concentrations (Fig. 5.4b-c). Drip water samples with relatively high Ca concentrations display an increasing Sr/Ca with decreasing Ca concentration. This is in contrast with the drip water samples characterized by relatively low Ca concentrations. These show decreasing drip water Sr/Ca ratios with decreasing Ca concentrations (Fig. 5.4d). Note that these samples are characterized by Mg/Ca ratios >2 (Fig. 5.4b). The relation between rainfall, drip rate and drip water Mg/Ca ratios is presented in Fig. S5.1.

5.4.2. Age-depth model

The 14C analysis of four samples indicate significantly elevated 14C activity in the upper two samples showing that stalagmite GP5 was at least still growing in the early 1960’s (Fig. 5.5a). After the 1970’s annual rainfall in the Atlantic part of Morocco decreased considerably and probably induced slow or discontinuous growth. Based on a comparison of the 14C activity of the stalagmite and an atmospheric 14C activity curve (Levin and Kromer, 2004; Reimer et al., 2004; Levin et al., 2010), the year 1964 was assigned to a depth of 0.2 mm beneath the stalagmite top (Fig. 5.5). The fact that the drip water from drip site 14 is still supersaturated suggests that stalagmite GP5 was actively growing at the time of collection (2010 AD), albeit slow due to low mean drip water Ca concentrations (0.57 mmol/l). The year 2010 AD is assigned to the top of stalagmite GP5, and is included in the calculation of the age depth model.

1900 1920 1940 1960 1980Year (AD)

80100120140160180200

14C

Act

ivity

(pm

C)

0.2 0.1

Atmosphere

Stalagmite

Hiatus

481216Depth (mm)

a b

0 40 80 120 160 200Depth (mm)

20001750150012501000750500

Yea

r (A

D)

Fig. 5.5. Age-depth model stalagmite GP5. (A) Atmospheric 14C activity versus stalagmite GP5 14C activity. The year 1964 AD has been assigned to a depth of 0.2 mm beneath the stalagmite top (2010 AD). (B) Age depth model obtained with StalAge (Scholz and Hoffmann, 2011). Red dashed lines indicate 95%-confidence limits. The age uncertainty of the outlier at 5 mm depth was enlarged in order to fit the age depth model according to the estimated position of the 14C bomb peak. Note that for the basal section linear interpolation was used due to the presence of a hiatus (indicated by the black bar).

Eight samples were dated by the U-Th dating method (Table 6.1). Considering that parts of

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Prior Aragonite Precipitation

the 14C bomb-peak could be identified, one outlier in the U-Th dating (close to the stalagmite top; sample GP5 U4; Table 5.1) was recognized. Using the StalAge algorithm for the age depth model (Scholz and Hoffmann, 2011) the error bar for this particular sample was enlarged. The stalagmite has a hiatus at 182.7 mm distance from the top (Fig.3c). For the basal section, constrained by two ages, linear interpolation was used to construct an age model.

The hiatus surface macroscopically appears as a compact grey aragonite layer (Fig. 5.3c). Between 195.7 and 182.7 mm from the top (hiatus surface), an interval with similar grey layers was identified (Fig. 5.3a-c). These layers possibly coincide with several changes in the drip position, which induced changing growth directions and may be coupled to a period of discontinuous speleothem growth (Fig. 5.3b). Therefore, the age model of the basal section of the stalagmite is associated with larger uncertainty than the upper section. Discontinuous growth started after 619 (± 3) years AD, and stalagmite growth ceased at approximately 904 AD. Growth started again between 906 and 982 AD as given by the StalAge algorithm (Scholz and Hoffmann, 2011). Between 943 and 1964 AD the stalagmite grew with an average rate of 180 μm per year.

5.4.3. Petrography

Stalagmite GP5 is aragonitic, but XRD suggest that minor (<2%) amounts of calcite are present. The Mg content within the crystal lattice of the subordinate calcite phase ranges from 0.8 to 1.9 mol-%. This suggests that calcite co-precipitated with aragonite but was also formed as a secondary phase. Calcite is not recognized in thin sections (Fig. 5.3). Aragonite needle crystals show a length to width ratio >> 6:1 and are organized in fan like structures, which show a sweeping extinction across several crystals. These are characteristics of an acicular fabric (Frisia and Borsato, 2010).

5.4.4. Geochemistry

Magnesium, Sr and Ba concentrations from the five year resolution transect covering the period 747-1962 AD is presented in Fig. 5.6a. The average concentrations for Mg, Sr and Ba are 87 (± 25), 426 (± 49) and 32 (± 3) ppm respectively. Magnesium and Ba show very similar trends and are positively correlated (r = 0.75, p<0.001). Between 747 and 1402 AD, Sr is negatively correlated to Mg (r = -0.78, p<0.001) and Ba (r = -0.78, p<0.001). Between 1402 and 1962 AD, the correlation is weak or insignificant (p>0.01). In addition, the Medieval Warm Period (MWP) is characterized by higher Sr concentrations (394 ppm) compared to the Little Ice Age (LIA; 453 ppm). Strontium decreases towards the hiatus surface (Fig. 5.6a).

Magnesium, Sr and Ba concentrations from the high resolution (i.e., subannual) transect (1270-1330 AD) are presented in Fig. 5.6b. Porous layers coincide with higher Sr and lower Mg concentrations. Strontium and Mg are negatively correlated (r = -0.54, p < 0.001), whereas Mg and Ba are positively correlated (r = 0.78, p < 0.001).

Chapter 5

100

a

b

MWP LIA

1270 1290 1310 1330Year (AD)

40

60

80

100

120

Mg

(ppm

)

200

300

400

500

600

Sr (p

pm)

20

24

28

32

36

Ba

(ppm

)

500 800 1100 1400 1700 2000Year (AD)

250

350

450

550

Sr (p

pm)

4080120160200

Mg

(ppm

)

2025303540

Ba

(ppm

)

Fig. 5.6. Stalagmite GP5 geochemistry. Barium, Mg and Sr concentrations. (A) 500-2000 AD, 5 year resolution. Black bar indicates the position of hiatus. Grey bar indicates the interval which has been analysed on subannual resolution presented in 6b. Black squares at the bottom of the figure indicate position of U-Th sampling sites and the age assigned to 0.2 mm depth due to the 14C bomb peak. Timing of the Medieval Warm Period (MWP) and the Little Ice Age (LIA) is indicated. (B) 1270-1330 AD, sub-annual resolution. Grey shaded bars indicate the position of more porous layers, which are alternated with less porous layers.

101

Prior Aragonite Precipitation

Sam

ple

Nr.

Initi

al

(234 U

/238 U

)

GP5

U4

4.8

±2

4.53

2±

0.00

310

6±

15.

697

±0.

006

5.70

0.16

7±

0.00

218

43±

2G

P5 U

3.3

16.2

±1.

52.

975

±0.

002

116

±1

5.81

4±

0.00

45.

820.

114

±0.

001

1896

±1

GP5

U3.

246

.9±

1.8

3.74

4±

0.00

216

99±

191

5.81

2±

0.00

45.

820.

251

±0.

001

1759

±1

GP5

U3.

111

7.9

±1.

42.

299

±0.

001

3588

±58

45.

611

±0.

003

5.62

0.62

9 ±

0.00

213

81±

2G

P5 U

3.0

137.

1±

1.4

3.26

6±

0.00

322

55±

495.

298

±0.

006

5.31

0.74

1 ±

0.00

312

69±

3G

P5 U

317

2.4

±1.

64.

003

±0.

002

5044

±19

75.

869

±0.

003

5.88

1.01

3±

0.00

799

7±

7G

P5 U

2.5

188.

1±

1.4

3.82

0±

0.00

396

2±

66.

077

±0.

006

6.09

1.19

2 ±

0.00

681

8±

6G

P5 U

2.4

200.

5±

1.3

3.15

5±

0.00

133

35±

129

5.92

6±

0.00

35.

951.

391

±0.

003

619

±3

GP5

top

0.2

±0.

110

0.6

±0.

33G

P5 1

mm

0.95

±0.

5599

.47

±0.

29G

P5 5

mm

5.85

±0.

7589

.06

±0.

26G

P5 1

6mm

15.3

5±

0.65

89.1

7±

0.27

Yea

r

AD

± 1σ

(230 Th

/232 Th

)

± 1σ

(ppm

)±

1σ (p

mC

)(m

m)

Age

ka (B

P)

For t

he c

orre

ctio

n of

det

rital

230 Th

a 23

0 Th/23

2 Th a

ctiv

ity ra

tio o

f 0.6

± 0

.2 w

as u

sed

Tabl

e 5.

1. R

esul

ts fr

om U

/Th

datin

g an

d 14

C a

naly

sis

U/T

h

14C

Dec

ay c

onst

ants

use

d: λ

230 =

9.1

58 X

10-6

y-1

, λ23

2 = 4

.947

5 X

10-1

1 y-1

, λ23

4 = 2

.826

3 X

10-6

y-1

, λ23

8 = 1

.551

3 X

10-1

0 y-1

14C

act

ivity

Dep

th23

8 U(23

4 U/23

8 U)

± 1σ

Chapter 5

102

5.4.5. Updated tree-ring self-calibrating Palmer Drought Severity Index reconstruction

The updated, tree-ring based drought reconstruction presented here explains about 50% of the variance retained in the instrumentally derived scPDSI timeseries (r1931-2008 = 0.69). It shows substantial decadal to centennial scale drought variability of the 1043 to 2008 AD period, including a persistent change from dryer conditions during late medieval times into a pluvial period after about 1400 AD (Fig. S5.2). The past 600 years are characterized by substantial dry and pluvial swings and a shift towards severe drought in the late 20th century. The scale of PDSI variations also differs between the original and updated reconstructions (Fig. S5.2). A feature that is largely attributed to the self-calibration process (van der Schrier et al., 2006).

5.5. Discussion and climatic interpretation

5.5.1. Prior Calcite Precipitation versus Prior Aragonite Precipitation

Precipitation of a carbonate mineral affects the trace element to Ca ratios of the fluid if trace elements are taken up disproportional with respect to Ca. Prior calcite precipitation (Fairchild et al., 2000; McMillan et al., 2005; Fairchild and Treble, 2009; Sherwin and Baldini, 2011; Wong et al., 2011; Sinclair et al., 2012) takes place if the water encounters a gas phase with a lower pCO2 causing CO2 degassing within the karst aquifer or at the cave ceiling. This in turn leads to super-saturation of the water with respect to CaCO3, leading to precipitation (Fairchild and Treble, 2009). Under dry climate conditions PCP can increase because of the increasing abundance of gas filled voids within the karst aquifer and decreasing drip rates. Nevertheless, changes in soil CO2 production and cave air pCO2 may be important as well (Sherwin and Baldini, 2011; Wong et al., 2011).

In contrast, prior aragonite precipitation (PAP) has been given little attention so far (Fairchild and Treble, 2009; Wassenburg et al., 2012). Due to the different distribution coefficients of Mg, Sr and Ba (DMg, DSr, DBa), the potential effects of PCP and PAP on stalagmite Mg, Sr and Ba concentrations are considerably different. The distribution coefficient in an unlimited reservoir is defined as:

Dtrace= (trace/Ca)solid/(trace/Ca)solution. (1),where (trace/Ca)solid and (trace/Ca)solution are the element to Ca ratio in the precipitated mineral and the solution, respectively. The drip water Ca concentrations in this study show a relation to drip rate, whereas drip rate reflects the seasonality in the rainfall. Magnesium/Ca and Ba/Ca ratios increase with decreasing drip rates for all drip sites, whereas Sr/Ca ratios display a bimodal behaviour (Fig. 5.4). Drip sites 17 and 18, which both exhibit Mg/Ca ratios below 1, show increasing drip water Sr/Ca ratios with decreasing Ca concentrations. This is in contrast with drip site 13 and 14, which exhibit Mg/Ca ratios >2 and drip water Sr/Ca ratios decreasing with decreasing Ca concentration. High drip water Mg/Ca ratios in cave environments can induce precipitation of aragonite (Frisia et al., 2002; McMillan et al., 2005; Wassenburg et al., 2012). Frisia et al. (2002) observed aragonitic speleothems under drip sites with Mg/Ca ratios of approximately 1.2. Wassenburg et al. (2012) calculated a potential drip water Mg/Ca ratio threshold of 2.1 based on calcite-to-aragonite transitions in Moroccan speleothems, whereas

103

Prior Aragonite Precipitation

0 3 6 9 12Mg/Ca (mmol/mmol)

00.40.81.21.6

Ca

(mm

ol/l)

0 1 2 3Drip rate (dr/min)

00.40.81.21.6

Ca

(mm

ol/l)

0.1 0.3 0.5 0.7Sr/Ca (µmol/mmol)

00.40.81.21.6

Ca

(mm

ol/l)

0 0.3 0.6 0.9Ba/Ca (µmol/mmol)

00.40.81.21.6

Ca

(mm

ol/l)

a

c

b

d

PCP

PAP1; 2

PAP1

PCP

PAP2

PCP

PAP1 PAP2

Fig. 5.7. Drip water monitoring data compared to modelling results. Orange circles represent drip site 13. Red rhombus indicate drip site 14. Dark blue triangles indicate drip site 17. Light blue crosses indicate drip site 18. Black line represents prior calcite precipitation (PCP) evolution line, whereas blue lines represent the prior aragonite precipitation (PAP) evolution line. PAP1 corresponds to the distribution coefficients derived from the stalagmite GP5 and monitoring data. PAP2 (blue dashed line) corresponds to the distribution coefficients derived from the literature. The highlighted data points (dashed circles) represent the two fastest drips from drip site 14. Refer to text for more details. (A) Calcium concentration versus drip rate. (B) Calcium concentration versus Mg/Ca ratio. (C) Calcium concentration versus 1000*Ba/Ca. (D) Calcium concentration versus 1000*Sr/Ca.

Railsback et al. (1994) suggested that aragonite starts to precipitate if drip water Mg/Ca ratios reach a value of approximately 3.3. The bimodal behaviour of the drip water Sr/Ca ratios may, therefore, be related to PCP if drip water Mg/Ca <1 and PAP if drip water Mg/Ca is between 1 and 3 or >3. This is due to the very different DSr during precipitation of calcite and aragonite precipitation, respectively (Tesoriero and Pankow, 1996; Huang and Fairchild, 2001; Dietzel et al., 2004; Gaetani and Cohen, 2006).

It is important to note, however, that precipitation of aragonite is not solely depending on the drip water Mg/Ca ratio, as CO2 degassing rates, temperature, CaCO3 saturation state and CO3

2- controlled kinetic effects may play a role as well (Fernández-Díaz et al., 1996; Zuddas and Mucci, 1998; De Choudens-Sanchez and Gonzalez, 2009). These factors potentially affect the drip water Mg/Ca threshold for the precipitation of aragonite.

Based on the above presented monitoring data, a simple modelling approach was used in order to calculate evolution lines of drip water Mg/Ca, Ba/Ca and Sr/Ca ratios with respect to the drip water Ca concentration under both a PCP and a PAP regime. It is acknowledged that the saturation index of the drip water affects the trace element distribution coefficients. Reliable pH values can, however,

Chapter 5

104

only be derived from drip water that has not undergone any CO2 degassing. In Grotte de Piste, drip rates are too slow to collect enough water to measure pH within a few minutes upon entering the cave. As a consequence, this factor could not be included in the modelling.

The following distribution coefficients were used for the PCP model: DMg = 0.019, DSr = 0.072, and DBa = 0.012. These were derived from laboratory experiments performed at 15°C, except for DBa, which corresponds to 25°C (Tesoriero and Pankow, 1996; Huang and Fairchild, 2001). For the PAP model, distribution coefficients were derived from laboratory experiments as well as estimated from the average stalagmite GP5 Mg/Ca, Ba/Ca, Sr/Ca ratios and the average drip water Mg/Ca, Ba/Ca, Sr/Ca ratios from drip site 14 (the one feeding stalagmite GP5). It is acknowledged that this approach does not account for a potential averaging effect due to changing solution compositions, while the drip water remains on top of the stalagmite (Johnson et al., 2006). For elements with a distribution coefficient close to unity (DSr) this effect is small and does not have a large affect on the shape of the evolution line in the monitoring plots in Fig. 5.7. The distribution coefficients estimated from stalagmite GP5 and monitoring data are 0.0001, 0.14 and 1.35 for DMg, DBa and DSr respectively. The distribution coefficients derived from laboratory experiments at 15°C are 0.0017, 1.8 and 1.2 for DMg, DBa and DSr respectively (Dietzel et al., 2004; Gaetani and Cohen, 2006). A drip water Mg/Ca-threshold (2.5) is used to define the transition from PCP to PAP.

It is obvious that DBa differs considerably from the experimentally derived distribution coefficients. DBa in aragonite was suggested to be 1.8 at 15°C (Dietzel et al., 2004) versus 0.14 derived from stalagmite GP5 and the monitoring data. However, Ba concentrations across calcite aragonite transitions in Holocene and Pleistocene speleothems from Morocco and southern France (McMillan et al., 2005; Wassenburg et al., 2012) showed that Ba concentrations increased only 4 times at the transition from calcite to aragonite, whereas Sr concentrations were 8 times higher in aragonite than in calcite. This shows that DBa in speleothem aragonite is probably much smaller than 1.8 and calls for a higher degree of understanding of Ba distribution coefficients during speleothem aragonite precipitation.

For the modelling, initial drip water Ca, Mg, Ba and Sr concentrations (starting values) were chosen within the range provided by the monitoring data from drip site 14 (the one feeding stalagmite GP5). For Ca, Ba and Sr, it is important to use only drip water samples, which are not strongly affected by PCP and PAP. Therefore, the highest observed values are used for the initial concentration. The initial Mg concentration is based on the averaged Mg concentration from drip site 14 because PCP or PAP has a negligible effect on drip water Mg concentrations. Modelled trends in drip water Mg/Ca, Ba/Ca and Sr/Ca ratios are plotted against monitoring data in Fig. 5.7. The modelled evolution lines for the PCP regime agree well with the monitoring data. The small offset between the drip water Mg/Ca ratios of drip site 17 and 18 can be explained by the relatively high initial Mg concentrations (Fig. 5.7) and shows that the drip water from the different drip sites probably encounters different amounts of dolomite within the karst aquifer. The modelled evolution lines for the PAP regime agree for Mg/Ca. For Sr/Ca and especially Ba/Ca a large difference can be observed between the evolution lines based on distribution coefficients derived from the literature and distribution coefficients derived from the stalagmite and monitoring data. The large deviation of the modelled Ba/Ca ratio suggests that during aragonite precipitation in cave systems DBa

105

Prior Aragonite Precipitation

Fig. 5.8. Stalagmite GP5 versus self-calibrated (sc) Palmer Drought Severity Index (PDSI) reconstruction. Bottom: Sr concentrations (blue; 1000-1900 AD: 21 point running mean; 790-860 AD: 5 point running mean) versus scPDSI (black; 25 year running mean), black bar represents timing of hiatus (904-943 AD). Top: High resolution Sr concentrations versus scPDSI reconstruction (non-smoothed data) between 1270 and 1330 AD. Period dominated by Prior Calcite Precipitation (PCP) is indicated by the light blue bar, whereas the period dominated by Prior Aragonite Precipitation is indicated by the red bar. Black squares at the bottom of the figure indicate position of U/Th sampling sites and the age assigned to 0.2 mm depth due to the 14C bomb peak. Timing of the Medieval Warm Period (MWP) and the Little Ice Age (LIA) is indicated.

is indeed smaller than 1 (Fig. 5.7). The modelled Sr/Ca ratios for the PCP and PAP regimes display an offset. For the PCP regime, this may be explained by the fact that growth rate effects on DSr in calcite (Treble et al. 2005) are not included in the model and that the highest Sr concentration taken as the initial value is possibly too high.

An important result, however, is the distinct shift from PCP to PAP as recognized in both the monitoring and the modelling data. This clearly reflects a distribution coefficient of Sr <1 for PCP and a distribution coefficient of Sr >1 for PAP. Therefore, we suggest that a negative correlation between Mg/Ca and Sr/Ca and Ba/Ca and Sr/Ca can be explained by PAP (Fig. 5.7).

Another important feature is that the drip water Mg/Ca value corresponding to the fastest drip from site 14 plots on the PCP evolution line in the Sr/Ca plot. In contrast, the second fastest drip plots in the transition zone from PCP to PAP. All other values plot within the PAP regime (Fig. 5.7). This shows that the drip water trace element to Ca ratio of an individual drip site may be affected by both PCP and PAP.

PCP

PAP

500 1000 1500 2000Year (AD)

250

350

450

550

Sr (p

pm)

-3

-1

1

scPD

SI

1270 1290 1310 1330Year (AD)

150

300

450

600

Sr (p

pm)

-3

-1

1

scPD

SI

Sr

Sr

MWP LIA

Chapter 5

106

5.5.2. Interpretation of Strontium data from stalagmite GP5

Based on previous work, Sr concentrations in aragonitic speleothems are related to effective rainfall (Finch et al., 2003; Wassenburg et al., 2012). Wassenburg et al. (2012) published data from Pleistocene and Holocene speleothems with several stratigraphic and lateral calcite-to-aragonite transitions and suggested that Sr variations in speleothem aragonite are related to changes in input rates of soil-derived organics because of the positive correlation of Sr with P and Y. A relationship

900 1000 1100 1200 1300 1400Years (AD)

480440400360320280

Sr (p

pm)

200

160

120

80

40

Mg

(ppm

)

Interpretation:

Mg

Sr

PAP PCP PAP PAP PAPPCP

Fig. 5.9. Stalagmite Mg and Sr data. Periods dominated by Prior Calcite Precipitation (PCP) are indicated by the blue bars, these periods show a tendency towards positive correlations between Mg and Sr. Periods dominated by Prior Aragonite Precipitation are indicated by the red bars, these periods show a tendency towards a negative correlation between Mg and Sr. Inferred climate interpretation in terms of high (blue) and low (red) effective rainfall is indicated on top. In periods when PAP dominated high Sr concentrations infer high effective rainfall, in periods dominated by PCP high Sr concentrations infer low effective rainfall. Magnesium is responding similar to PCP and PAP. Note that both y-axis are inverted.

between Mg, Ba, and Sr in speleothem aragonite was not found. Finch et al. (2003) found a positive correlation between Sr and Ba and effective rainfall, a feature that has mainly been attributed to the absence of PCP (Wassenburg et al., 2012).

Based on the monitoring and the modelling data, PAP in Grotte de Piste is enhanced during the dry season in Morocco. Prior aragonite precipitation is able to induce negative correlations between Mg and Sr and Sr and Ba. Therefore, relatively high Sr concentrations combined with relatively low Mg and Ba concentrations may be interpreted in terms of effective rainfall. Esper et al. (2007) proposed that the latter part of the MWP in Morocco was characterised by relatively dry climatic conditions compared to the LIA. Additionally a slight decreasing trend in the scPDSI reconstruction can be observed after 1750 AD. Indeed, stalagmite Sr concentrations are lower during the MWP compared to the LIA and the decreasing trend after 1750 AD is clearly visible in the GP5 Sr record (Fig. 5.8). This is in line with enhanced PAP during periods of lower effective rainfall. Furthermore, from 747 to 1402 AD, a period including the dry MWP, a strong negative correlation between Mg,

107

Prior Aragonite Precipitation

Ba and Sr is observed. This also suggests a role for PAP as a consequence of lower effective rainfall. Under relatively wet conditions, the amount of PAP is probably reduced, whereas PCP may be enhanced, this may be visible in the absence of a negative correlation between Mg and Sr and Sr and Ba for the period between 1402 and 1962 AD.

The absence of a negative correlation between Mg, Ba and Sr from 1402 to 1962 AD may also be explained by the characteristics of Mg and Ba incorporation into aragonite. The distribution coefficients of Mg and Ba between the precipitating fluid and aragonite are substantially <1 as suggested by the stalagmite and monitoring data. Therefore, it seems possible that Mg and Ba are (i) preferentially incorporated at crystal defect sites or (ii) absorbed onto the crystal surface. Thus, Mg and Ba may be more sensitive to competition effects in the presence of, for instance, phosphate ions, organic colloidal material or clay particles. This may be particularly pronounced during periods of reduced PAP/PCP as a consequence of increased effective rainfall. Moreover, the high coherence on multi-centennial timescales between the GP5 Sr record and the tree-ring scPDSI record demonstrates that Sr represents the most sensitive proxy for PAP variability related to effective rainfall.

However, the exact timing of the Sr peak around 1488 AD cannot be shifted within the age uncertainties to fit the peak in the scPDSI reconstruction (1450 AD). This may suggest that there is either a delay in the Sr signal of approximately 38 years or changes in the stalagmite growth rate have not been captured by the relatively low density of U-Th samples for this interval. Another explanation involves the high interannual rainfall variability observed in the tree ring scPDSI reconstruction combined with the relatively small spotsize with respect to the mean speleothem growth rate (100 µm spots and a 180 µm/a growth rate), therefore it might be possible that the extreme wet years have not been sampled. However, a detailed examination of the Mg and Sr data also shows that in the period from 900 to 1400 AD, when PAP was recognized as playing a major role, time intervals characterized by positive correlations between Mg and Sr indicate short intervals when PCP dominated. This has a large effect on the interpretation of the Sr data on multi-decadal to centennial timescales (Fig. 5.9). This mechanism might be able to explain why the most humid period indicated by the scPDSI reconstruction is not accompanied by the highest Sr concentrations. It is acknowledged that this should be confirmed by higher resolution data.

Other factors that may affect trace element concentrations in aragonitic speleothems are co-precipitation of primary calcite and diagenetic transformation of aragonite to secondary calcite, (micro)biological activity in the soil zone and chemical weathering (Hellstrom and McCulloch, 2000; Li et al., 2005). The co-precipitation of calcite and aragonite within the same speleothem may have a significant effect on Sr, Mg and Ba concentrations. Strontium and Ba abundances are higher in aragonite, whilst Mg is enriched in calcite. The positive correlation between Mg and Ba (Fig. 5.6), however, suggests that it is very unlikely that the Mg record reflects different admixtures of calcite and aragonite. In addition, XRD-analysis indicates that the amount of calcite present in stalagmite GP5 does not exceed 2%. Therefore, an effect on Sr or Ba content can be excluded (Wassenburg et al., 2012). Biological activity in the soil zone is expected to decrease during periods of increased aridity because it strongly depends on temperature and the availability of water. A reduction in effective rainfall is, therefore, expected to result in lower drip water Sr/Ca potentially amplifying the effect of PAP.

Chapter 5

108

CentralEuropean Alps

This study

Mangini et al. (2005)

Proctor et al. (2002)

MoroccoAtlantic

Scotland

-3

-2

-1

0

1

scPD

SI

500 750

A

B

C

D

a

EF

500 750 1000 1250 1500 1750 2000Years (AD)

0

20

40

60

80

Ban

d w

idth

(µm

)

MWP LIA

2 3 41 5 6 7

360

400

440

480

Sr (p

pm)

3

2

1

0

-1

Tem

pera

ture

3210

-1-2-3

NA

O

Humid

Dry

Dry/warm

Humid/cold

Cold

Warm

+

-

NAOWest

Greenland

Olsen et al. (2012)

Fig. 5.10. Comparison of Moroccan drought records with other climate reconstructions sensitive to the North Atlantic Oscillation (NAO). (A) NAO reconstruction from West Greenland (Olsen et al. 2012), note inverted Y-axis. (B) Temperature reconstruction from Spannagel Cave (Central European Alps, Austria; Mangini et al. 2005). (C) Tree-ring self-calibrating (sc) Palmer Drought Severity Index (PDSI) reconstruction (black; 25 year running mean). (D) Stalagmite GP5 Sr (light blue; 790-860 AD: 5 point running mean; 1000-1900 AD: 21 point running mean). (E) Stalagmite GP5 interpretation based on Mg and Sr concentrations as indicated in Fig. 5.9. (F) Speleothem band width record from Scotland (Proctor et al. 2002). Grey bars (1-7) represent arid phases in Morocco based on the presence of the hiatus in stalagmite GP5 (black bar) and the interpretation from stalagmite GP5 Mg and Sr concentrations. The timing of the hiatus is not well constrained, the grey bar represents an arbitrary uncertainty. Black squares at the bottom of the figure indicate U/Th sampling positions and the age assigned to 0.2 mm depth based on the 14C bomb peak. Triangles at the bottom of the graph indicate U-Th sampling positions for the speleothem record from the Central European Alps. Timing of the Medieval Warm Period (MWP) and the Little Ice Age (LIA) is indicated.

109

Prior Aragonite Precipitation

5.5.3. Climatic implications

As suggested by the relatively low Sr concentrations and the more negative scPDSI, the MWP in Morocco is clearly characterized by more arid climate conditions compared to the LIA (Fig. 5.10). In addition, Détriché et al. (2009) examined core data from lake Afourgagh, located approximately 100 km south-west of Grotte de Piste. They identified a lake level lowstand between 900 and 1211 AD coinciding with the MWP. These findings are in agreement with records from the Douro and Tagus mud patch (Abrantes et al., 2005; Abrantes et al., 2011), Iberian lake records (Martin-Puertas et al., 2008; Moreno et al., 2008) and marine proxy data from the western Mediterranean (Nieto-Moreno et al., 2011) and confirm the influence of the NAO on Moroccan climate (Trouet et al., 2009).

The influence of the NAO was studied by a proxy surrogate reconstruction (Trouet et al., 2009). In order to support their reconstruction, they used a temperature reconstruction from the Austrian Alps (Mangini et al., 2005). Here, we compare this temperature reconstruction with the extended bandwidth record from Scottish speleothems from Uamh an Tartair Cave (Proctor et al., 2002), our scPDSI reconstruction and our interpretation derived from GP5 Mg and Sr together with the recently published NAO reconstruction from Olsen et al. (2012). This in order to assess the influence of the NAO on Moroccan climate just before and through the MWP.

The tree-ring scPDSI reconstruction and the Scottish speleothem band width records have very small age uncertainties due to the annual layer counting. Mean analytical age uncertainties for stalagmite GP5 are ±4 years (Table 6.1), although additional uncertainty may exist due to the thickness of the sample hole (±12 years). Typical age uncertainties for the Spannagel record (Mangini et al., 2005) are ±20 years, although young ages have generally lower uncertainties compared to older ages.

5.5.3.1. Influence of NAO (500-1450 AD)

The lake level lowstand identified at lake Afourgagh (900-1211 AD) was preceded by higher lake levels (Détriché et al., 2009). This suggests more humid conditions prior to 900 AD. Between 818 and 1450 AD, our stalagmite suggests the presence of at least seven arid intervals, (Fig. 5.10). The first one (grey bar nr. 1; Fig. 5.10) commences around 850 AD and ends with a hiatus. The timing of the hiatus is at present poorly constrained. The second until the seventh arid period (grey bars nr. 2-7) date around 1000 AD, 1075 AD, 1160 AD, 1220 AD, 1310 AD and 1375 AD (Fig. 5.10).

Considering a minimal age-uncertainty in the stalagmite GP5 record, the coherence between stalagmite derived arid intervals nr. 3-6 and the scPDSI reconstruction is high, supporting our stalagmite Mg/Sr interpretation (Fig. 5.10). The speleothem record from the central European Alps, (Austria; Mangini et al., 2005) is clearly showing the MWP – LIA transition (Fig. 5.10), which has been related to the NAO (Trouet et al. 2009). On multi-decadal to centennial timescales during the 747 – 1450 AD interval the records seem consistent in terms of NAO for arid intervals nr. 3, 4 and 6. The most arid conditions in Morocco as recognized in the scPDSI reconstruction within arid interval nr. 5 at 1250 AD also coincides with a relatively warm oscillation in the Austrian Alps, whereas arid interval nr. 2 coincides with a warm peak recorded at 1025 AD, which is still within the age-uncertainty of the Austrian speleothem record. There seems to be no warm interval in the European

Chapter 5

110

Alps at the time of the hiatus in stalagmite GP5. The speleothem record from Scotland, shows increasingly humid periods during arid intervals

nr. 2, 4, 5, 6, and maybe during intervals nr. 3 and 7. This suggests that these periods were dominated by positive NAO conditions. As mentioned earlier the exact timing of the hiatus (arid interval nr. 1; Fig. 5.10) in stalagmite GP5 is not well constrained, but in the context of the NAO the authors consider it very likely that the hiatus is for a large part overlapping with the more humid period in Scotland and the reconstructed positive NAO conditions in the West Greenland record around 950 AD (Fig. 5.10). Additionally, arid intervals 2, 4, 5, 6 and maybe nr. 7 coincide with generally positive NAO conditions as reconstructed in West Greenland. It should be mentioned, however, that the West Greenland NAO reconstruction remains positive and shows little variability between 1100 AD and 1400 AD (Fig. 5.10). It thus appears that on multi-decadal to centennial timescales during the 747 – 1450 AD period stalagmite GP5 has been able to provide evidence that the NAO showed considerable variability just before and throughout the MWP confirming the tree ring scPDSI reconstruction.

Another interesting feature of stalagmite GP5 is the change in drip position shortly after 619 AD. As mentioned earlier this coincided with a period of discontinuous speleothem growth, which potentially indicates relatively arid conditions in Atlantic Morocco and thus the onset of positive NAO conditions. Indeed, around 675 AD the west Greenland NAO reconstruction (Olsen et al., 2012) suggests that positive NAO conditions persisted during this interval, which is also supported by a tendency towards warmer temperatures recorded in the Austrian speleothem (Fig. 5.10).The Scottish speleothems, however, imply relatively dry conditions. This apparent contradiction can be explained by the fact that Proctor et al. (2000; 2002) showed that speleothem growth rates in Uamh an Tartair Cave are also sensitive to temperature. Positive NAO conditions could, therefore, induce both higher growth rates due to increasing temperatures and lower growth rates due to increasing rainfall in the Scottish speleothems (Fig. 5.10).

5.6. Conclusions

Monitoring data and modelling of drip water Mg/Ca, Ba/Ca and Sr/Ca ratios from Grotte de Piste (Gravel Road Cave) in Morocco document that prior aragonite precipitation (PAP) has a substantially different impact on speleothem aragonite Sr concentrations than prior calcite precipitation (PCP). Prior aragonite precipitation, driven by increased aridity, is able to induce negative correlations in aragonitic speleothems between Mg and Sr and Sr and Ba. Higher Sr and lower Mg and Ba concentrations indicate lower amounts of PAP. A comparison between Sr concentrations from stalagmite GP5 and an updated tree-ring based scPDSI reconstruction from Morocco shows that Sr in aragonite speleothems is a particularly sensitive proxy for variations in PAP.

The general pattern of increasingly arid conditions during the Medieval Warm Period (MWP) compared to the Little Ice Age (LIA) in Atlantic Morocco is confirmed by our aragonite speleothem Sr record and agrees with several reconstructions from the Iberian Peninsula. A comparison of 1) a speleothem based temperature reconstruction from the central European Alps, 2) speleothem growth rates from NW Scotland, 3) the West Greenland North Atlantic Oscillation (NAO) reconstruction and 4) the interpretation from our Moroccan speleothem Mg/Sr record, indicates that shortly before

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and during the MWP six phases of increased aridity in Atlantic Morocco (950 AD, 1000 AD, 1160 AD, 1220 AD, 1310 AD and 1375 AD) are most likely related to positive modes of the NAO. The NAO thus showed considerable variability on multi-decadal and centennial timescales just before and during the MWP.

Acknowledgements

This work was financed by the Deutsche Forschungsgemeinschaft (DFG; project IM 44/1). We would like to thank the following people for fruitful discussions and support: A. Borsato, C. Spötl, D. Fleitmann, U. Weis, B. Stoll, D. Buhl, B. Gehnen, T. Reinecke, H.-J. Bernard, I. Sadalmelik, Mileud, H. Mansouri, T. Echchibi, M. Born and A. Schulz.

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Methods

Monitoring

Drip rates were measured manually for all drip sites and continuously using an automatic drip counter for drip site 17 (Stalagmate; Collister and Mattey, 2005). Drip water was sampled over a two day period and stored in a fridge in Morocco for the duration of the monitoring trips. Upon return to Germany, water samples for the cation analysis were acidified with 100µl 65% HNO3 per 10 ml of water sample. Drip water was analysed for Ca, Mg, Ba, and Sr concentrations using a Vista MPX ICP-OES (Varian) at the institute for Geosciences, Heidelberg University, Germany. NIST 1643e and SPS SW2 are used as standards and the long term 1σ reproducibility is 2-3%.

CO2 was measured with a portable Vaisala GMP 222 probe (0-2000 ppmv) coupled to a Vaisala MI 70. Typical uncertainties are ±20 ppmv plus 2% between 0 and 2000 ppmv. At CO2 concentrations >2000 ppmv the values were corrected for the offset from the “real” value.

14C analysis

Samples were drilled with a hand held dental burr (1 mm). Calcite powder was acidified in vacuum with HCl. The emerging CO2 was combusted to C with H2 and an iron catalyst at 575°C (Fohlmeister et al., 2011). Measurements were performed with a MICASAS AMS system (Synal et al., 2007) in the Klaus-Tschirra laboratory Mannheim.

Supplementary figures

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Fig. S5.1. Relation between rainfall, drip rate and drip water Mg/Ca ratio for drip sites 13, 14, 17 and 18. In red: Drip rates counted manually, in blue: Drip rate counted by automatic drip counter, in black: Rainfall (bottom panel) and drip water Mg/Ca ratio.

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Fig. S5.2. Upper panel: Comparison between the instrumental self-calibrating Palmer Drought Severity Index reconstruction (scPDSI; black) and the tree-ring based scPDSI reconstruction (orange). Bottom panel: Comparison between the original PDSI reconstruction (black) and the updated tree-ring based scPDSI reconstruction (ornage). Both records are smoothed with a 25 year running mean.

References

Collister, C., Mattey, D., High resolution measurement of water drip rates in caves using an acoustic drip counter, American Geophysical Union Fall Meeting 2005, Abstract # PP31A-1496, 2005.

Fohlmeister, J., Kromer, B., Mangini, A., 2011. The influence of soil organic matter age spectrum on the reconstruction of atmospheric C-14 levels via stalagmites. Radiocarbon 53, 99-115.

Synal, H.A., Stocker, M., Suter, M., 2007. MICADAS: A new compact radiocarbon AMS system. Nuclear Instruments & Methods in Physics Research Section B-Beam Interactions with Materials and Atoms 259, 7-13.

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North Atlantic Oscillation Holocene

6. THE NORTH ATLANTIC OSCILLATION: EVOLUTION THROUGHOUT THE HOLOCENE*

Abstract

The North Atlantic Oscillation (NAO) has a major impact on Northern Hemisphere winter climate. Its evolution throughout the Holocene, however, is still largely unknown. Here we present a precisely-dated, high resolution rainfall record from NW Morocco covering the Early to Late Holocene and compare it with a rainfall reconstruction from Western Germany. Our data provide evidence that the NAO has been dominating Moroccan and German climate for a large part of the Holocene. The relation between Moroccan and German rainfall has not been stationary. This is evident from the change in the sign of correlation between 9 and 8 ka BP, which might be linked to non-stationary behavior of the NAO and more ocean-dominated climate conditions related to the presence and melting of the Laurentide ice-sheet and Arctic sea-ice.

6.1. Introduction

The North Atlantic Oscillation (NAO) has a large impact on winter surface temperature and rainfall in the Mediterranean Realm, (North) western Europe, Greenland and Eurasia (Hurrell, 1995; Marshall et al., 2001) and represents the dominating atmospheric pressure mode in the North Atlantic/European area (Hurrell, 1995). The NAO controls the strength and direction of the Westerlies and storm tracks across the North Atlantic and can be described by the NAO index, which is defined as the normalized sea level pressure difference between the Icelandic low and the Azores subtropical high. The NAO-index is negatively correlated to winter rainfall amounts in the West Mediterranean and surface air temperature in West Greenland, but positively correlated to winter rainfall amounts and surface air temperature in (North) western Europe (Fig. 6.1). The NAO is subjected to what is referred to as non-stationary behavior (Jung et al., 2003; Raible et al., 2006; Lehner et al., 2012; Wang et al., 2012) expressed by changes in the latitudinal or longitudinal position of (one of) the NAO sea level pressure centers. Combined with a shift of the NAO sea level pressure centers, the NAO-rainfall/temperature correlation belts may shift along. This feature complicates the reconstruction of the NAO with proxy-data as they are stationary by definition. Because NAO variability has severe socio-economic and ecological consequences in especially the North Atlantic European area (Post and Forchhammer, 2002; Vicente Serrano and Trigo, 2011), it is highly important to assess the NAO’s natural spatial and temporal variability during the Holocene in order to improve its prediction under influence of anthropogenically induced warming (Ulbrich and Christoph, 1999; Hoerling et al., 2001). Climate modeling data has already suggested that NAO sea level pressure patterns were present during the Early, Mid and Late Holocene (Wei and Lohmann, 2012). At present, the longest continental proxy based NAO reconstruction extends back to the Mid Holocene (Olsen et al., 2012). It is, however, based on one location only (West Greenland). This fact complicates the assessment of non-stationarities of the NAO (Raible et al., 2006; Lehner et al., 2012; Wang et al., 2012). Here we present a high resolution, precisely dated speleothem δ18O rainfall record from Grotte de Piste in NW

* In collaboration with: S. Dietrich, J. Fietzke, J. Fohlmeister, K. P. Jochum, D. Scholz, D. K. Richter, A. Sabaoui, G. Lohmann, W. Wei, M. O. Andrae and A. Immenhauser

Chapter 6

124

Correlation NAO-A vs Temperature (1901-2001)

70N

60N

50N

40N

30N

20N

70N

60N

50N

40N

30N

20N60W 40W 20W 0 20E 40E

Correlation NAO-A vs Rainfall (1901-2001)60W 40W 20W 0 20E 40E

-0.6 -0.5 -0.4 -0.3 -0.2 0.2 0.3 0.4 0.5 0.6

1

2

3

4

56

7

1

2

3

4

56

7

1 = Grotte de Piste2 = Bunker Cave3 = Uamh an Tartair Cave4 = Lake SS-12205 = Cova da Arcoia6 = Grotta di Ernesto7 = Bucca della Renella

Fig. 6.1. Correlations NAO-index (based on Ponta del Gada, Azores and Stikkysholmur, Iceland sea level pressure data) versus surface air temperature and rainfall. Positions of climate reconstructions discussed in the text are indicated. 1) Grotte de Piste, northwest Morocco (this study), 2) Bunker Cave, West Germany (Fohlmeister et al. 2012), 3) Uamh an Tartair Cave, Northwest Scotland (Proctor et al. 2002), 4) Lake SS-1220, West Greenland (Olsen et al. 2012), 5) Cova da Arcoia, northwest Spain (Railsback et al. 2011), 6) Grotta di Ernesto, Northeast Italy (Scholz et al. 2012), 7) Bucca della Renella, North Italy (Drysdale et al. 2006). Maps computed with KNMI Climate Explorer: http://climexp.knmi.nl/start.cgi?id=someone@somewhere.

Morocco (Fig. S6.1 and Wassenburg et al., 2012), which covers the complete Early to Mid Holocene. Morocco, located in the SW Mediterranean, has already been used in several NAO reconstructions (Glueck and Stockton, 2001; Cook et al., 2002; Trouet et al., 2009) and is considered as a key NAO region (Fig. 6.1). Trouet et al. (Trouet et al., 2009) used a Moroccan tree-ring based PDSI reconstruction (Esper et al., 2007), which was updated and compared to a stalagmite Sr record from Grotte de Piste in chapter 5 of this thesis. The records showed a high coherence around the well known Medieval Warm Period – Little Ice Age transition but also on multidecadal to centennial timescales during the Medieval Warm Period. This together with a high negative correlation between instrumental rainfall data from Taza (a small town in the vicinity of Grotte de Piste) and the NAO-index (Fig. 6.2) emphasizes that Grotte de Piste in NW Morocco is a suitable location for reconstructing NAO variability. Even though the NAO reconstruction from Trouet et al. (2009) fails to verify against the instrumental NAO-index for the 19th century (Lehner et al., 2012), the NAO reconstruction from

125

North Atlantic Oscillation Holocene

Fig. 6.2. Scatter plot and correlation coefficient between the NAOG-index and winter rainfall amounts in Taza (a city in the vicinity of Grotte de Piste). Plot includes data for the periods 1926-1936 and 1963-1997 of December-February rainfall amounts. NAOG stands for the North Atlantic Oscillation index based on the weather station data from Reykjavik, Iceland and Gibraltar, Spain (Jones et al., 1997).

West Greenland is in good agreement with the Trouet NAO reconstruction (Olsen et al., 2012). We compare the NW Moroccan Holocene record to a rainfall record from West Germany (Fohlmeister et al., 2012), which is located on the southern border of the northern NAO-rainfall correlation belt (Fig. 6.1). Therefore this comparison allows us to study NAO non-stationarities during the Holocene. 6.2. Results and interpretation*

The Holocene part of stalagmite GP2 is 601 mm long and has a transition from calcite to aragonite at 11.2 ka BP, which was explained by the high drip water Mg/Ca ratio due to the dolomite host rock combined with a relatively small decrease in rainfall (Wassenburg et al., 2012). After this transition GP2 remains aragonitic. The Holocene part of GP2 is constrained by 20 U-Th age data, which are all in stratigraphic order with an average analytical uncertainty of ±37 years (2σ) for the 19 aragonitic samples and ±38 years due to the thickness of the sample hole, although this remains difficult to include quantitatively within the StalAge age-depth modeling (Table 6.1 and Fig. 6.3). The calcitic sample at the base has a higher uncertainty due to its lower U concentration (Table 6.1). The fact that the ages are in stratigraphic order shows the primary nature of the aragonite, this is supported by a lack of evidence for diagenetic alteration of the aragonite in thin sections (Fig. S6.2). Furthermore, X-Ray Diffraction analysis demonstrates that the amount of calcite within the aragonite fabric is typically below 2% (Wassenburg et al., 2012). Carbon and oxygen isotopes were measured on an average resolution of 15 a (± 11 a), specific intervals were analyzed for P, U and Sr concentrations on the same resolution. GP2 shows (multi-) centennial timescale trends in δ18O superimposed on a long term decreasing trend, which lasts until approximately 8 ka BP followed by a slight increasing trend up to 2.6 ka BP. For this study, however, we focus on the (multi-) centennial patterns, therefore the GP2 δ18O and δ13C record were detrended (Fig. 6.4).

* For the methodology section the reader is referred to the supplement

Chapter 6

126

GP2

U3.

16.

4±

61.

485

±0.

002

5345

.00

±48

.25

6.00

0±

0.01

26.

040

2.78

2±

0.01

8G

P2U

334

±4

1.66

6±

0.00

220

062.

93±

1787

.26

6.08

3±

0.01

16.

136

3.64

6±

0.02

5G

P2 U

2.5.

163

.2±

12.

721

±0.

001

1959

6.05

±20

7.10

6.32

7±

0.00

56.

389

4.12

0±

0.01

3G

P2 U

2.5

130.

9±

2.5

1.74

1±

0.00

390

70.3

8±

60.2

46.

356

±0.

013

6.43

04.

852

±0.

027

GP2

U2.

4.2

177.

51±

1.25

1.69

5±

0.00

112

085.

48±

97.6

66.

333

±0.

005

6.41

55.

424

±0.

019

GP2

U2.

4.1

198.

1±

12.

061

±0.

001

3192

3.06

±57

7.06

6.45

7±

0.00

66.

547

5.81

7±

0.01

6G

P2 U

2.4

216.

1±

1.5

1.87

5±

0.00

332

129.

44±

545.

546.

515

±0.

015

6.60

95.

995

±0.

040

GP2

U2.

3.3

246.

21±

0.75

1.15

9±

0.00

112

424.

40±

126.

296.

609

±0.

005

6.71

06.

319

±0.

023

GP2

U2.

3.2

265.

49±

0.75

1.83

7±

0.00

195

78.7

4±

59.4

36.

643

±0.

004

6.75

06.

609

±0.

017

GP2

U2.

3.1

280.

6±

12.

805

±0.

002

1918

2.19

±11

4.88

6.68

1±

0.00

66.

789

6.64

1±

0.04

7G

P2 U

2.3

301.

4±

2.5

1.26

1±

0.00

219

918.

21±

252.

136.

603

±0.

013

6.71

46.

950

±0.

039

GP2

-U2.

2a31

6.5

±1.

256.

442

±0.

004

3958

7.80

±86

3.52

6.78

9±

0.00

56.

910

7.33

8±

0.02

2G

P2 U

2.2

365.

02±

1.25

2.44

7±

0.00

412

891.

76±

77.5

16.

753

±0.

013

6.87

87.

632

±0.

047

GP2

-U2.

1a41

4.52

±1.

252.

318

±0.

001

2809

0.81

±11

41.8

26.

723

±0.

005

6.86

18.

407

±0.

060

GP2

U2.

142

6.23

±2.

252.

843

±0.

003

2142

5.50

±13

1.92

6.68

5±

0.00

96.

827

8.71

4±

0.04

4G

P2-U

2.0

432.

.77

±1.

253.

165

±0.

002

1154

7.39

±13

5.36

6.73

5±

0.00

66.

883

9.06

0±

0.02

8G

P2U

249

3.5

±3

2.06

6±

0.00

314

832.

24±

285.

276.

821

±0.

012

6.98

59.

813

±0.

059

GP2

U1.

454

0.92

±1.

251.

590

±0.

001

2108

5.65

±16

6.23

7.00

1±

0.00

57.

185

10.6

41±

0.09

5G

P2 U

1.3

582.

5±

21.

374

±0.

002

7468

7.94

±21

30.5

16.

998

±0.

013

7.18

911

.110

±0.

058

GP2

U1.

259

7.1

±2

0.01

3±

0.00

038

0.22

±5.

997.

054

±0.

035

7.25

411

.487

±0.

165

For t

he c

orre

ctio

n of

det

rital

230 Th

a 23

0 Th/23

2 Th a

ctiv

ity ra

tio o

f 0.6

± 0

.2 w

as u

sed

Age

(ka

BP

2010

)In

itial

(23

4 U/23

8 U)

Sam

ple

Nr.

Dec

ay c

onst

ants

use

d: λ

230 =

9.1

58 X

10-6

y-1

, λ23

2 = 4

.947

5 X

10-1

1 y-1

, λ23

4 = 2

.826

3 X

10-6

y-1

, λ23

8 = 1

.551

3 X

10-1

0 y-

Tabl

e 6.

1. R

esul

ts fr

om U

/Th

datin

g

Dep

th (m

m)

238 U

± 1σ

(ppm

)(23

0 Th/23

2 Th)

± 1σ

(234 U

/238 U

) ± 1σ

127

North Atlantic Oscillation Holocene

Fig. 6.3. Age depth model stalagmite GP2. The black line is the age-depth model calculated with StalAge (Scholz and Hoffmann, 2011). Red lines indicate 95% confidence levels. Original ages with uncertainties are indicated in blue.

Chapter 6

128

12 11 10 9 8 7 6 5 4 3 2Age (kyr) BP

-2-10123

δ13 C

(‰)

-0.8

-0.4

0

0.4

0.8

δ18 O

(‰)

4

2

0

U (p

pm)

100806040200

P (p

pm)

-5.6-5.2-4.8-4.4

-4-3.6-3.2

δ18 O

(‰) -7

-6-5-4-3-2-1

δ13 C

(‰)

a

b

c

d

e

f

g

1

0.1

0.01

0.001Y

(ppm

)

Fig. 6.4. Trace element and isotope data stalagmite GP2. (A) Original δ18O data with third order polynomial trendline used for detrending (red). (B) Original δ13C data with sixth order polynomial trendline used for detrending (blue). (C) Detrended δ18O (red). (D) Detrended δ13C (blue). (E-G) U (brown), P (purple) and Y (green) respectively. Thick lines represent 5 point running means.

Acknowledging that rainfall δ18O can be affected by changes in the oxygen isotope composition of the moisture source region and temperature (Lachniet, 2009), detrended GP2 δ18O and δ13C are positively correlated (r = 0.66). This suggests that they may be controlled by drip rate related CO2 degassing as a consequence of rainfall perturbations (Mangini et al., 2007). Lower rainfall reduces soil CO2 production, which decreases the drip water CaCO3 saturation and therefore may affect speleothem growth rate. Indeed, thin section analysis shows that high carbon and oxygen isotope values coincide with a tendency towards coarser aragonite crystals, indicating slower growth, which is confirmed by speleothem growth rate calculated from the high density U-Th data (Fig. 6.5). Kinetic

129

North Atlantic Oscillation Holocene

12 11 10 9 8 7 6 5 4 3 2Age (kyr) BP

-7-6-5-4-3-2-1

δ13 C

(‰)

-5.6

-5.2

-4.8

-4.4

-4

-3.6

-3.2

δ18 O

(‰)

04080120160200

Gro

wth

rate

(µm

/a)

Fig. 6.5. Comparison of stalagmite GP2 growth rate with original GP2 δ13C and GP2 δ18O. Yellow bars indicate periods of relatively slow growth. This growth rate is calculated from a lineair interpolated age-depth model, because this amplifies growth rate differences and thus facilitates visual comparison. Periods of relatively slow growth coincide with relatively high δ13C and δ18O values.

effects on speleothem carbon and oxygen isotopes related to speleothem growth rates typically cause lower speleothem δ18O and δ13C with lower growth rates (Polag et al., 2010). Here, we observe the opposite (i.e., lower GP2 δ18O and δ13C coincide with higher growth rates, Fig. 6.5), which shows that growth rate-related kinetic effects are not dominant in the case of GP2 δ18O. Instead, GP2 δ18O is suggested to reflect a rainfall signal, likely amplified by the rainfall amount effect (Ayalon et al., 1998). Additional evidence comes from the trace element analysis of P, Y, and U (Fig. 6.4). These elements have formerly been related to soil productivity (Treble et al., 2005; Borsato et al., 2007; Wassenburg et al. 2012). Uranium may also be related to aragonite precipitation rates (Gabitov et al., 2008). In (aragonitic) stalagmites, both processes force these elements in the same direction under influence of rainfall perturbations (Wassenburg et al., 2012), i.e. higher P, Y and U concentrations coincide with higher rainfall. Therefore these elements support the interpretation that GP2 δ18O indeed reflects rainfall on (multi-) centennial timescales (Fig. 6.4). High δ18O corresponds to low rainfall and vice versa. We would like to emphasize that the amplitude of the observed oscillations in both δ18O (± 0.7‰) and δ13C (± 2‰) cannot be explained by changing percentages of calcite, whilst the difference in isotope fractionation between calcite and aragonite is approximately 0.8‰ for δ18O (Kim et al., 2007) and 1.7‰ for δ13C (Romanek et al., 1992). This would imply a shift from 100% calcite towards 100% aragonite. Moreover, our multi-proxy approach shows that GP2 δ18O is reflecting variations in rainfall.

Chapter 6

130

6.3. Discussion and conclusions

We compared the GP2 δ18O record with a high resolution winter rainfall record from Bunker Cave Western Germany (Fohlmeister et al., 2012), which covers nearly the entire Holocene (Fig. 6.6). The Bunker Cave record chronology was tuned within its age uncertainties to the very precise GP2 chronology (see methodology). Subsequently we compared both records to rainfall and temperature

NAO

-

+

12 11 10 9 8 7 6 5 4 3 2 1 0Age (kyr BP 2010)

12 11 10 9 8 7 6 5 4 3 2 1 0Age (kyr BP 2010)

-3

-2

-1

0

1

2

3

Bun

ker M

g/C

a

0.4

0.2

0

-0.2

-0.4

-0.6

GP2

δ18

O (‰

)

B

Wet

Dry

Dry

Wet

A

+ - + - Correlationsign

Fig. 6.6. Comparison of stalagmite GP2 detrended δ18O (A; red; this study) with normalized Bunker cave Mg/Ca record (B; purple; Fohlmeister et al. 2012). The sign of the correlation is indicated above the two plots. Positions of original datings and age uncertainties are indicated by the diamonds, which are colored corresponding to the records, age uncertainties smaller as the diamonds are not indicated. The effect of the tuning of the Bunker Cave Mg/Ca age models is indicated by yellow dots plotted on top of the original age uncertainties.

records from NAO sensitive areas in order to show that the GP2 and Bunker record bare a NAO signal (Fig. 6.1 and Fig. 6.7). Trouet et al. (2009) suggested that the Little Ice Age (LIA) was dominated by negative NAO conditions, whereas the Medieval Warm Period (MWP) was dominated by positive NAO conditions. This implies relatively wet (dry) conditions in West Germany during the LIA (MWP). Indeed the MWP-LIA transition is clearly visible in the Bunker record (Fohlmeister et al., 2012) and Fig. 6.7, where the relatively “early” transition in the Bunker record may be due to uncertainties in the age model. Dry conditions prevailed in Western Germany at around 1.4, 2.5 and 3.1 ka BP, which all have a counterpart in the NAO reconstruction from West Greenland (Olsen et al., 2012) and the Scottish rainfall record (Proctor et al., 2002). This is except for 1.4 ka BP, which was assigned to warm temperatures as a consequence of prevailing positive NAO conditions (Fig. 6.7 and chapter 5). Around 4.4 ka BP, a clear transition from more positive NAO towards more negative NAO conditions is visible in the GP2, Bunker and West Greenland NAO record (Fig. 6.7). In addition eight out of

131

North Atlantic Oscillation Holocene

C

12 11 10 9 8 7 6 5 4 3 2 1 0Age (kyr BP 2010)

-3

-2

-1

0

1

2

3

Bun

ker M

g/C

a

020406080

100

Ban

dwid

th (µ

m)

0.4

0.2

0

-0.2

-0.4

-0.6

GP2

δ18

O (‰

)

A) Morocco RainfallB) Germany RainfallC) NW Spain Wet PeriodsD) NW Scotland RainfallE) West Greenland NAO

12 11 10 9 8 7 6 5 4 3 2 1 0Age (kyr BP 2010)

210-1-2-3

NA

O

A

B

D

E

Dry

Wet

Wet

Dry

NAO

-

+

Dry

Wet

+

-

NAO

a

a’

a’’

Fig. 6.7. Comparison of stalagmite GP2 detrended δ18O (A; red; this study) with normalized Bunker cave Mg/Ca record (B; purple; Fohlmeister et al. 2012), together with the timing of relatively wet periods in Northwest Spain (C; green; Railsback et al. 2011) the rainfall sensitive bandwidth record from Northwest Scotland (D; light blue; Proctor et al. 2002) and the NAO reconstruction from lake SS1220 from West Greenland (E; dark blue; Olsen et al. 2012). Green bars represent relatively wet periods in Northwest Morocco and relatively dry periods in West Germany, which coincide with negative North Atlantic Oscillation conditions and or relatively wet periods in Northwest Spain and or relatively dry conditions in Northwest Scotland. Note that the apparently dry peak in Northwest Scotland around 1.32 ka BP has been related to warm temperatures in Chapter 5 of this thesis. The peak labeled “a”, recognized in Northwest Morocco and West Germany, does not match within the given age-uncertainties with the peaks labeled a’ and a’’ recognized in the Northwest Scotland and West Greenland records.

13 relatively wet intervals recognized in NW Spain (Railsback et al., 2011) seem to coincide with wet periods in NW Morocco and dry conditions in West Germany. The overall coherence strongly suggests that the Bunker and GP2 records are suitable to study NAO variability. Of special interest is that the Bunker record is positioned on the southern border of the northern NAO-rainfall correlation belt (Fig. 6.1 and Langebroek et al., 2011). It is therefore also sensitive to non-stationary behavior of the NAO.

Chapter 6

132

As explained above, under modern climate conditions negative NAO conditions coincide with higher (lower) winter rainfall in NW Morocco (W Germany), thus a negative correlation between GP2 δ18O and the Bunker Mg/Ca record would be expected. The tuning of the Bunker record to GP2 δ18O resulted in a positive correlation at 10.7-9 ka BP (r = +0.62, 99%*), a negative correlation at 8-6 ka BP (r = -0.57, 94%*), a positive correlation at 6-4.8 ka BP (r = +0.69, 65%*) and a negative correlation at 4.8-2.6 ka BP (r = -0.61, 95%*) (Table 6.2 and Fig. 6.6). Where the low significance level for the 6-4.8 ka BP interval might be related to both the relatively large age errors in the Bunker record in this interval and the relatively little amount of data points. From these results it can thus be concluded that the intervals characterized by positive correlations were not dominated by NAO or that the NAO showed a strong non-stationary behavior (Jung et al., 2003; Raible et al., 2006; Wang et al., 2012). Non-stationary NAO behavior, which could induce these positive correlations include: 1) a NW-SE tilted teleconnection axis (i.e. a line connecting the pressure centres of the Icelandic low and the Azores subtropical high (Raible et al., 2006), also described by a negative angle index (Wang et al., 2012) inducing southwestern winds and therefore forcing SW-NE directed NAO correlation belts and 2) a northward shift of the Icelandic low and or the Azores subtropical high, which may shift the NAO correlation belts northwards as well.

* The given numbers can be interpreted in terms of “Significance limits”. The real p-value is slightly different defined, which prohibits us to give the confidence level as such.

Time-interval Positive Significance limit Negative Significance limitBu2 tuned to GP2 10.6-7.6* 0.62 99% -0.36 ns

8.1-6 0.31 ns -0.57 94%6-4.8 0.69 65% -0.57 ns4.8-2.6 -0.13 ns -0.61 95%

Table 6.2. Pearson correlation coefficients between GP2 δ18O and tuned Bunker Mg/Ca for attempts towards positive and towards negative correlation. All records were smoothed with a 50 year window. Significance limits (see methodology) are indicated. "ns" stands for "not signifant"

Bu4 tuned to GP2

*Positive correlation is mainly driven by the interval 10.6-9 ka BP

In order to provide an explanation for the observed changes in the sign of the correlations, we examined the climate dynamics by analyzing 100-year time slices from climate modeling runs with Late Holocene (pre-industrial; PI), Mid Holocene (6 ka BP; 6k) and Early Holocene (9 ka BP) boundary conditions using the fully coupled state-of-the-art Earth system model COSMOS (Table 6.3 and supplement) (Wei and Lohmann, 2012). Four different modeling runs for the Early Holocene were performed: 1) a modeling run with only orbital forcing and greenhouse gasses prescribed (9k), 2) a 9k run with prescribed Laurentide Ice Sheet (9k.ice), 3) a 9k run with prescribed meltwater flux (9k.melt) and 4) a 9k run with both prescribed Laurentide Ice Sheet and meltwater flux (9k.comb) (Table 6.3). Please note, that the resolution of the model does not allow for a precise characterization of the transition between the southern and northern NAO correlation belts. We therefore emphasize that the model is used to study the climate dynamics. The results indicate that with respect to the PI and 6k runs, in the 9k.comb run the Icelandic low is extended eastward, whereas the subtropical high has a more northeast ward position (Fig. 6.8). In addition, the shape of the subtropical high pressure centre is more circular compared to the more elongated pressure centres in the PI and 6k runs (Fig. 6.8). The more northeast ward positioned subtropical high is potentially explaining the observed positive correlation between NW Moroccan and W German rainfall for the Early Holocene, because the southern NAO correlation belt must have shifted northwards. This is also indicated by the stronger

133

North Atlantic Oscillation Holocene

Experiment Orbital CO2 (ppm) CH4 (ppb) N2O (ppb) Ice Sheet Melt flux (Sv) Integration time (years)PI Present 280 760 270 Present 0 35006k 6 ka BP 280 650 270 Present 0 35009k 9 ka BP 265 700 245 Present 0 35009k.ice 9 ka BP 265 700 245 9 ka BP 0 10009k.melt 9 ka BP 265 700 245 Present 0.09 10009k.comb 9 ka BP 265 700 245 9 ka BP 0.09 1500

Table. 6.3. Boundary conditions used in each simulation. For PI and 6k Greenhouse gasses (GHG's) areprescribed according to the Paleoclimate Modelling Intercomparison Project (PMIP; Crucifix et al., 2005). Forthe early Holocene experiments GHGs are taken from ice core measurements (Indermuhle et al., 1999; Brook etal., 2000; Sowers et al., 2003). Early Holocene ice sheet topography is derived from the ice sheet model ICE-5G(VM2) (Peltier, 2004). LIS background melt flux is approached by adding 0.09 Sv freshwater into the NorthAtlantic Ocean between 40° and 60°N (Licciardi et al., 1999). These four early Holocene experiments enable usto distinguish the climate impact of the LIS and its melting.

negative (positive) correlation between modelled rainfall at Bunker cave and sea level pressure at the subtropical high (Icelandic low) for the 9k.comb run, which resembles the relation between NW Moroccan rainfall and sea level pressure. This mechanism thus explains an in-phase relation between W German and NW Moroccan rainfall, which is likely amplified by the more circular shape of the subtropical high pressure centre as this extends the southern NAO-rainfall correlation belt to the north by forcing the Westerlies northwards. We specifically argue that the southern NAO-rainfall correlation belt is extended northwards because the southern edge of the subtropical high pressure centre is comparable to that from the PI and 6k runs such that NW Morocco remains within the southern NAO-rainfall correlation belt. This can be explained by the more circular shape of the pressure centre, which compensates the absolute northward shift. The fact that the above mentioned response is absent in the 9k.ice and the 9k.melt modelling runs (Fig. 6.8) suggests that the shift from an in-phase to an out-of-phase NAO relation between NW Moroccan and W German rainfall is directly related to non-linear effects due to deglaciation processes (i.e. both the Laurentide Ice Sheet and the melt water are a prerequisite). Furthermore, the melt water flux reduced the Atlantic Meridional Overturning Circulation (AMOC), this combined with the presence of the Laurentide Ice Sheet caused a general cooling of the northern hemisphere climate with the largest cooling in the northern North Atlantic area (Fig. 6.9; Renssen et al., 2009). Generally, a weaker AMOC due to the presence of melt water also makes the AMOC more vulnerable for changing melt water fluxes and other external forcings (Wei and Lohmann, 2012). Because the AMOC strength is affecting sea surface temperatures (SST) in the North Atlantic basin (Lohmann, 2003; Kim et al., 2007a), it may affect the moisture availability for rainfall (Kutzbach and Liu, 1997) in the North Atlantic European area. Therefore, its higher vulnerability during the Early Holocene might imply a more dominant role for the AMOC on rainfall in the North Atlantic European area. Additionally the strength of the AMOC is highly correlated with the Atlantic Multi-decadal Oscillation, which is associated with a SW-NE tilted subtropical high pressure centre extended towards Western Europe (Wei and Lohmann, 2012). This pattern might be able to induce an in-phase drying trend between W Germany and NW Morocco during periods of relatively cold North Atlantic SST’s.

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Fig. 6.8A. Correlation map, sea level pressure (SLP) anomaly (hPa), and the 15% winter sea ice contour for the Late Holocene (Pre-industrial; PI). Correlations are calculated between SLP fields and local winter (DJF) precipitation at the location of the Bunker Cave record. Only statistically significant correlations (at 95% confidence) are plotted. The SLP contours are associated with the NAO index during the winters (DJF) for positive NAO conditions (1σ). Note that the results from the Mid Holocene climate modelling run is very similar to the Late Holocene climate modelling run, therefore the Mid Holocene run is not shown.

Fig. 6.8B. Correlation map, sea level pressure (SLP) anomaly (hPa), and the 15% winter sea ice contour for the Early Holocene with prescribed Laurentide Ice Sheet combined with Meltwater (9k.comb). Correlations are calculated between SLP fields and local winter (DJF) precipitation at the location of the Bunker Cave record. Only statistically significant correlations (at 95% confidence) are plotted. The SLP contours are associated with the NAO index during the winters (DJF) for positive NAO conditions (1σ). The yellow contour lines represent the contour lines from the Late Holocene modelling run (A) for ease of comparison.

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Fig. 6.8C. Correlation map, sea level pressure (SLP) anomaly (hPa), and the 15% winter sea ice contour for the Early Holocene with only the prescribed Laurentide Ice Sheet (9k.ice). Correlations are calculated between SLP fields and local winter (DJF) precipitation at the location of the Bunker Cave record. Only statistically significant correlations (at 95% confidence) are plotted. The SLP contours are associated with the NAO index during the winters (DJF) for positive NAO conditions (1σ).

Fig. 6.8D. Correlation map, sea level pressure (SLP) anomaly (hPa), and the 15% winter sea ice contour for the Early Holocene with only Meltwater (9k.melt). Correlations are calculated between SLP fields and local winter (DJF) precipitation at the location of the Bunker Cave record. Only statistically significant correlations (at 95% confidence) are plotted. The SLP contours are associated with the NAO index during the winters (DJF) for positive NAO conditions (1σ).

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Fig. 6.9. Annual mean surface air temperature anomalies of (A) Δ9k.comb – Δ9k.ice and (B) Δ9k.melt. The Δ-notations denote the anomalies with respect to the 9k simulation. The anomaly in (A) isolates the temperature response due to the melt water flux in the 9k.comb. The observed temperature response is much larger in (A) compared to the explicit 9k.melt simulation in (B). (C) Synergetic effect of the ice sheet-melt water combination during the Early Holocene.

Whilst the observed periods in the W German and NW Moroccan records during the Early Holocene are relatively long compared to the multi-decadal frequencies known for the Atlantic Multidecadal Oscillation (Delworth and Mann, 2000; Kerr, 2000; Wei and Lohmann, 2012), we argue that a similar association of AMOC strength and a SW-NE tilted subtropical high sea level pressure centre may have been present on longer timescales as well. We can thus suggest that the change from a positive correlation (in-phase relationship) towards a negative correlation (out-of-phase relationship) between W German and NW Moroccan rainfall between 9 and 8 ka BP is related to a southwestward shift of the Azores subtropical high and an increasingly elongated subtropical high sea level pressure centre possibly combined with a weakening of the North Atlantic SST forcing on moisture availability and AO/NAO sea level pressure patterns, linked to the AMOC strength. It has to be mentioned that the two mechanisms described above may be dominant on different timescales, therefore they may co-exist. The 100 year timeslices from the modeling runs used to study NAO dynamics are not long enough to study AMOC variations.

Between 8 and 6 ka BP, a negative correlation between W German and NW Moroccan rainfall persisted. After 6 ka BP, however, a period with a tendency towards positive correlations between W German and NW Moroccan rainfall exists until 4.8 ka BP. In order to investigate this period, we compared the GP2 δ18O with a temperature-sensitive speleothem record from Grotta di Ernesto, NE Italy (Scholz et al., 2012) (a cave located on the southern border of the northern NAO-temperature correlation belt). It appears that between 6 and 4.8 ka BP, two warm events occurred in NE Italy, which coincide with dry periods in NW Morocco (Fig. 6.10), suggesting a dominance of positive NAO conditions. A rainfall sensitive speleothem record from Bucca della Renella, West Italy (Drysdale et al., 2006) (a cave located in the southern NAO-rainfall correlation belt), however, shows periods of increased rainfall, contrasting with NW Morocco. It is thus not possible to explain these patterns by NAO dynamics. This period encompasses one of the periods of Rapid Climate Change (RCC) at approximately 5.5 ka BP identified by (Mayewski et al., 2004). The trigger for this RCC is still underexplored, although solar forcing has been invoked (Wanner et al., 2008). Additional detailed

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investigations of other proxy data are required for this period, which is beyond the scope of this study.Although the forcing factors of the NAO is still a matter of debate (Hurrell and Deser, 2009),

it has been suggested that sea ice dynamics (Magnusdottir et al., 2004), AMOC strength (Gastineau and Frankignoul, 2012), North Atlantic SST’s (Rodwell et al., 1999) and even tropical Pacific and Indian ocean SST’s (Hoerling et al., 2001; Hurrell et al., 2004) may play an important role. This study has clearly demonstrated that in the Early Holocene the interaction of the Laurentide Ice Sheet and

Fig. 6.10. Comparison of Bunker cave Mg/Ca and GP2 δ18O with records from NAO sensitive regions in Italy. (A) Normalized Mg/Ca record from Bunker Cave, West Germany (purple; Fohlmeister et al., 2012) versus the δ13C record from Bucca della Renella, West Italy (black; Drysdale et al., 2006). (B) Grotte de Piste GP2 δ18O, Northwest Morocco (detrended; red; this study) versus the δ13C record from Bucca della Renella (black). (C) Grotte de Piste GP2 δ18O, Northwest Morocco (detrended; red) versus the lamineae thickness record from Grotta di Ernesto (green; winter temperature; (Scholz et al., 2012). Age uncertainties are indicated with diamonds in the corresponding colors. Note that age uncertainties for the GP2 record are smaller than the diamonds. GP2 δ18O, Renella δ13C and Bunker Mg/Ca show a high coherence before 6 ka BP and after 3.7 ka BP. Renella δ13C and Bunker Mg/Ca show very similar patterns between 6 and 4.5 ka BP (b), which might suggest a dominance of negative NAO conditions. The comparison between the Northwest Moroccan GP2 δ18O and the winter temperature sensitive record from Northeast Italy (Grotta di Ernesto) suggests a dominance of positive NAO conditions (C).

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the strength of the AMOC had an impact on the configuration of the Icelandic low and the Azores subtropical high pressure centers. Despite the different climatic background we postulate that the predicted melting of the Greenland Ice Sheet (Hanna et al., 2008; Kamenos et al., 2012) and its interaction with the AMOC may affect the NAO in the (nearby) future.

Acknowledgements

The staff in the isotope laboratories at Bochum and Mainz (U. Weis, B. Stoll, A. Niedermayr, D. Buhl, B. Gehnen) is acknowledged for their help with sample preparations and measurements. We would like to thank D. Fleitmann for many fruitful discussions. Additionally T. Reinecke, the thin section lab at Bochum and our local speleoguides El Houcine El Mansouri and Tarik Echchibi are greatfully acknowledged. A. Fink (Institute for Geophysics and Meteorology, University of Cologne) is thanked for providing rainfall data from the weather station in Taza, Morocco.

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SUPPLEMENTARY MATERIAL CHAPTER 6

Methods

Carbon and Oxygen isotopes

Carbon and oxygen isotope analyses were performed at the Ruhr University Bochum, Germany, with a Gasbench coupled to a Finnigan MAT 253 mass spectrometer. For sampling at one mm resolution a hand held (Dremel) equipped with a flat-tipped, 0.5 mm diameter dentist drill was used. Carbon and oxygen isotope values are expressed in ‰ with respect to the Vienna PDB (VPDB) standard. Sample aliquots weighing between 0.27 and 0.33 mg were dried in an oven at 105°C for 48 hours. The vials were flushed with He in order to avoid atmospheric contamination. Phosphoric acid (104%) was added to the sample. CO1 and CO8 carbonate standards were used for correction, whereas the NBS19 and the RUB internal carbonate standards were used as a quality control. Four duplicates were analyzed for every sample batch of 48 samples, in order to check for sample homogeneity. Adding the averaged internal standard deviations derived from the analysis of 9 peaks per sample, to the averaged difference of each duplicate, suggests a precision of ± 0.12‰ for δ13C and ± 0.14‰ for δ18O.

Trace elements

31P, 89Y and 238U abundances were analysed with a Thermo Finnigan Element 2 ICP-MS at the Max Planck Institute for Chemistry, Mainz, Germany. The analysis is accurate as proved by (Jochum et al., 2012), who focussed on LA-ICP-MS analysis on carbonates including speleothems. Samples were ablated with a New Wave UP213 laser with an energy of 15.7 J/cm2 at a one mm resolution. A round, 100 μm diameter spot was used for all measurements. The relatively large spot size was necessary to average out heterogeneities within a given growth increment (Finch et al., 2003; McMillan et al., 2005). In order to avoid an effect of surface contamination the first two to five scans of every single spot analysis were discarded. Total measurement time per spot analysis was between 100 and 105 seconds. Intensities or “counts per second” were corrected for background noise, therefore all data shown were significantly elevated above the background value and therefore above the detection limit. The NIST-612 glass reference material and the MACS3 and MACS1 carbonate reference material were measured 9-15 times equally distributed in the sequence in blocks of three individual spot analyses. An averaged relative sensitivity factor (Jochum et al., 2007) from the NIST612 and MACS3 was used to derive absolute concentrations with the newest reference values (Jochum et al., 2011), whereas MACS1 elemental concentrations were used as a quality control.

Detection limits for 31P, 89Y and 238U are 4, 0.01 and 0.0002 ppm respectively (Jochum et al., 2012), measured 238U values are thus several orders of magnitude higher as the detection limit, whereas the lowest concentrations of 89Y appear to be lower and 31Phosphorus is a factor of two higher. However, detection limits may vary by a factor of 3-4 depending on the measurement conditions. The relative uncertainty is derived from the MACS1 elemental abundances, and is hereby defined as the relative standard deviation in percent. Concentration of 89Y and 31P are close to the detection limit therefore a relative uncertainty of approximately 20% is arbitrarily applied (Wassenburg et al., 2012). Oscillations in 31P, 89Y and 238U all exceed the relative uncertainties and are therefore considered

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reliable. For more information on the method, accuracy and precision the reader is referred to (Jochum et al., 2007; Jochum et al., 2011; Jochum et al., 2012) and (Mertz-Kraus et al., 2009).

Dating and age-depth modelling

U-series dating of the speleothems was conducted at the Helmholtz Centre for Ocean Research Kiel (GEOMAR), Germany, with an AXIOM MIC-ICP-MS (multiple ion counting inductively coupled plasma mass spectrometer). Before Present is here defined as the year 2010 AD. Further methodological details can be found in (Fietzke et al., 2005). Age-depth modeling was performed with the StalAge algorithm designed by Scholz and Hoffmann (2011).

Tuning Bunker Mg/Ca record

Because the GP2 record has a very precise chronology and small uncertainties the Bunker record was tuned to the GP2 record (i.e. the GP2 chronology was regarded as the “true” age with negligible age uncertainties). For tuning the Bu records we adopted the idea of (Fohlmeister, 2012), to obtain maximum correlating proxy time series of both locations. However, in contrast to the before mentioned publication we only allow one record to be shifted within its measured age uncertainties. Nevertheless, the applied methods for interpolation are similar. In order to assess the significance of the obtained correlation, the same tuning approach was applied to 2000 artificially generated random time series. These artificial time series have the same characteristics (i.e. variance, auto-correlation coefficients, data resolution and absolute ages with according age-uncertainties) as the real time series (in this case Bunker Mg/Ca). By tuning these 2000 artificial time series to the main record (GP2 δ18O) a distribution of maximum correlation coefficients can be obtained. This tuning was performed with the same procedure as for the measured time series From the distribution of maximum correlation coefficients derived by the artificial data sets the significance level of a correlation coefficient for the measured time series can be estimated. For example, if less than 99% of the tuned artificial time series reach a correlation coefficient of +0.7, then it can be stated that every correlation coefficient of the real time series higher than +0.7 is significant at a 99% significance level. Please note that significance level is slightly different defined as for the normally used p-value. This tuning method can thus be considered as objective compared to other methods like the software ANALYSERIES.

We used the Mg/Ca ratio of Bu2 and Bu4 out of the four stalagmites used for climate reconstruction in a recent study (Fohlmeister et al., 2012). Bu2 covers the interval from 10.6 to 7.6 ka BP, whereas Bu4 covers the interval from 8.1 to 0 ka BP. The Bu4 record was subdivided into three parts before tuning (8.1-6, 6-4.8, 4.8-2.6 ka BP) based on a comparison of the untuned Bu4 Mg/Ca and GP2 δ18O (Fig. S6.3). Trends in untuned Bu2 and untuned Bu4 Mg/Ca are consistent with each other between 8.1 and 7.6 ka BP (Fohlmeister et al., 2012). The obtained positive correlation between the tuned Bu2 Mg/Ca and GP2 δ18O is mainly forced by the interval from 10.6 to 9 ka BP. The younger part (i.e. after 9 ka BP) is reducing the obtained positive correlation, because there is a tendency towards a negative correlation. In addition the newly tuned Bu2 and tuned Bu4 Mg/Ca are not consistent with each other anymore in periods of contemporaneous growth, demonstrating that the young part of the Bu2 age model is incorrect. The exact timing of the transition (either abrupt or gradual) from a

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positive to a negative correlation between Bunker Mg/Ca and GP2 δ18O is thus difficult to constrain. We did not attempt to subdivide Bu2 Mg/Ca into two parts and tune the youngest part towards a negative correlation, because only one U/Th dating with a relatively high age-uncertainty is present after 9 ka BP (Fohlmeister et al., 2012). Note that we tried to tune towards both positive and negative correlations for each tuned interval in order to show it is only possible to obtain either a significant positive or negative correlation (Table 6.2).

Climate modeling

1) We applied six different experiments using the fully coupled earth system model Community Earth System Models (COSMOS; Wei and Lohmann, 2012), covering the late Holocene (LH), mid Holocene (MH) and early Holocene (EH) with prescribed orbital parameters (calculated after Berger, 1978) and greenhouse gases (Indermuhle et al., 1999; Brook et al., 2000; Sowers et al., 2003):Pre-industrial control simulation (denoted as PI);

2) Mid Holocene (6k);3) Early Holocene (9k);4) Early Holocene, including the Laurentide Ice Sheet (LIS) and its ice melt that lead to

freshwater input of 0.09Sv in the North Atlantic (9k.comb);5) Early Holocene only including the LIS (9k.ice);6) Early Holocene only including the melt water perturbation (9k.melt)

Each of the experiments was run into quasi-equilibrium (Table 6.3). COSMOS consists of the three model compartments ECHAM5 (the spectral atmosphere model (Roeckner et al., 2003), the land surface model Jena Scheme for Biosphere–Atmosphere Coupling in Hamburg (JSBACH) (Raddatz et al., 2007) and the Max Planck Institute Ocean Model (MPIOM; ocean general circulation model; (Marsland et al., 2003). The atmosphere results of all experiments have a spatial resolution of approx 3.75°x3.75° with 19 vertical levels (T31L19). For this study the last 100 model years were used for further investigation. For additional information about the model setup the reader is referred to Wei and Lohmann (2012).

Supplementary figures

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Tanger

RabatCasablanca

Fes

ErrachidiaMarrakech

Ouarzazate

AA

HA

MA

Rif

b

a

1417

1813

GP2

Entrance

Upper level

20 m

c

d GP2

Upper level

Entrance

20 m

Fig. S6.1. Setting Grotte de Piste with respect to the North Atlantic. (A) Location Morocco is indicated by the red box. (B) Location of Grotte de Piste as indicated by the red star (map modified after Sadalmelik: http://commons.wikimedia.org/wiki/File:Morocco_Topography.png). (C) Cross section of Grotte de Piste with indication of sampling location stalagmite GP2. (D) Cave map Grotte de Piste.

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50 mm

StalagmiteGP2

2.782 +/- 0.018 kyr

5.995 +/- 0.040 kyr

6.950 +/- 0.039 kyr

7.632 +/- 0.047 kyr

8.714 +/- 0.044 kyr

9.813 +/- 0.059 kyr

11.110 +/- 0.058 kyr

11.487 +/- 0.165 kyr

3.646 +/- 0.025 kyr

4.852 +/- 0.027 kyr

4.120 +/- 0.013 kyr

5.817 +/- 0.016 kyr5.424 +/- 0.019 kyr

6.319 +/- 0.023 kyr

6.641 +/- 0.047 kyr6.609 +/- 0.017 kyr

7.338 +/- 0.022 kyr

8.407 +/- 0.060 kyr

9.060 +/- 0.28 kyr

10.641 +/- 0.095 kyr

A

B C

D

100 μm 100 μm

100 μmFig. S6.2. Overview stalagmite GP2. Scalebars are indicated. (A) Stalagmite GP2 sample positions U/Th dating and age. Sampling transects for trace element analysis is indicated b the red transects. Sampling transect for carbon and oxygen isotopes is continuous (i.e. covers the trace element transects and everything in between, indicated with blue). (B-C) Pictures of unaltered primary aragonite crystals. (C) Same as (B) but under crossed nichols.

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9 8 7 6 5 4 3 2Age (kyr BP)

-0.6

-0.4

-0.2

0

0.2

0.4

δ18 O

(‰)

-0.08

0

0.08

0.16

Bu4

Mg/

Ca

+ --

Fig. S6.3. Comparison of the untuned Bu4 Mg/Ca record with GP2 δ18O, showing the visual correlations for the respective time intervals.

References

Berger, A.L., 1978. Long term variations of daily insolation and Quaternary climatic changes. Journal of the Atmospheric Sciences 35, 2362-2367.

Brook, E.J., Harder, S., Severinghaus, J., Steig, E.J., Sucher, C.M., 2000. On the origin and timing of rapid changes in atmospheric methane during the last glacial period. Global Biogeochemical Cycles 14, 559-572.

Fietzke, J., Liebetrau, V., Eisenhauer, A., Dullo, C., 2005. Determination of uranium isotope ratios by multi-static MIC-ICP-MS: method and implementation for precise U- and Th-series isotope measurements. Journal of Analytical Atomic Spectrometry 20, 395-401.

Finch, A.A., Shaw, P.A., Holmgren, K., Lee-Thorp, J., 2003. Corroborated rainfall records from aragonitic stalagmites. Earth and Planetary Science Letters 215, 265-273.

Fohlmeister, J., 2012. A statistical approach to construct composite climate records of dated archives. Quaternary Geochronology 14, 48-56.

Fohlmeister, J., Schroder-Ritzrau, A., Scholz, D., Riechelmann, D.F.C., Mudelsee, M., Wackerbarth, A., Gerdes, A., Riechelmann, S., Immenhauser, A., Richter, D.K., Mangini, A., 2012. Bunker Cave stalagmites: an archive for central European Holocene climate variability. Climate of the Past 8, 1751-1764.

Indermuhle, A., Stocker, T.F., Joos, F., Fischer, H., Smith, H.J., Wahlen, M., Deck, B., Mastroianni, D., Tschumi, J., Blunier, T., Meyer, R., Stauffer, B., 1999. Holocene carbon-cycle dynamics based on CO2 trapped in ice at Taylor Dome, Antarctica. Nature 398, 121-126.

Jochum, K.P., Stoll, B., Herwig, K., Willbold, M., 2007. Validation of LA-ICP-MS trace element analysis of geological glasses using a new solid-state 193 nm Nd : YAG laser and matrix-matched calibration. Journal of Analytical Atomic Spectrometry 22, 112-121.

Jochum, K.P., Weis, U., Stoll, B., Kuzmin, D., Yang, Q., Raczek, I., Jacob, D.E., Stracke, A., Birbaum, K., Frick, D.A., Günther, D., Enzweiler, J., 2011. Determination of Reference Values for NIST SRM 610--617 Glasses Following ISO Guidelines. Geostandards and Geoanalytical

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Research doi: 10.1111/j.1751-908X.2011.00120.x, Jochum, K.P., Scholz, D., Stoll, B., Weis, U., Wilson, S.A., Yang, Q., Schwalb, A., Börner, N., Jacob,

D.E., Andreae, M.O., 2012. Accurate trace element analysis of speleothems and biogenic calcium carbonates by LA-ICP-MS. Chemical Geology 318, 31-44.

Marsland, S.J., Haak, H., Jungclaus, J.H., Latif, M., Roske, F., 2003. The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates. Ocean Modelling 5, 91-127.

McMillan, E.A., Fairchild, I.J., Frisia, S., Borsato, A., McDermott, F., 2005. Annual trace element cycles in calcite-aragonite speleothems: evidence of drought in the western Mediterranean 1200-1100 yr BP. Journal of Quaternary Science 20, 423-433.

Mertz-Kraus, R., Brachert, T.C., Jochum, K.P., Reuter, M., Stoll, B., 2009. LA-ICP-MS analyses on coral growth increments reveal heavy winter rain in the Eastern Mediterranean at 9 Ma. Palaeogeography Palaeoclimatology Palaeoecology 273, 25-40.

Raddatz, T.J., Reick, C.H., Knorr, W., Kattge, J., Roeckner, E., Schnur, R., Schnitzler, K.G., Wetzel, P., Jungclaus, J., 2007. Will the tropical land biosphere dominate the climate-carbon cycle feedback during the twenty-first century? Climate Dynamics 29, 565-574.

Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U., Tompkins, A., The atmospheric general circulation model ECHAM5. Part1: Model description, Max Planck Institute for Meteorology, Hamburg, 2003, p. 131.

Scholz, D., Hoffmann, D.L., 2011. StalAge - An algorithm designed for construction of speleothem age models. Quaternary Geochronology 6, 369-382.

Sowers, T., Alley, R.B., Jubenville, J., 2003. Ice core records of atmospheric N2O covering the last 106,000 years. Science 301, 945-948.

Wassenburg, J.A., Immenhauser, A., Richter, D.K., Jochum, K.P., Fietzke, J., Deininger, M., Goos, M., Scholz, D., Sabaoui, A., 2012. Climate and cave control on Pleistocene/Holocene calcite-to-aragonite transitions in speleothems from Morocco: elemental and isotopic evidence. Geochimica Et Cosmochimica Acta 92, 23-47.

Wei, W., Lohmann, G., 2012. Simulated Atlantic Multidecadal Oscillation during the Holocene. Journal of Climate 6989-7002.

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7. SYNTHESIS AND OUTLOOK

The main aim of this thesis was to (i) reconstruct the Holocene climate of northwest Morocco by using speleothem archive data and to (ii) place the data in a climate dynamical context with respect to published reconstructions from the North Atlantic area. A major open debate is the evolution of the North Atlantic Oscillation through the Holocene. In chapter six, this issue was addressed and the author introduced new insights into the development of the NAO through the Holocene. The second order aim was to explore and to document the high potential of aragonite speleothems as climate archives. Therefore, a considerable portion of this thesis is dedicated to the processes determining the dominant CaCO3 polymorph in the caves under investigation and to the processes affecting the trace element behavior within aragonitic speleothems. In Grotte de Piste and Grotte Prison de Chien, the presence of aragonite has been related to increasing climate aridity, whereas monitoring data has led to the development of a new model for the interpretation of trace elements in aragonite speleothems.

7.1. Calcite versus aragonite

7.1.1. Presence of aragonite in caves: An indication for climate aridity?

The occurrence of aragonite in cave environments - but also in marine calcifying organisms such as corals and bivalves - has been a matter of debate in the literature as aragonite is the high pressure polymorph of calcite, which is usually formed several kilometers beneath the earth’s surface. In geological time periods so called “calcite” seas have alternated with periods of so called “aragonite” seas (Stanley and Hardie, 1998). Additionally, lab controlled aragonite precipitation experiments and field studies have suggested a complex array of controlling factors on aragonite precipitation, but generally agree on the importance of elevated fluid Mg/Ca ratios and lower fluid CaCO3 saturation (Frisia et al., 2002; De Choudens-Sanchez and Gonzalez, 2009). Thus, the first fundamental step before aragonite speleothems can be used for climate reconstructions is to understand the driving mechanisms of aragonite precipitation. In Grotte Prison de Chien and Grotte de Piste in NW Morocco, speleothems HK3 (Grote Prison de Chien) and GP2 (Grotte de Piste) exhibit stratigraphical transitions from calcite to aragonite. These transitions were excellent targets to study aragonite precipitation in these caves. This is because the trace element and carbon and oxygen isotope composition of the calcite just beneath the aragonite can be examined at high resolution (100 µm). Trace element behavior in speleothem calcite is relatively well understood and can thus provide important insights into the major processes at work just before aragonite starts to precipitate (Fairchild and Treble, 2009). In chapter 4 of this thesis, it was shown that the host rock plays an important role in determining the dominant speleothem mineralogy. Grotte Prison de Chien has a limestone dominated host rock whereas Grotte de Piste has a dolostone dominated host rock. This has important implications for the drip water Mg/Ca ratio (i.e. high Mg/Ca ratios due the dominance of dolomite or low Mg/Ca ratios due to the dominance of calcite). Consequently, it should be easier to precipitate aragonite in Grotte de Piste in comparison to Grotte Prison de Chien (Fig. 7.1). It was, however, demonstrated that other (climate related) processes affect the drip water Mg/Ca ratio as well.

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Dry Wet

Soil

Karst

No/slow growth

PCP

CalciteAragonite

Dry Wet

Soil

Karst

No/slowgrowth

PCP

CalciteAragonite

PCP/PAPPCP PAPPCP

Dolostone host rockLimestone host rock

+ +- -

Calcite precipitation takes up Mg, Sr and Ba disproportionally with respect to Ca and increases the drip water Mg/Ca ratio in addition to fluid Sr/Ca and Ba/Ca ratios. Prior Calcite Precipitation (PCP; Johnson et al., 2006), a process involving the precipitation of calcite from the drip water before the drip water reaches the stalagmite’s surface, was shown to be a prerequisite for both stalagmites HK3 and GP2 to precipitate aragonite. This is because PCP increases the fluid Mg/Ca ratio but also decreases the fluid CaCO3 saturation. Prior Calcite Precipitation increased within the examined calcite intervals towards the aragonite intervals, as indicated by the increasing concentrations of Mg, Sr and Ba and their strong positive correlations. Prior Calcite Precipitation occurred as a consequence of increasing climate aridity (Fig. 7.1), which was supported by vegetation productivity related elements like P, Y and U. These showed a negative correlation with Mg, Sr and Ba registering a reduction of the vegetation productivity above the cave associated with an increase in PCP. The transitions from calcite to aragonite in these caves were thus a consequence of increasing aridity (Fig. 7.1). Due to the dolostone dominated host rock of Grotte de Piste, the climatic significance of the calcite-to-aragonite-transition in stalagmite GP2 is likely to be smaller (Fig. 7.1).

However, it is important to emphasize that the presence of aragonite does not necessarily implies dryer conditions relative to intervals when calcite precipitated. This is because there is a

Fig. 7.1. Simplified overview of the host rock effect on the dominant mineralogy under varying climate conditions. A limestone host rock (left) contains little amounts of Mg, therefore the dominant speleothem mineralogy can be expected to be calcite. A dolostone host rock (right) contains high amounts of Mg, therefore the presence of aragonite may be expected. With increasing aridity Prior Calcite Precipitation (PCP) may increase the Mg/Ca ratio of the water and thus increases the likeliness to precipitate aragonite at the stalagmite surface but potentially in the karst aquifer or at the stalactite tip as well. In a cave with a limestone host rock PCP represents the dominating mode (left), on the contrary in caves with a dolostone host rock a mixture of Piror Aragonite Precipitation (PAP) and PCP and maybe under increasingly arid conditions PAP might be the only dominant mode (right). Note that PCP and PAP also affect the CaCO3 saturation state of the drip water, another important feature concerning aragonite precipitation.

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tendency to continue to precipitate the same CaCO3 polymorph as its substrate. This is clearly shown by the fact that the Holocene part of stalagmite GP2 initially starts to grow through the precipitation of calcite but after the transition to aragonite remains aragonitic, although another study has suggested that the Early Holocene in NW Morocco was dryer compared to the Mid Holocene. Additionally, depending on the homogeneity of the host rock, both calcite and aragonite speleothems may grow simultaneously in the same cave environment due to differing background fluid Mg/Ca ratios for the different drip sites. Also, the change in PCP that occurs as a consequence of one unit change in aridity is highly drip site dependent. The presence of aragonite should thus not be simply interpreted as reflecting arid climate conditions. Transitions from calcite-to-aragonite or aragonite-to-calcite in continuously growing speleothems only imply that a threshold was reached, which initiated the growth of the other polymorph. Therefore, the striking appearance of the transitions does not imply anything about the amplitude of the change in aridity. This is also indicated by data from stalagmite HK3 (not shown) where a calcite layer, inter-bedded by two aragonite layers, only showed a minimum variation in its trace element concentrations. Magnesium concentrations were continuously high and thus close to the threshold for aragonite precipitation.

7.1.2. Interpretation of trace element variations in aragonite speleothems

As mentioned in the introduction (see chapter one of this thesis) speleothems are well established climate archives, but usually require multi-proxy approaches in order to provide robust climate reconstructions. This accounts particularly for fossil speleothems. Processes involving carbon and oxygen isotope systematics in calcite speleothems do not differ much from aragonitic speleothems due to the fact that there is only an absolute offset due the different isotope fractionation factors (Kim et al., 2007; Romanek et al., 1992). Trace elements, however, do show large differences due to their different incorporation mechanisms and their different partition coefficients during the precipitation of the respective mineral (Fairchild and Treble, 2009).

Prior Calcite Precipitation affects drip water Mg/Ca ratios and the fluid CaCO3 saturation state. As explained above, PCP is therefore a powerful mechanism to induce aragonite precipitation. Once the threshold for aragonite precipitation has been reached (drip water Mg/Ca >1.1) and the drip water remains in this state or drip water Mg/Ca ratios increase further, Prior Aragonite Precipitation (PAP) may start to play an important role (a mechanism similar to PCP but then associated with aragonite) (Fig. 7.1). Due to the different crystallography from calcite, aragonite preferably takes up Sr from the fluid instead of Ca. Therefore enhanced PAP would decrease the Sr/Ca ratio of the drip water (Fig. 7.2).

Based on monitoring data from Grotte de Piste combined with a Mg, Sr and Ba record from an actively growing aragonitic stalagmite (stalagmite GP5), it has for the first time been implied that PAP may indeed play an important role in the interpretation of especially Sr and most likely Mg and Ba concentrations in aragonitic stalagmites. Northwestern Morocco is characterized by extremely dry summers and relatively wet winters, the monitoring program (four visits per year) thus includes the wet and dry end-members. In Grotte de Piste, two drip sites (one drip site corresponding to stalagmite GP5) which showed the highest drip water Mg/Ca ratios, showed indications for the existence of PAP.

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Enhanced PAP as a consequence of increased aridity decreases the drip water Sr/Ca ratios, whereas PCP increases the drip water Sr/Ca ratios (Fig. 7.2). For the drip site corresponding to stalagmite GP5, both PCP and PAP may have been important. This potentially complicates the interpretation of Sr in aragonite stalagmites and implies that Sr should be plotted together with Mg (Fig. 7.2). However, a comparison of the Sr record from stalagmite GP5 with an updated tree-ring based drought reconstruction over the last 1000 years (updated from Esper et al. (2007) does suggest that on longer multi-centennial timescales PAP has dominated GP5 Sr concentrations. In the context of PAP, it has thus been possible to confirm that the Little Ice Age was more humid compared to the Medieval Warm Period in northwest Morocco. In addition detailed examination of GP5 Mg and Sr concentrations identified seven arid intervals in NW Morocco, of which six intervals may be related to a dominance of positive North Atlantic Oscillation conditions.

Mg/Ca Sr/Ca

+

-

Prior Aragonite Precipitation

+

-

PAP

Dry WetWetWet

Prior Calcite PrecipitationDryWet+

-

PCP

Fig. 7.2. Simplified overview of the effect of Prior Aragonite Precipitation (PAP) and Prior Calcite Precipitation (PCP) on drip water Mg/Ca and Sr/Ca ratios under varying climate conditions. Prior Aragonite Precipitation induces a negative correlation between drip water Mg/Ca and Sr/Ca ratios (left), whereas PCP induces a positive correlation between drip water Mg/Ca and Sr/Ca ratios (right).

7.2. The evolution of the North Atlantic Oscillation through the Holocene

The North Atlantic Oscillation (NAO) has a major impact on North Atlantic/European winter climate. The results of a comparison between stalagmite GP2 δ18O ratios from Grotte de Piste and stalagmites Bu2 and Bu4 from Bunker Cave (Western Germany) with other speleothem records from Northern Spain, Northern Italy and Northwestern Scotland and a lake record from West Greenland (Proctor et al., 2002; Drysdale et al., 2006; Railsback et al., 2011; Fohlmeister et al., 2012; Scholz et al., 2012) demonstrated that both the West German Bunker cave and the northwestern Moroccan caves were sensitive to the NAO. The West German record covers the entire Holocene, whereas the Moroccan record covers the complete Early to Mid Holocene. It was demonstrated that these records were significantly correlated to each other and that the sign of correlation changed from dominantly positive in the Early Holocene to dominantly negative in the Mid to Late Holocene. From climate modeling data derived from the fully coupled COSMOS earth system model (Wei and Lohmann, 2012) it was possible to come up with a climate dynamical context.

The Early Holocene was still characterized by the presence and melting of the Laurentide Ice

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Sheet in northeast America. On the “short” term climate modeling over a 100 year time slice during the Early Holocene showed that the Azores Subtropical High was shifted in a northeast direction and that the shape of its center was more circular. This is able to explain a positive correlation between West German and Northwest Moroccan rainfall, because the NAO-rainfall correlation belts shift north as well. The fact that this effect was only visible in the model run with both the prescribed Laurentide Ice Sheet and the melt water flux demonstrates that it concerns a non lineair response to deglaciation processes.

Additionally, on a longer term (multi-centennial timescales) melt water had a profound impact on the thermo haline circulation, which most likely affected the strength of the west east flowing North Atlantic Current (Bamberg et al., 2010). It is well known that the North Atlantic Current plays an important role for North Atlantic/European temperature and rainfall patterns (Gastineau and Frankignoul, 2012). A slow down of the North Atlantic Current generally induces a cooling in the North Atlantic basin reducing the moisture availability due to decreasing evaporation. This cooling was amplified by the high albedo from the Laurentide Ice Sheet (Renssen et al., 2009). The thermohaline circulation was thus weaker and therefore more vulnerable for melt water intrusions during the Early Holocene (Wei and Lohmann, 2012). Additionally, the strength of the thermo haline circulation affects mechanisms like the Atlantic Multidecadal Oscillation (AMO; (Kerr, 2000). The AMO has an impact on the NAO by affecting the configuration and shape of the Azores subtropical high and the Icelandic low pressure zones, such that a positive correlation between Western German and Northwest Moroccan rainfall can be explained. Therefore, it is likely that the Early Holocene North Atlantic/European climate may have been more ocean dominated compared to the Mid-Late Holocene. In addition to the changing signs of correlation between West German and northwest Moroccan rainfall many oscillations have been reconciled with periods varying between 400 and 600 years, which shows that the NAO has been varying throughout the Holocene on multi-centennial timescales. This study thus represents a major contribution to the existing NAO literature.

7.3. Outlook

The results from this thesis have shown that aragonite speleothems have a high potential in providing climate reconstructions from trace element records. Especially the very small uncertainties with U/Th dating techniques represent a major advantage over calcitic speleothems. In addition to Sr and Mg, P and U seem to be sensitive to climate controlled processes (Wassenburg et al., 2012). However, the fact that aragonite may be precipitating on top of a stalagmite at the moment that PCP is controlling the drip water trace element/Ca ratios may complicate the interpretation of Mg and Sr in aragonite speleothems. A potential study could thus focus on modeling the drip water trace element/Ca ratios as a consequence of different balances in PCP versus PAP, this would definitely increase the understanding of Mg and Sr records from aragonite speleothems. A second topic which has to be assessed in order to improve the understanding of NAO dynamics is to construct one Holocene NAO record, which includes records from key regions affected by the NAO. This record could then be compared to potential forcing mechanisms like reconstructions

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from the strength of the thermohaline circulation, solar forcing, or sea surface temperatures. It has to be noted, however that this is challenging because climate reconstructions have different resolution, dating uncertainties and may not be representative for only the winter season (i.e. the dominating season of the NAO).

References

Bamberg, A., Rosenthal, Y., Paul, A., Heslop, D., Mulitza, S., Ruhlemann, C., Schulz, M., 2010. Reduced North Atlantic Central Water formation in response to early Holocene ice-sheet melting. Geophysical Research Letters 37, 5.

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Romanek, C.S., Grossman, E.L., Morse, J.W., 1992. Carbon isotope fractionation in synthetic aragonite and calcite - effects of temperature and precipitation rate. Geochimica Et Cosmochimica Acta 56, 419-430.

Scholz, D., Frisia, S., Borsato, A., Spotl, C., Fohlmeister, J., Mudelsee, M., Miorandi, R., Mangini, A., 2012. Holocene climate variability in north-eastern Italy: potential influence of the NAO and solar activity recorded by speleothem data. Climate of the Past 8, 1367-1383.

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160

Curriculum Vitae

161

CURRICULUM VITAE

Nationality: DutchDate of birth: 04-07-1982Place of birth: Leiden, Netherlands Civil status: Unmarried

Education: 2009 – 2013 PhD, Institute of Geology, Mineralogy and Geophysics, Ruhr-University

Bochum, Germany.

Supervision: A. Immenhauser

Title thesis: Holocene climate evolution of NW Morocco as recorded in aragonitic speleothems: Significance of the North Atlantic Oscillation

2006 – 2008 Master Environment and Resource Management, Free University, Amsterdam, Netherlands > not completed

2004 – 2008 Master earth science, direction Palaeoclimatology, Palaeoecology, Palaeoceanography, Free University, Amsterdam, Netherlands > Master diploma, achieved level: Master of Science (MSc)

Supervision: J. Zinke

Title thesis: A proposition of a better yearly sampling method and a (long term) climate reconstruction from coral Sr/Ca and δ18Oseawater reconstruction from the Southern Indian Ocean. Indian-Pacific Ocean teleconnections

2001 – 2005 Bachelor earth science, Physical Geography, Free University, Amsterdam, Netherlands > Bachelor diploma

1994 – 2001 High school VWO (Preparing Scientific Education), Alphen aan den Rijn, Netherlands > high school diploma

Academic posts: 07/08 – 01/09 Research assistant (funded by the Natural Environment Research Council,

NERC) at Manchester Metropolitan University (MMU), United Kingdom. Supervision: C. Perry

Project title: Historical timescale records of coral growth and skeletal carbonate deposition under conditions of high turbidity and terrigenous sediment influence

162

Appendix

163

APPENDIX

The appendix is attached following this page.

Appendix Chapter 4 Stalagmite HK1 230Th/U ages

sample Age ± min-Age max-Age U238 ± Th232 ±Th230 ± Th230

/Th232 ± U238 /Th232 ± Th230

/U238 ±Th230 excess /U238

± U234 /U238 ±

U234 /U238 initial

ky ky ky ky ppm ppm ppb ppb ppt ppt dpm/dpmdpm/dpmdpm/dpmdpm/dpmdpm/dpmdpm/dpmdpm/dpmdpm/dpmdpm/dpmdpm/dpmHK1U1 36.47 0.26 36.210 36.730 0.3525 0.0004 0.1269 0.0048 2.099 0.006 3088.0 117.9 8597 327 0.35918 0.00113 0.35911 0.00143 1.2521 0.0025 1.279HK1U2 33.41 0.29 33.116 33.702 11.0412 0.0253 0.0418 0.0047 58.519 0.185 261630.1 29275.9 818391 91559 0.31969 0.00125 0.31969 0.00147 1.2035 0.0034 1.224HK1U6 18.87 0.14 18.722 19.010 12.5363 0.0245 0.4980 0.0049 41.772 0.149 15662.0 165.2 77927 789 0.20098 0.00082 0.20098 0.00091 1.2598 0.0031 1.274

Appendix Chapter 4. Stalagmite HK1 trace elements

Sample nr.

Distance from 

transition (mm)

MG25 Al27 P31 Ti47 Sr86 Y89 Ba137 Pb208 Th232 U238

HK1‐CA1‐1 2.4 7180.44 1.51718 59.497 75.8762 0.00328 32.414 0.00741 0 0.39747

HK1‐CA1‐2 2.2 7073.85 1.05289 64.304 74.729 0.00532 32.9103 0.00469 0 0.33702

HK1‐CA1‐3 2 7317.98 0.51842 68.1062 75.4602 0.00468 32.4107 0.00433 0.32664

HK1‐CA1‐4 1.8 7282.96 0.31022 58.8932 0.00736 80.5393 0.00412 36.2062 0.00388 0.29376

HK1‐CA1‐5 1.6 7410.4 1.37572 59.3329 0.00808 76.808 0.00803 33.2502 0.0044 0 0.3177

HK1‐CA1‐6 1.4 7289.24 0.88158 62.7024 76.1774 0.00869 33.8767 0.00743 0 0.30367

HK1‐CA1‐7 1.2 7174.27 0.25485 64.2098 77.6068 0.00528 33.5346 0.00361 0 0.30867

HK1‐CA1‐8 1 7084.88 0.80557 61.4153 74.8933 0.00363 32.2026 0.00431 0 0.31335

HK1‐CA1‐9 0.8 7384.51 0.68686 54.6253 0.12283 80.5108 0.00567 35.9116 0.00555 0 0.30645

HK1‐CA1‐10 0.6 7417.11 1.20484 55.9178 77.5986 0.00582 32.893 0.00636 0.34519

HK1‐CA1‐11 0.4 7547.47 0.89405 64.6565 0.02468 83.4863 0.00464 34.8415 0.00513 0.0001 0.38252

HK1‐CA1‐12 0.2 7944.5 0.59606 65.933 0.00795 86.1001 0.00462 36.3111 0.00565 0 0.364

HK1‐CA1‐13 0 3950.29 0.64106 85.272 0.01434 543.046 0.00692 128.995 0.0064 0.00033 16.1762

HK1‐CA1‐14 ‐0.2 981.862 0.93502 102.729 0.01815 829.32 0.00864 178.262 0.00513 0.00026 24.6495

HK1‐CA1‐15 ‐0.4 126.317 0.75211 54.2542 0.04807 806.292 0.00609 179.11 0.00478 0.00026 15.2835

HK1‐CA1‐16 ‐0.6 88.392 0.52673 42.3455 0.12437 769.254 0.00555 167.46 0.0054 0.00021 10.5122

HK1‐CA1‐17 ‐0.8 94.9468 1.10729 45.3509 753.839 0.00559 162.571 0.00471 0.00028 12.1493

HK1‐CA1‐18 ‐1 131.436 0.71211 52.5746 0.02586 757.236 0.00607 164.918 0.00571 0.00026 13.6933

HK1‐CA1‐19 ‐1.2 264.838 1.06544 53.6845 0.01721 749.509 0.00648 166.498 0.00586 0.00024 14.4246

HK1‐CA1‐20 ‐1.4 241.124 2.38169 58.3226 0.08091 772.444 0.00676 174.131 0.00447 0.0003 15.8464

Sample nr.

Distance from 

transition (mm)

MG25 Al27 P31 Ti47 Sr86 Y89 Ba137 Pb208 Th232 U238

HK1‐CA2‐1 2.2 7199.38 0.49297 53.4988 0.01269 97.6386 0.00497 44.957 0.00717 0.00058 0.48959

HK1‐CA2‐2 2 7135.07 0.24321 51.9859 #DIV/0! 97.4716 0.00387 45.0319 0.00557 0.00027 0.48893

HK1‐CA2‐3 1.8 6940.17 0.18248 51.4627 #DIV/0! 98.9583 0.00405 46.2048 0.00805 #DIV/0! 0.51181

HK1‐CA2‐4 1.6 6888.28 0.16671 49.7715 #DIV/0! 102.86 0.00387 45.4639 0.00526 #DIV/0! 0.54979

HK1‐CA2‐5 1.4 6935.94 0.15276 47.5249 #DIV/0! 105.925 0.00316 48.3001 0.00603 0.00026 0.56182

HK1‐CA2‐6 1.2 7248.23 0.16616 45.8076 #DIV/0! 109.449 0.00255 50.5074 0.0072 0 0.56551

HK1‐CA2‐7 1 7130.04 0.12155 44.9726 #DIV/0! 112.045 0.00253 51.2178 0.00536 0 0.57947

HK1‐CA2‐8 0.8 6892.41 0.11915 45.0317 #DIV/0! 110.545 0.0024 48.0118 0.00666 #DIV/0! 0.57679

HK1‐CA2‐9 0.6 7149.15 0.15352 42.4743 #DIV/0! 109.238 0.00218 47.7704 0.00585 0.00026 0.52644

HK1‐CA2‐10 0.4 7204.01 0.11188 43.3693 #DIV/0! 112.196 0.00275 49.7076 0.00604 #DIV/0! 0.56024

HK1‐CA2‐11 0.2 7300.67 0.14448 41.1731 0.00519 125.294 0.00297 53.991 0.00816 #DIV/0! 0.79816

HK1‐CA2‐12 0 3815.42 0.47795 66.8308 #DIV/0! 520.672 0.00583 144.935 0.00634 0.00041 18.1605

HK1‐CA2‐13 ‐0.2 100.105 0.21196 71.7777 0.05928 823.783 0.00766 205.814 0.00731 0.00032 21.3588

HK1‐CA2‐14 ‐0.4 78.0009 0.092 62.0348 #DIV/0! 832.846 0.0076 212.267 0.00688 0 21.0814

HK1‐CA2‐15 ‐0.6 139.001 0.13459 56.3036 #DIV/0! 865.549 0.00768 214.727 0.00491 0 21.395

HK1‐CA2‐16 ‐0.8 91.8373 0.10061 48.3656 0.0064 822.045 0.00728 207.116 0.00461 0 16.9753

HK1‐CA2‐17 ‐1 74.4793 0.06553 43.0869 #DIV/0! 760.816 0.00635 188.431 0.00425 0 12.5231

HK1‐CA2‐18 ‐1.2 210.003 0.52548 32.28 #DIV/0! 824.178 0.00652 192.38 0.00397 0 12.4595

HK1‐CA2‐19 ‐1.4 159.263 0.32378 34.4813 #DIV/0! 809.571 0.00616 189.858 0.00377 0 14.1728

HK1‐CA2‐20 ‐1.6 81.0261 0.29195 34.9707 #DIV/0! 805.809 0.00615 188.568 0.00397 0 13.2391

Appendix Chapter 4. Stalagmite HK3, 230Th/U datings

sample Age ± min-Age max-Age U238 ± Th232 ± Th230 ± Th230 /Th232 ± U238

/Th232 ± Th230 /U238 ±

Th230 excess /U238

± U234 /U238 ±

U234 /U238 initial

ky ky ky ky ppm ppm ppb ppb ppt ppt dpm/dpmdpm/dpmdpm/dpmdpm/dpmdpm/dpmdpm/dpmdpm/dpmdpm/dpmdpm/dpmdpm/dpm

HK3U1 27.48 0.20 27.272 27.680 10.1692 0.0197 0.7013 0.0053 50.191 0.134 13363.0 107.1 44886 350 0.29771 0.00098 0.29769 0.00119 1.3258 0.0033 1.352HK3 U1.1 14.36 0.09 14.27 14.46 36.9959 0.0679 4.426 0.012 77.172 0.159 3255.3 11.3 25873 87 0.1258 0.0003 0.1258 0.0005 1.0203 0.0025 1.021

HK3U2 23.53 0.17 23.366 23.700 6.3396 0.0097 1.4043 0.0054 27.905 0.092 3710.1 18.8 13974 58 0.26550 0.00096 0.26546 0.00112 1.3576 0.0029 1.382HK3U3 7.655 0.067 7.588 7.722 0.2390 0.0002 1.3969 0.0065 0.389 0.002 52.0 0.4 530 3 0.09824 0.00064 0.09711 0.00066 1.4298 0.0024 1.439HK3U7 4.237 0.048 4.190 4.285 0.2337 0.0002 0.4462 0.0037 0.195 0.002 81.7 1.0 1621 13 0.05041 0.00043 0.05004 0.00044 1.3128 0.0028 1.317

Appendix Chapter 4. Stalagmite HK3, carbon and oxygen isotopes

Transect depth (mm) Sample No. d13C (‰) d18O (‰)Top 0.01 HK3 ‐ CA 1 ‐2.23 ‐1.27

0.76 HK3 ‐ CA 2 ‐2.29 ‐1.27

1.26 HK3 ‐ CA 3 ‐1.34 ‐0.97

1.76 HK3 ‐ CA 4a ‐1.26 ‐0.88

2.26 HK3 ‐ CA 5 ‐1.55 ‐0.70

2.76 HK3 ‐ CA 6 ‐1.51 ‐0.48

3.26 HK3 ‐ CA 7 ‐1.76 ‐0.64

3.56 HK3 ‐ CA 8 ‐1.95 ‐0.72

3.66 HK3 ‐ CA 9 ‐1.85 ‐0.87

3.76 HK3 ‐ CA 10 ‐1.92 ‐0.87

3.86 HK3 ‐ CA 11 ‐1.73 ‐0.63

3.96 HK3 ‐ CA 12 ‐1.93 ‐0.75

4.06 HK3 ‐ CA 13 ‐1.23 ‐0.21

4.16 HK3 ‐ CA 14 ‐1.55 ‐0.39

4.26 HK3 ‐ CA 15 ‐1.45 ‐0.38

4.36 HK3 ‐ CA 16 ‐1.45 ‐0.21

4.46 HK3 ‐ CA 17 ‐1.50 ‐0.36

4.56 HK3 ‐ CA 18 ‐1.42 ‐0.17

4.685 HK3 ‐ CA 19 ‐1.05 ‐0.08

4.82 HK3 ‐ CA 20 ‐1.05 ‐0.03

Aragonite 4.94 HK3 ‐ CA 21 ‐1.75 ‐0.44

Calcite 5.06 HK3 ‐ CA 22

5.18 HK3 ‐ CA 23 ‐2.19 ‐0.52

5.3 HK3 ‐ CA 24 ‐2.58 ‐0.76

5.41 HK3 ‐ CA 25 ‐2.21 ‐0.53

5.51 HK3 ‐ CA 26 ‐2.31 ‐0.40

5.61 HK3 ‐ CA 27 ‐2.59 ‐0.65

5.71 HK3 ‐ CA 28 ‐2.24 ‐0.25

5.81 HK3 ‐ CA 29 ‐2.74 ‐0.55

5.91 HK3 ‐ CA 30 ‐2.54 ‐0.54

6.01 HK3 ‐ CA 31 ‐2.43 ‐0.37

6.11 HK3 ‐ CA 32 ‐2.61 ‐0.64

6.22 HK3 ‐ CA 33 ‐2.55 ‐0.56

6.39 HK3 ‐ CA 35 ‐2.78 ‐0.87

6.55 HK3 ‐ CA 36 ‐2.69 ‐0.84

6.66 HK3 ‐ CA 37 ‐2.58 ‐0.78

6.77 HK3 ‐ CA 38a ‐2.73 ‐1.01

6.87 HK3 ‐ CA 39 ‐2.78 ‐0.98

6.97 HK3 ‐ CA 40 ‐2.74 ‐1.20

7.27 HK3 ‐ CA 41 ‐2.80 ‐1.32

7.77 HK3 ‐ CA 42 ‐2.83 ‐1.77

8.27 HK3 ‐ CA 43 ‐2.95 ‐1.80

8.77 HK3 ‐ CA 44 ‐3.61 ‐1.77

9.27 HK3 ‐ CA 45 ‐2.74 ‐0.82

15.27 HK3 ‐ CA 57 ‐4.83 ‐1.26

15.77 HK3 ‐ CA 58 ‐4.81 ‐1.15

16.27 HK3 ‐ CA 59 ‐4.68 ‐1.26

16.77 HK3 ‐ CA 60 ‐4.60 ‐1.22

17.27 HK3 ‐ CA 61 ‐4.50 ‐1.65

17.77 HK3 ‐ CA 62a ‐4.55 ‐1.72

18.27 HK3 ‐ CA 63 ‐4.30 ‐1.74

18.77 HK3 ‐ CA 64 ‐3.57 ‐1.32

19.27 HK3 ‐ CA 65 ‐3.55 ‐1.70

19.77 HK3 ‐ CA 66 ‐3.13 ‐1.85

20.27 HK3 ‐ CA 67 ‐3.04 ‐1.81

20.57 HK3 ‐ CA 68 ‐3.11 ‐1.59

20.695 HK3 ‐ CA 69 ‐3.24 ‐1.45

20.87 HK3 ‐ CA 70 ‐3.39 ‐1.29

21.045 HK3 ‐ CA 71 ‐3.32 ‐1.38

21.195 HK3 ‐ CA 72 ‐3.25 ‐1.38

21.32 HK3 ‐ CA 73 ‐3.14 ‐1.35

21.47 HK3 ‐ CA 74 ‐2.96 ‐1.58

21.62 HK3 ‐ CA 75 ‐2.97 ‐1.51

21.745 HK3 ‐ CA 76 ‐2.98 ‐1.74

21.895 HK3 ‐ CA 77 ‐2.97 ‐1.64

22.045 HK3 ‐ CA 78 ‐2.63 ‐1.73

Calcite 22.17 HK3 ‐ CA 79 ‐2.56 ‐1.55

Aragonite 22.27 HK3 ‐ CA 80 ‐2.07 ‐1.35

22.37 HK3 ‐ CA 81 ‐2.09 ‐1.36

22.495 HK3 ‐ CA 82 ‐1.95 ‐1.12

22.63 HK3 ‐ CA 83 ‐1.86 ‐0.83

22.74 HK3 ‐ CA 84 ‐1.76 ‐0.81

22.865 HK3 ‐ CA 85 ‐1.64 ‐0.65

23.04 HK3 ‐ CA 86 ‐1.59 ‐0.72

23.24 HK3 ‐ CA 87 ‐1.45 ‐0.80

23.44 HK3 ‐ CA 88 ‐1.40 ‐0.84

23.64 HK3 ‐ CA 89 ‐1.45 ‐0.80

23.84 HK3 ‐ CA 90 ‐1.52 ‐0.58

24.04 HK3 ‐ CA 91 ‐1.54 ‐0.70

24.24 HK3 ‐ CA 92 ‐1.64 ‐0.67

24.44 HK3 ‐ CA 93 ‐1.41 ‐0.75

24.69 HK3 ‐ CA 94 ‐1.42 ‐1.02

25.09 HK3 ‐ CA 95 ‐1.77 ‐1.07

25.59 HK3 ‐ CA 96 ‐1.90 ‐0.73

26.09 HK3 ‐ CA 97 ‐1.71 ‐0.92

26.59 HK3 ‐ CA 98 ‐1.82 ‐1.08

27.09 HK3 ‐ CA 99 ‐1.88 ‐0.95

Bottom 27.59 HK3 ‐ CA 100 ‐1.38 ‐0.58

Appendix Chapter 4. Stalagmite HK3, trace elements

Sample nr. Transect depth (mm) MG25 Al27 P31 Ti47 Sr86 Y89 Ba137 Pb208 Th232 U238Top HK‐3‐1 0.15 Aragonite 54.82075 7.585519 32.93361 0.359962 688.3256 0.007363 175.7336 0.008518 0.00202 10.61143

HK‐3‐2 0.25 54.72071 9.84213 30.9458 0.762262 684.5549 0.009726 #WERT! 0.012574 0.001258 10.07095

HK‐3‐3 0.35 48.2798 3.373554 28.94162 0.170654 656.7814 0.007677 163.7924 0.008126 0.001 9.10412

HK‐3‐4 0.45 47.37246 0.332876 29.23485 0.181184 642.8558 0.006595 160.7411 0.010692 0.001 8.835231

HK‐3‐5 0.55 45.54866 0.7724 27.82875 0.190893 668.5863 0.003904 157.9099 0.011044 0.001 7.740338

HK‐3‐6 0.65 49.3173 0.663206 25.82763 0.130193 699.9531 0.006076 159.9104 0.006941 0.001 7.310177

HK‐3‐7 0.75 48.14298 1.863622 24.01823 0.01 693.9273 0.006418 160.231 0.007965 0.001 7.266927

HK‐3‐8 0.85 48.2783 0.986869 23.42792 0.523266 694.5107 0.005571 161.6987 0.011841 0.001 7.587906

HK‐3‐9 0.95 50.9637 2.650849 25.35538 0.356633 683.9821 0.005751 162.6102 0.009517 0.001 8.788256

HK‐3‐10 1.05 52.01356 1.360506 25.87998 0.01 697.607 0.006743 166.6074 0.008977 0.001 8.964398

HK‐3‐11 1.15 51.15428 0.816319 27.82411 0.31411 675.3417 0.00716 165.4168 0.011873 0.001 8.235557

HK‐3‐12 1.25 51.9704 0.794313 29.72734 0.01 641.7452 0.003957 164.9103 0.007499 0.001 8.309967

HK‐3‐13 1.35 55.66075 1.07757 30.43464 0.439092 662.012 0.0064 173.5235 0.006159 0.001 11.05636

HK‐3‐14 1.45 59.13227 0.770334 30.11416 0.057674 712.2549 0.005073 #WERT! 0.004885 0.001 13.55491

HK‐3‐15 1.55 51.81851 0.862057 29.45926 0.01 682.2748 0.004607 168.0857 0.01051 0.001 13.47799

HK‐3‐16 1.65 49.47181 1.058131 29.74409 0.238115 699.5778 0.006589 168.5226 0.012291 0.001 14.11433

HK‐3‐17 1.75 52.21206 1.008611 29.72992 0.040711 696.5482 0.005964 170.6557 0.026395 0.001 14.55859

HK‐3‐18 1.85 52.02744 2.106948 31.5961 0.01 705.9682 0.00579 174.1377 0.006024 0.001 15.56984

HK‐3‐19 1.95 52.26087 3.253011 33.80131 0.01 682.6054 0.005591 174.8818 0.008098 0.001 15.6297

HK‐3‐20 2.05 51.67352 3.907647 30.28263 0.17765 677.8765 0.005106 170.5911 0.006194 0.001 15.36704

HK‐3‐21 2.15 49.26833 7.104279 32.10482 0.033933 689.5098 0.007886 170.45 0.004124 0.001 14.10131

HK‐3‐22 2.25 43.7799 1.107403 28.25633 0.270722 669.0139 0.006813 161.457 0.004999 0.001 12.93968

HK‐3‐23 2.35 46.98629 1.021209 27.98375 0.093768 692.1046 0.007292 165.7101 0.008134 0.001 12.5446

HK‐3‐24 2.45 42.17496 0.968215 28.762 0.01 686.8458 0.007387 162.1261 0.004972 0.001 11.8174

HK‐3‐25 2.55 44.5758 1.3032 29.79271 0.01 679.893 0.008405 155.998 0.006441 0.001 12.40203

HK‐3‐26 2.65 44.56345 0.639923 26.4469 0.031101 651.905 0.007204 156.5133 0.010115 0.001 12.33918

HK‐3‐27 2.75 45.06218 0.703509 25.46417 0.563669 644.3891 0.006534 153.9055 0.01056 0.001 10.12928

HK‐3‐28 2.85 42.77802 0.535581 25.83298 0.057011 648.8925 0.006334 158.544 0.003069 0.001 8.917732

HK‐3‐29 2.95 41.38044 0.603106 26.72904 0.01 651.1506 0.004694 149.79 0.006182 0.001 9.561796

HK‐3‐30 3.05 42.97702 0.951987 30.04994 0.529294 670.0474 0.006727 154.2089 0.007268 0.001 11.27897

HK‐3‐31 3.15 42.57657 1.040248 31.87266 0.01 661.4481 0.007611 161.0979 0.008875 0.001 11.54235

HK‐3‐32 3.25 42.85009 1.365212 29.93293 0.146834 652.3394 0.005754 158.8485 0.008741 0.001 10.84441

HK‐3‐33 3.35 44.88178 0.989638 30.31403 0.209745 641.3499 0.005845 159.7273 0.006477 0.001 10.9967

HK‐3‐34 3.45 42.74541 1.312191 30.5122 0.149752 603.6292 0.005861 153.8072 0.008185 0.001 10.71246

HK‐3‐35 3.55 43.9721 1.763146 33.85076 0.01 627.9059 0.004415 158.3496 0.006713 0.001 10.82188

HK‐3‐36 3.65 39.62749 0.961279 33.57981 0.01 636.2909 0.004911 156.1117 0.006831 0.001 10.7168

HK‐3‐37 3.75 39.8759 1.075977 35.09879 0.327269 674.0246 0.006835 160.0911 0.007487 0.001 11.98607

HK‐3‐38 3.85 38.57934 1.767803 43.14791 0.360824 722.9122 0.007581 167.4506 0.009102 0.001 14.56338

HK‐3‐39 3.95 42.1297 8.281727 50.99822 0.31841 701.1939 0.006679 166.1797 0.01213 0.002035 13.88679

HK‐3‐40 4.05 45.47204 3.438758 45.83323 0.01 697.7272 0.005599 165.9779 0.012624 0.001 13.01862

HK‐3‐41 4.15 45.17524 1.586612 38.23875 0.493526 685.419 0.006579 162.2782 0.01198 0.001 12.51411

HK‐3‐42 4.25 45.24381 0.369934 28.20403 0.117912 671.4472 0.00609 166.237 0.012479 0.001 11.59278

HK‐3‐43 4.35 43.14417 1.982684 27.70345 0.215748 651.9762 0.00976 158.7797 0.015804 0.001 10.31669

HK‐3‐44 4.45 59.78047 17.17208 29.16733 0.856619 680.3435 0.015576 168.1398 0.024994 0.00284 9.104388

HK‐3‐45 4.55 47.66209 9.433031 23.88997 0.540351 706.0713 0.00841 174.5393 0.02308 0.001481 8.709397

HK‐3‐46 4.65 54.93047 1.265017 29.52922 0.01 730.5024 0.008446 162.9727 0.012782 0.001 12.69081

HK‐3‐47 4.75 45.46926 1.043645 34.03523 0.155255 740.5619 0.007853 160.958 0.022172 0.001 15.46406

HK‐3‐48 4.85 408.9684 1.30455 36.42934 0.23617 720.1895 0.011927 158.2739 0.021054 0.001 17.74232

Aragonite K‐3‐49 Aragoni 4.95 1611.763 1.560813 34.54288 0.273812 545.1375 0.011164 113.8034 0.026354 0.001 12.44436

Calcite HK‐3‐50 Calcite 5.05 8569.816 8.805649 47.73727 0.516996 129.6619 0.011668 45.15457 0.020418 0.001868 1.879832

HK‐3‐51 5.15 8275.521 80.52831 60.41915 3.284634 76.30894 0.041455 37.51526 0.072208 0.007461 0.231506

HK‐3‐52 5.25 8014.449 18.02814 54.80547 0.732914 77.48872 0.016373 37.23928 0.040798 0.003113 0.238203

HK‐3‐53 5.35 8240.346 22.6078 44.90852 0.951113 90.03622 0.018859 40.98576 0.029429 0.003634 0.494835

HK‐3‐54 5.45 8196.698 50.18971 39.76008 1.21263 80.05342 0.02183 38.47252 0.046985 0.004171 0.221889

HK‐3‐55 5.55 8253.362 25.62772 47.61552 1.416313 77.79169 0.022216 36.37441 0.035665 0.004175 0.241311

HK‐3‐56 5.65 8533.148 90.78255 43.10484 8.84606 74.12383 0.03337 35.27976 0.071559 0.007588 0.235157

HK‐3‐57 5.75 8667.13 106.2463 51.72141 4.359808 73.95479 0.029738 35.13366 0.043659 0.007642 0.23121

HK‐3‐58 5.85 8872.306 6.410955 47.02213 0.507576 71.7306 0.007917 33.97739 0.014076 0.001487 0.20633

HK‐3‐59 5.95 8819.74 5.966124 42.24561 0.44108 81.64168 0.009379 39.1967 0.025259 0.001635 0.194953

HK‐3‐60 6.05 9170.759 7.993613 40.86654 0.822113 82.45334 0.017103 38.66127 0.037216 0.002588 0.365364

HK‐3‐61 6.15 8341.392 15.76982 48.91811 0.907121 115.4228 0.019631 44.97296 0.056792 0.003424 1.234386

HK‐3‐62 6.25 7259.293 3.7678 43.23606 0.408228 82.84385 0.011299 35.62102 0.029697 0.002206 0.403782

HK‐3‐63 6.35 8106.881 33.14223 45.88611 1.732824 84.22276 0.020423 38.08955 0.051995 0.005465 0.298502

HK‐3‐64 6.45 7593.652 53.90484 59.82056 2.213574 85.6633 0.024846 37.32446 0.047146 0.007055 0.376059

HK‐3‐65 6.55 7139.35 5.015717 62.57115 0.75314 76.23923 0.018211 33.06127 0.03166 0.002547 0.276796

HK‐3‐66 6.65 7013.746 18.693 55.94032 1.08649 79.64824 0.016603 35.97892 0.03606 0.002805 0.264804

HK‐3‐67 6.75 6481.848 9.170348 66.07019 0.868626 73.20382 0.0187 31.01875 0.020481 0.002181 0.261247

HK‐3‐68 6.85 6731.457 135.4987 107.7304 6.832651 107.8119 0.097409 42.53584 0.230039 0.033481 0.448132

HK‐3‐69 6.95 6479.014 45.74341 103.3405 3.175568 79.45419 0.079965 31.56431 0.096357 0.007907 0.313058

HK‐3‐70 7.05 6608.877 11.26421 104.4105 0.828919 64.89319 0.057478 26.14267 0.036947 0.003501 0.281437

HK‐3‐71 7.15 7082.016 48.51808 96.06269 1.612552 75.70684 0.14374 35.64506 0.04343 0.00656 0.351879

HK‐3‐72 7.25 5870.694 17.39242 111.7452 0.707922 67.62155 0.29756 26.87547 0.038282 0.004904 0.282605

HK‐3‐73 7.35 5700.723 26.72802 108.6327 1.251598 65.03646 0.303618 26.86305 0.045371 0.004244 0.247326

HK‐3‐74 7.45 5566.84 19.13852 108.8366 0.686114 62.41802 0.324221 25.28528 0.037954 0.004424 0.209493

HK‐3‐75 7.55 5537.998 31.82057 120.18 1.125437 57.60701 0.541164 23.27977 0.041261 0.005232 0.212496

HK‐3‐76 7.65 5225.05 33.7487 125.3971 1.438418 55.38475 0.630944 20.97304 0.045313 0.005367 0.216999

HK‐3‐77 7.75 5130.686 25.23178 127.5205 0.876177 55.33515 0.816201 21.532 0.045975 0.005137 0.211372

HK‐3‐78 7.85 5328.833 48.4531 127.1161 1.78691 55.10543 0.783613 21.42345 0.065592 0.009351 0.18308

HK‐3‐79 7.95 5310.65 117.7105 134.6945 4.935566 53.22933 0.746717 21.22538 0.096454 0.016712 0.186101

HK‐3‐80 8.05 5329.976 112.6146 138.7474 4.638587 51.80356 0.84581 20.45858 0.071352 0.014848 0.215248

HK‐3‐81 8.15 5408.335 30.70286 119.2535 0.623281 43.62297 0.755842 21.68869 #DIV/0! 0.005198 0.231341

HK‐3‐82 8.25 5322.756 24.42096 108.1017 0.71341 56.04554 0.547697 23.4838 0.031269 0.003602 0.199267

HK‐3‐83 8.35 5567.248 25.27358 127.4305 1.196502 54.38026 0.422865 21.12014 0.040605 0.003121 0.199824

HK‐3‐84 8.45 5435.226 165.8416 133.3318 5.753299 55.13383 0.483583 20.46359 0.089486 0.014319 0.235326

HK‐3‐85 8.55 5378.221 60.05268 120.9873 2.048467 54.18176 0.41058 20.92977 0.058042 0.005374 0.231418

HK‐3‐86 8.65 5662.871 55.20139 122.2382 2.054487 58.03186 0.328895 22.56525 0.048473 0.008484 0.236089

HK‐3‐87 8.75 5825.689 50.36759 110.3005 2.435999 60.97395 0.227643 23.90311 0.039452 0.005662 0.239011

HK‐3‐88 8.85 5736.003 42.09681 108.2369 3.03728 63.99826 0.314923 25.23349 0.045363 0.008395 0.238058

HK‐3‐89 8.95 5246.412 9.48497 97.00648 0.620445 65.38635 0.236617 26.18737 0.027849 0.001715 0.231373

HK‐3‐90 9.05 5241.347 18.98998 120.9165 1.173575 64.71771 0.455832 24.72006 0.036055 0.003075 0.233924

HK‐3‐91 9.15 5101.395 11.80341 94.72015 0.950027 69.61731 0.234563 26.4557 0.029285 0.001486 0.291582

HK‐3‐92 9.25 5235.731 2.371623 85.71515 0.630245 69.56404 0.16476 26.10059 0.015705 0.001966 0.32187

HK‐3‐93 9.35 5802.327 7.73955 86.07154 0.01 66.13785 0.150063 26.67727 0.028456 0.002558 0.245378

HK‐3‐94 9.45 6236.619 15.52657 83.20468 0.407122 68.45647 0.097747 28.57351 0.027051 0.003452 0.206597

HK‐3‐95 9.55 6010.658 18.74857 82.35525 0.641181 67.83082 0.101453 27.11249 0.020674 0.00278 0.230985

HK‐3‐96 9.65 5684.871 10.99897 93.9389 0.529858 68.24523 0.174986 26.11425 0.017125 0.00246 0.263598

HK‐3‐97 9.75 5370.985 7.796923 91.08062 0.630738 70.73896 0.245066 26.75468 0.019214 0.001772 0.293212

HK‐3‐98 9.85 5342.931 16.69127 98.03598 1.034946 70.73766 0.341696 27.3064 0.036927 0.001585 0.303313

HK‐3‐99 9.95 5762.06 2.683162 94.59775 0.486646 68.64596 0.536198 27.94462 0.034247 0.001261 0.278912

Bottom HK‐3‐100 10.05 Calcite 5921.675 4.300313 89.82296 0.01 70.59608 0.470414 27.42539 0.033962 0.001 0.285492

Top HK3‐AC‐1 17.47 Calcite 7622.084 2.054763 50.45368 0.01 88.34539 0.090107 34.67594 0.018636 0.001 0.204221

HK3‐AC‐2 17.57 6781.28 2.095676 70.93253 0.477532 83.21173 0.091021 30.39197 0.010383 0.001 0.240207

HK3‐AC‐3 17.67 6834.961 2.643533 73.94925 0.528344 81.95586 0.096878 29.87372 0.014502 0.001 0.257448

HK3‐AC‐4 17.77 7003.476 2.330257 70.74702 0.140931 83.21697 0.080061 30.63989 0.015059 0.001 0.261309

HK3‐AC‐5 17.87 6851.278 1.977901 75.03462 0.01 83.57278 0.091922 29.2357 0.011554 0.001 0.251919

HK3‐AC‐6 17.97 6731.619 1.486438 70.92547 0.01 75.90227 0.101798 27.65039 0.015697 0.001 0.267806

HK3‐AC‐7 18.07 6875.901 4.48398 77.86186 0.01 79.93119 0.170856 28.28948 0.012249 0.001 0.257197

HK3‐AC‐8 18.17 6799.627 2.049218 84.94023 0.01 79.95666 0.244085 28.52707 0.015315 0.001 0.265717

HK3‐AC‐9 18.27 6773.553 4.644382 81.18304 0.289935 82.81525 0.213657 30.03808 0.018666 0.001 0.252356

HK3‐AC‐10 18.37 6604.422 6.021977 77.66012 0.910109 85.48589 0.205039 31.35751 0.023331 0.001144 0.260871

HK3‐AC‐11 18.47 7055.578 8.993858 70.68754 0.220366 81.6221 0.157997 30.90544 0.023859 0.001835 0.211179

HK3‐AC‐12 18.57 6906.857 1.752992 70.60576 0.01 77.92917 0.222119 29.41516 0.0148 0.001 0.222173

HK3‐AC‐13 18.67 6866.205 53.68739 71.98303 1.82894 80.00585 0.180428 31.30802 0.030121 0.005761 0.221989

HK3‐AC‐14 18.77 7325.976 43.13742 82.03389 2.059402 76.81093 0.308398 28.47589 0.058566 0.004585 0.218941

HK3‐AC‐15 18.87 7226.483 11.28182 72.87792 0.825973 73.69631 0.323629 26.42399 0.027279 0.002463 0.188913

HK3‐AC‐16 18.97 6552.51 23.37916 77.3044 1.382355 78.51534 0.383984 28.08665 0.042297 0.004904 0.206527

HK3‐AC‐17 19.07 7536.908 27.90118 80.42309 6.131201 81.23391 0.433924 30.61677 0.104081 0.017724 0.202564

HK3‐AC‐18 19.17 6941.644 18.80039 92.4908 0.979414 74.00202 0.538084 27.49564 0.050454 0.003762 0.182135

HK3‐AC‐19 19.27 6976.586 4.115482 96.36011 0.385485 74.55848 0.587104 27.42033 0.029583 0.001 0.210617

HK3‐AC‐20 19.37 6881.36 17.34141 88.65182 1.036572 77.87075 0.440609 27.43007 0.030815 0.003283 0.200748

HK3‐AC‐21 19.47 6738.827 4.255898 95.93507 0.866402 76.35231 0.314379 27.72309 0.020012 0.001 0.215764

HK3‐AC‐22 19.57 6766.452 12.02174 98.39991 0.01 75.03435 0.301275 28.61383 0.019468 0.001944 0.216151

HK3‐AC‐23 19.67 6588.474 15.41881 106.0362 0.719389 74.78754 0.650582 28.38985 0.029467 0.002158 0.206875

HK3‐AC‐24 19.77 6747.936 6.26761 98.36362 0.355537 74.79222 0.421899 28.93007 0.027594 0.002202 0.20425

HK3‐AC‐25 19.87 6726.21 6.342342 103.749 0.605769 72.10436 0.243821 26.68115 0.025183 0.001 0.206366

HK3‐AC‐26 19.97 6953.715 76.6066 111.5977 3.911307 72.24094 0.310849 27.13895 0.052178 0.007625 0.186379

HK3‐AC‐27 20.07 6767.353 42.96599 122.9351 1.336488 71.65672 0.252608 23.51227 0.030854 0.005241 0.235418

HK3‐AC‐28 20.17 7421.642 16.29486 88.33971 1.58225 73.06209 0.415274 28.83857 0.02323 0.003888 0.187665

HK3‐AC‐29 20.27 7594.522 13.83805 82.31067 0.821943 75.9323 0.374908 29.60236 0.023 0.00252 0.181316

HK3‐AC‐30 20.37 7448.72 16.83498 74.97701 0.097229 80.65737 0.352241 32.23605 0.021659 0.002315 0.203013

HK3‐AC‐31 20.47 7169.187 14.72407 85.55848 0.440831 80.945 0.310487 29.94871 0.015086 0.001796 0.229302

HK3‐AC‐32 20.57 7468.852 4.579369 73.21238 0.077621 81.11723 0.288792 31.7443 0.017799 0.000952 0.200145

HK3‐AC‐33 20.67 7468.966 3.106892 80.5313 0.516329 80.64959 0.237747 30.53864 0.015094 0.001981 0.203966

HK3‐AC‐34 20.77 7580.524 5.334007 69.54309 0.119628 78.95648 0.20131 30.74389 0.00812 0.001 0.191667

HK3‐AC‐35 20.87 7432.127 6.349624 79.35884 0.01 81.08202 0.21742 30.5882 0.012097 0.002005 0.208686

HK3‐AC‐36 20.97 7521.02 11.9904 82.04258 0.490271 78.05969 0.331892 29.76352 0.019666 0.0018 0.20844

HK3‐AC‐37 21.07 7726.764 6.116536 78.25081 0.148092 76.0602 0.343887 28.66584 0.016675 0.001 0.214744

HK3‐AC‐38 21.17 7421.642 16.29486 88.33971 1.58225 73.06209 0.415274 28.83857 0.02323 0.003888 0.187665

HK3‐AC‐39 21.27 7883.161 9.386936 78.37167 0.750791 81.06221 0.265609 29.92536 0.018191 0.002321 0.201348

HK3‐AC‐40 21.37 8114.466 7.063783 68.2376 0.394004 81.99561 0.40882 29.96952 0.015608 0.001773 0.181403

HK3‐AC‐41 21.47 8301.408 8.400809 67.27129 0.453055 83.18681 0.418022 30.66469 0.013458 0.001237 0.18311

HK3‐AC‐42 21.57 8027.006 12.51633 83.3217 0.01 86.09369 0.502758 32.47913 0.022758 0.00239 0.224246

HK3‐AC‐43 21.67 8181.831 12.6383 68.97062 0.457227 84.07953 0.270714 32.9126 0.019094 0.002981 0.20866

HK3‐AC‐44 21.77 7832.074 16.38043 79.12969 0.983797 85.65529 0.229993 33.15647 0.019617 0.002783 0.214734

HK3‐AC‐45 21.87 7896.569 15.32776 72.61214 0.651569 86.05467 0.262829 34.03348 0.015321 0.002541 0.206159

HK3‐AC‐46 21.97 7633.606 4.058992 67.22785 0.514737 82.31017 0.164323 33.48506 0.009885 0.001 0.206874

HK3‐AC‐47 22.07 7093.057 16.60966 83.4379 0.314814 97.47387 0.19335 34.72965 0.021992 0.002384 0.465001

Calcite HK3‐AC‐48 22.17 5390.611 16.55888 91.33596 0.40982 223.6664 0.168942 54.94181 0.016678 0.002735 3.131462

Aragonite HK3‐AC‐49 22.27 3932.179 33.8278 86.71181 1.332755 374.6883 0.130185 82.7208 0.028214 0.004869 6.197072

HK3‐AC‐50 22.37 1537.899 3.265535 63.24968 0.136972 607.2961 0.050962 123.1866 0.010908 0.001 9.402661

HK3‐AC‐51 22.47 1168.796 1.362785 52.23894 0.209071 631.0659 0.045655 132.8558 0.005261 0.001 9.554828

HK3‐AC‐52 22.57 793.716 0.578372 47.58295 0.01 645.2567 0.035598 134.0724 0.007937 0.001 9.105168

HK3‐AC‐53 22.67 337.1649 1.58296 55.11007 0.01 668.4471 0.030485 138.5774 0.003994 0.001 9.713495

HK3‐AC‐54 22.77 342.5091 2.127914 55.03707 0.01 659.6435 0.042143 140.3523 0.007327 0.001 10.50508

HK3‐AC‐55 22.87 280.6643 1.300927 51.24701 0.01 655.8399 0.046971 143.3066 0.00876 0.001 10.00594

HK3‐AC‐56 22.97 530.7253 1.153719 47.84652 0.01 648.4871 0.034914 138.7963 0.006333 0.001 9.840391

HK3‐AC‐57 23.07 196.6116 1.802861 50.30788 0.296899 658.8659 0.035362 137.4389 0.007213 0.001 9.804463

HK3‐AC‐58 23.17 198.1003 1.473464 45.35144 0.022247 648.2754 0.036934 140.3975 0.006024 0.001 9.52368

HK3‐AC‐59 23.27 421.0328 0.720207 47.07789 0.623566 650.8385 0.039859 142.7306 0.005751 0.001 9.069272

HK3‐AC‐60 23.37 162.4602 1.277662 45.03451 0.196649 648.347 0.032623 139.4905 0.007583 0.001 9.164535

HK3‐AC‐61 23.47 105.666 1.88499 52.26121 0.01 650.3539 0.044644 140.551 0.011509 0.001 9.833283

HK3‐AC‐62 23.57 48.38645 2.541178 54.91323 0.01 653.8478 0.051385 145.7014 0.016051 0.001 9.769793

HK3‐AC‐63 23.67 46.99586 1.614159 43.82121 0.33989 641.0204 0.041813 136.7411 0.00978 0.001 8.922299

HK3‐AC‐64 23.77 #DIV/0! 1.83825 37.45966 0.348449 637.4278 0.038362 139.9448 0.011592 0.001 8.708023

HK3‐AC‐65 23.87 45.16872 1.784489 44.2687 0.01 632.1515 0.037128 134.9507 0.018854 0.001 8.249612

HK3‐AC‐66 23.97 41.756 4.439232 44.8769 0.051368 652.7589 0.027556 141.486 0.014544 0.001 7.92139

HK3‐AC‐67 24.07 40.51867 3.181737 56.61399 0.376658 651.07 0.026879 138.7752 0.006548 0.001 7.938052

HK3‐AC‐68 24.17 38.32181 2.389275 42.07129 0.450592 640.5769 0.027502 133.332 0.004934 0.001 7.817553

HK3‐AC‐69 24.27 39.55094 1.42842 46.1119 0.150703 646.6854 0.025113 135.8426 0.003787 0.001 8.838145

HK3‐AC‐70 24.37 36.00084 1.382664 40.94815 0.01 636.7966 0.026691 135.4321 0.004442 0.001 8.41318

HK3‐AC‐71 24.47 31.58309 0.4736 43.96488 0.01 653.9591 0.026808 138.0576 0.010729 0.001 8.053906

HK3‐AC‐72 24.57 34.75281 1.409733 46.62869 0.01 646.3573 0.022668 139.9561 0.009174 0.001 7.841975

HK3‐AC‐73 24.67 35.75205 2.857271 44.0932 0.351835 641.2976 0.032186 136.559 0.011234 0.001 8.817283

HK3‐AC‐74 24.77 39.25355 7.609815 58.39869 0.986601 639.4293 0.035709 136.7664 0.013281 0.002577 8.356882

HK3‐AC‐75 24.87 48.35956 55.05452 40.12267 3.325719 629.9416 0.030945 135.1202 0.02786 0.007756 6.483171

HK3‐AC‐76 24.97 53.24612 89.23365 43.99747 4.454992 622.2242 0.048221 138.6441 0.042141 0.014258 4.775066

HK3‐AC‐77 25.07 43.48999 8.746019 32.62839 0.299874 611.8522 0.015858 144.926 0.013622 0.001339 4.418582

HK3‐AC‐78 25.17 44.82724 0.497454 31.60548 0.176077 602.991 0.008397 149.7098 0.014732 0.001 5.400668

HK3‐AC‐79 25.27 47.3354 0.405364 41.97674 0.01 631.56 0.014151 157.1246 0.010355 0.001 7.150211

HK3‐AC‐80 25.37 45.46414 0.771214 52.81203 0.01 642.6923 0.020153 152.3014 0.00556 0.001 8.498412

HK3‐AC‐81 25.47 43.68084 0.608086 51.06019 0.01 645.5577 0.023908 150.6406 0.007536 0.001 9.575282

HK3‐AC‐82 25.57 43.17887 1.132115 70.73361 0.284756 663.6841 0.032864 156.0654 0.004817 0.001 10.07264

HK3‐AC‐83 25.67 38.79519 0.941767 66.97723 0.348698 675.5844 0.023849 150.7615 0.007061 0.001 9.252148

HK3‐AC‐84 25.77 35.6395 1.343227 64.95467 0.01 660.2468 0.015373 139.1823 0.009771 0.001 8.131217

HK3‐AC‐85 25.87 36.66211 1.022317 53.26997 0.289751 645.9303 0.019046 135.6339 0.006995 0.001 8.200938

HK3‐AC‐86 25.97 36.15765 2.749044 61.9181 0.311726 657.2159 0.022733 139.704 0.006718 0.001 8.009132

HK3‐AC‐87 26.07 37.8727 4.39693 60.09893 0.107851 644.8921 0.023935 139.721 #DIV/0! 0.001 8.325327

HK3‐AC‐88 26.17 34.72896 1.372643 62.95034 0.19004 666.9414 0.021292 140.0102 0.009424 0.001 9.023089

HK3‐AC‐89 26.27 #DIV/0! 0.504288 44.90905 0.01 639.6248 0.027034 140.0793 0.009311 0.001 9.446808

HK3‐AC‐90 26.37 44.42648 1.839034 50.11279 0.329476 650.0352 0.028842 143.9222 0.012624 0.001 9.270693

HK3‐AC‐91 26.47 41.50328 0.376966 33.48075 0.01 645.9931 0.025555 149.1176 0.008652 0.001 9.246781

HK3‐AC‐92 26.57 41.91583 0.267406 35.56512 0.01 643.9506 0.030226 148.9147 0.005294 0.001 9.934679

HK3‐AC‐93 26.67 42.29221 0.271149 36.54775 0.01 621.8323 0.026997 143.1945 0.005227 0.001 9.521252

HK3‐AC‐94 26.77 41.49151 0.85676 36.03506 0.105611 650.7543 0.023101 141.2684 0.004919 0.001 8.920133

HK3‐AC‐95 26.87 44.0906 1.650553 34.21847 0.01 654.6662 0.023609 147.9093 0.008411 0.001 8.678036

HK3‐AC‐96 26.97 43.04072 1.760475 35.40898 0.01 #WERT! 0.0184 144.8642 0.01088 0.001 8.982016

HK3‐AC‐97 27.07 41.75006 0.634617 35.55913 0.01 658.3721 0.013592 145.0148 0.011111 0.001 8.652429

HK3‐AC‐98 27.17 37.68823 1.356386 35.40339 0.09767 651.6636 0.014337 141.9858 0.014996 0.001 8.365995

HK3‐AC‐99 27.27 38.09217 1.063819 29.88866 0.41947 649.4368 0.014618 139.2036 0.010904 0.001 8.004321

Bottom HK3‐AC‐100 27.37 Aragonite 38.65975 1.691058 26.37729 0.048541 640.9862 0.013298 140.2624 0.013918 0.001 8.067811

Appendix Chapter 4. Stalagmite GP2: trace elements and isotopes

Sample nr. Depth isot MG25 Al27 P31 Sr86(LR) Y89(LR) Ba137(LR) Pb208(LR) U238(LR) Sample Nr Depth isot Mg/Ca Sr/Ca d13C d18O

GP2‐CA‐1 591.2 7545.741 0.660501 44.77903 49.9325966 0.029596 7.483039 0.076686 0.020501 578 ‐5.79 ‐4.40

GP2‐CA‐2 591.1 7641.555 0.604983 45.56624 50.1315164 0.037113 7.654965 0.024717 0.020003 579 ‐5.75 ‐4.41

GP2‐CA‐3 591 7716.495 0.676191 44.09639 50.5369103 0.033944 7.484946 0.021991 0.020067 580 ‐5.58 ‐4.36

GP2‐CA‐4 590.9 7864.877 0.680253 44.37751 52.1815858 0.030984 7.502998 0.022491 0.020572 581 ‐5.14 ‐4.48

GP2‐CA‐5 590.8 7900.644 0.675708 42.5719 50.9296457 0.023533 7.368922 0.02942 0.0207 582 ‐5.04 ‐4.52

GP2‐CA‐6 590.7 7938.179 0.691229 42.24037 50.5767681 0.021804 7.471293 0.034825 0.017924 583 ‐3.49 ‐3.80

GP2‐CA‐7 590.6 7296.854 0.782415 41.31471 51.0906538 0.027333 7.588588 0.029807 0.021151 584 ‐4.38 ‐3.75

GP2‐CA‐8 590.5 7433.601 0.900029 41.63031 51.772471 0.030038 7.4351 0.027949 0.024275 MG‐a15 585.1 0.00010123 0.00144035 ‐4.53 ‐4.15

GP2‐CA‐9 590.4 7436.051 0.741244 41.63205 51.5503847 0.025121 7.292307 0.021469 0.025302 MG‐a14 585.2 0.00010619 0.00144197 ‐4.54 ‐4.17

GP2‐CA‐10 590.3 7296.543 0.722516 42.06947 52.2600225 0.021733 7.098614 0.025385 0.028166 MG‐a13 585.3 0.00011648 0.00144112 ‐4.58 ‐4.25

GP2‐CA‐11 590.2 7100.734 0.703915 41.42128 52.2022601 0.019825 6.970505 0.025487 0.030126 MG‐a12 585.4 0.00011901 0.00145199 ‐4.68 ‐4.34

GP2‐CA‐12 590.1 7073.154 0.710983 39.27997 53.8270206 0.014888 7.323882 0.018783 0.030691 MG‐a11 585.5 0.00012253 0.00145343 ‐4.78 ‐4.34

GP2‐CA‐13 590 7227.704 0.758572 37.93315 54.5761311 0.011671 7.498519 0.048298 0.030452 MG‐a10 585.6 0.00013625 0.00145942 ‐4.82 ‐4.28

GP2‐CA‐14 589.9 7595.658 0.709903 33.86531 56.9100419 0.008399 8.206022 0.025563 0.02888 MG‐a9 585.7 0.00016732 0.00145799 ‐4.87 ‐4.50

GP2‐CA‐15 589.8 8082.439 0.595408 30.48286 59.9670855 0.011855 9.558418 0.023708 0.024372 MG‐a8 585.8 0.00027936 0.00146355 ‐4.79 ‐4.33

GP2‐CA‐16 589.7 8111.084 0.580027 29.8676 60.1904124 0.014354 9.873445 0.017939 0.022508 MG‐a7 585.9 0.00092367 0.00144195 ‐4.85 ‐4.29

GP2‐CA‐17 589.6 8277.798 0.581992 27.84952 60.5356148 0.006355 9.786778 0.01766 0.022436 MG‐a6 586 0.00118878 0.00141496 ‐4.68 ‐4.37

GP2‐CA‐18 589.5 8233.628 0.629313 28.19715 61.0956091 0.004319 9.684694 0.012486 0.02424 MG‐a5 586.1 0.00416429 0.00124955 ‐4.90 ‐4.34

GP2‐CA‐19 589.4 8093.712 0.775638 31.71775 57.1232083 0.007755 8.826224 0.015055 0.02331 MG‐a4 586.2 0.00713572 0.00107812 ‐5.23 ‐4.42

GP2‐CA‐20 589.3 7622.886 1.024226 30.75288 56.1179972 0.013612 8.967707 0.019417 0.025042 MG‐a3 586.3 0.01135215 0.00084355 ‐5.60 ‐4.59

GP2‐CA‐21 589.2 7761.944 0.994704 32.40971 56.5472829 0.012055 8.388023 0.012887 0.026728 MG‐a2 586.4 0.01474302 0.00064153 ‐5.87 ‐4.54

GP2‐CA‐22 589.1 7624.334 0.779298 32.48604 57.1969721 0.010754 8.243178 0.016754 0.027913 MG‐a1 586.5 0.01747854 0.0004882 ‐5.71 ‐4.63

GP2‐CA‐23 589 7789.829 0.755724 33.57516 56.9511942 0.010026 8.482584 0.014642 0.029058 MG‐c00 586.6 0.0193543 0.00036348 ‐6.16 ‐4.75

GP2‐CA‐24 588.9 7741.954 0.847144 35.80498 53.7309462 0.010893 7.641128 0.019272 0.030709 MG‐c01 586.7 0.01969935 0.00025974 ‐6.37 ‐4.88

GP2‐CA‐25 588.8 7641.104 0.997525 37.72966 53.3811239 0.018743 7.215362 0.019302 0.031412 MG‐c02 586.8 0.02030447 0.00020267 ‐6.54 ‐4.77

GP2‐CA‐26 588.7 7582.483 1.004789 40.37858 52.4344588 0.021024 7.06193 0.023484 0.029427 MG‐c03 586.9 0.02028252 0.00018809 ‐6.51 ‐4.79

GP2‐CA‐27 588.6 7401.373 1.065445 42.05589 51.2689648 0.023245 7.037948 0.030761 0.028979 MG‐c04 587 0.02014831 0.00017069 ‐6.61 ‐4.89

GP2‐CA‐28 588.5 7188.546 1.096273 41.1944 51.1989213 0.031055 6.864693 0.035126 0.033787 MG‐c05 587.1 0.01978004 0.00016904 ‐6.73 ‐5.03

GP2‐CA‐29 588.4 7219.704 1.053281 38.4711 51.5318498 0.024586 6.967242 0.02857 0.031196 MG‐c06 587.2 0.01922384 0.00016633 ‐6.85 ‐5.08

GP2‐CA‐30 588.3 7273.503 1.009422 39.65672 51.7875657 0.024839 7.071268 0.02828 0.032325 MG‐c07 587.3 0.01932522 0.00016279 ‐6.82 ‐5.05

GP2‐CA‐31 588.2 7357.168 1.139353 38.475 51.8709244 0.019413 7.137781 0.029314 0.0309 MG‐c08 587.4 0.01962894 0.00016117 ‐6.68 ‐4.93

GP2‐CA‐32 588.1 7510.902 1.165343 37.96862 54.0505335 0.024454 7.427448 0.024278 0.030905 MG‐c09 587.5 0.01930189 0.00015374 ‐6.59 ‐4.93

GP2‐CA‐33 588 7406.75 1.10167 38.80739 53.9537603 0.031996 7.605332 0.024248 0.030554 MG‐c10 587.6 0.01913181 0.00015351 ‐6.55 ‐4.90

GP2‐CA‐34 587.9 7445.402 1.06072 36.45911 55.8281732 0.028849 7.94628 0.022138 0.029869 MG‐c11 587.7 0.01882729 0.00015706 ‐6.57 ‐5.01

GP2‐CA‐35 587.8 7388.878 0.99074 33.20994 56.0672909 0.014088 8.18714 0.013287 0.02981 MG‐c12 587.8 0.01863708 0.00015318 ‐6.59 ‐5.13

GP2‐CA‐36 587.7 7697.519 0.948339 31.75027 60.5636112 0.012358 8.331902 0.010757 0.03333 MG‐c13 587.9 0.01859626 0.00015375 ‐6.58 ‐5.17

GP2‐CA‐37 587.6 7791.784 0.85639 29.50333 60.321457 0.013797 8.980294 0.011897 0.028144 MG‐c14 588 0.01864425 0.00015365 ‐6.50 ‐5.17

GP2‐CA‐38 587.5 7751.096 0.671495 26.94743 61.9676295 0.010123 9.901479 0.009679 0.025833 MG‐c15 588.1 0.01881613 0.00015107 ‐6.38 ‐5.16

GP2‐CA‐39 587.4 7484.523 0.577346 26.00643 66.3137919 0.008974 11.00386 0.009595 0.029115 MG‐c16 588.2 0.01935679 0.00014896 ‐6.14 ‐4.96

GP2‐CA‐40 587.3 7317.347 0.513924 25.96914 66.7879545 0.012706 11.18432 0.01005 0.029952 MG‐c17 588.3 0.01944708 0.00014953 ‐6.04 ‐4.94

GP2‐CA‐41 587.2 7826.201 0.538545 24.78201 69.6425591 0.009858 11.76801 0.01039 0.027325 MG‐c18 588.4 0.01956212 0.00015152 ‐5.91 ‐4.90

GP2‐CA‐42 587.1 8350.779 0.537213 22.39317 65.0167788 0.009093 11.22379 0.010885 0.022079 MG‐c19 588.5 0.01947341 0.00015035 ‐5.93 ‐4.96

GP2‐CA‐43 587 8728.486 0.516057 21.63145 67.4647996 0.003124 11.54727 0.007418 0.021351 MG‐c20 588.6 0.01963255 0.00014864 ‐5.76 ‐4.87

GP2‐CA‐44 586.9 9052.035 0.55956 21.02567 66.7079927 0.002716 11.00568 0.005274 0.021119 MG‐c21 588.7 0.01985561 0.00014833 ‐5.65 ‐4.80

GP2‐CA‐45 586.8 9575.724 0.560627 17.53115 67.4707571 #DIV/0! 11.31694 0.00683 0.018025 MG‐c22 588.8 0.0200975 0.00015202 ‐5.53 ‐4.69

GP2‐CA‐46 586.7 9240.872 0.612089 20.24205 63.9363763 0.002864 10.64457 0.005603 0.019797 MG‐c23 588.9 0.02019732 0.00015412 ‐5.43 ‐4.70

GP2‐CA‐47 586.6 8852.727 0.597581 24.43035 68.2085404 0.008799 10.38413 0.012346 0.019141 MG‐c24 589 0.02025066 0.00015747 ‐5.31 ‐4.82

GP2‐CA‐48 586.5 8338.788 0.663827 26.87285 84.0111947 0.017506 11.3821 0.011148 0.374543 MG-c25 589.1 ‐5.27 ‐4.82

GP2‐CA‐49 586.4 6437.168 0.624107 28.57801 89.7603834 0.032665 10.9995 0.01659 0.689273 MG‐c26 589.2 0.02015769 0.00015632 ‐5.25 ‐4.83

GP2‐CA‐50 586.3 1254.914 0.746019 29.74084 452.061346 0.03022 23.24185 0.026423 3.131508 MG‐c27 589.3 0.01947757 0.00015066 ‐5.17 ‐4.80

GP2‐CA‐51 586.2 73.27791 0.115827 28.33376 506.857008 0.02517 30.71117 0.01731 3.149286 MG‐c28 589.4 0.01928872 0.00014908 ‐5.30 ‐4.84

GP2‐CA‐52 586.1 37.65814 0.08328 28.91095 533.669006 0.025081 33.72428 0.01805 3.017513 589.5 ‐5.53 ‐4.64

GP2‐CA‐53 586 36.11936 0.077828 30.49685 531.83753 0.028155 32.78977 0.020696 3.221133 591 ‐4.62 ‐4.74

GP2‐CA‐54 585.9 37.58454 0.075895 33.19345 537.897393 0.03383 33.18601 0.02084 3.353151 592 ‐4.93 ‐4.74

GP2‐CA‐55 585.8 39.43438 0.089326 35.72969 527.242696 0.036848 32.93875 0.022291 3.593391

GP2‐CA‐56 585.7 36.60633 0.105773 38.23582 525.359282 0.039592 31.18781 0.023116 3.570118

GP2‐CA‐57 585.6 28.12251 0.130246 37.72677 535.106891 0.041905 30.32905 0.023826 3.670961

GP2‐CA‐58 585.5 35.45633 0.243707 34.51186 527.986954 0.02892 28.97406 0.031675 3.149244

GP2‐CA‐59 585.4 36.17043 0.18165 31.60069 527.463105 0.016227 29.53965 0.023341 2.750882

GP2‐CA‐60 585.3 36.14341 0.221855 29.01134 534.405038 0.01477 30.2681 0.02156 2.735797

GP2‐CA‐61 585.2 34.49224 0.108947 27.61366 525.641343 0.016797 30.90418 0.021834 2.676491

GP2‐CA‐62 585.1 35.32815 0.115873 27.28874 519.898971 0.012285 30.95577 0.016107 2.527499

GP2‐CA‐63 585 38.32771 0.229688 27.33426 513.033438 0.012838 32.14846 0.016678 2.542418

GP2‐CA‐64 584.9 38.65029 0.147446 26.45053 519.239047 0.012162 32.97035 0.012406 2.465427

GP2‐CA‐65 584.8 36.67296 0.086477 26.4056 510.557636 0.010746 32.94634 0.010831 2.417297

GP2‐CA‐66 584.7 34.48702 0.112633 26.54248 519.039519 0.010902 33.79681 0.010301 2.345966

GP2‐CA‐67 584.6 32.15984 0.066176 26.80402 515.020753 0.009044 33.07936 0.00922 2.270125

GP2‐CA‐68 584.5 30.14262 0.094203 27.67432 512.869376 0.006782 31.74363 0.008868 2.123445

GP2‐CA‐69 584.4 29.88117 0.101968 32.06535 515.502517 0.006946 31.99983 0.008503 2.226693

GP2‐CA‐70 584.3 31.17358 0.505641 39.72022 526.166958 0.010175 32.62526 0.010596 2.370296

GP2‐CA‐71 584.2 31.05053 0.486654 39.8819 517.895923 0.011593 32.7394 0.011087 2.381565

GP2‐CA‐72 584.1 32.47615 0.141578 35.33797 513.788701 0.015897 33.66335 0.01499 2.369824

GP2‐CA‐73 584 34.17133 0.112917 32.40945 511.173373 0.017529 34.75329 0.01654 2.429389

GP2‐CA‐74 583.9 34.8064 0.27475 35.25655 506.748695 0.013014 34.91126 0.009299 2.17434

GP2‐CA‐75 583.8 36.87369 3.072593 39.20099 500.325908 0.00934 33.5706 0.013486 1.96259

GP2‐CA‐76 583.7 34.08297 0.167537 36.17258 503.866705 0.007534 34.62179 0.011617 2.039527

GP2‐CA‐77 583.6 33.81214 0.137038 35.86115 491.425697 0.006662 33.24004 0.009517 1.857163

GP2‐CA‐78 583.5 33.93609 0.162672 31.60643 490.74944 0.00649 33.64315 0.010344 1.684357

GP2‐CA‐79 583.4 34.57943 0.175083 30.50186 485.318203 0.007465 33.16054 0.008281 1.477716

GP2‐CA‐80 583.3 34.25848 0.120559 30.65798 487.046489 0.006084 33.12771 0.010972 1.287949

GP2‐CA‐81 583.2 34.77215 0.138859 30.60586 482.113589 0.007248 33.73671 0.010181 1.376785

GP2‐CA‐82 583.1 34.07554 0.120419 29.95555 472.706374 0.007015 32.95304 0.008206 1.233943

GP2‐CA‐83 583 34.43796 0.153753 31.9247 473.252936 0.007174 33.55123 0.012002 1.183595

GP2‐CA‐84 582.9 33.56391 0.148626 29.81553 468.494035 0.006153 32.01257 0.008174 1.065194

GP2‐CA‐85 582.8 33.73105 0.121134 28.5466 465.918782 0.006516 32.5555 0.009752 1.112296

GP2‐CA‐86 582.7 34.80304 0.150644 29.80627 465.961882 0.005955 32.97567 0.010014 1.119932

GP2‐CA‐87 582.6 34.68455 0.176793 31.32529 463.746331 0.005669 32.79077 0.008764 1.105728

GP2‐CA‐88 582.5 34.42791 0.17439 29.99703 458.260955 0.005225 32.69904 0.008611 1.091763

GP2‐CA‐89 582.4 34.70536 0.20626 32.6572 469.674635 0.005955 34.31194 0.009787 1.167009

GP2‐CA‐90 582.3 35.05806 0.236755 30.29988 462.547112 0.0064 34.01847 0.011187 1.117222

GP2‐CA‐91 582.2 32.66295 0.153875 21.13923 456.689408 0.0044 31.79643 0.012687 0.867905

GP2‐CA‐92 582.1 31.93145 0.075162 21.8828 449.707576 0.004721 31.02218 #DIV/0! 0.656115

GP2‐CA‐93 582 34.0579 0.076041 17.07134 430.988443 0.004835 31.78078 0.012389 0.604097

GP2‐CA‐94 581.9 34.78988 0.177175 17.4917 426.516717 0.00423 32.23562 0.009853 0.663522

GP2‐CA‐95 581.8 34.62487 0.122474 20.36287 424.455161 0.004797 31.53506 0.012091 0.550641

GP2‐CA‐96 581.7 35.29455 0.147217 19.90916 430.008233 0.003871 32.41765 0.010362 0.532381

GP2‐CA‐97 581.6 35.11766 0.091406 22.95782 433.851794 0.003654 33.01992 0.01162 0.667441

GP2‐CA‐98 581.5 34.38265 0.080516 22.55359 427.191686 0.005141 31.90715 0.011737 0.614263

GP2‐CA‐99 581.4 34.12233 0.169637 28.02286 435.321706 0.007027 31.89033 0.011835 0.75223

GP2‐CA‐100 581.3 34.03337 0.128839 23.62306 435.96193 0.005731 32.22941 0.013153 0.788058

GP2‐CA‐101 581.2 34.0435 0.119912 25.67462 441.972903 0.007987 33.69157 0.010574 0.980447

LA‐ICP‐MS Micro‐mill / ICP‐OES

Appendix Chapter 5. U‐Th ages and 14C derived age stalagmite GP5

sample comments Age (ka BP 2010) ± min-Age max-Age U238 ± Th232 ± Th230 ± Th230/Th232 ± U238/Th232 ± Th230/U238 ± Th230excess/U238 ± U234/U238 ± U234/U238initialGP5 U4 Dated in 2010 0.1672 0.0015 0.1657 0.1687 4.5317 0.0034 1.1582 0.0019 0.6586 0.0052 106.1735 0.8502 12111.2572 21.7592 0.0088 0.0001 0.0087 0.0001 5.6974 0.0056 5.6996GP5 U3.3 Dated in 2010 0.1137 0.0007 0.1131 0.1144 2.9749 0.0017 0.4792 0.0036 0.3000 0.0015 116.8920 1.0499 19216.3536 144.2610 0.0061 0.0000 0.0061 0.0000 5.8140 0.0042 5.8155

GP5 U3.2 Dated in 2010 0.2512 0.0007 0.2506 0.2519 3.7441 0.0017 0.0911 0.0102 0.8296 0.0016 1699.8442 191.0191 127193.2593 14291.4083 0.0134 0.0000 0.0134 0.0000 5.8118 0.0036 5.8152

GP5 U3.1 Dated in 2010 0.6287 0.0016 0.6272 0.6303 2.2995 0.0009 0.0640 0.0104 1.2293 0.0023 3588.4222 583.5499 111285.9189 18096.2265 0.0322 0.0001 0.0322 0.0001 5.6113 0.0031 5.6195

GP5 U3.0 Dated in 2010 0.7407 0.0029 0.7379 0.7436 3.2660 0.0028 0.1607 0.0035 1.9416 0.0048 2255.5977 49.4616 62903.7170 1371.7968 0.0359 0.0001 0.0358 0.0001 5.2981 0.0057 5.3071

GP5 U3 Dated in 2010 1.0125 0.0065 1.0060 1.0191 4.0034 0.0016 0.1332 0.0052 3.6001 0.0210 5044.4712 197.3898 93001.2044 3598.6576 0.0542 0.0003 0.0542 0.0003 5.8693 0.0033 5.8833

GP5 U2.5 Dated in 2010 1.1918 0.0055 1.1863 1.1972 3.8204 0.0030 0.8118 0.0042 4.1864 0.0140 962.9011 5.8790 14567.8539 75.3952 0.0661 0.0002 0.0661 0.0002 6.0770 0.0062 6.0942

GP5 U2.4 Dated in 2010 1.3909 0.0026 1.3883 1.3934 3.1552 0.0012 0.2200 0.0085 3.9303 0.0049 3335.6315 129.3756 44394.9433 1721.1070 0.0751 0.0001 0.0751 0.0001 5.9258 0.0029 5.9452

14C derived age0.2mm depth from top 0.0460

Appendix Chapter 5. Trace elements stalagmite GP5

Sample nr. Depth "R" Age (kyr) BP (2010) Recent4 MG25 Sr86(LR) Ba137(LR) Sample nr. Age (AD) Lineair interpol. Mg25 Sr86 Ba137GP5_4C_191‐00191.asc 0.6 0.048171157 63.78450663 419.3186664 29.01767896 GP5A‐4B‐77‐0077.asc 1324.09 62.63463704 371.9134418 29.19976469

GP5_4C_190‐00190.asc 1.7 0.053079979 83.13098886 435.2153637 37.66199766 GP5A‐4B‐76‐0076.asc 1323.5 55.97500363 377.7275723 26.06535791

GP5_4C_189‐00189.asc 2.6 0.057105175 58.47118971 410.1634499 30.55262426 GP5A‐4B‐75‐0075.asc 1322.91 61.06937002 367.8528598 29.1589187

GP5_4C_188‐00188.asc 3.7 0.062000663 123.0138597 439.4303813 39.95262212 GP5A‐4B‐74‐0074.asc 1322.32 61.10922967 375.3143813 28.22220921

GP5_4C_187‐00187.asc 4.5 0.065514782 76.30105652 408.5272717 33.14668739 GP5A‐4B‐73‐0073.asc 1321.73 64.68637364 346.0029402 29.29215426

GP5_4C_186‐00186.asc 5.5 0.0698521 82.74463941 389.2956936 30.21501932 GP5A‐4B‐72‐0072.asc 1321.14 64.33749023 398.6798632 28.5715304

GP5_4C_185‐00185.asc 6.5 0.074181618 73.51848411 394.2298392 32.34879511 GP5A‐4B‐71‐0071.asc 1320.55 67.02428412 356.2875331 29.08792802

GP5_4C_184‐00184.asc 7.7 0.07933859 70.74151412 410.9536847 31.81549043 GP5A‐4B‐77‐0077.asc 1319.96 67.19247234 366.7079326 29.20113339

GP5_4C_183‐00183.asc 8.7 0.083444561 82.29520642 321.0232307 32.46845476 GP5A‐4B‐69‐0069.asc 1319.36 60.52980367 398.9318909 28.46404373

GP5_4C_182‐00182.asc 9 0.084626415 84.68335 380.7530308 33.00709265 GP5A‐4B‐68‐0068.asc 1318.77 56.1425344 387.1453291 26.67144597

GP5_4C_181‐00181.asc 10 0.088397033 70.37958203 454.1192912 29.16350439 GP5A‐4B‐67‐0067.asc 1318.18 48.72693079 411.9739474 24.58369216

GP5_4C_180‐00180.asc 11 0.091928683 77.13814625 472.5590156 28.00575705 GP5A‐4B‐66‐0066.asc 1317.59 46.21295041 417.0409861 22.02748646

GP5_4C_179‐00179.asc 12 0.095388891 90.59688541 397.0323865 31.66182109 GP5A‐4B‐65‐0065.asc 1317 52.22666851 441.926751 24.36824943

GP5_4C_178‐00178.asc 13.1 0.099373248 77.65485546 437.5218839 31.96351732 GP5A‐4B‐64‐0064.asc 1316.41 40.98185925 441.6663503 23.03930452

GP5_4C_177‐00177.asc 14 0.102887048 112.2144492 441.0060704 31.73032951 GP5A‐4B‐63‐0063.asc 1315.82 50.07967896 481.6434375 25.96320801

GP5_4C_176‐0047.asc 15 0.107118708 90.16793016 397.5719463 30.87900402 GP5A‐4B‐62‐0062.asc 1315.23 52.29399293 469.3202356 25.45882912

GP5_4C_175‐0046.asc 16 0.111572686 93.24958498 355.1340745 30.16402567 GP5A‐4B‐61‐0061.asc 1314.64 51.94267418 482.3835117 25.53062294

GP5_4C_174‐0045.asc 17.3 0.117411922 125.0229727 382.0263705 32.17997658 GP5A‐4B‐60‐0060.asc 1314.05 53.77028511 461.8802221 26.14976943

GP5_4C_173‐0044.asc 18.3 0.12190991 114.0815455 436.4037573 34.31740644 GP5A‐4B‐59‐0059.asc 1313.45 49.72810295 405.8773798 24.02600749

GP5_4C_172‐0043.asc 19.3 0.126417134 95.82800106 453.4668626 29.93857274 GP5A‐4B‐58‐0058.asc 1312.86 53.46563662 383.3574094 25.01067012

GP5_4C_171‐0042.asc 20.3 0.130858373 83.94422776 386.9327603 27.82139285 GP5A‐4B‐57‐0057.asc 1312.27 71.6371375 366.3415112 29.07221698

GP5_4C_170‐0041.asc 21.3 0.135210383 88.46268233 384.4817876 29.18683733 GP5A‐4B‐56‐0056.asc 1311.68 76.40374822 352.1273879 28.48912165

GP5_4C_169‐0040.asc 22.3 0.139646366 72.68968983 448.7860189 29.90227545 GP5A‐4B‐55‐0055.asc 1311.09 73.46119158 364.0069732 27.62361981

GP5_4C_168‐0039.asc 23.3 0.144291965 79.31573015 479.5397996 26.96145384 GP5A‐4B‐54‐0054.asc 1310.5 71.50187489 349.2216177 27.62125685

GP5_4C_167‐0038.asc 24.3 0.149023617 69.16391569 486.9702441 24.99509208 GP5A‐4B‐53‐0053.asc 1309.91 72.23866889 336.7543092 28.51341498

GP5_4C_166‐0037.asc 25.3 0.153731164 65.11692732 420.1402909 28.91976489 GP5A‐4B‐52‐0052.asc 1309.32 66.77099903 408.5174004 28.31341782

GP5_4C_165‐0036.asc 26.3 0.15848116 99.11154633 433.8397916 33.00553969 GP5A‐4B‐51‐0051.asc 1308.73 53.16056299 364.5268545 26.78589294

GP5_4C_164‐0035.asc 27.3 0.163314727 78.02064224 426.5938776 30.88715128 GP5A‐4B‐50‐0050.asc 1308.14 58.02553724 370.0877831 27.84436934

GP5_4C_163‐0034.asc 28.3 0.168100364 83.31186817 423.5466266 29.68855208 GP5A‐4B‐49‐0049.asc 1307.54 61.62425861 462.5534089 31.28398967

GP5_4C_162‐0033.asc 29.2 0.172294272 118.1106065 365.9222867 33.58738777 GP5A‐4B‐48‐0048.asc 1306.95 57.02305274 494.0175727 31.32847649

GP5_4C_161‐0032.asc 30.2 0.176980033 76.48658789 399.0767722 33.92176069 GP5A‐4B‐47‐0047.asc 1306.36 56.58961957 506.1621248 30.90901403

GP5_4C_160‐0031.asc 31.2 0.181828115 73.51523957 448.015544 31.17468803 GP5A‐4B‐46‐0046.asc 1305.77 52.42601403 503.5270497 28.51030132

GP5_4C_159‐0030.asc 32.2 0.186689106 79.30877617 436.5002636 32.68212474 GP5A‐4B‐45‐0045.asc 1305.18 51.19380318 537.053638 29.88066409

GP5_4C_158‐0029.asc 33.2 0.191409691 78.01094328 469.6668784 31.23102471 GP5A‐4B‐44‐0044.asc 1304.59 49.65796466 512.252443 29.03843553

GP5_4C_157‐0028.asc 34.2 0.19611261 81.70704288 454.0545072 30.71131016 GP5A‐4B‐43‐0043.asc 1304 53.02321339 461.3374045 27.73831545

GP5_4C_156‐0027.asc 35.2 0.200936728 88.17058248 512.3109797 33.65971493 GP5A‐4B‐42‐0042.asc 1303.41 59.48263745 464.0474865 29.20953041

GP5_4C_155‐0027.asc 36.2 0.20580936 70.00028177 478.9875499 33.25474485 GP5A‐4B‐41‐0041.asc 1302.82 68.41362322 445.0140632 29.78824007

GP5_4C_154‐0026.asc 37.2 0.210633524 54.36215758 444.870849 28.79071777 GP5A‐4B‐40‐0040.asc 1302.23 77.271835 419.3099798 32.28307077

GP5_4C_153‐0025.asc 38.2 0.215426588 59.50271061 458.5318246 32.27164564 GP5A‐4B‐39‐0039.asc 1301.63 71.5050561 371.5032551 31.50645087

GP5_4C_152‐0024.asc 39.2 0.220231639 91.95015419 453.7025239 30.98629579 GP5A‐4B‐38‐0038.asc 1301.04 83.43741886 406.031399 30.29587654

GP5_4C_151‐0023.asc 40.3 0.225568636 60.65777938 476.3366078 29.18635134 GP5A‐4B‐37‐0037.asc 1300.45 72.85561277 406.7182225 29.79942967

GP5_4C_150‐0022.asc 41.2 0.229989265 61.90857177 501.0304476 30.99697744 GP5A‐4B‐36‐0036.asc 1299.86 82.52422469 432.5185896 31.74266056

GP5_4C_149‐0021.asc 42.2 0.23492742 57.79051455 479.4310293 31.28061242 GP5A‐4B‐35‐0035.asc 1299.27 78.14105631 415.018256 32.356808

GP5_4C_148‐0020.asc 43.2 0.239866801 59.69268337 504.3072793 29.26690941 GP5A‐4B‐34‐0034.asc 1298.68 82.2905616 477.9927743 34.02920274

GP5_4C_147‐0019.asc 44.2 0.244840304 104.2164565 519.6706953 33.40951022 GP5A‐4B‐33‐0033.asc 1298.09 82.61878043 490.9495649 30.90403096

GP5_4C_146‐0018.asc 45.2 0.249870899 84.64692999 437.6906135 33.58984275 GP5A‐4B‐32‐0032.asc 1297.5 81.25500977 452.180307 32.54164287

GP5_4C_145‐0017.asc 46.2 0.254881009 44.74847141 513.6134158 26.11601534 GP5A‐4B‐31‐0031.asc 1296.91 78.87588316 405.7638158 32.85003137

GP5_4C_144‐0016.asc 47.2 0.259810252 90.32520835 418.0302074 34.86024055 GP5A‐4B‐30‐0030.asc 1296.32 89.17276639 450.473225 34.39375665

GP5_4C_143‐0015.asc 48.2 0.264767569 85.32149694 415.8967456 33.23794857 GP5A‐4B‐29‐0029.asc 1295.72 98.51568696 357.1441784 35.86648376

GP5_4C_142‐0014.asc 48.7 0.26729894 73.62938353 475.6293213 34.57272271 GP5A‐4B‐28‐0028.asc 1295.13 102.4487897 335.6512501 33.62053084

GP5_4B_141‐0013.asc 50.4 0.27608465 66.05828416 479.4558997 32.32848893 GP5A‐4B‐27‐0027.asc 1294.54 98.25009425 350.025246 33.68243389

GP5_4B_140‐0012.asc 50.8 0.278161453 58.82206421 469.943774 28.69285283 GP5A‐4B‐26‐0026.asc 1293.95 86.50540516 327.4974557 32.3081306

GP5_4B_139‐0011.asc 51.5 0.281793603 42.91329395 464.8430804 23.49993825 GP5A‐4B‐25‐0025.asc 1293.36 76.79530861 321.0657358 28.53667425

GP5_4B_138‐0010.asc 52.7 0.288015146 83.89923237 388.6056755 32.13646036 GP5A‐4B‐24‐0024.asc 1292.77 83.29806477 316.8566702 29.55409921

GP5_4B_137‐009.asc 53.6 0.292693355 59.82747556 455.7342213 26.05061887 GP5A‐4B‐23‐0023.asc 1292.18 83.0654823 277.8968734 31.41642924

GP5_4B_136‐008.asc 54.4 0.296884806 43.3665486 441.0980035 23.4965579 GP5A‐4B‐22‐0022.asc 1291.59 76.52097021 276.9915513 28.33664842

GP5_4B_135‐007.asc 55.4 0.302190405 77.72483665 407.3629279 31.90476392 GP5A‐4B‐21‐0021.asc 1291 94.83376245 272.672737 30.48930178

GP5‐4B‐134 55.9 0.3048735 72.29658805 458.2459754 31.36351227 GP5A‐4B‐20‐0020.asc 1290.41 88.01465255 278.3849957 32.10456506

GP5‐4B‐133 56.9 0.310300348 85.85932392 476.4298915 34.18607599 GP5A‐4B‐19‐0019.asc 1289.82 80.29415586 318.6266933 28.74625021

GP5‐4B‐132 57.8 0.315218894 85.12682037 512.1582174 34.87621403 GP5A‐4B‐18‐0018.asc 1289.22 75.40699716 338.0606318 30.96115707

GP5‐4B‐131 58.8 0.320660551 56.91136074 473.6778531 30.37923505 GP5A‐4B‐17‐0017.asc 1288.63 74.31910682 303.7316387 31.19850221

GP5‐4B‐130 59.8 0.326058126 72.72127921 442.96276 33.35253991 GP5A‐4B‐16‐0016.asc 1288.04 68.17573457 347.4775896 31.66606867

GP5‐4B‐129 60.8 0.331426377 67.915888 443.6008785 28.90131428 GP5A‐4B‐15‐0015.asc 1287.45 55.57302318 343.459996 26.9487116

GP5‐4B‐128 61.8 0.336795158 84.93001138 482.1563397 31.4736945 GP5A‐4B‐14‐0014.asc 1286.86 53.3232871 319.7295354 28.9246697

GP5‐4B‐127 62.7 0.341658614 66.40692162 461.1306966 30.87654632 GP5A‐4B‐13‐0013.asc 1286.27 57.97881663 289.8580872 28.671489

GP5‐4B‐126 63.7 0.347073755 76.71925205 420.8199897 33.56937111 GP5A‐4B‐12‐0012.asc 1285.68 77.63671575 294.9236217 32.33506583

GP5‐4B‐125 64.7 0.352425317 78.46073308 411.1202567 35.37086776 GP5A‐4B‐11‐0011.asc 1285.09 83.02256294 267.499978 33.12711714

GP5‐4B‐124 65.7 0.357707645 75.59289618 441.1823658 35.41686344 GP5A‐4B‐10‐0010.asc 1284.5 73.02421939 279.8849827 29.29454814

GP5‐4B‐123 66.7 0.36298731 123.1417098 474.445679 36.29604708 GP5A‐4B‐9‐009.asc 1283.91 91.65994326 261.6230315 30.01235308

GP5‐4B‐122 67.7 0.36829025 50.79484465 468.7907229 26.00962557 GP5A‐4B‐8‐008.asc 1283.31 84.09044003 234.9448838 30.35052733

GP5‐4B‐121 68.6 0.373067908 92.55219365 439.9557035 36.92853158 GP5A‐4B‐7‐007.asc 1282.72 83.02423351 270.0398168 29.85402205

GP5‐4B‐120 69.6 0.378358456 64.64951955 441.5895491 30.14014314 GP5A‐4B‐6‐006.asc 1282.13 56.51758525 306.7311169 31.3532646

GP5‐4B‐119 70.6 0.383599793 76.24033273 452.5627913 35.15044916 GP5A‐4B‐5‐005.asc 1281.54 93.21464768 280.8577581 31.72498209

GP5‐4B‐118 71.6 0.388788451 79.9127675 441.955567 33.63983387 GP5A‐4B‐4‐004.asc 1280.95 86.06246631 327.31137 30.02715239

GP5‐4B‐117 72.6 0.393957275 84.21244652 466.0078157 34.041607 GP5A‐4B‐3‐003.asc 1280.36 81.92769818 293.7380062 30.03658545

GP5‐4B‐116 73.5 0.398610641 102.6381033 449.5981682 36.33323053 GP5A‐4B‐2‐002.asc 1279.77 74.08829748 302.7476795 31.58622322

GP5‐4B‐115 74.5 0.403786234 91.44047245 488.7928311 34.12111352 GP5A‐4B‐1‐001.asc 1279.18 104.3821047 277.4796702 34.92129969

GP5‐4B‐114 75.4 0.408444279 87.32409479 471.7603581 31.40830736

GP5‐4B‐113 76.5 0.414115022 82.19489962 442.6104876 33.87012584

GP5‐4B‐112 77.5 0.419245889 78.03879242 420.4839118 34.19411156

GP5‐4B‐111 78.7 0.425417088 114.7657105 429.8504629 37.73834286

GP5‐4B‐110 79.6 0.430072907 90.62061028 467.8121366 30.33438152

GP5‐4B‐109 80.6 0.435268474 72.03926496 456.7304568 27.04594936

GP5‐4B‐108 81.6 0.440479015 91.26350388 443.7215024 33.14634937

GP5‐4B‐107 82.6 0.445693342 58.73566589 402.471439 27.72461571

GP5‐4B‐106 83.6 0.450900801 119.0446723 394.5862007 37.69821491

GP5‐4B‐105 84.6 0.45609202 157.691225 477.4139925 35.82762483

GP5‐4B‐104 85.6 0.461272454 118.6010468 449.2787526 38.06685686

GP5‐4B‐103 86.6 0.466466279 125.5885604 476.8346999 33.68539532

GP5‐4B‐102 87.6 0.471680898 122.4157594 436.4428533 34.5735406

GP5‐4B‐101 88.6 0.476900261 99.14841837 451.2299372 35.91304105

GP5‐4B‐100 89.6 0.482106601 88.42886178 403.0833476 36.49673097

GP5‐4B‐99 90.6 0.487282831 103.724834 441.7925126 34.76281606

GP5‐4B‐98 91.6 0.492445761 93.82732183 457.7745188 36.76803477

GP5‐4B‐97 92.6 0.497654489 65.84373712 465.2378417 29.09588681

GP5‐4B‐96 93.6 0.502902682 84.60395339 454.2931455 31.33295823

GP5‐4B‐95 94.5 0.507582277 96.87282226 493.7110859 29.11864418

GP5‐4B‐94 95.5 0.512715537 97.14723354 461.3036155 31.71399941

GP5‐4B‐93 96.3 0.516838434 114.2669558 526.6650395 35.3034484

GP5‐4B‐92 97.3 0.522065153 110.9114847 505.7688683 30.1836624

GP5‐4B‐91 98.3 0.527316409 99.04982865 510.6959172 32.34149976

"Coarse resolution" "High" resolution

GP5‐4B‐90 99.3 0.532539244 110.3751077 447.606711 34.1087309

GP5‐4B‐89 100.3 0.537751725 104.9158656 465.9340034 31.27179703

GP5‐4B‐88 101.3 0.542975009 96.75573704 464.311204 32.18782364

GP5‐4B‐87 101.7 0.545065712 109.5145214 404.1161736 35.64643667

GP5‐4B‐86 102.7 0.550289055 70.90912149 453.5684694 30.40855618

GP5‐4B‐85 103.7 0.555521369 104.6075676 443.2534041 33.96208299

GP5‐4B‐84 104.7 0.560796411 113.7656189 488.9232694 34.12076659

GP5‐4B‐83 105.7 0.566095973 128.7679036 446.259091 36.04830002

GP5‐4B‐82 106.7 0.57135182 105.8896965 463.9797823 35.95575263

GP5‐4B‐81 107.7 0.576562465 137.9872668 379.287989 36.7737774

GP5‐4B‐80 108.7 0.581793227 103.0083569 419.9299725 34.73142878

GP5‐4B‐79 109.6 0.586533235 90.02791022 348.2983665 32.59276714

GP5‐4B‐78 110.7 0.592330691 110.0896262 422.9793495 34.97811576

GP5‐4B‐77 111.7 0.597592892 94.89679333 396.8820583 35.16053654

GP5‐4B‐76 112.7 0.602861856 116.9200572 373.8606714 38.27002098

GP5‐4B‐75 113.7 0.60813268 98.09040333 341.7665222 34.05727258

GP5‐4B‐74 114.7 0.613381551 113.6546987 401.3075006 37.38687738

GP5‐4B‐73 115.7 0.618623132 424.3809412 37.47492667

GP5‐4B‐72 116.7 0.62390961 136.5002303 372.9427133 33.03511053

GP5‐4B‐71 117.7 0.629252419 82.38595055 364.7271053 30.32345368

GP5‐4B‐70 118.7 0.63462198 103.2702622 336.8241824 35.43574322

GP5‐4B‐69 119.7 0.640020287 95.42129716 346.6470601 35.34723711

GP5‐4B‐68 120.7 0.645482117 99.81976316 402.1063436 32.70762812

GP5‐4B‐67 121.7 0.651029041 59.87036572 423.8682228 27.81095213

GP5‐4B‐66 122.7 0.656666637 56.41496792 478.3818747 28.19307437

GP5‐4B‐65 123.7 0.662369098 75.90211417 442.8654522 31.40070792

GP5‐4B‐64 124.7 0.668081773 60.68413674 460.87716 28.01568936

GP5‐4B‐63 125.7 0.673792513 63.22477413 460.0672652 29.97216514

GP5‐4B‐62 126.7 0.679531041 49.47920375 452.9897811 24.28985034

GP5‐4B‐61 127.7 0.68528382 54.69604167 431.8204991 27.2807378

GP5‐4B‐60 128.7 0.690993222 55.5335536 427.7491185 27.66276297

GP5‐4B‐59 129.7 0.696624452 76.39128271 363.2988972 31.21751013

GP5‐4B‐58 130.7 0.702168642 95.10926493 394.9149664 27.43217007

GP5‐4B‐57 131.7 0.70764414 86.9861392 403.0864935 35.36985166

GP5‐4B‐56 132.7 0.713091277 70.81203099 438.4429351 33.80213599

GP5‐4B‐55 133.7 0.718456007 80.23062498 417.3788614 30.69948355

GP5‐4B‐54 134.7 0.723607759 84.36855193 341.5120797 33.36019513

GP5‐4B‐53 135.7 0.72884849 100.5277145 330.536302 32.45059991

GP5‐4B‐52 136.7 0.734875952 96.99996299 339.2114454 36.28984138

GP5‐4B‐51 137.7 0.741466504 99.39625201 304.9711439 34.12348684

GP5‐4B‐50 138.7 0.74749849 114.5381946 307.1577629 33.74037302

GP5‐4B‐49 139.7 0.752783691 164.1126378 392.0980505 38.8662832

GP5‐4B‐48 140.7 0.758085232 101.457707 367.4632893 37.30879865

GP5‐4B‐47 141.7 0.763680097 128.9104075 389.9297563 34.17624971

GP5‐4B‐46 142.6 0.768765304 107.2527849 385.26165 35.71865085

GP5‐4B‐45 143.6 0.774467188 101.7673861 396.7607249 31.9170931

GP5‐4B‐44 144.6 0.78053166 104.5193225 358.2170403 30.88460596

GP5‐4B‐43 145.6 0.788077765 93.38843106 382.3513496 34.55718525

GP5‐4B‐42 146.7 0.800504452 89.77400842 353.7640671 34.30560064

GP5‐4B‐41 147.7 0.814507552 123.4433353 348.5997257 33.11397779

GP5‐4B‐40 148.7 0.82667081 82.7365074 360.2251757 32.03992278

GP5‐4B‐39 149.7 0.835871411 121.9225839 346.6072749 31.50556735

GP5‐4B‐38 150.7 0.84427564 87.93667683 374.6594763 32.51312334

GP5‐4B‐37 151.7 0.852723438 115.8645724 386.7292649 34.79960577

GP5‐4B‐36 152.7 0.860607652 109.2107508 380.2920974 34.85042411

GP5‐4B‐35 153 0.862824048 79.04668162 358.5841704 29.03691428

GP5‐4B‐34 154 0.869942626 75.14831716 383.5709726 30.31176764

GP5‐4B‐33 155 0.876979911 53.70251202 413.1872244 26.95172059

GP5‐4B‐32 156.1 0.884679615 90.27516989 449.7226988 28.49558523

GP5‐4B‐31 157 0.890854227 62.48088789 417.917541 27.3802419

GP5‐4B‐30 158 0.897656465 77.18209066 434.4526783 29.04335519

GP5‐4B‐29 159 0.904524957 98.69217302 411.6646893 28.44635629

GP5‐4B‐28 160 0.911456841 88.0540977 457.5164065 29.70338255

GP5‐4B‐27 161 0.918393145 92.76312678 430.8570069 30.04836631

GP5‐4B‐26 162 0.92530959 97.57579532 376.5219476 30.61062367

GP5‐4B‐25 163 0.932201119 125.9508415 356.34036 31.41726522

GP5‐4B‐24 163.7 0.937021054 136.7862465 475.2892256 36.24058604

GP5‐4B‐23 165 0.945997675 102.0073416 408.6267548 32.19659199

GP5‐4B‐22 166 0.952888253 89.88481617 388.4778684 32.14863137

GP5‐4B‐21 167 0.959708631 86.50926655 339.0488124 32.63435625

GP5‐4B‐20 168 0.966519037 108.8791139 330.203455 33.07813611

GP5‐4B‐19 168.9 0.972718979 91.91841093 354.6594631 31.35926116

GP5‐4B‐18 170 0.9803431 91.85709917 386.4591007 31.07495022

GP5‐4B‐17 170.9 0.986537067 94.97035613 424.5785498 34.43627903

GP5‐4B‐16 172 0.994055773 73.07393416 422.0081972 27.8606186

GP5‐4B‐15 173 1.00088978 86.66938997 416.5003754 29.80793702

GP5‐4B‐14 173.9 1.007044628 114.4739844 295.2386916 31.72938171

GP5‐4B‐13 174.8 1.013193801 73.72335361 324.9240229 31.60091349

GP5‐4B‐12 175.9 1.020710737 64.65636179 448.9085532 27.71133799

GP5‐4B‐10 176.6 1.025506127 89.55404762 394.428078 29.8233638

GP5‐4B‐11 177 1.028250198 65.87940722 477.3975128 26.26267252

GP5‐4B‐9 177.6 1.032365659 76.91101432 388.6677568 28.88436403

GP5‐4B‐8 178.4 1.037839804 56.02686676 427.8514524 27.08422615

GP5‐4B‐7 180 1.048749869 69.52883686 452.4992816 24.63632058

GP5‐4B‐6 182.6 1.066576472 69.52732012 452.4898634 24.63746251

Hiatus 182.7 1.067262024

GP5‐4B‐4 183.2 1.1131 95.17019307 413.0128658 29.41659799

GP5‐4B‐3 184.1 1.12755 77.04210288 397.3836642 29.22380646

GP5‐4B‐2 185.9 1.15645 57.48868726 404.9291771 28.41007356

GP5‐4B‐1 186.9 1.17251 59.59383866 422.8973842 31.43334266

GP5_4B_‐1‐006.asc 187.1 1.17572 49.58760402 414.5119421 25.04531508

GP5_4B_‐2‐005.asc 188.3 1.19499 51.43979074 513.4792232 27.65144117

GP5_4B_‐3‐004.asc 189.3 1.21104 48.01549925 514.3909096 26.79892481

GP5_4B_‐4‐003.asc 190 1.22228 62.1549654 536.15047 29.92084995

GP5_4B_‐5‐002.asc 191.3 1.24315 45.77872172 534.6044724 24.39249652

GP5_4B_‐6‐001.asc 192.5 1.26242 60.56460368 501.3618189 28.74042079

Lineair age model

Appendix Chapter 5. Drip water chemistry, monitoring

Drip site Monitoring trip Drip rate (sec./drip) Drip rate (drips/min.) Ca (mg/l) Mg (mg/l) Ba (µg/l) Sr (µg/l) pH HCO3 (mg/l) si_Aragonite si_Calcite

02‐10 161 0.37 21.30 37.00 12.70 15.90 8.55 226.64

06‐10 270 0.22 12.50 35.80 11.30 8.29 8.60 174.34 0.16 0.31

09‐10 720 0.08 13.40 63.30 33.10 7.23 ‐

12‐10 370 0.16 13.60 36.50 22.00 8.00 8.16 217.92 ‐0.15 ‐0.01

03‐11 202 0.30 15.30 37.40 12.00 9.00 8.40 213.56 0.12 0.27

06‐11 372 0.16 15.10 33.20 10.00 10.00 8.55 200.50 0.23 0.38

09‐11 ‐

12‐11 259 0.23 16.30 36.10 11.00 11.00 8.36 209.20 0.10 0.25

03‐12 597 0.10 15.20 40.40 11.60 9.90 8.47

02‐10 45 1.33 41.50 41.30 14.10 23.50 8.45 305.09

06‐10 93 0.65 28.20 40.80 11.50 32.70 8.48 257.14 0.51 0.67

09‐10

12‐10 314 0.19 15.20 40.70 14.00 12.00 8.57 226.64 0.29 0.44

03‐11 104 0.58 21.10 45.30 13.00 17.00 8.44 257.14 0.35 0.50

06‐11 113 0.53 19.50 45.40 12.00 17.00 8.54 252.79 0.40 0.55

09‐11

12‐11 175 0.34 16.10 42.10 12.00 13.00 8.53 222.28 0.26 0.42

03‐12 165 0.36 19.00 45.20 12.80 16.50 8.48 248.43 0.33 0.48

02‐10

06‐10 39 1.54 43.70 17.20 10.80 23.30 8.49 204.84 0.64 0.80

09‐10

12‐10 70 0.86 45.60 16.90 17.00 22.00 8.30 226.64 0.52 0.68

03‐11 32 1.88 52.40 18.60 14.00 24.00 8.25 261.50 0.58 0.74

06‐11 23 2.61 50.40 18.60 12.00 24.00 8.31 252.80 0.61 0.77

09‐11

12‐11 115 0.52 42.90 18.00 14.00 24.00 8.47 211.38 0.63 0.78

03‐12 145 0.41 41.70 18.40 13.80 23.60 8.30 218.00 0.47 0.62

09‐11 650 0.09

12‐11 26 2.31 39.70 21.40 14.00 29.00 8.32 213.56 0.45 0.61

03‐12 27 2.22 38.90 22.70 14.10 30.30 8.40 222.00 0.54 0.69

GP‐Dr.13

GP‐Dr.14

GP‐Dr.17

GP‐Dr.18

Appendix Chapter 5. Modelling_Ba‐only_PAP2

Initial values Derived from drip 17+14 Calcite see MS Aragonite

Ca= 1.3 mmol/l T=15°C Literature Cc‐Ar transitions Moni.+Stal. Ave.

Mg= 1.77 mmol/l DMg= 0.019 Lit check for 15°C DMg= 0.0017 0.000126667 0.00011031

Sr= 0.3700 μmol/l DSr= 0.0001 DSr= 1.2 0.0008 1.347989474

Ba= 0.1030 μmol/l DBa= 0.012 DBa= 1.8 0.048000 0.136072222

Threshold Mg 2.5000

Ca Ca Mg Sr Ba Mg Sr Ba Mg/Ca Sr/Ca

1.3 1.77 0.37 0.103 1.361538462 0.284615385 0.079230769

0.9 1.17 0.13 0.0034 4E‐06 0.0001236 1.7666 0.3699963 0.1028764 1.509946154 0.316236154 0.087928547

0.89 1.157 0.013 0.0004 4E‐07 1.37169E‐05 1.7663 0.3700 0.1029 1.527 0.320 0.089

0.88 1.144 0.0130 0.0004 0.0000 0.0000 1.7659 0.3700 0.1028 1.544 0.323 0.090

0.87 1.131 0.0130 0.0004 0.0000 0.0000 1.7655 0.3700 0.1028 1.561 0.327 0.091

0.86 1.118 0.0130 0.0004 0.0000 0.0000 1.7651 0.3700 0.1028 1.579 0.331 0.092

0.85 1.105 0.0130 0.0004 0.0000 0.0000 1.7647 0.3700 0.1028 1.597 0.335 0.093

0.84 1.092 0.0130 0.0004 0.0000 0.0000 1.7643 0.3700 0.1028 1.616 0.339 0.094

0.83 1.079 0.0130 0.0004 0.0000 0.0000 1.7639 0.3700 0.1028 1.635 0.343 0.095

0.82 1.066 0.0130 0.0004 0.0000 0.0000 1.7635 0.3700 0.1028 1.654 0.347 0.096

0.81 1.053 0.0130 0.0004 0.0000 0.0000 1.7631 0.3700 0.1027 1.674 0.351 0.098

0.8 1.04 0.0130 0.0004 0.0000 0.0000 1.7627 0.3700 0.1027 1.695 0.356 0.099

0.79 1.027 0.0130 0.0004 0.0000 0.0000 1.7623 0.3700 0.1027 1.716 0.360 0.100

0.78 1.014 0.0130 0.0004 0.0000 0.0000 1.7619 0.3700 0.1027 1.738 0.365 0.101

0.77 1.001 0.0130 0.0004 0.0000 0.0000 1.7614 0.3700 0.1027 1.760 0.370 0.103

0.76 0.988 0.0130 0.0004 0.0000 0.0000 1.7610 0.3700 0.1027 1.782 0.374 0.104

0.75 0.975 0.0130 0.0004 0.0000 0.0000 1.7606 0.3700 0.1027 1.806 0.379 0.105

0.74 0.962 0.0130 0.0004 0.0000 0.0000 1.7601 0.3700 0.1026 1.830 0.385 0.107

0.73 0.949 0.0130 0.0005 0.0000 0.0000 1.7597 0.3700 0.1026 1.854 0.390 0.108

0.72 0.936 0.0130 0.0005 0.0000 0.0000 1.7592 0.3700 0.1026 1.879 0.395 0.110

0.71 0.923 0.0130 0.0005 0.0000 0.0000 1.7587 0.3700 0.1026 1.905 0.401 0.111

0.7 0.91 0.0130 0.0005 0.0000 0.0000 1.7583 0.3700 0.1026 1.932 0.407 0.113

0.69 0.897 0.0130 0.0005 0.0000 0.0000 1.7578 0.3700 0.1026 1.960 0.412 0.114

0.68 0.884 0.0130 0.0005 0.0000 0.0000 1.7573 0.3700 0.1025 1.988 0.419 0.116

0.67 0.871 0.0130 0.0005 0.0000 0.0000 1.7568 0.3700 0.1025 2.017 0.425 0.118

0.66 0.858 0.0130 0.0005 0.0000 0.0000 1.7563 0.3700 0.1025 2.047 0.431 0.119

0.65 0.845 0.0130 0.0005 0.0000 0.0000 1.7558 0.3700 0.1025 2.078 0.438 0.121

0.64 0.832 0.0130 0.0005 0.0000 0.0000 1.7553 0.3700 0.1025 2.110 0.445 0.123

0.63 0.819 0.0130 0.0005 0.0000 0.0000 1.7548 0.3700 0.1024 2.143 0.452 0.125

0.62 0.806 0.0130 0.0005 0.0000 0.0000 1.7543 0.3700 0.1024 2.176 0.459 0.127

0.61 0.793 0.0130 0.0005 0.0000 0.0000 1.7537 0.3700 0.1024 2.211 0.467 0.129

0.6 0.78 0.0130 0.0005 0.0000 0.0000 1.7532 0.3700 0.1024 2.248 0.474 0.131

0.59 0.767 0.0130 0.0006 0.0000 0.0000 1.7526 0.3700 0.1024 2.285 0.482 0.133

0.58 0.754 0.0130 0.0006 0.0000 0.0000 1.7521 0.3700 0.1023 2.324 0.491 0.136

0.57 0.741 0.0130 0.0006 0.0000 0.0000 1.7515 0.3700 0.1023 2.364 0.499 0.138

0.56 0.728 0.0130 0.0006 0.0000 0.0000 1.7509 0.3700 0.1023 2.405 0.508 0.141

0.55 0.715 0.0130 0.0006 0.0000 0.0000 1.7503 0.3700 0.1023 2.448 0.517 0.143

0.54 0.702 0.0130 0.0006 0.0000 0.0000 1.7497 0.3700 0.1023 2.492 0.527 0.146

0.53 0.689 0.0130 0.0006 0.0000 0.0000 1.7491 0.3700 0.1022 2.539 0.537 0.148

0.52 0.676 0.0130 0.0001 0.0084 0.0035 1.7490 0.3616 0.0988 2.587 0.535 0.146

0.51 0.663 0.0130 0.0001 0.0083 0.0034 1.7490 0.3533 0.0953 2.638 0.533 0.144

0.5 0.65 0.0130 0.0001 0.0083 0.0034 1.7489 0.3449 0.0920 2.691 0.531 0.141

0.49 0.637 0.0130 0.0001 0.0083 0.0033 1.7488 0.3367 0.0887 2.745 0.529 0.139

0.48 0.624 0.0130 0.0001 0.0082 0.0033 1.7488 0.3284 0.0854 2.803 0.526 0.137

0.47 0.611 0.0130 0.0001 0.0082 0.0032 1.7487 0.3202 0.0822 2.862 0.524 0.135

0.46 0.598 0.0130 0.0001 0.0082 0.0031 1.7487 0.3120 0.0791 2.924 0.522 0.132

0.45 0.585 0.0130 0.0001 0.0081 0.0031 1.7486 0.3039 0.0760 2.989 0.519 0.130

0.44 0.572 0.0130 0.0001 0.0081 0.0030 1.7485 0.2958 0.0729 3.057 0.517 0.127

0.43 0.559 0.0130 0.0001 0.0081 0.0030 1.7485 0.2877 0.0699 3.128 0.515 0.125

0.42 0.546 0.0130 0.0001 0.0080 0.0029 1.7484 0.2797 0.0670 3.202 0.512 0.123

0.41 0.533 0.0130 0.0001 0.0080 0.0029 1.7483 0.2717 0.0641 3.280 0.510 0.120

0.4 0.52 0.0130 0.0001 0.0080 0.0028 1.7483 0.2638 0.0613 3.362 0.507 0.118

0.39 0.507 0.0130 0.0001 0.0079 0.0028 1.7482 0.2558 0.0586 3.448 0.505 0.116

0.38 0.494 0.0130 0.0001 0.0079 0.0027 1.7481 0.2480 0.0559 3.539 0.502 0.113

0.37 0.481 0.0130 0.0001 0.0078 0.0026 1.7480 0.2401 0.0532 3.634 0.499 0.111

0.36 0.468 0.0130 0.0001 0.0078 0.0026 1.7479 0.2323 0.0506 3.735 0.496 0.108

0.35 0.455 0.0130 0.0001 0.0077 0.0025 1.7479 0.2246 0.0481 3.841 0.494 0.106

0.34 0.442 0.0130 0.0001 0.0077 0.0025 1.7478 0.2169 0.0456 3.954 0.491 0.103

0.33 0.429 0.0130 0.0001 0.0077 0.0024 1.7477 0.2092 0.0432 4.074 0.488 0.101

0.32 0.416 0.0130 0.0001 0.0076 0.0024 1.7476 0.2016 0.0408 4.201 0.485 0.098

0.31 0.403 0.0130 0.0001 0.0076 0.0023 1.7475 0.1941 0.0386 4.336 0.482 0.096

0.3 0.39 0.0130 0.0001 0.0075 0.0022 1.7474 0.1866 0.0363 4.481 0.478 0.093

0.29 0.377 0.0130 0.0001 0.0075 0.0022 1.7473 0.1791 0.0341 4.635 0.475 0.091

0.28 0.364 0.0130 0.0001 0.0074 0.0021 1.7472 0.1717 0.0320 4.800 0.472 0.088

0.27 0.351 0.0130 0.0001 0.0074 0.0021 1.7471 0.1643 0.0300 4.977 0.468 0.085

0.26 0.338 0.0130 0.0001 0.0073 0.0020 1.7470 0.1570 0.0280 5.169 0.465 0.083

0.25 0.325 0.0130 0.0001 0.0072 0.0019 1.7469 0.1498 0.0260 5.375 0.461 0.080

0.24 0.312 0.0130 0.0001 0.0072 0.0019 1.7468 0.1426 0.0242 5.599 0.457 0.077

0.23 0.299 0.0130 0.0001 0.0071 0.0018 1.7466 0.1355 0.0223 5.842 0.453 0.075

0.22 0.286 0.0130 0.0001 0.0071 0.0017 1.7465 0.1284 0.0206 6.107 0.449 0.072

0.21 0.273 0.0130 0.0001 0.0070 0.0017 1.7464 0.1214 0.0189 6.397 0.445 0.069

0.2 0.26 0.0130 0.0001 0.0069 0.0016 1.7462 0.1145 0.0173 6.716 0.440 0.066

0.19 0.247 0.0130 0.0001 0.0069 0.0016 1.7461 0.1076 0.0157 7.069 0.436 0.064

0.18 0.234 0.0130 0.0002 0.0068 0.0015 1.7459 0.1008 0.0142 7.461 0.431 0.061

0.17 0.221 0.0130 0.0002 0.0067 0.0014 1.7458 0.0941 0.0128 7.899 0.426 0.058

0.16 0.208 0.0130 0.0002 0.0066 0.0014 1.7456 0.0874 0.0115 8.392 0.420 0.055

0.15 0.195 0.0130 0.0002 0.0066 0.0013 1.7454 0.0809 0.0102 8.951 0.415 0.052

0.14 0.182 0.0130 0.0002 0.0065 0.0012 1.7452 0.0744 0.0089 9.589 0.409 0.049

0.13 0.169 0.0130 0.0002 0.0064 0.0012 1.7450 0.0680 0.0078 10.325 0.403 0.046

0.12 0.156 0.0130 0.0002 0.0063 0.0011 1.7448 0.0617 0.0067 11.184 0.396 0.043

0.11 0.143 0.0130 0.0002 0.0062 0.0010 1.7445 0.0556 0.0057 12.199 0.389 0.040

0.1 0.13 0.0130 0.0003 0.0061 0.0009 1.7442 0.0495 0.0048 13.417 0.381 0.037

0.09 0.117 0.0130 0.0003 0.0059 0.0009 1.7439 0.0436 0.0039 14.906 0.372 0.033

0.08 0.104 0.0130 0.0003 0.0058 0.0008 1.7436 0.0378 0.0031 16.766 0.363 0.030

0.07 0.091 0.0130 0.0004 0.0057 0.0007 1.7432 0.0321 0.0024 19.157 0.353 0.027

0.06 0.078 0.0130 0.0004 0.0055 0.0006 1.7428 0.0266 0.0018 22.344 0.341 0.023

0.05 0.065 0.0130 0.0005 0.0053 0.0005 1.7423 0.0213 0.0013 26.805 0.327 0.019

0.04 0.052 0.0130 0.0006 0.0051 0.0005 1.7417 0.0162 0.0008 33.495 0.311 0.016

0.03 0.039 0.0130 0.0007 0.0049 0.0004 1.7410 0.0113 0.0004 44.641 0.290 0.011

0.02 0.026 0.0130 0.0010 0.0045 0.0003 1.7400 0.0068 0.0002 66.924 0.261 0.007

0.01 0.013 0.0130 0.0015 0.0041 0.0002 1.7385 0.0027 0.0000 133.733 0.209 0.001

Use Transition Cc ‐ Ar 

(under assumption that 

the chemistry is not 

changing significantly)

Appendix Chapter 5. Modelling_Ba‐only PCP‐PAP1

Initial values Derived from drip 17+14 Calcite see MS AragoniteCa= 1.3000 mmol/l T=15°C Literature Cc‐Ar transitions Moni.+Stal. Ave.

Mg= 1.7700 mmol/l DMg= 0.019 Lit check for 15°C DMg= 0.0017 0.000127 0.00011031

Sr= 0.3700 μmol/l DSr= 0.0001 DSr= 1.2 0.001 1.347989474

Ba= 0.1030 μmol/l DBa= 0.012 DBa= 1.800 0.048 0.136072222

Threshold Mg 2.5000

Ca Ca Mg Sr Ba Mg Sr Ba Mg/Ca Sr/Ca Ba/Ca

1.3 1.7700 0.3700 0.1030 1.362 0.285 0.079

0.9 1.17 0.1300 0.0034 0.0000 0.0001 1.7666 0.3700 0.1029 1.510 0.316 0.088

0.89 1.157 0.0130 0.0004 0.0000 0.0000 1.7663 0.3700 0.1029 1.527 0.320 0.089

0.88 1.144 0.0130 0.0004 0.0000 0.0000 1.7659 0.3700 0.1028 1.544 0.323 0.090

0.87 1.131 0.0130 0.0004 0.0000 0.0000 1.7655 0.3700 0.1028 1.561 0.327 0.091

0.86 1.118 0.0130 0.0004 0.0000 0.0000 1.7651 0.3700 0.1028 1.579 0.331 0.092

0.85 1.105 0.0130 0.0004 0.0000 0.0000 1.7647 0.3700 0.1028 1.597 0.335 0.093

0.84 1.092 0.0130 0.0004 0.0000 0.0000 1.7643 0.3700 0.1028 1.616 0.339 0.094

0.83 1.079 0.0130 0.0004 0.0000 0.0000 1.7639 0.3700 0.1028 1.635 0.343 0.095

0.82 1.066 0.0130 0.0004 0.0000 0.0000 1.7635 0.3700 0.1028 1.654 0.347 0.096

0.81 1.053 0.0130 0.0004 0.0000 0.0000 1.7631 0.3700 0.1027 1.674 0.351 0.098

0.8 1.04 0.0130 0.0004 0.0000 0.0000 1.7627 0.3700 0.1027 1.695 0.356 0.099

0.79 1.027 0.0130 0.0004 0.0000 0.0000 1.7623 0.3700 0.1027 1.716 0.360 0.100

0.78 1.014 0.0130 0.0004 0.0000 0.0000 1.7619 0.3700 0.1027 1.738 0.365 0.101

0.77 1.001 0.0130 0.0004 0.0000 0.0000 1.7614 0.3700 0.1027 1.760 0.370 0.103

0.76 0.988 0.0130 0.0004 0.0000 0.0000 1.7610 0.3700 0.1027 1.782 0.374 0.104

0.75 0.975 0.0130 0.0004 0.0000 0.0000 1.7606 0.3700 0.1027 1.806 0.379 0.105

0.74 0.962 0.0130 0.0004 0.0000 0.0000 1.7601 0.3700 0.1026 1.830 0.385 0.107

0.73 0.949 0.0130 0.0005 0.0000 0.0000 1.7597 0.3700 0.1026 1.854 0.390 0.108

0.72 0.936 0.0130 0.0005 0.0000 0.0000 1.7592 0.3700 0.1026 1.879 0.395 0.110

0.71 0.923 0.0130 0.0005 0.0000 0.0000 1.7587 0.3700 0.1026 1.905 0.401 0.111

0.7 0.91 0.0130 0.0005 0.0000 0.0000 1.7583 0.3700 0.1026 1.932 0.407 0.113

0.69 0.897 0.0130 0.0005 0.0000 0.0000 1.7578 0.3700 0.1026 1.960 0.412 0.114

0.68 0.884 0.0130 0.0005 0.0000 0.0000 1.7573 0.3700 0.1025 1.988 0.419 0.116

0.67 0.871 0.0130 0.0005 0.0000 0.0000 1.7568 0.3700 0.1025 2.017 0.425 0.118

0.66 0.858 0.0130 0.0005 0.0000 0.0000 1.7563 0.3700 0.1025 2.047 0.431 0.119

0.65 0.845 0.0130 0.0005 0.0000 0.0000 1.7558 0.3700 0.1025 2.078 0.438 0.121

0.64 0.832 0.0130 0.0005 0.0000 0.0000 1.7553 0.3700 0.1025 2.110 0.445 0.123

0.63 0.819 0.0130 0.0005 0.0000 0.0000 1.7548 0.3700 0.1024 2.143 0.452 0.125

0.62 0.806 0.0130 0.0005 0.0000 0.0000 1.7543 0.3700 0.1024 2.176 0.459 0.127

0.61 0.793 0.0130 0.0005 0.0000 0.0000 1.7537 0.3700 0.1024 2.211 0.467 0.129

0.6 0.78 0.0130 0.0005 0.0000 0.0000 1.7532 0.3700 0.1024 2.248 0.474 0.131

0.59 0.767 0.0130 0.0006 0.0000 0.0000 1.7526 0.3700 0.1024 2.285 0.482 0.133

0.58 0.754 0.0130 0.0006 0.0000 0.0000 1.7521 0.3700 0.1023 2.324 0.491 0.136

0.57 0.741 0.0130 0.0006 0.0000 0.0000 1.7515 0.3700 0.1023 2.364 0.499 0.138

0.56 0.728 0.0130 0.0006 0.0000 0.0000 1.7509 0.3700 0.1023 2.405 0.508 0.141

0.55 0.715 0.0130 0.0006 0.0000 0.0000 1.7503 0.3700 0.1023 2.448 0.517 0.143

0.54 0.702 0.0130 0.0006 0.0000 0.0000 1.7497 0.3700 0.1023 2.492 0.527 0.146

0.53 0.689 0.0130 0.0006 0.0000 0.0000 1.7491 0.3700 0.1022 2.539 0.537 0.148

0.52 0.676 0.0130 0.0000 0.0094 0.0003 1.7491 0.3606 0.1020 2.587 0.533 0.151

0.51 0.663 0.0130 0.0000 0.0093 0.0003 1.7491 0.3512 0.1017 2.638 0.530 0.153

0.5 0.65 0.0130 0.0000 0.0093 0.0003 1.7491 0.3419 0.1014 2.691 0.526 0.156

0.49 0.637 0.0130 0.0000 0.0092 0.0003 1.7491 0.3327 0.1012 2.746 0.522 0.159

0.48 0.624 0.0130 0.0000 0.0092 0.0003 1.7491 0.3236 0.1009 2.803 0.519 0.162

0.47 0.611 0.0130 0.0000 0.0091 0.0003 1.7491 0.3145 0.1006 2.863 0.515 0.165

0.46 0.598 0.0130 0.0000 0.0090 0.0003 1.7491 0.3055 0.1003 2.925 0.511 0.168

0.45 0.585 0.0130 0.0000 0.0090 0.0003 1.7490 0.2965 0.1000 2.990 0.507 0.171

0.44 0.572 0.0130 0.0000 0.0089 0.0003 1.7490 0.2876 0.0997 3.058 0.503 0.174

0.43 0.559 0.0130 0.0000 0.0088 0.0003 1.7490 0.2788 0.0994 3.129 0.499 0.178

0.42 0.546 0.0130 0.0000 0.0087 0.0003 1.7490 0.2701 0.0991 3.203 0.495 0.181

0.41 0.533 0.0130 0.0000 0.0087 0.0003 1.7490 0.2614 0.0988 3.281 0.490 0.185

0.4 0.52 0.0130 0.0000 0.0086 0.0003 1.7490 0.2528 0.0984 3.364 0.486 0.189

0.39 0.507 0.0130 0.0000 0.0085 0.0003 1.7490 0.2443 0.0981 3.450 0.482 0.193

0.38 0.494 0.0130 0.0000 0.0084 0.0003 1.7490 0.2358 0.0977 3.541 0.477 0.198

0.37 0.481 0.0130 0.0000 0.0084 0.0004 1.7490 0.2275 0.0974 3.636 0.473 0.202

0.36 0.468 0.0130 0.0000 0.0083 0.0004 1.7490 0.2192 0.0970 3.737 0.468 0.207

0.35 0.455 0.0130 0.0000 0.0082 0.0004 1.7490 0.2110 0.0967 3.844 0.464 0.212

0.34 0.442 0.0130 0.0000 0.0081 0.0004 1.7490 0.2029 0.0963 3.957 0.459 0.218

0.33 0.429 0.0130 0.0000 0.0080 0.0004 1.7490 0.1948 0.0959 4.077 0.454 0.224

0.32 0.416 0.0130 0.0000 0.0080 0.0004 1.7490 0.1869 0.0955 4.204 0.449 0.230

0.31 0.403 0.0130 0.0000 0.0079 0.0004 1.7490 0.1790 0.0951 4.340 0.444 0.236

0.3 0.39 0.0130 0.0000 0.0078 0.0004 1.7490 0.1712 0.0947 4.485 0.439 0.243

0.29 0.377 0.0130 0.0000 0.0077 0.0004 1.7490 0.1635 0.0943 4.639 0.434 0.250

0.28 0.364 0.0130 0.0000 0.0076 0.0004 1.7490 0.1559 0.0938 4.805 0.428 0.258

0.27 0.351 0.0130 0.0000 0.0075 0.0005 1.7489 0.1484 0.0934 4.983 0.423 0.266

0.26 0.338 0.0130 0.0000 0.0074 0.0005 1.7489 0.1410 0.0929 5.174 0.417 0.275

0.25 0.325 0.0130 0.0000 0.0073 0.0005 1.7489 0.1337 0.0924 5.381 0.411 0.284

0.24 0.312 0.0130 0.0000 0.0072 0.0005 1.7489 0.1265 0.0919 5.606 0.405 0.295

0.23 0.299 0.0130 0.0000 0.0071 0.0005 1.7489 0.1194 0.0914 5.849 0.399 0.306

0.22 0.286 0.0130 0.0000 0.0070 0.0005 1.7489 0.1124 0.0908 6.115 0.393 0.318

0.21 0.273 0.0130 0.0000 0.0069 0.0006 1.7489 0.1055 0.0903 6.406 0.386 0.331

0.2 0.26 0.0130 0.0000 0.0068 0.0006 1.7489 0.0987 0.0897 6.727 0.380 0.345

0.19 0.247 0.0130 0.0000 0.0067 0.0006 1.7489 0.0921 0.0891 7.080 0.373 0.361

0.18 0.234 0.0130 0.0000 0.0065 0.0006 1.7489 0.0855 0.0884 7.474 0.366 0.378

0.17 0.221 0.0130 0.0000 0.0064 0.0007 1.7489 0.0791 0.0878 7.913 0.358 0.397

0.16 0.208 0.0130 0.0000 0.0063 0.0007 1.7489 0.0729 0.0871 8.408 0.350 0.419

0.15 0.195 0.0130 0.0000 0.0061 0.0007 1.7488 0.0667 0.0863 8.968 0.342 0.443

0.14 0.182 0.0130 0.0000 0.0060 0.0008 1.7488 0.0607 0.0856 9.609 0.334 0.470

0.13 0.169 0.0130 0.0000 0.0058 0.0008 1.7488 0.0549 0.0847 10.348 0.325 0.501

0.12 0.156 0.0130 0.0000 0.0057 0.0009 1.7488 0.0492 0.0838 11.210 0.315 0.537

0.11 0.143 0.0130 0.0000 0.0055 0.0010 1.7488 0.0437 0.0829 12.229 0.305 0.580

0.1 0.13 0.0130 0.0000 0.0054 0.0010 1.7488 0.0383 0.0819 13.452 0.295 0.630

0.09 0.117 0.0130 0.0000 0.0052 0.0011 1.7487 0.0331 0.0807 14.947 0.283 0.690

0.08 0.104 0.0130 0.0000 0.0050 0.0012 1.7487 0.0282 0.0795 16.815 0.271 0.765

0.07 0.091 0.0130 0.0000 0.0047 0.0014 1.7487 0.0234 0.0782 19.216 0.258 0.859

0.06 0.078 0.0130 0.0000 0.0045 0.0015 1.7487 0.0189 0.0767 22.419 0.243 0.983

0.05 0.065 0.0130 0.0000 0.0043 0.0017 1.7486 0.0147 0.0749 26.902 0.226 1.153

0.04 0.052 0.0130 0.0000 0.0040 0.0020 1.7486 0.0107 0.0729 33.627 0.206 1.401

0.03 0.039 0.0130 0.0000 0.0036 0.0025 1.7486 0.0071 0.0704 44.835 0.182 1.805

0.02 0.026 0.0130 0.0001 0.0032 0.0032 1.7485 0.0039 0.0672 67.250 0.150 2.585

0.01 0.013 0.0130 0.0001 0.0026 0.0046 1.7484 0.0013 0.0626 134.492 0.098 4.818

Use Transition Cc ‐ Ar 

(under assumption that 

the chemistry is not 

changing significantly)

Appendix Chapter 5. Modeling_Sr_Mg_PAP2

Initial values Derived from drip 17+14 Calcite see MS AragoniteCa= 1.3000 mmol/l T=15°C Literature Cc‐Ar transitions Moni.+Stal. Ave.

Mg= 1.7700 mmol/l DMg= 0.019 Lit check for 15°C DMg= 0.0017 0.000127 0.00011031

Sr= 0.3700 μmol/l DSr= 0.072 DSr= 1.2 0.576 1.347989474

Ba= 0.1092 μmol/l DBa= 0.012 DBa= 1.800 0.048 0.136072222

Threshold Mg 2.5000

Ca Ca Mg Sr Ba Mg Sr Ba Mg/Ca Sr/Ca Ba/Ca

1.3 1.7700 0.3700 0.1092 1.362 0.285 0.084

0.9 1.17 0.1300 0.0034 0.0027 0.0001 1.7666 0.3673 0.1091 1.510 0.314 0.093

0.89 1.157 0.0130 0.0004 0.0003 0.0000 1.7663 0.3670 0.1091 1.527 0.317 0.094

0.88 1.144 0.0130 0.0004 0.0003 0.0000 1.7659 0.3667 0.1091 1.544 0.321 0.095

0.87 1.131 0.0130 0.0004 0.0003 0.0000 1.7655 0.3664 0.1091 1.561 0.324 0.096

0.86 1.118 0.0130 0.0004 0.0003 0.0000 1.7651 0.3661 0.1091 1.579 0.327 0.098

0.85 1.105 0.0130 0.0004 0.0003 0.0000 1.7647 0.3658 0.1090 1.597 0.331 0.099

0.84 1.092 0.0130 0.0004 0.0003 0.0000 1.7643 0.3655 0.1090 1.616 0.335 0.100

0.83 1.079 0.0130 0.0004 0.0003 0.0000 1.7639 0.3652 0.1090 1.635 0.338 0.101

0.82 1.066 0.0130 0.0004 0.0003 0.0000 1.7635 0.3649 0.1090 1.654 0.342 0.102

0.81 1.053 0.0130 0.0004 0.0003 0.0000 1.7631 0.3646 0.1090 1.674 0.346 0.103

0.8 1.04 0.0130 0.0004 0.0003 0.0000 1.7627 0.3643 0.1090 1.695 0.350 0.105

0.79 1.027 0.0130 0.0004 0.0003 0.0000 1.7623 0.3639 0.1089 1.716 0.354 0.106

0.78 1.014 0.0130 0.0004 0.0003 0.0000 1.7619 0.3636 0.1089 1.738 0.359 0.107

0.77 1.001 0.0130 0.0004 0.0003 0.0000 1.7614 0.3633 0.1089 1.760 0.363 0.109

0.76 0.988 0.0130 0.0004 0.0003 0.0000 1.7610 0.3629 0.1089 1.782 0.367 0.110

0.75 0.975 0.0130 0.0004 0.0003 0.0000 1.7606 0.3626 0.1089 1.806 0.372 0.112

0.74 0.962 0.0130 0.0004 0.0003 0.0000 1.7601 0.3622 0.1089 1.830 0.377 0.113

0.73 0.949 0.0130 0.0005 0.0004 0.0000 1.7597 0.3619 0.1088 1.854 0.381 0.115

0.72 0.936 0.0130 0.0005 0.0004 0.0000 1.7592 0.3615 0.1088 1.879 0.386 0.116

0.71 0.923 0.0130 0.0005 0.0004 0.0000 1.7587 0.3612 0.1088 1.905 0.391 0.118

0.7 0.91 0.0130 0.0005 0.0004 0.0000 1.7583 0.3608 0.1088 1.932 0.396 0.120

0.69 0.897 0.0130 0.0005 0.0004 0.0000 1.7578 0.3604 0.1088 1.960 0.402 0.121

0.68 0.884 0.0130 0.0005 0.0004 0.0000 1.7573 0.3600 0.1088 1.988 0.407 0.123

0.67 0.871 0.0130 0.0005 0.0004 0.0000 1.7568 0.3597 0.1087 2.017 0.413 0.125

0.66 0.858 0.0130 0.0005 0.0004 0.0000 1.7563 0.3593 0.1087 2.047 0.419 0.127

0.65 0.845 0.0130 0.0005 0.0004 0.0000 1.7558 0.3589 0.1087 2.078 0.425 0.129

0.64 0.832 0.0130 0.0005 0.0004 0.0000 1.7553 0.3585 0.1087 2.110 0.431 0.131

0.63 0.819 0.0130 0.0005 0.0004 0.0000 1.7548 0.3581 0.1087 2.143 0.437 0.133

0.62 0.806 0.0130 0.0005 0.0004 0.0000 1.7543 0.3577 0.1086 2.176 0.444 0.135

0.61 0.793 0.0130 0.0005 0.0004 0.0000 1.7537 0.3573 0.1086 2.211 0.451 0.137

0.6 0.78 0.0130 0.0005 0.0004 0.0000 1.7532 0.3568 0.1086 2.248 0.457 0.139

0.59 0.767 0.0130 0.0006 0.0004 0.0000 1.7526 0.3564 0.1086 2.285 0.465 0.142

0.58 0.754 0.0130 0.0006 0.0004 0.0000 1.7521 0.3560 0.1085 2.324 0.472 0.144

0.57 0.741 0.0130 0.0006 0.0004 0.0000 1.7515 0.3555 0.1085 2.364 0.480 0.146

0.56 0.728 0.0130 0.0006 0.0004 0.0000 1.7509 0.3551 0.1085 2.405 0.488 0.149

0.55 0.715 0.0130 0.0006 0.0005 0.0000 1.7503 0.3546 0.1085 2.448 0.496 0.152

0.54 0.702 0.0130 0.0006 0.0005 0.0000 1.7497 0.3542 0.1085 2.492 0.504 0.154

0.53 0.689 0.0130 0.0006 0.0005 0.0000 1.7491 0.3537 0.1084 2.539 0.513 0.157

0.52 0.676 0.0130 0.0001 0.0080 0.0037 1.7490 0.3457 0.1047 2.587 0.511 0.155

0.51 0.663 0.0130 0.0001 0.0080 0.0036 1.7490 0.3377 0.1011 2.638 0.509 0.153

0.5 0.65 0.0130 0.0001 0.0079 0.0036 1.7489 0.3298 0.0976 2.691 0.507 0.150

0.49 0.637 0.0130 0.0001 0.0079 0.0035 1.7488 0.3218 0.0940 2.745 0.505 0.148

0.48 0.624 0.0130 0.0001 0.0079 0.0035 1.7488 0.3140 0.0906 2.803 0.503 0.145

0.47 0.611 0.0130 0.0001 0.0078 0.0034 1.7487 0.3061 0.0872 2.862 0.501 0.143

0.46 0.598 0.0130 0.0001 0.0078 0.0033 1.7487 0.2983 0.0839 2.924 0.499 0.140

0.45 0.585 0.0130 0.0001 0.0078 0.0033 1.7486 0.2905 0.0806 2.989 0.497 0.138

0.44 0.572 0.0130 0.0001 0.0077 0.0032 1.7485 0.2828 0.0773 3.057 0.494 0.135

0.43 0.559 0.0130 0.0001 0.0077 0.0032 1.7485 0.2751 0.0742 3.128 0.492 0.133

0.42 0.546 0.0130 0.0001 0.0077 0.0031 1.7484 0.2674 0.0711 3.202 0.490 0.130

0.41 0.533 0.0130 0.0001 0.0076 0.0030 1.7483 0.2597 0.0680 3.280 0.487 0.128

0.4 0.52 0.0130 0.0001 0.0076 0.0030 1.7483 0.2521 0.0650 3.362 0.485 0.125

0.39 0.507 0.0130 0.0001 0.0076 0.0029 1.7482 0.2446 0.0621 3.448 0.482 0.123

0.38 0.494 0.0130 0.0001 0.0075 0.0029 1.7481 0.2370 0.0593 3.539 0.480 0.120

0.37 0.481 0.0130 0.0001 0.0075 0.0028 1.7480 0.2296 0.0564 3.634 0.477 0.117

0.36 0.468 0.0130 0.0001 0.0074 0.0027 1.7479 0.2221 0.0537 3.735 0.475 0.115

0.35 0.455 0.0130 0.0001 0.0074 0.0027 1.7479 0.2147 0.0510 3.841 0.472 0.112

0.34 0.442 0.0130 0.0001 0.0074 0.0026 1.7478 0.2074 0.0484 3.954 0.469 0.109

0.33 0.429 0.0130 0.0001 0.0073 0.0026 1.7477 0.2000 0.0458 4.074 0.466 0.107

0.32 0.416 0.0130 0.0001 0.0073 0.0025 1.7476 0.1928 0.0433 4.201 0.463 0.104

0.31 0.403 0.0130 0.0001 0.0072 0.0024 1.7475 0.1855 0.0409 4.336 0.460 0.101

0.3 0.39 0.0130 0.0001 0.0072 0.0024 1.7474 0.1783 0.0385 4.481 0.457 0.099

0.29 0.377 0.0130 0.0001 0.0071 0.0023 1.7473 0.1712 0.0362 4.635 0.454 0.096

0.28 0.364 0.0130 0.0001 0.0071 0.0022 1.7472 0.1641 0.0340 4.800 0.451 0.093

0.27 0.351 0.0130 0.0001 0.0070 0.0022 1.7471 0.1571 0.0318 4.977 0.448 0.091

0.26 0.338 0.0130 0.0001 0.0070 0.0021 1.7470 0.1501 0.0297 5.169 0.444 0.088

0.25 0.325 0.0130 0.0001 0.0069 0.0021 1.7469 0.1432 0.0276 5.375 0.441 0.085

0.24 0.312 0.0130 0.0001 0.0069 0.0020 1.7468 0.1363 0.0256 5.599 0.437 0.082

0.23 0.299 0.0130 0.0001 0.0068 0.0019 1.7466 0.1295 0.0237 5.842 0.433 0.079

0.22 0.286 0.0130 0.0001 0.0068 0.0019 1.7465 0.1227 0.0218 6.107 0.429 0.076

0.21 0.273 0.0130 0.0001 0.0067 0.0018 1.7464 0.1160 0.0201 6.397 0.425 0.073

0.2 0.26 0.0130 0.0001 0.0066 0.0017 1.7462 0.1094 0.0183 6.716 0.421 0.071

0.19 0.247 0.0130 0.0001 0.0066 0.0017 1.7461 0.1028 0.0167 7.069 0.416 0.068

0.18 0.234 0.0130 0.0002 0.0065 0.0016 1.7459 0.0964 0.0151 7.461 0.412 0.065

0.17 0.221 0.0130 0.0002 0.0064 0.0015 1.7458 0.0899 0.0136 7.899 0.407 0.062

0.16 0.208 0.0130 0.0002 0.0063 0.0014 1.7456 0.0836 0.0122 8.392 0.402 0.058

0.15 0.195 0.0130 0.0002 0.0063 0.0014 1.7454 0.0773 0.0108 8.951 0.396 0.055

0.14 0.182 0.0130 0.0002 0.0062 0.0013 1.7452 0.0711 0.0095 9.589 0.391 0.052

0.13 0.169 0.0130 0.0002 0.0061 0.0012 1.7450 0.0650 0.0083 10.325 0.385 0.049

0.12 0.156 0.0130 0.0002 0.0060 0.0011 1.7448 0.0590 0.0071 11.184 0.378 0.046

0.11 0.143 0.0130 0.0002 0.0059 0.0011 1.7445 0.0531 0.0061 12.199 0.372 0.042

0.1 0.13 0.0130 0.0003 0.0058 0.0010 1.7442 0.0473 0.0051 13.417 0.364 0.039

0.09 0.117 0.0130 0.0003 0.0057 0.0009 1.7439 0.0417 0.0042 14.906 0.356 0.036

0.08 0.104 0.0130 0.0003 0.0056 0.0008 1.7436 0.0361 0.0033 16.766 0.347 0.032

0.07 0.091 0.0130 0.0004 0.0054 0.0007 1.7432 0.0307 0.0026 19.157 0.337 0.028

0.06 0.078 0.0130 0.0004 0.0053 0.0007 1.7428 0.0254 0.0019 22.344 0.326 0.025

0.05 0.065 0.0130 0.0005 0.0051 0.0006 1.7423 0.0203 0.0013 26.805 0.313 0.021

0.04 0.052 0.0130 0.0006 0.0049 0.0005 1.7417 0.0155 0.0009 33.495 0.297 0.016

0.03 0.039 0.0130 0.0007 0.0046 0.0004 1.7410 0.0108 0.0005 44.641 0.277 0.012

0.02 0.026 0.0130 0.0010 0.0043 0.0003 1.7400 0.0065 0.0002 66.924 0.250 0.007

0.01 0.013 0.0130 0.0015 0.0039 0.0002 1.7385 0.0026 0.0000 133.733 0.200 0.001

Use Transition Cc ‐ Ar (under 

assumption that the chemistry 

is not changing significantly)

Appendix Chapter 5. Modelling‐Sr‐Mg‐ PCP_PAP1

Initial values Derived from drip 17+14 Calcite see MS AragoniteCa= 1.3000 mmol/l T=15°C modelling  Literatur Cc‐Ar transitions Moni.+Stal. Ave.

Mg= 1.7700 mmol/l DMg= 0.019 check for 15°C DMg= 0.0017 0.0017 0.000127 0.00011031

Sr= 0.3700 μmol/l DSr= 0.072 DSr= 1.2 1.2 0.576 1.347989474

Ba= 0.1092 μmol/l DBa= 0.012 DBa= 0.048 1.8 0.048 0.136072222

Threshold Mg 2.5000

Ca Ca Mg Sr Ba Mg Sr Ba Mg/Ca Sr/Ca Ba/Ca

1.3 1.7700 0.3700 0.1092 1.362 0.285 0.084

0.9 1.17 0.1300 0.0034 0.0027 0.0001 1.7666 0.3673 0.1091 1.510 0.314 0.093

0.89 1.157 0.0130 0.0004 0.0003 0.0000 1.7663 0.3670 0.1091 1.527 0.317 0.094

0.88 1.144 0.0130 0.0004 0.0003 0.0000 1.7659 0.3667 0.1091 1.544 0.321 0.095

0.87 1.131 0.0130 0.0004 0.0003 0.0000 1.7655 0.3664 0.1091 1.561 0.324 0.096

0.86 1.118 0.0130 0.0004 0.0003 0.0000 1.7651 0.3661 0.1091 1.579 0.327 0.098

0.85 1.105 0.0130 0.0004 0.0003 0.0000 1.7647 0.3658 0.1090 1.597 0.331 0.099

0.84 1.092 0.0130 0.0004 0.0003 0.0000 1.7643 0.3655 0.1090 1.616 0.335 0.100

0.83 1.079 0.0130 0.0004 0.0003 0.0000 1.7639 0.3652 0.1090 1.635 0.338 0.101

0.82 1.066 0.0130 0.0004 0.0003 0.0000 1.7635 0.3649 0.1090 1.654 0.342 0.102

0.81 1.053 0.0130 0.0004 0.0003 0.0000 1.7631 0.3646 0.1090 1.674 0.346 0.103

0.8 1.04 0.0130 0.0004 0.0003 0.0000 1.7627 0.3643 0.1090 1.695 0.350 0.105

0.79 1.027 0.0130 0.0004 0.0003 0.0000 1.7623 0.3639 0.1089 1.716 0.354 0.106

0.78 1.014 0.0130 0.0004 0.0003 0.0000 1.7619 0.3636 0.1089 1.738 0.359 0.107

0.77 1.001 0.0130 0.0004 0.0003 0.0000 1.7614 0.3633 0.1089 1.760 0.363 0.109

0.76 0.988 0.0130 0.0004 0.0003 0.0000 1.7610 0.3629 0.1089 1.782 0.367 0.110

0.75 0.975 0.0130 0.0004 0.0003 0.0000 1.7606 0.3626 0.1089 1.806 0.372 0.112

0.74 0.962 0.0130 0.0004 0.0003 0.0000 1.7601 0.3622 0.1089 1.830 0.377 0.113

0.73 0.949 0.0130 0.0005 0.0004 0.0000 1.7597 0.3619 0.1088 1.854 0.381 0.115

0.72 0.936 0.0130 0.0005 0.0004 0.0000 1.7592 0.3615 0.1088 1.879 0.386 0.116

0.71 0.923 0.0130 0.0005 0.0004 0.0000 1.7587 0.3612 0.1088 1.905 0.391 0.118

0.7 0.91 0.0130 0.0005 0.0004 0.0000 1.7583 0.3608 0.1088 1.932 0.396 0.120

0.69 0.897 0.0130 0.0005 0.0004 0.0000 1.7578 0.3604 0.1088 1.960 0.402 0.121

0.68 0.884 0.0130 0.0005 0.0004 0.0000 1.7573 0.3600 0.1088 1.988 0.407 0.123

0.67 0.871 0.0130 0.0005 0.0004 0.0000 1.7568 0.3597 0.1087 2.017 0.413 0.125

0.66 0.858 0.0130 0.0005 0.0004 0.0000 1.7563 0.3593 0.1087 2.047 0.419 0.127

0.65 0.845 0.0130 0.0005 0.0004 0.0000 1.7558 0.3589 0.1087 2.078 0.425 0.129

0.64 0.832 0.0130 0.0005 0.0004 0.0000 1.7553 0.3585 0.1087 2.110 0.431 0.131

0.63 0.819 0.0130 0.0005 0.0004 0.0000 1.7548 0.3581 0.1087 2.143 0.437 0.133

0.62 0.806 0.0130 0.0005 0.0004 0.0000 1.7543 0.3577 0.1086 2.176 0.444 0.135

0.61 0.793 0.0130 0.0005 0.0004 0.0000 1.7537 0.3573 0.1086 2.211 0.451 0.137

0.6 0.78 0.0130 0.0005 0.0004 0.0000 1.7532 0.3568 0.1086 2.248 0.457 0.139

0.59 0.767 0.0130 0.0006 0.0004 0.0000 1.7526 0.3564 0.1086 2.285 0.465 0.142

0.58 0.754 0.0130 0.0006 0.0004 0.0000 1.7521 0.3560 0.1085 2.324 0.472 0.144

0.57 0.741 0.0130 0.0006 0.0004 0.0000 1.7515 0.3555 0.1085 2.364 0.480 0.146

0.56 0.728 0.0130 0.0006 0.0004 0.0000 1.7509 0.3551 0.1085 2.405 0.488 0.149

0.55 0.715 0.0130 0.0006 0.0005 0.0000 1.7503 0.3546 0.1085 2.448 0.496 0.152

0.54 0.702 0.0130 0.0006 0.0005 0.0000 1.7497 0.3542 0.1085 2.492 0.504 0.154

0.53 0.689 0.0130 0.0006 0.0005 0.0000 1.7491 0.3537 0.1084 2.539 0.513 0.157

0.52 0.676 0.0130 0.0000 0.0090 0.0003 1.7491 0.3447 0.1082 2.587 0.510 0.160

0.51 0.663 0.0130 0.0000 0.0089 0.0003 1.7491 0.3358 0.1079 2.638 0.506 0.163

0.5 0.65 0.0130 0.0000 0.0089 0.0003 1.7491 0.3269 0.1076 2.691 0.503 0.166

0.49 0.637 0.0130 0.0000 0.0088 0.0003 1.7491 0.3181 0.1073 2.746 0.499 0.168

0.48 0.624 0.0130 0.0000 0.0088 0.0003 1.7491 0.3093 0.1070 2.803 0.496 0.171

0.47 0.611 0.0130 0.0000 0.0087 0.0003 1.7491 0.3006 0.1067 2.863 0.492 0.175

0.46 0.598 0.0130 0.0000 0.0086 0.0003 1.7491 0.2920 0.1064 2.925 0.488 0.178

0.45 0.585 0.0130 0.0000 0.0086 0.0003 1.7490 0.2835 0.1061 2.990 0.485 0.181

0.44 0.572 0.0130 0.0000 0.0085 0.0003 1.7490 0.2750 0.1057 3.058 0.481 0.185

0.43 0.559 0.0130 0.0000 0.0084 0.0003 1.7490 0.2665 0.1054 3.129 0.477 0.189

0.42 0.546 0.0130 0.0000 0.0084 0.0003 1.7490 0.2582 0.1051 3.203 0.473 0.192

0.41 0.533 0.0130 0.0000 0.0083 0.0003 1.7490 0.2499 0.1047 3.281 0.469 0.197

0.4 0.52 0.0130 0.0000 0.0082 0.0003 1.7490 0.2417 0.1044 3.364 0.465 0.201

0.39 0.507 0.0130 0.0000 0.0081 0.0004 1.7490 0.2335 0.1040 3.450 0.461 0.205

0.38 0.494 0.0130 0.0000 0.0081 0.0004 1.7490 0.2255 0.1037 3.541 0.456 0.210

0.37 0.481 0.0130 0.0000 0.0080 0.0004 1.7490 0.2175 0.1033 3.636 0.452 0.215

0.36 0.468 0.0130 0.0000 0.0079 0.0004 1.7490 0.2095 0.1029 3.737 0.448 0.220

0.35 0.455 0.0130 0.0000 0.0078 0.0004 1.7490 0.2017 0.1025 3.844 0.443 0.225

0.34 0.442 0.0130 0.0000 0.0078 0.0004 1.7490 0.1939 0.1021 3.957 0.439 0.231

0.33 0.429 0.0130 0.0000 0.0077 0.0004 1.7490 0.1862 0.1017 4.077 0.434 0.237

0.32 0.416 0.0130 0.0000 0.0076 0.0004 1.7490 0.1786 0.1013 4.204 0.429 0.244

0.31 0.403 0.0130 0.0000 0.0075 0.0004 1.7490 0.1711 0.1009 4.340 0.425 0.250

0.3 0.39 0.0130 0.0000 0.0074 0.0004 1.7490 0.1637 0.1004 4.485 0.420 0.258

0.29 0.377 0.0130 0.0000 0.0074 0.0005 1.7490 0.1563 0.1000 4.639 0.415 0.265

0.28 0.364 0.0130 0.0000 0.0073 0.0005 1.7490 0.1490 0.0995 4.805 0.409 0.273

0.27 0.351 0.0130 0.0000 0.0072 0.0005 1.7489 0.1419 0.0990 4.983 0.404 0.282

0.26 0.338 0.0130 0.0000 0.0071 0.0005 1.7489 0.1348 0.0985 5.174 0.399 0.292

0.25 0.325 0.0130 0.0000 0.0070 0.0005 1.7489 0.1278 0.0980 5.381 0.393 0.302

0.24 0.312 0.0130 0.0000 0.0069 0.0005 1.7489 0.1209 0.0975 5.606 0.388 0.312

0.23 0.299 0.0130 0.0000 0.0068 0.0006 1.7489 0.1141 0.0969 5.849 0.382 0.324

0.22 0.286 0.0130 0.0000 0.0067 0.0006 1.7489 0.1074 0.0964 6.115 0.376 0.337

0.21 0.273 0.0130 0.0000 0.0066 0.0006 1.7489 0.1008 0.0958 6.406 0.369 0.351

0.2 0.26 0.0130 0.0000 0.0065 0.0006 1.7489 0.0944 0.0951 6.727 0.363 0.366

0.19 0.247 0.0130 0.0000 0.0064 0.0006 1.7489 0.0880 0.0945 7.080 0.356 0.383

0.18 0.234 0.0130 0.0000 0.0062 0.0007 1.7489 0.0818 0.0938 7.474 0.349 0.401

0.17 0.221 0.0130 0.0000 0.0061 0.0007 1.7489 0.0756 0.0931 7.913 0.342 0.421

0.16 0.208 0.0130 0.0000 0.0060 0.0007 1.7489 0.0696 0.0924 8.408 0.335 0.444

0.15 0.195 0.0130 0.0000 0.0059 0.0008 1.7488 0.0638 0.0916 8.968 0.327 0.470

0.14 0.182 0.0130 0.0000 0.0057 0.0008 1.7488 0.0580 0.0907 9.609 0.319 0.499

0.13 0.169 0.0130 0.0000 0.0056 0.0009 1.7488 0.0525 0.0899 10.348 0.310 0.532

0.12 0.156 0.0130 0.0000 0.0054 0.0009 1.7488 0.0470 0.0889 11.210 0.301 0.570

0.11 0.143 0.0130 0.0000 0.0053 0.0010 1.7488 0.0417 0.0879 12.229 0.292 0.615

0.1 0.13 0.0130 0.0000 0.0051 0.0011 1.7488 0.0366 0.0868 13.452 0.282 0.668

0.09 0.117 0.0130 0.0000 0.0049 0.0012 1.7487 0.0317 0.0856 14.947 0.271 0.732

0.08 0.104 0.0130 0.0000 0.0047 0.0013 1.7487 0.0269 0.0843 16.815 0.259 0.811

0.07 0.091 0.0130 0.0000 0.0045 0.0014 1.7487 0.0224 0.0829 19.216 0.246 0.911

0.06 0.078 0.0130 0.0000 0.0043 0.0016 1.7487 0.0181 0.0813 22.419 0.232 1.042

0.05 0.065 0.0130 0.0000 0.0041 0.0018 1.7486 0.0140 0.0795 26.902 0.216 1.222

0.04 0.052 0.0130 0.0000 0.0038 0.0022 1.7486 0.0102 0.0773 33.627 0.197 1.486

0.03 0.039 0.0130 0.0000 0.0035 0.0026 1.7486 0.0068 0.0747 44.835 0.174 1.915

0.02 0.026 0.0130 0.0001 0.0031 0.0034 1.7485 0.0037 0.0713 67.250 0.144 2.742

0.01 0.013 0.0130 0.0001 0.0025 0.0048 1.7484 0.0012 0.0664 134.492 0.094 5.110

Appendix Chapter 6. U‐Th ages stalagmite GP2

sample comments Age ± min-Age max-Age U238 ± Th232 ± Th230 ± Th230/Th232 ± U238/Th232 ± Th230/U238 ± Th230excess/U238 ± U234/U238 ± U234/U238initialky ky ky ky ppm ppm ppb ppb ppt ppt dpm/dpm dpm/dpm dpm/dpm dpm/dpm dpm/dpm dpm/dpm dpm/dpm dpm/dpm dpm/dpm dpm/dpm

GP2 U3.1 2.782 0.018 2.764 2.800 1.485 0.002 0.130 0.001 3.729 0.013 5345 48.254 35290.406 296.390 0.151 0.001 0.151 0.001 6.000 0.012 6.040GP2U3 3.646 0.025 3.621 3.671 1.666 0.002 0.052 0.005 5.540 0.025 20063 1787.265 100014.015 8899.399 0.201 0.001 0.201 0.001 6.083 0.011 6.136GP2 U2.5.1 4.120 0.013 4.107 4.133 2.7213 0.0014 0.101 0.001 10.621 0.022 19596 207 83243 863 0.2354 0.0005 0.2354 0.0005 6.3268 0.0048 6.39GP2 U2.5 4.852 0.027 4.824 4.879 1.741 0.003 0.165 0.001 8.021 0.020 9070 60.237 32645.801 207.354 0.278 0.001 0.278 0.001 6.356 0.013 6.430GP2 U2.4.2 5.424 0.019 5.404 5.443 1.6951 0.0009 0.134 0.001 8.679 0.022 12085 98 39133 301 0.3088 0.0008 0.3088 0.0008 6.3326 0.0049 6.42GP2 U2.4.1 5.817 0.016 5.801 5.833 2.0606 0.0013 0.067 0.001 11.522 0.017 31923 577 94653 1706 0.3373 0.0005 0.3373 0.0006 6.4569 0.0057 6.55GP2 U2.4 5.995 0.040 5.955 6.034 1.875 0.003 0.063 0.001 10.895 0.032 32129 545.543 91664.041 1540.345 0.351 0.001 0.351 0.001 6.515 0.015 6.609GP2 U2.3.3 6.319 0.023 6.296 6.342 1.1591 0.0005 0.108 0.001 7.195 0.019 12424 126 33184 326 0.3744 0.0010 0.3744 0.0011 6.6091 0.0048 6.71GP2 U2.3.2 6.609 0.017 6.593 6.626 1.8374 0.0008 0.234 0.001 11.980 0.020 9579 59 24356 146 0.3933 0.0007 0.3933 0.0007 6.6432 0.0043 6.75GP2 U2.3.1 6.641 0.047 6.595 6.688 2.8050 0.0019 0.180 0.001 18.480 0.027 19182 115 48271 282 0.3974 0.0006 0.3974 0.0024 6.6812 0.0058 6.79GP2 U2.3 6.950 0.039 6.910 6.989 1.261 0.002 0.080 0.001 8.583 0.022 19918 252.130 48516.506 605.662 0.411 0.001 0.411 0.001 6.603 0.013 6.714GP2-U2.2a 7.338 0.022 7.316 7.360 6.4423 0.0042 0.224 0.005 47.540 0.095 39588 863.5 88940 1933 0.4451 0.0009 0.4451 0.0010 6.7889 0.0054 6.910GP2 U2.2 7.632 0.047 7.584 7.679 2.447 0.004 0.270 0.001 18.659 0.064 12892 77.515 28025.706 145.735 0.460 0.002 0.460 0.002 6.753 0.013 6.878GP2-U2.1a 8.407 0.060 8.346 8.467 2.3183 0.0015 0.129 0.005 19.339 0.118 28091 1141.8 55826 2244 0.5032 0.0031 0.5032 0.0031 6.7229 0.0055 6.861GP2 U2.1 8.714 0.044 8.670 8.759 2.843 0.003 0.213 0.001 24.419 0.076 21425 131.916 41352.735 223.894 0.518 0.002 0.518 0.002 6.685 0.009 6.827GP2-U2.0 9.060 0.028 9.031 9.088 3.1647 0.0017 0.460 0.005 28.439 0.054 11547 135.4 21304 247 0.5420 0.0011 0.5420 0.0012 6.7346 0.0056 6.883GP2U2 9.813 0.059 9.754 9.872 2.066 0.003 0.256 0.005 20.318 0.069 14832 285.270 25005.410 474.817 0.593 0.002 0.593 0.002 6.821 0.012 6.985GP2 U1.4 10.641 0.095 10.546 10.736 1.5897 0.0008 0.154 0.001 17.353 0.026 21086 166 32024 248 0.6584 0.0010 0.6584 0.0052 7.0015 0.0053 7.18GP2 U1.3 11.110 0.058 11.052 11.168 1.374 0.002 0.039 0.001 15.628 0.032 74688 2130.512 108874.482 3101.077 0.686 0.002 0.686 0.002 6.998 0.013 7.189GP2 U1.2 11.487 0.165 11.323 11.653 0.013 0.000 0.074 0.001 0.150 0.001 380 5.987 531.612 7.915 0.715 0.004 0.714 0.006 7.054 0.035 7.254

Appendix Chapter 6. Carbon and oxygen isotopes GP2

Sample Name  Depth (mm) from top "R" Age (kyr) BP (2010) d13C d18OGP2‐0 0.5 2.597162991 ‐3.94 ‐4.56

GP2‐0.1 1.104 2.616108993 ‐4.17 ‐4.68

GP2‐0.2 1.292 2.622008718 ‐4.02 ‐4.95

GP2‐0.3 1.832 2.638964521 ‐4.02 ‐4.67

GP2‐0.4 2.196 2.650404135 ‐3.70 ‐4.59

GP2‐1 2.891 2.672273133 ‐2.91 ‐4.38

GP2‐1.1 4 2.707151559 ‐3.02 ‐4.62

GP2‐1.2 4.5 2.722811164 ‐3.11 ‐4.60

GP2‐1.3 5.581 2.756485572 ‐2.96 ‐4.41

GP2‐1.4 6.419 2.782595592 ‐3.11 ‐4.50

GP2‐1.5 7.323 2.81094872 ‐2.93 ‐4.38

GP2‐1.6 8.238 2.839789197 ‐3.04 ‐4.44

GP2‐1.7 9 2.863833965 ‐3.18 ‐4.45

GP2‐1.8 9.637 2.883991521 ‐3.28 ‐4.19

GP2‐2 10.486 2.911094413 ‐3.79 ‐4.34

GP2‐2.1 11.732 2.951621557 ‐3.87 ‐4.60

GP2‐2.2 12.658 2.982269562 ‐3.60 ‐4.67

GP2‐2.3 13.232 3.001473723 ‐3.35 ‐4.47

GP2‐2.4 13.96 3.026113826 ‐3.38 ‐4.65

GP2‐2.5 14.797 3.054928314 ‐3.24 ‐4.64

GP2‐2.6 15.326 3.073409547 ‐3.36 ‐4.80

GP2‐2.7 15.899 3.093594678 ‐3.16 ‐4.61

GP2‐2.8 16.737 3.123280691 ‐3.19 ‐4.45

GP2‐2.9 17.619 3.154416464 ‐3.65 ‐4.57

GP2‐3 18.435 3.182654195 ‐4.28 ‐4.50

GP2‐3.1 20.022 3.235540104 ‐3.99 ‐4.63

GP2‐3.2 21.059 3.270279022 ‐4.05 ‐4.56

GP2‐3.3 21.654 3.290414899 ‐3.77 ‐4.53

GP2‐3.4 22.558 3.320522109 ‐3.84 ‐4.66

GP2‐3.5 23.44 3.348777716 ‐3.75 ‐4.47

GP2‐3.6 23.66 3.355695873 ‐3.68 ‐4.65

GP2‐3.7 24.388 3.37842351 ‐3.77 ‐4.65

GP2‐3.8 24.785 3.39079785 ‐3.72 ‐4.60

GP2‐3.9 25.49 3.412597277 ‐3.52 ‐4.45

GP2‐4 25.997 3.427873141 ‐2.39 ‐4.22

GP2‐4.1 26.923 3.454194925 ‐2.22 ‐4.07

GP2‐4.2 27.519 3.470077649 ‐2.06 ‐4.31

GP2‐4.3 28.158 3.486677234 ‐2.59 ‐4.64

GP2‐4.4 29.04 3.509690678 ‐2.99 ‐4.48

GP2‐4.5 29.856 3.53135969 ‐3.62 ‐4.55

GP2‐4.6 30.76 3.55559298 ‐4.07 ‐4.62

GP2‐4.7 31.598 3.578009929 ‐3.99 ‐4.52

GP2‐4.8 32.391 3.598851605 ‐3.80 ‐4.54

GP2‐4.9 32.964 3.613534078 ‐3.77 ‐4.29

GP2‐4.10 34 3.639644711 ‐3.82 ‐4.75

GP2‐4.11 34.64 3.655897421 ‐3.59 ‐4.36

GP2‐5 35.764 3.684104418 ‐4.63 ‐4.62

GP2‐5.1 36.933 3.708734911 ‐5.78 ‐5.02

GP2‐5.2 38.124 3.726681229 ‐5.80 ‐5.14

GP2‐5.3 38.719 3.733681543 ‐5.45 ‐4.94

GP2‐5.4 39.755 3.744398294 ‐5.24 ‐5.12

GP2‐5.5 40.637 3.753946245 ‐5.02 ‐5.23

GP2‐5.6 41.387 3.763417879 ‐4.56 ‐4.98

GP2‐5.7 42.225 3.775162828 ‐4.32 ‐4.65

GP2‐5.8 43.327 3.791621122 ‐4.64 ‐4.69

GP2‐5.9 44.165 3.804715525 ‐4.24 ‐4.79

GP2‐5.10 45.312 3.823471638 ‐3.75 ‐4.70

GP2‐6 46.524 3.843988327 ‐3.49 ‐4.42

GP2‐6.1 47.891 3.867342303 ‐3.66 ‐4.42

GP2‐6.2 48.861 3.883846406 ‐3.71 ‐4.51

GP2‐6.3 49.677 3.897668258 ‐3.87 ‐4.61

GP2‐6.4 50.868 3.917925996 ‐4.42 ‐4.72

GP2‐6.5 51.353 3.926223828 ‐4.22 ‐4.66

GP2‐6.6 52.367 3.943517461 ‐3.69 ‐4.84

GP2‐6.7 53.116 3.956136956 ‐3.88 ‐4.83

GP2‐6.8 53.888 3.969055036 ‐4.01 ‐4.82

GP2‐6.9 54.792 3.984232649 ‐4.58 ‐4.68

GP2‐6.10 55.74 4.000273631 ‐5.14 ‐4.82

GP2‐6.11 56.578 4.01444115 ‐4.70 ‐4.85

GP2‐6.12 57.5 4.029913566 ‐5.18 ‐4.60

GP2‐7 59 4.054906982 ‐2.53 ‐4.21

GP2‐7.1 59.5 4.063167132 ‐3.13 ‐4.32

GP2‐7.2 60 4.071330894 ‐3.24 ‐4.40

GP2‐7.3 61.142 4.089417601 ‐3.87 ‐4.95

GP2‐7.4 62 4.102599482 ‐4.26 ‐4.64

GP2‐7.5 63 4.117919488 ‐5.04 ‐4.75

GP2‐7.6 63.5 4.12566451 ‐4.91 ‐4.77

GP2‐7.7 64.713 4.144899294 ‐5.11 ‐4.69

GP2‐7.8 65.308 4.1546108 ‐5.63 ‐4.79

GP2‐7.9 65.903 4.164446584 ‐5.71 ‐4.92

GP2‐7.10 66.741 4.178388109 ‐5.44 ‐4.85

GP2‐7.11 67.777 4.195605657 ‐5.24 ‐4.70

GP2‐8 68.527 4.208011689 ‐4.78 ‐4.68

GP2‐8.1 70.137 4.234345514 ‐5.31 ‐4.82

GP2‐8.2 71.305 4.253135117 ‐4.97 ‐4.72

GP2‐8.3 72.099 4.265938381 ‐5.12 ‐4.82

GP2‐8.4 73.091 4.282253192 ‐4.83 ‐4.72

GP2‐8.5 73.709 4.292296004 ‐4.53 ‐4.54

GP2‐8.6 74.965 4.310647079 ‐5.00 ‐4.67

GP2‐8.7 75.913 4.321090519 ‐4.63 ‐4.54

GP2‐8.8 76.707 4.327910545 ‐4.54 ‐4.50

GP2‐9 77.28 4.333378022 ‐4.52 ‐4.50

GP2‐9.1 78.162 4.338412717 ‐4.90 ‐4.81

GP2‐9.2 78.802 4.338536012 ‐4.76 ‐4.77

GP2‐9.3 79.728 4.338714403 ‐4.93 ‐4.89

GP2‐9.4 80.367 4.338837505 ‐4.71 ‐4.83

GP2‐9.5 81.161 4.338990468 ‐4.27 ‐4.70

GP2‐9.6 82.175 4.345535206 ‐4.22 ‐4.71

GP2‐9.7 83.079 4.351629956 ‐4.68 ‐4.87

GP2‐9.8 84.336 4.357578074 ‐5.67 ‐4.88

GP2‐9.9 85.394 4.367460802 ‐5.25 ‐4.78

GP2‐10 86.519 4.380194721 ‐5.73 ‐4.75

GP2‐10.0 87.709 4.393542883 ‐5.60 ‐4.67

GP 2‐10.1 88.878 4.406602925 ‐5.66 ‐4.83

GP2‐10.1.1 89.98 4.419077706 ‐5.61 ‐4.85

GP 2‐10.2 91.171 4.432609685 ‐4.94 ‐4.64

GP2‐10.2.1 92.053 4.442621743 ‐4.82 ‐4.72

GP2‐11 93.64 4.460637632 ‐5.64 ‐4.79

GP2‐11.0.1 94.985 4.475877546 ‐4.41 ‐4.68

GP 2‐11.1 96.617 4.494305373 ‐4.35 ‐4.66

GP2‐11.2 97.874 4.508487908 ‐5.24 ‐4.78

GP2‐11.3 99.086 4.522215688 ‐5.31 ‐4.62

GP2‐11.4 99.946 4.53199068 ‐5.34 ‐4.59

GP2‐11.5 101.291 4.547273506 ‐5.61 ‐4.71

GP2‐11.6 101.975 4.555035285 ‐5.72 ‐4.88

GP2‐11.7 103.011 4.566787025 ‐5.81 ‐4.82

GP2‐12 103.606 4.573534654 ‐5.71 ‐4.73

GP2‐12.0.1 104.929 4.588524629 ‐5.65 ‐4.71

GP 2‐12.1 105.877 4.599261682 ‐5.56 ‐4.77

GP2‐12.1.1 106.958 4.611535194 ‐5.49 ‐4.84

GP2‐12.1.2 107.641 4.619310319 ‐5.49 ‐4.78

GP 2‐12.2 108.17 4.625336491 ‐5.55 ‐4.80

GP2‐12.2.1 109 4.634787287 ‐5.16 ‐4.73

GP 2‐12.3 109.78 4.643654463 ‐5.10 ‐4.66

GP2‐12.3.1 110.86 4.655895281 ‐5.66 ‐4.61

GP2‐13 111.544 4.66362919 ‐5.49 ‐4.60

GP2‐13.0.1 112.69 4.676602364 ‐5.09 ‐4.54

GP 2‐13.1 113.661 4.687632936 ‐4.79 ‐4.46

GP2‐13.2 114.741 4.699897427 ‐4.74 ‐4.47

GP2‐13.3 116.152 4.715873595 ‐5.05 ‐4.32

GP2‐13.4 117.144 4.727109375 ‐5.26 ‐4.54

GP2‐13.5 118.136 4.738347887 ‐5.34 ‐4.59

GP2‐14 119.349 4.752058891 ‐5.15 ‐4.59

GP2‐14.0.1 120.143 4.761018123 ‐5.07 ‐4.57

GP2‐14.1 121.311 4.774199402 ‐5.04 ‐4.71

GP2‐14.1.1 122.083 4.78291921 ‐4.76 ‐4.73

GP 2‐14.2 122.899 4.792144247 ‐4.37 ‐4.58

GP2‐15 124.09 4.805625943 ‐4.56 ‐4.42

GP2‐15.0.1 124.751 4.813117592 ‐4.68 ‐4.53

GP 2‐15.1 125.743 4.824370459 ‐5.19 ‐4.59

GP2‐15.1.1 126.603 4.834128513 ‐5.01 ‐4.57

GP 2‐15.2 127.617 4.845635653 ‐5.12 ‐4.56

GP2‐15.2.1 128.676 4.85767905 ‐4.88 ‐4.77

GP 2‐15.3 129.69 4.869241851 ‐5.01 ‐4.59

GP2‐15.3.1 130.44 4.877788317 ‐4.95 ‐4.60

GP2‐H4g 131.366 4.888306674 ‐4.22 ‐4.52

GP2‐H4g.0.1 132.358 4.899541318 ‐3.72 ‐4.59

GP 2‐H4g.1 133.24 4.909515961 ‐3.54 ‐4.48

GP2‐H4g.1.1 134.32 4.921722551 ‐3.16 ‐4.28

GP 2‐H4g.2 135.555 4.935678195 ‐3.78 ‐4.39

GP2‐H4g.2.1 136.172 4.94264544 ‐4.01 ‐4.41

GP2‐H4g.2.2 136.878 4.950609487 ‐4.32 ‐4.49

GP 2‐H4g.3 137.649 4.959306174 ‐5.37 ‐4.86

GP2‐H4g.3.1 138.84 4.972791071 ‐4.92 ‐4.59

GP2‐16 139.81 4.983832518 ‐4.83 ‐4.69

GP2‐16.0.1 140.714 4.994126749 ‐4.56 ‐4.41

GP 2‐16.1 141.552 5.00365283 ‐4.57 ‐4.41

GP2‐16.1.1 142.544 5.014936167 ‐4.45 ‐4.43

GP 2‐16.2 143.559 5.026507412 ‐4.20 ‐4.35

GP2‐16.2.1 144.529 5.037545228 ‐4.68 ‐4.65

GP 2‐16.3 145.389 5.047281308 ‐4.68 ‐4.61

GP2‐16.3.1 146.667 5.061708588 ‐4.71 ‐4.70

GP2‐17 147.615 5.072417565 ‐4.62 ‐4.69

GP2‐17.0.1 148.674 5.08438091 ‐5.05 ‐4.71

GP 2‐17.1 149.688 5.095835866 ‐5.28 ‐4.81

GP2‐17.1.1 150.7 5.107305325 ‐4.89 ‐4.50

GP 2‐17.2 151.915 5.121129661 ‐5.16 ‐4.71

GP2‐17.2.1 152.863 5.131884969 ‐4.89 ‐4.46

GP 2‐17.3 154.164 5.146572121 ‐5.12 ‐4.77

GP2‐17.3.1 155.2 5.158274783 ‐4.56 ‐4.65

GP 2‐17.4 156.391 5.171726837 ‐4.44 ‐4.66

GP2‐17.4.1 157.339 5.1823954 ‐4.64 ‐4.63

GP2‐18 158.552 5.196081303 ‐4.97 ‐4.78

GP2‐18.0.1 159.764 5.209882579 ‐4.78 ‐4.73

GP 2‐18.1 161.043 5.224425363 ‐4.35 ‐4.60

GP2‐18.1.1 161.969 5.234893785 ‐3.42 ‐4.38

GP 2‐18.2 163.248 5.24936371 ‐3.58 ‐4.32

GP2‐18.2.1 164.13 5.259368025 ‐4.01 ‐4.45

GP 2‐18.3 165.497 5.274886607 ‐4.31 ‐4.57

GP2‐18.3.1 166.379 5.284903638 ‐4.77 ‐4.62

GP2‐19 167.239 5.294675336 ‐4.71 ‐4.61

GP2‐19.0.1 168.165 5.30519906 ‐4.79 ‐4.56

GP 2‐19.1 169.399 5.319217658 ‐5.45 ‐4.81

GP2‐19.1.1 170.259 5.328974298 ‐5.75 ‐4.81

GP2‐19.1.2 171.23 5.339967696 ‐6.13 ‐5.04

GP 2‐19.2 172.31 5.352176283 ‐5.63 ‐4.91

GP2‐19.2.1 172.993 5.359895647 ‐5.83 ‐4.93

GP2‐19.2.2 173.941 5.370611462 ‐5.31 ‐4.73

GP 2‐19.3 175.044 5.383078755 ‐5.18 ‐4.77

GP2‐19.3.1 175.727 5.390803313 ‐5.25 ‐4.79

GP2‐19.3.2 176.565 5.400298231 ‐4.50 ‐4.63

GP2‐19.3.3 177.513 5.411091792 ‐4.35 ‐4.63

GP2‐19.3.4 178.528 5.422793197 ‐4.35 ‐4.62

GP2‐19.3.5 181 5.450848255 ‐3.93 ‐4.56

GP 2‐19.4 182.41 5.468332403 ‐4.14 ‐4.57

GP2‐19.4.1 183.41 5.484654498 ‐4.59 ‐4.78

GP2‐20 184.998 5.498258291 ‐4.07 ‐4.49

GP2‐20.0.1 185.939 5.509299213 ‐4.45 ‐4.71

GP2‐20.1 187.056 5.577905209 ‐3.82 ‐4.20

GP2‐20.1.1 188.15 5.680538741 ‐3.42 ‐4.50

GP 2‐20.2 189.643 5.731492189 ‐3.83 ‐4.53

GP2‐20.2.1 190.76 5.732371301 ‐3.47 ‐4.50

GP2‐20.2.2 191.525 5.738210497 ‐4.18 ‐4.48

GP 2‐20.3 193.053 5.760145189 ‐4.12 ‐4.36

GP2‐20.3.1 193.759 5.767713047 ‐4.00 ‐4.45

GP2‐20.3.2 194.994 5.780446806 ‐3.65 ‐4.64

GP2‐21 195.699 5.788494884 ‐4.26 ‐4.62

GP2‐21.0.1 197.052 5.804000415 ‐5.20 ‐4.98

GP2‐21.1 198.228 5.816709223 ‐4.91 ‐4.65

GP2‐21.1.1 199.345 5.828465611 ‐4.65 ‐4.95

GP2‐21.1.2 200.403 5.83952556 ‐5.58 ‐4.94

GP2‐21.2 201.697 5.853075982 ‐5.67 ‐4.65

GP2‐21.2.1 202.755 5.864142331 ‐6.00 ‐5.09

GP2‐21.3 203.99 5.87701711 ‐5.90 ‐4.80

GP2‐21.3.1 204.695 5.884375132 ‐5.57 ‐4.93

GP2‐21.3.2 205.871 5.896674121 ‐5.45 ‐4.94

GP2‐22 206.636 5.904656354 ‐5.21 ‐4.82

GP2‐22.0.1 207.576 5.914432371 ‐5.14 ‐5.04

GP2‐22.0.2 208.694 5.926108368 ‐5.06 ‐4.95

GP 2‐22.1 209.282 5.932296514 ‐4.99 ‐5.04

GP2‐22.1.1 210.34 5.943436746 ‐5.20 ‐5.18

GP 2‐22.2 211.986 5.960584908 ‐5.30 ‐4.99

GP2‐22.2.1 212.692 5.967914764 ‐5.26 ‐4.86

GP2‐22.2.2 213.574 5.977095407 ‐5.31 ‐4.79

GP 2‐22.3 215.161 5.993663233 ‐4.64 ‐4.76

GP2‐22.3.1 216.102 6.003478458 ‐4.76 ‐4.64

GP2‐23 217.101 6.013840762 ‐4.11 ‐4.64

GP 2‐23.1 218.513 6.028459986 ‐3.68 ‐4.49

GP2‐23.1.1 219.512 6.03888166 ‐5.08 ‐4.74

GP 2‐23.2 220.512 6.049351998 ‐5.28 ‐4.81

GP2‐23.2.1 221.629 6.061029938 ‐5.13 ‐4.68

GP 2‐23.3 223.099 6.076321288 ‐5.17 ‐4.79

GP2‐23.3.1 224.216 6.087906996 ‐5.52 ‐4.78

GP 2‐23.4 225.039 6.096470851 ‐5.09 ‐4.80

GP2‐23.4.1 226.274 6.109370683 ‐3.80 ‐4.59

GP2‐24 227.508 6.122271994 ‐5.19 ‐4.76

GP2‐24.0.1 228.626 6.133944376 ‐4.63 ‐4.63

GP2‐24.02 229.6 6.144094981 ‐4.76 ‐4.58

GP 2‐24.1 230.684 6.155392048 ‐5.02 ‐4.66

GP2‐24.1.1 231.918 6.168276603 ‐4.69 ‐4.75

GP 2‐24.2 233.153 6.181201497 ‐4.91 ‐4.71

GP2‐24.2.1 234.27 6.192900018 ‐4.66 ‐4.88

GP 2‐24.3 235.505 6.205808739 ‐5.13 ‐4.96

GP2‐24.3.1 236.504 6.216222393 ‐5.26 ‐4.97

GP2‐24.3.2 237.32 6.224712985 ‐5.33 ‐4.93

GP2‐25 238.268 6.234586085 ‐5.13 ‐4.89

GP2‐25.0.1 239.327 6.245658445 ‐5.77 ‐5.10

GP 2‐25.1 240.561 6.258548789 ‐5.69 ‐4.90

GP2‐25.1.1 241.62 6.269546085 ‐5.63 ‐5.00

GP 2‐25.2 242.737 6.281213305 ‐5.86 ‐4.99

GP2‐25.2.1 243.56 6.289897798 ‐5.74 ‐5.11

GP2‐25.2.2 244.67 6.301563535 ‐5.69 ‐5.16

GP 2‐25.3 245.667 6.311906831 ‐5.66 ‐5.00

GP2‐25.3.1 246.559 6.321182629 ‐5.68 ‐5.13

GP2‐25.3.2 247.264 6.328600552 ‐4.04 ‐4.72

GP2‐H3d 248.382 6.340439459 ‐4.93 ‐4.85

GP2‐H3d.0.1 249.616 6.353508341 ‐5.15 ‐5.04

GP 2‐H3d.1 250.498 6.363047844 ‐4.06 ‐4.61

GP2‐H3d.1.1 252.027 6.380562957 ‐3.17 ‐4.60

GP 2‐H3d.2 252.85 6.390697263 ‐4.44 ‐4.69

GP2‐H3d.2.1 254.79 6.41603809 ‐5.00 ‐4.99

GP2‐H3d.2.2 255.79 6.430269847 ‐4.84 ‐4.68

GP 2‐H3d.3 256.789 6.448165202 ‐3.95 ‐4.55

GP2‐H3d.3.1 257.965 6.473604205 ‐3.71 ‐4.63

GP2‐H3d.3.2 258.847 6.491226066 ‐3.96 ‐4.68

GP2‐H3d.3.3 260.023 6.510113198 ‐4.28 ‐4.64

GP2‐26 260.964 6.523582709 ‐3.19 ‐4.43

GP2‐26.0.1 261.963 6.537439013 ‐3.17 ‐4.58

GP2‐26.0.2 262.904 6.549861957 ‐4.17 ‐4.75

GP 2‐26.1 263.668 6.559433782 ‐4.07 ‐4.56

GP2‐26.1.1 264.962 6.574791315 ‐3.74 ‐4.71

GP 2‐26.2 266.256 6.588986044 ‐3.60 ‐4.51

GP2‐26.2.1 267.784 6.603747465 ‐4.40 ‐4.93

GP2‐26.2.2 268.372 6.609129925 ‐5.19 ‐5.00

GP 2‐26.3 269.43 6.618915231 ‐5.36 ‐4.83

GP2‐26.3.1 271.136 6.634886192 ‐5.63 ‐5.09

GP2‐27 272.018 6.643121142 ‐5.32 ‐5.02

GP2‐27.0.1 273.311 6.655031777 ‐5.53 ‐5.30

GP 2‐27.1 274.722 6.666155736 ‐5.43 ‐5.08

GP2‐27.1.1 275.781 6.672209981 ‐5.45 ‐5.07

GP 2‐27.2 277.192 6.677889261 ‐5.43 ‐4.91

GP2‐27.2.1 278.191 6.679098241 ‐5.48 ‐5.15

GP2‐27.2.2 279.25 6.679104536 ‐5.26 ‐5.23

GP 2‐27.3 280.132 6.679109778 ‐5.68 ‐5.15

GP2‐27.3.1 281.602 6.687604642 ‐5.50 ‐5.17

GP2‐28 283.071 6.708951188 ‐5.59 ‐5.08

GP2‐28.0.1 284.541 6.729458853 ‐5.07 ‐5.11

GP 2‐28.1 286.07 6.748720703 ‐4.54 ‐4.73

GP2‐28.1.1 287.364 6.766117379 ‐4.77 ‐4.93

GP 2‐28.2 288.422 6.781074679 ‐4.64 ‐4.72

GP2‐28.2.1 289.421 6.794783609 ‐4.65 ‐4.86

GP2‐28.2.2 290.009 6.802779843 ‐4.57 ‐5.14

GP 2‐28.3 290.95 6.81591139 ‐4.91 ‐5.00

GP2‐28.3.1 292.067 6.832295674 ‐4.69 ‐5.20

GP2‐28.3.2 292.773 6.843042408 ‐4.91 ‐5.17

GP2‐29 293.419 6.853079025 ‐4.46 ‐4.83

GP 2‐29.1 294.889 6.876222155 ‐4.81 ‐4.89

GP 2‐29.2 296.771 6.906254311 ‐4.33 ‐4.68

GP 2‐29.3 298.182 6.929834417 ‐4.27 ‐4.73

GP 2‐29.4(2) 300.064 6.963530382 ‐3.71 ‐4.76

GP2‐29.4 301.416 6.988746028 ‐2.87 ‐4.66

GP2‐29.4.1 302.65 7.012712079 ‐2.73 ‐4.61

GP2‐29.4.2 304.003 7.040594658 ‐3.08 ‐4.62

GP2‐30 304.65 7.054382272 ‐3.59 ‐4.68

GP2‐30.1 305.708 7.077342465 ‐3.77 ‐4.79

GP2‐30.2 307.766 7.122988596 ‐4.83 ‐5.04

GP2‐30.3 308.53 7.140233104 ‐4.37 ‐5.09

GP2‐30.4 310 7.17370839 ‐4.82 ‐5.22

GP2‐30.5 311.2 7.200611833 ‐5.11 ‐5.23

GP2‐30.6 312.5 7.229157374 ‐5.04 ‐5.33

GP2‐30.7 314 7.26183759 ‐5.11 ‐5.15

GP2‐30.8 316 7.299629101 ‐5.45 ‐5.22

GP2‐30.9 317.5 7.314720912 ‐5.58 ‐5.45

GP2‐30.10 318.5 7.324472203 ‐5.44 ‐5.37

GP2‐31 319.407 7.333483433 ‐5.26 ‐5.23

GP2‐31.1 320.407 7.343445944 ‐5.34 ‐5.31

GP2‐31.2 321.407 7.353195561 ‐5.24 ‐5.18

GP2‐31.3 321.994 7.358850246 ‐5.17 ‐5.19

GP2‐31.4 322.494 7.3636665 ‐5.17 ‐5.18

GP2‐31.5 323.817 7.37649867 ‐5.14 ‐5.26

GP2‐31.6 324.417 7.382328058 ‐5.06 ‐5.10

GP2‐31.7 325.346 7.391276284 ‐5.01 ‐5.18

GP2‐31.8 325.846 7.395970872 ‐4.70 ‐5.01

GP2‐31.9 326.846 7.404882519 ‐4.80 ‐5.10

GP2‐31.10 327.846 7.413735156 ‐4.90 ‐4.93

GP2‐31.11 328.846 7.424354216 ‐4.91 ‐4.97

GP2‐31.12 329.846 7.436878528 ‐5.10 ‐4.92

GP2‐31.13 330.846 7.448738789 ‐5.05 ‐4.88

GP2‐31.14 332.283 7.456966711 ‐4.82 ‐5.09

GP2‐32 333.636 7.457261482 ‐4.94 ‐5.02

GP2‐32.1 334.636 7.457479346 ‐5.01 ‐5.08

GP2‐32.2 335.136 7.457588278 ‐5.13 ‐5.27

GP2‐32.3 336.136 7.457806143 ‐5.29 ‐5.31

GP2‐32.4 336.636 7.457915075 ‐5.11 ‐4.92

GP2‐32.5 337.636 7.45813294 ‐5.09 ‐5.06

GP2‐32.6 340.136 7.458677601 ‐5.00 ‐4.63

GP2‐32.7 342.636 7.459222262 ‐5.29 ‐4.91

GP2‐32.8 345.136 7.462890886 ‐5.28 ‐4.89

GP2‐32.9 346.136 7.465892005 ‐5.54 ‐4.90

GP2‐33 347.747 7.473842255 ‐5.60 ‐5.02

GP2‐33.1 349.099 7.483582113 ‐5.63 ‐4.98

GP2‐33.2 350 7.491239171 ‐5.65 ‐5.07

GP2‐33.3 350.52 7.495775754 ‐5.62 ‐5.21

GP2‐33.4 351.686 7.505772289 ‐5.39 ‐5.01

GP2‐33.5 352.568 7.513273167 ‐5.40 ‐5.02

GP2‐33.6 353.685 7.522850248 ‐5.48 ‐5.11

GP2‐33.7 354.567 7.530431506 ‐5.53 ‐5.06

GP2‐33.8 355.449 7.537993185 ‐5.29 ‐5.04

GP2‐34 356.39 7.54608497 ‐5.32 ‐5.00

GP2‐34.1 357.389 7.554754573 ‐5.50 ‐5.03

GP2‐34.2 357.977 7.559873925 ‐5.47 ‐5.01

GP2‐34.3 358.859 7.567523898 ‐5.48 ‐5.06

GP2‐34.4 360.035 7.577652514 ‐5.37 ‐4.96

GP2‐34.5 361.048 7.586369959 ‐5.37 ‐4.90

GP2‐34.6 361.93 7.593973303 ‐5.05 ‐4.81

GP2‐34.7 363.253 7.605380038 ‐5.18 ‐4.93

GP2‐34.8 364.311 7.614489873 ‐4.60 ‐4.83

GP 2‐35 365.017 7.621543986 ‐4.24 ‐4.88

GP2‐35.1 365.767 7.634445503 ‐2.30 ‐4.59

GP2‐35.2 366.296 7.643567044 ‐2.86 ‐4.70

GP2‐35.3 366.913 7.654244667 ‐2.77 ‐4.64

GP2‐35.4 368.325 7.678728442 ‐3.56 ‐4.80

GP2‐35.5 369.119 7.692421777 ‐4.02 ‐4.60

GP2‐35.6 370.927 7.723718435 ‐4.33 ‐5.00

GP2‐35.7 372.1 7.74429937 ‐4.81 ‐5.08

GP2‐35.8 372.294 7.7477024 ‐4.87 ‐5.18

GP2‐35.9 373.53 7.769249951 ‐4.90 ‐5.01

GP2‐35.10 374.058 7.778380678 ‐5.02 ‐5.20

GP2‐35.11 375.293 7.799584235 ‐4.77 ‐5.01

GP2‐36 376.881 7.826750951 ‐4.71 ‐4.99

GP2‐36.1 377.94 7.844966231 ‐4.77 ‐5.05

GP2‐36.2 379.218 7.867101724 ‐4.70 ‐5.00

GP2‐36.3 380.012 7.88087187 ‐4.54 ‐5.09

GP2‐36.4 381.114 7.899831161 ‐4.30 ‐5.05

GP2‐36.5 382.041 7.915613871 ‐3.98 ‐4.97

GP2‐36.6 382.305 7.92008893 ‐3.62 ‐4.97

GP2‐36.7 383.717 7.943960151 ‐3.84 ‐4.95

GP2‐36.8 384.202 7.952169243 ‐3.63 ‐5.01

GP2‐37 385.569 7.975456985 ‐4.10 ‐4.82

GP2‐37.1 386.803 7.996680836 ‐4.68 ‐4.91

GP2‐37.2 387.979 8.016999528 ‐4.88 ‐4.81

GP2‐37.3 388.626 8.028141075 ‐4.86 ‐4.86

GP2‐37.4 389.92 8.050309582 ‐4.71 ‐4.63

GP2‐37.5 390.743 8.064451146 ‐4.06 ‐4.58

GP2‐37.6 391.801 8.082722649 ‐4.16 ‐4.53

GP2‐37.7 392.683 8.097891962 ‐4.33 ‐4.69

GP2‐37.8 393.859 8.117939832 ‐4.34 ‐4.68

GP2‐37.9 394.8 8.133994333 ‐4.24 ‐4.94

GP2‐37.10 395.799 8.151151274 ‐4.11 ‐4.84

GP2‐T6 396.799 8.168396235 ‐4.12 ‐5.00

GP2‐37.11 397.299 8.177031093 ‐4.12 ‐4.95

GP2‐37.12 398.299 8.194319578 ‐3.96 ‐4.91

GP2‐37.13 399.299 8.211627559 ‐4.20 ‐5.03

GP2‐T5 400.799 8.237582804 ‐4.10 ‐4.92

GP2‐T4.1 402.799 8.271938163 ‐3.50 ‐4.98

GP2‐T4 403.799 8.288958094 ‐3.90 ‐4.89

GP2‐37.14 405.299 8.314800522 ‐3.95 ‐5.07

GP2‐T3.1 406.299 8.332181645 ‐4.31 ‐5.23

GP2‐37.15 407.299 8.349386069 ‐4.38 ‐5.38

GP2‐T3 408.299 8.36642773 ‐4.67 ‐5.40

GP2‐37.16 409.299 8.383436664 ‐4.44 ‐5.28

GP2‐37.17 410.299 8.400472544 ‐4.49 ‐5.19

GP2‐37.18 411.299 8.41756659 ‐4.71 ‐5.12

GP2‐37.19 412.799 8.443442741 ‐4.49 ‐4.96

GP2‐T2 413.858 8.461867593 ‐4.61 ‐4.99

GP2‐37.20 414.519 8.473316282 ‐4.01 ‐4.84

GP2‐37.21 416.13 8.50090515 ‐4.46 ‐4.95

GP2‐T1 417.15 8.518428537 ‐3.24 ‐4.75

GP2‐37.22 417.852 8.530639168 ‐2.84 ‐4.71

GP2‐37.23 418.868 8.548634264 ‐3.01 ‐4.65

GP2‐37.24 419.617 8.561895786 ‐3.13 ‐4.67

GP2‐37.25 420.465 8.576127801 ‐3.15 ‐4.80

GP2‐37.26 421.293 8.589010754 ‐2.96 ‐4.72

GP2‐37.27 422.441 8.609869751 ‐2.44 ‐4.56

GP2‐37.28 423.058 8.624366743 ‐2.29 ‐4.70

GP2‐37.29 424.16 8.642146075 ‐2.44 ‐4.65

GP2‐37.30 424.998 8.648921467 ‐2.58 ‐4.75

GP2‐H2f 426.234 8.660389998 ‐3.15 ‐4.86

GP2‐H2f.1 427.292 8.779111591 ‐3.46 ‐4.99

GP2‐H2f.2 428.394 8.935748228 ‐3.50 ‐4.87

GP2‐H2f.3 429.232 8.993729867 ‐3.41 ‐5.00

GP2‐H2f.4 430.379 9.007347249 ‐3.77 ‐5.10

GP2‐H2f.5 431.613 9.023139251 ‐4.49 ‐4.99

GP2‐H2f.6 432.407 9.038673226 ‐4.59 ‐4.96

GP2‐H2f.7 433.509 9.05602234 ‐4.22 ‐4.83

GP2‐H2f.8 434.524 9.069215114 ‐4.27 ‐4.92

GP2‐H2f.9 435.274 9.079498065 ‐4.54 ‐5.01

GP2‐H2f.10 435.98 9.089621103 ‐4.44 ‐4.96

GP2‐38 437.216 9.107282056 ‐4.42 ‐4.88

GP2‐38.1 438.627 9.127052662 ‐4.51 ‐5.18

GP2‐38.2 439.95 9.14575883 ‐4.63 ‐5.05

GP2‐38.3 440.876 9.158845399 ‐4.48 ‐4.91

GP2‐38.4 442.464 9.18113678 ‐4.36 ‐4.87

GP2‐38.5 443.126 9.190415779 ‐4.89 ‐4.88

GP2‐38.6 444.892 9.215232753 ‐4.85 ‐4.98

GP2‐38.7 445.245 9.220208476 ‐5.11 ‐5.04

GP2‐38.8 446.26 9.234511716 ‐5.11 ‐5.14

GP2‐38.9 446.613 9.23947605 ‐5.05 ‐5.02

GP2‐T39a 447.613 9.253504184 ‐4.32 ‐5.04

GP2‐39.0.1a 448.73 9.269164515 ‐3.32 ‐4.58

GP2‐39.0.2a 449.436 9.279078775 ‐3.91 ‐4.72

GP2‐T39.1a 450.435 9.293107253 ‐3.63 ‐4.92

GP2‐39.1.1a 451.317 9.305468989 ‐4.14 ‐4.87

GP2‐39.1.2a 452.552 9.32273712 ‐4.70 ‐5.10

GP2‐39.1.3a 453.61 9.337505219 ‐4.86 ‐5.06

GP2‐T40a 454.434 9.349009253 ‐4.91 ‐5.15

GP2‐40.0.1a 455.433 9.362976653 ‐5.00 ‐4.99

GP2‐40.0.2a 456.492 9.377798521 ‐4.91 ‐4.89

GP2‐T40.1a 457.491 9.391779842 ‐4.75 ‐4.81

GP2‐40.1.1a 458.491 9.405759741 ‐5.06 ‐4.92

GP2‐40.1.2a 459.491 9.419718851 ‐4.88 ‐4.90

GP2‐40.1.3a 460.314 9.431213233 ‐4.60 ‐4.94

GP2‐40.2a 461.784 9.451794949 ‐4.59 ‐4.76

GP2‐40.2.1a 462.843 9.466590175 ‐4.87 ‐4.89

GP2‐40.2.2a 463.901 9.481309239 ‐4.77 ‐4.80

GP2‐40.2.3a 464.489 9.489483405 ‐4.71 ‐4.95

GP2‐40.3a 466.076 9.511583139 ‐4.66 ‐4.68

GP2‐40.3.1a 467.487 9.531267879 ‐4.46 ‐4.71

GP2‐T41a 469.016 9.552683195 ‐4.21 ‐4.83

GP2‐41.0a 470.309 9.570850886 ‐4.08 ‐4.72

GP2‐41.1a 471.426 9.586501834 ‐4.23 ‐4.58

GP2‐41.1.1a 472.544 9.602126388 ‐4.51 ‐4.81

GP2‐41.1.2a 473.429 9.614492815 ‐4.41 ‐4.72

GP2‐41.1.3a 474.072 9.623495989 ‐4.24 ‐4.57

GP2‐41.2a 475.072 9.637558655 ‐4.22 ‐4.57

GP2‐41.2.1a 476.13 9.652485187 ‐4.52 ‐4.82

GP2‐41.2.2a 477 9.664733539 ‐4.68 ‐4.83

GP2‐41.3a 478.247 9.682235489 ‐4.63 ‐4.63

GP2‐41.3.1a 479.246 9.696255904 ‐4.58 ‐4.55

GP2‐41.3.2a 480.128 9.708637644 ‐4.83 ‐4.66

GP2‐41.3.3a 480.951 9.720181998 ‐4.57 ‐4.56

GP2‐T42a 481.833 9.732532468 ‐4.60 ‐4.74

GP2‐42.0.1a 482.48 9.741571509 ‐4.75 ‐4.63

GP2‐42.1a 483.362 9.753868582 ‐4.28 ‐4.64

GP2‐42.1.1a 484.479 9.769485881 ‐3.87 ‐4.65

GP2‐42.2a 485.42 9.782748267 ‐3.82 ‐4.45

GP2‐42.2.1a 486.419 9.796870522 ‐4.51 ‐4.58

GP2‐T43a 486.949 9.804346475 ‐4.70 ‐4.76

GP2‐43.0.1a 487.831 9.816750276 ‐4.01 ‐4.55

GP2‐43.0.2a 488.801 9.830351365 ‐3.87 ‐4.54

GP2‐43.1a 490.016 9.847369041 ‐4.80 ‐4.51

GP2‐43.1.1a 490.868 9.859329203 ‐4.81 ‐4.62

GP2‐43.2a 492.015 9.875488112 ‐3.57 ‐4.58

GP2‐T44a 493.5 9.896468095 ‐4.30 ‐4.60

GP2‐44.1 494.179 9.906050649 ‐4.59 ‐4.48

GP2‐44.2 495.119 9.919266465 ‐4.41 ‐4.53

GP2‐44.3 495.942 9.930806364 ‐4.67 ‐4.57

GP2‐44.4 497 9.945663941 ‐4.73 ‐4.64

GP2‐44.5 497.706 9.955600135 ‐4.22 ‐4.61

GP2‐44.6 499.058 9.974604098 ‐4.25 ‐4.57

GP2‐44.7 500.175 9.990276215 ‐4.54 ‐4.52

GP2‐44.8 500.998 10.00184746 ‐4.63 ‐4.60

GP2‐45 502.056 10.01674859 ‐4.25 ‐4.52

GP2‐45.1 502.997 10.02998419 ‐3.46 ‐4.47

GP2‐45.2 503.82 10.0415397 ‐3.19 ‐4.35

GP2‐45.3 504.761 10.05475267 ‐3.34 ‐4.25

GP2‐45.4 505.643 10.06716331 ‐3.85 ‐4.39

GP2‐45.5 506.349 10.07713458 ‐3.82 ‐4.31

GP2‐45.6 507.407 10.09215615 ‐4.20 ‐4.39

GP2‐45.7 508.407 10.106377 ‐4.19 ‐4.46

GP2‐45.8 509.23 10.11804179 ‐4.10 ‐4.49

GP2‐45.9 510.171 10.13135553 ‐4.01 ‐4.46

GP2‐45.10 511.17 10.1455192 ‐3.86 ‐4.49

GP2‐45.11 512.346 10.16227627 ‐3.91 ‐4.39

GP2‐45.12 513.581 10.17999048 ‐4.51 ‐4.52

GP2‐46 514.58 10.19437977 ‐5.06 ‐4.61

GP2‐46.1 515.756 10.21133747 ‐4.57 ‐4.56

GP2‐46.2 516.814 10.22656519 ‐4.70 ‐4.53

GP2‐46.3 517.696 10.23922556 ‐4.56 ‐4.50

GP2‐46.4 519.166 10.26031179 ‐5.00 ‐4.52

GP2‐46.5 519.696 10.26791717 ‐4.43 ‐4.32

GP2‐46.6 520.636 10.28140198 ‐4.50 ‐4.52

GP2‐46.7 521.695 10.29656689 ‐5.21 ‐4.70

GP2‐46.8 522.821 10.31260832 ‐3.61 ‐4.25

GP2‐47 523.753 10.32583241 ‐5.50 ‐4.63

GP2‐47.1 524.635 10.33839398 ‐5.48 ‐4.65

GP2‐47.2 525.693 10.35356432 ‐5.72 ‐4.71

GP2‐40 (48) 526.693 10.36785455 ‐5.34 ‐4.81

GP2‐48.1 527.633 10.38116269 ‐5.35 ‐4.80

GP2‐48.2 528.692 10.39613935 ‐5.14 ‐4.75

GP2‐48.3 529.75 10.41117075 ‐5.43 ‐4.77

GP2‐48.4 531.22 10.43197034 ‐5.72 ‐4.87

GP2‐48.5 532.219 10.44602625 ‐5.03 ‐4.63

GP2‐48.6 533.336 10.46177545 ‐4.49 ‐4.69

GP2‐48.7 534.159 10.47340472 ‐5.01 ‐4.67

GP2‐49 535.217 10.48835036 ‐4.66 ‐4.46

GP2‐49.1 536.335 10.50413109 ‐5.07 ‐4.52

GP2‐49.2 537.569 10.5215464 ‐5.14 ‐4.44

GP2‐49.3 538.922 10.54063025 ‐4.45 ‐4.43

GP2‐50 540.068 10.55679508 ‐5.21 ‐4.64

GP2‐50.1 540.95 10.56926246 ‐5.48 ‐4.81

GP2‐50.2 541.788 10.58111732 ‐4.89 ‐4.52

GP2‐50.3 542.802 10.59541394 ‐4.58 ‐4.46

GP2‐50.4 544.802 10.6234891 ‐4.44 ‐4.40

GP2‐50.5 546.301 10.64464261 ‐4.89 ‐4.40

GP2‐50.6 546.83 10.65213092 ‐5.17 ‐4.42

GP2‐50.7 547.948 10.6679519 ‐5.34 ‐4.42

GP2‐50.8 548.8 10.67995095 ‐5.58 ‐4.28

GP2‐50.9 549.565 10.6906648 ‐5.37 ‐4.14

GP2‐51 550.594 10.70503075 ‐5.31 ‐4.18

GP2‐51.1 552.034 10.72511281 ‐4.57 ‐4.02

GP2‐51.2 552.504 10.73165519 ‐4.58 ‐4.16

GP2‐51.3 553.386 10.74390507 ‐4.72 ‐4.45

GP2‐51.4 554.033 10.75286595 ‐4.87 ‐4.37

GP2‐51.5 555.21 10.76910937 ‐4.91 ‐4.32

GP2‐51.6 556.474 10.78649629 ‐5.81 ‐4.49

GP2‐51.7 557.708 10.80343307 ‐5.43 ‐4.21

GP2‐51.8 558.443 10.81346015 ‐5.58 ‐4.11

GP2‐51.9 559.267 10.82460725 ‐5.28 ‐4.13

GP2‐52 560.56 10.84188892 ‐5.00 ‐4.11

GP2‐52.1 561.973 10.86053641 ‐5.70 ‐4.13

GP2‐52.2 562.723 10.87040256 ‐6.02 ‐4.20

GP2‐52.3 563.737 10.8837512 ‐5.75 ‐4.17

GP2‐52.4 564.619 10.89534863 ‐5.52 ‐4.17

GP2‐52.5 565.765 10.9103929 ‐5.55 ‐4.43

GP2‐52.6 566.956 10.92609253 ‐5.41 ‐4.36

GP2‐52.7 567.706 10.93603976 ‐5.24 ‐4.22

GP2‐52.8 568.808 10.95071302 ‐5.48 ‐4.27

GP2‐52.9 569.646 10.96189968 ‐5.47 ‐4.34

GP2‐52.10 570.748 10.97664097 ‐5.82 ‐4.38

GP2‐53 571.939 10.99259418 ‐5.27 ‐4.37

GP2‐53.1 573.174 11.00911921 ‐5.92 ‐4.44

GP2‐53.2 574.1 11.02151798 ‐5.93 ‐4.55

GP2‐53.3 575.202 11.0363491 ‐5.58 ‐4.59

GP2‐53.4 576.349 11.05183432 ‐5.82 ‐4.69

GP2‐53.5 577.363 11.06549723 ‐5.99 ‐4.57

GP2‐53.6 578.421 11.07984831 ‐5.79 ‐4.40

GP2‐53.7 579.347 11.0926204 ‐5.75 ‐4.41

GP2‐53.8 580.141 11.10371198 ‐5.58 ‐4.36

GP2‐54 581.199 11.11863739 ‐5.14 ‐4.48

GP2‐54.1 582.478 11.13733295 ‐5.04 ‐4.52

GP2‐54.2 583.404 11.15169148 ‐3.49 ‐3.80

GP2‐54.3 584.595 11.17082866 ‐4.38 ‐3.75

GP2‐54.4 585.653 11.18785619 ‐4.75 ‐4.03

GP2‐54.5 587.755 11.21975526 ‐4.94 ‐3.85

GP2‐54.6 589.048 11.24110453 ‐4.28 ‐3.82

GP2‐54.7 589.812 11.25473533 ‐3.83 ‐3.84

GP2‐55 591.165 11.2763364 ‐2.92 ‐3.94

GP2‐55.1 592.223 11.29333464 ‐3.23 ‐3.94

GP2‐55.2 593.046 11.3111406 ‐3.39 ‐4.11

GP2‐55.3 594.163 11.34061865 ‐3.27 ‐3.99

GP2‐55.4 595.104 11.36530265 ‐3.18 ‐3.99

GP2‐55.5 596.221 11.39083063 ‐3.73 ‐4.09

GP2‐55.6 597.103 11.40714744 ‐3.30 ‐4.08

GP2‐55.7 598.278 11.4253813 ‐2.06 ‐3.60

GP2‐55.8 598.925 11.43521649 ‐1.94 ‐3.70

GP2‐55.9 600.219 11.45537884 ‐1.75 ‐3.67

GP2‐55.10 601.572 11.47594207 ‐2.08 ‐3.47

Corrected towards aragonite.

Appendix Chapter 6. Trace elements GP2

Sample nr Depth new (mm from top) Age R (kyr BP 2010) Age Max Age Min P31 Y89 U238

GP2‐D2‐12 1.832 2.639 2.662 2.615 71.78873875 0.001813044 1.707113164

GP2‐D2‐11 2.769 2.668 2.689 2.645 19.40596852 0.00226147 0.408398378

GP2‐D2‐10 3.707 2.698 2.716 2.675 23.31708093 0.001412153 2.352324691

GP2‐D2‐9 4.643 2.727 2.749 2.705 25.91447371 0.001663792 1.629810701

GP2‐D2‐8 5.581 2.756 2.785 2.736 23.78410961 0.001425643 1.771407611

GP2‐D2‐7 6.561 2.787 2.805 2.767 24.80573008 0.001683172 1.031182626

GP2‐D2‐6 7.542 2.818 2.807 2.798 23.88297922 0.001696478 1.077708664

GP2‐D2‐5 8.523 2.849 2.875 2.829 28.50766649 0.001602669 1.575811541

GP2‐D2‐4 9.504 2.880 3.064 2.860 41.72421505 0.002062983 1.393962483

GP2‐D2‐3 10.486 2.911 3.252 2.892 29.02266621 0.001349809 1.805371239

GP2‐D2‐2 11.789 2.953 3.315 2.933 47.27319833 0.002011872 3.560497023

GP2‐D2‐1 12.658 2.982 3.315 2.961 36.65547035 0.00081513 1.763381458

GP2‐D2‐A‐50.asc 13.797 3.021 3.336 2.998 28.35427268 0.002086711 2.094760194

GP2‐D2‐A‐49.asc 14.797 3.055 3.363 3.029 26.69277508 0.002667482 3.09537268

GP2‐D2‐A‐48.asc 15.770 3.089 3.379 3.060 27.83225077 0.002399111 1.98438939

GP2‐D2‐A‐47.asc 16.742 3.123 3.393 3.091 34.00288998 0.002259581 1.591541593

GP2‐D2‐A‐46.asc 17.714 3.158 3.408 3.122 27.58413888 0.002285614 1.928235314

GP2‐D2‐A‐45.asc 18.686 3.191 3.424 3.152 32.62214418 0.002471927 2.664009598

GP2‐D2‐A‐44.asc 19.658 3.224 3.439 3.182 31.60001036 0.003084833 1.820800624

GP2‐D2‐A‐43.asc 20.630 3.256 3.454 3.212 28.23865105 0.002619508 1.886754956

GP2‐D2‐A‐42.asc 21.602 3.289 3.469 3.242 24.85033057 0.002181017 2.043068035

GP2‐D2‐A‐41.asc 22.574 3.321 3.484 3.273 29.50534283 0.002868866 2.934328966

GP2‐D2‐A‐40.asc 23.546 3.352 3.500 3.302 28.37768577 0.003046759 1.771583324

GP2‐D2‐A‐39.asc 24.518 3.382 3.515 3.332 25.35126534 0.00254051 1.494421441

GP2‐D2‐A‐38.asc 25.490 3.413 3.530 3.362 21.65801508 0.002925369 1.247474411

GP2‐D2‐A‐37.asc 26.544 3.444 3.546 3.394 21.79928011 0.001737708 0.929369577

GP2‐D2‐A‐36.asc 27.598 3.472 3.563 3.426 33.14663506 0.002582893 0.910431816

GP2‐D2‐A‐35.asc 28.652 3.500 3.580 3.459 18.30474782 0.002464351 1.028829686

GP2‐D2‐A‐34.asc 29.706 3.527 3.596 3.491 20.12591892 0.002203654 0.908234537

GP2‐D2‐A‐33.asc 30.760 3.556 3.612 3.523 24.05549866 0.001830183 1.385383808

GP2‐D2‐A‐32.asc 31.761 3.582 3.628 3.551 27.68984504 0.002644756 1.619299883

GP2‐D2‐A‐31.asc 32.762 3.608 3.645 3.575 23.84799044 0.002053173 1.363163398

GP2‐D2‐A‐30.asc 33.762 3.634 3.667 3.595 22.95143456 0.002680409 1.011573289

GP2‐D2‐A‐29.asc 34.763 3.659 3.693 3.613 22.62270257 0.002779767 1.272496783

GP2‐D2‐A‐28.asc 35.764 3.684 3.725 3.631 51.4759643 0.008349886 3.510759265

GP2‐D2‐A‐27.asc 36.773 3.703 3.758 3.649 58.52989792 0.025960744 4.2445192

GP2‐D2‐A‐26.asc 37.781 3.722 3.791 3.667 53.15223586 0.006359219 3.646966536

GP2‐D2‐A‐25.asc 38.792 3.734 3.824 3.685 42.72867975 0.014257355 2.255383397

GP2‐D2‐A‐24.asc 39.803 3.745 3.856 3.702 45.66903103 0.011596065 3.411782143

GP2‐D2‐A‐23.asc 40.814 3.756 3.885 3.720 41.39199296 0.008413112 2.478947884

GP2‐D2‐A‐22.asc 41.825 3.769 3.912 3.738 30.0332634 0.005790101 1.466771641

GP2‐D2‐A‐21.asc 42.836 3.784 3.937 3.756 25.63249663 0.003015984 1.290742548

GP2‐D2‐A‐20.asc 43.847 3.800 3.953 3.774 23.3109257 0.003294717 0.877576438

GP2‐D2‐A‐19.asc 44.858 3.816 3.955 3.792 27.87040173 NA 0.776606152

GP2‐D2‐A‐18.asc 45.869 3.833 3.955 3.810 19.61784748 0.00255644 0.531604424

GP2‐D2‐A‐17.asc 46.880 3.850 3.955 3.829 21.55876755 0.004041091 0.56267081

GP2‐D2‐A‐16.asc 47.891 3.867 3.961 3.847 21.21387739 0.003400812 0.454741376

GP2‐D2‐A‐15.asc 48.784 3.883 3.970 3.863 20.56565311 0.00361562 0.767513082

GP2‐D2‐A‐14.asc 49.677 3.898 3.975 3.879 22.47211847 NA 1.106884962

GP2‐D2‐A‐13.asc 50.700 3.915 3.980 3.898 25.7442627 0.004569896 2.453755924

GP2‐D2‐A‐12.asc 51.723 3.933 3.992 3.916 21.97069254 0.00260055 1.234997544

GP2‐D2‐A‐11.asc 52.746 3.950 4.005 3.934 18.06518925 0.002542445 0.723501341

GP2‐D2‐A‐10.asc 53.769 3.967 4.017 3.952 18.62538771 0.003311934 0.876779087

GP2‐D2‐A‐9.asc 54.792 3.984 4.029 3.970 29.91898466 0.004377893 1.576094036

GP2‐D2‐A‐8.asc 55.792 4.001 4.040 3.987 32.737835 0.003751047 2.06067679

GP2‐D2‐A‐7.asc 56.792 4.018 4.051 4.005 29.02360996 0.004535133 2.583670242

GP2‐D2‐A‐6.asc 57.792 4.035 4.063 4.022 35.61625006 0.007115971 2.714401579

GP2‐D2‐A‐5.asc 58.792 4.051 4.074 4.039 17.85429996 0.003851787 0.558285235

GP2‐D2‐A‐4.asc 59.792 4.068 4.085 4.055 20.33457659 0.002609973 1.372644585

GP2‐D2‐A‐3.asc 60.792 4.084 4.098 4.071 21.3304868 0.003046244 1.665418553

GP2‐D2‐A‐2.asc 61.792 4.099 4.113 4.087 31.96542822 0.003162733 2.106746418

GP2‐D2‐A‐1.asc 62.792 4.115 4.129 4.101 38.80825846 0.024036384 4.137458356

GP2‐D1‐A‐45.asc 63.214 4.121 4.136 4.106 30.7121053 0.004226435 2.244344894

GP2‐D1‐A‐44.asc 63.821 4.131 4.147 4.113 37.55756335 0.003837774 3.90648241

GP2‐D1‐A‐43.asc 64.824 4.147 4.164 4.125 39.32921267 0.003964563 3.696648879

GP2‐D1‐A‐42.asc 65.827 4.163 4.182 4.136 35.01897164 0.005862382 3.031131241

GP2‐D1‐A‐41.asc 66.831 4.180 4.200 4.148 39.67778045 0.005280024 2.702677564

GP2‐D1‐A‐40.asc 67.834 4.197 4.218 4.159 39.99329929 0.00564643 2.232374177

GP2‐D1‐A‐39.asc 68.837 4.213 4.236 4.170 28.61513768 0.003489056 1.356140708

GP2‐D1‐A‐38.asc 69.840 4.230 4.254 4.182 29.8804345 0.004826907 1.832696282

GP2‐D1‐A‐37.asc 70.843 4.246 4.272 4.193 24.41840273 0.003346026 1.299974006

GP2‐D1‐A‐36.asc 71.846 4.262 4.290 4.205 30.70545604 0.006109843 1.958437033

GP2‐D1‐A‐35.asc 72.850 4.278 4.308 4.216 28.59190765 0.004701346 1.698326129

GP2‐D1‐A‐34.asc 73.853 4.295 4.327 4.227 30.37001768 0.002984466 2.167898027

GP2‐D1‐A‐33.asc 74.856 4.309 4.344 4.239 34.88182742 0.003496864 2.568808455

GP2‐D1‐A‐32.asc 75.859 4.321 4.362 4.250 32.61740777 0.003823984 1.579852095

GP2‐D1‐A‐31.asc 76.862 4.329 4.380 4.261 32.25752784 0.00641679 1.88235989

GP2‐D1‐A‐30.asc 77.866 4.338 4.399 4.272 31.50593741 0.004002261 1.798125327

GP2‐D1‐A‐29.asc 78.869 4.339 4.416 4.283 26.40158391 0.006721983 1.602454866

GP2‐D1‐A‐28.asc 79.872 4.339 4.432 4.295 32.25772495 0.01310098 1.66080521

GP2‐D1‐A‐27.asc 80.875 4.339 4.441 4.306 34.93331271 0.020132364 1.959369088

GP2‐D1‐A‐26.asc 81.878 4.343 4.449 4.317 24.29497026 0.009967609 1.255647375

GP2‐D1‐A‐25.asc 82.882 4.351 4.457 4.328 31.35572451 0.013146451 1.777768288

GP2‐D1‐A‐24.asc 83.885 4.356 4.464 4.339 39.55692196 0.026846069 3.851446001

GP2‐D1‐A‐23.asc 84.888 4.362 4.471 4.350 40.81865844 0.023389049 4.218500874

GP2‐D1‐A‐22.asc 85.891 4.373 4.475 4.361 42.88031638 0.040800437 4.631282042

GP2‐D1‐A‐21.asc 86.894 4.384 4.480 4.373 45.19040571 0.051670353 4.930198044

GP2‐D1‐A‐20.asc 87.897 4.396 4.480 4.384 43.04560348 0.00664183 3.393996448

GP2‐D1‐A‐19.asc 88.901 4.407 4.480 4.395 39.3696157 0.03181857 4.2149575

GP2‐D1‐A‐18.asc 89.904 4.418 4.480 4.407 37.17663839 0.023593396 3.430756941

GP2‐D1‐A‐17.asc 90.907 4.430 4.480 4.418 39.9721325 0.00980563 3.079387191

GP2‐D1‐A‐16.asc 91.910 4.441 4.487 4.429 28.43044516 0.006895583 1.787137768

GP2‐D1‐A‐15.asc 92.913 4.452 4.497 4.441 33.99381608 0.009663724 2.77642073

GP2‐D1‐A‐14.asc 93.917 4.464 4.502 4.452 50.22398234 0.056477555 4.035314212

GP2‐D1‐A‐13.asc 94.920 4.475 4.507 4.463 34.12694133 0.011451651 3.017463255

GP2‐D1‐A‐12.asc 95.923 4.486 4.513 4.475 19.61170915 0.00277046 0.579683921

GP2‐D1‐A‐11.asc 96.926 4.498 4.519 4.486 46.41315256 0.049256109 4.426513802

GP2‐D1‐A‐10.asc 97.929 4.509 4.524 4.497 48.48163364 0.183821553 4.500300652

GP2‐D1‐A‐9.asc 98.933 4.520 4.532 4.509 55.6456005 0.05844628 2.823383035

GP2‐D1‐A‐8.asc 99.936 4.532 4.543 4.520 33.78341433 0.009851225 2.173240607

GP2‐D1‐A‐7.asc 100.939 4.543 4.554 4.532 34.70791779 0.006833557 2.241068786

GP2‐D1‐A‐6.asc 101.942 4.555 4.566 4.543 36.61923841 0.007576118 2.544153304

GP2‐D1‐A‐5.asc 102.945 4.566 4.577 4.554 46.75231252 0.007645762 2.368895682

GP2‐D1‐A‐4.asc 103.948 4.577 4.589 4.566 35.56799243 0.004874702 2.043170874

GP2‐D1‐A‐3.asc 104.952 4.589 4.600 4.577 44.88479514 0.010355203 2.18184583

GP2‐D1‐A‐2.asc 105.955 4.600 4.611 4.588 45.04188705 0.003972441 1.457373934

GP2‐D1‐A‐1.asc 106.958 4.612 4.623 4.600 31.19241636 0.003801576 1.622125049

GP2‐D1‐B‐1.asc 107.980 4.623 4.635 4.611 43.65766237 0.007832983 1.596914737

GP2‐D1‐B‐2.asc 109.001 4.635 4.646 4.623 19.52165714 0.002825316 1.03200715

GP2‐D1‐B‐3.asc 110.023 4.646 4.658 4.634 38.04249256 0.012263882 1.279039273

GP2‐D1‐B‐4.asc 111.044 4.658 4.670 4.646 28.64400591 0.004758281 1.806385477

GP2‐D1‐B‐5.asc 112.066 4.670 4.681 4.657 26.97380234 0.005413347 1.440785902

GP2‐D1‐B‐6.asc 113.087 4.681 4.693 4.669 19.72750654 0.002793428 1.268235814

GP2‐D1‐B‐7.asc 114.109 4.693 4.704 4.680 22.11710109 0.003373161 1.617040189

GP2‐D1‐B‐8.asc 115.130 4.704 4.716 4.692 20.96828403 0.002288515 1.079030958

GP2‐D1‐B‐9.asc 116.152 4.716 4.727 4.703 22.90269185 0.002248042 0.896641793

GP2‐D1‐B‐10.asc 117.174 4.727 4.739 4.715 24.98471072 0.003100591 1.523805445

GP2‐D1‐B‐11.asc 118.195 4.739 4.751 4.726 26.02359775 0.003361321 2.006054606

GP2‐D1‐14 167.239 5.295 5.313 5.275 20.26291188 0.002002219 0.951574293

GP2‐D1‐13 168.253 5.306 5.325 5.287 30.77604574 0.002749294 1.279772714

GP2‐D1‐12 169.267 5.318 5.336 5.298 48.74260576 0.016100054 3.133405499

GP2‐D1‐11 170.282 5.329 5.348 5.309 58.75685643 0.016299298 3.536523236

GP2‐D1‐10 171.296 5.341 5.360 5.320 68.03528956 0.069019745 3.705206639

GP2‐D1‐9 172.310 5.352 5.372 5.332 70.40222396 0.022075503 3.149991719

GP2‐D1‐8 173.271 5.363 5.382 5.342 43.64431155 0.016896134 3.001621467

GP2‐D1‐7 174.233 5.374 5.393 5.353 45.96340031 0.017702551 3.025625466

GP2‐D1‐6 175.194 5.385 5.408 5.364 63.39410229 0.012456753 3.198295825

GP2‐D1‐5 176.156 5.396 5.418 5.375 57.49617534 0.006500046 2.989563743

GP2‐D1‐4 177.117 5.407 5.418 5.385 56.42730367 0.002436224 1.860712193

GP2‐D1‐3 178.078 5.418 5.424 5.396 31.79513725 0.001432478 2.253255167

GP2‐D1‐2 179.040 5.429 5.486 5.407 46.56882461 0.001689076 1.363956239

GP2‐D1‐1 180.001 5.440 5.584 5.418 35.43014383 0.001949962 1.855547402

GP2‐C3‐25 181.005 5.451 5.648 5.429 44.85646322 0.013791074 1.902017393

GP2‐C3‐24 182.009 5.463 5.660 5.441 33.37319616 0.004784086 1.639462631

GP2‐C3‐23 183.013 5.478 5.665 5.453 29.35277719 0.003002527 1.722794147

GP2‐C3‐22 184.017 5.493 5.682 5.465 23.57980721 0.00185415 0.959334604

GP2‐C3‐21 185.021 5.498 5.697 5.477 24.67404657 0.00141276 1.297609434

GP2‐C3‐20 186.025 5.512 5.707 5.489 26.02520068 0.00132224 1.229484477

GP2‐C3‐19 187.029 5.575 5.717 5.502 27.87048829 0.002869793 1.225309547

GP2‐C3‐18 188.033 5.671 5.728 5.514 37.17360619 0.002071502 1.001717161

GP2‐C3‐17 189.037 5.726 5.740 5.526 22.506942 0.001481571 0.755248112

GP2‐C3‐16 190.041 5.732 5.750 5.537 20.88160663 0.001536436 0.637943912

GP2‐C3‐15 191.045 5.733 5.760 5.549 21.54780112 0.001597746 0.905714986

GP2‐C3‐14 192.049 5.746 5.770 5.561 22.17893606 0 0.710022307

GP2‐C3‐13 193.053 5.760 5.780 5.577 17.67345821 0.003604821 0.616864692

GP2‐C3‐12 194.023 5.770 5.790 5.590 17.66682425 0 0.652650823

GP2‐C3‐11 194.993 5.780 5.800 5.590 24.80015835 0.002520438 1.044423519

GP2‐C3‐10 195.964 5.792 5.809 5.597 43.56390551 0.002592311 1.133667931

GP2‐C3‐9 196.934 5.803 5.819 5.655 43.1352608 0.00743005 1.799177441

GP2‐C3‐8 197.904 5.813 5.829 5.755 30.22833116 0.004309 1.686260471

GP2‐C3‐7 198.874 5.824 5.839 5.822 53.46825677 0.007169848 2.185572434

GP2‐C3‐6 199.844 5.834 5.848 5.828 62.70125556 0.004779813 2.848723592

GP2‐C3‐5 200.814 5.844 5.858 5.828 60.85765782 0.008316279 2.849440313

GP2‐C3‐4 201.785 5.854 5.868 5.836 51.66751568 0.004300448 2.353395069

GP2‐C3‐3 202.755 5.864 5.878 5.850 69.151697 0.014190678 4.385618969

GP2‐C3‐2 203.725 5.874 5.888 5.860 69.151697 0.014190678 4.385618969

GP2‐C3‐1 204.695 5.884 5.898 5.870 47.74844555 0.00327209 2.738124585

GP2‐C3‐A‐28.asc 205.409 5.892 5.905 5.877 46.52053315 0.003196734 2.450911206

GP2‐C3‐A‐27.asc 206.420 5.902 5.915 5.888 34.40746095 0.002780998 2.037263843

GP2‐C3‐A‐26.asc 207.431 5.913 5.926 5.898 33.70923185 0.004159447 1.884211386

GP2‐C3‐A‐25.asc 208.442 5.923 5.936 5.909 42.52517023 0.006735539 2.832162971

GP2‐C3‐A‐24.asc 209.453 5.934 5.947 5.920 53.15004962 0.007397001 2.404763952

GP2‐C3‐A‐23.asc 210.464 5.945 5.958 5.930 41.36494433 0.00691573 2.787807654

GP2‐C3‐A‐22.asc 211.475 5.955 5.968 5.941 52.98260745 0.005727533 2.774339293

GP2‐C3‐A‐21.asc 212.486 5.966 5.979 5.951 34.11886088 0.008367949 3.203871827

GP2‐C3‐A‐20.asc 213.497 5.976 5.989 5.962 51.12169452 0.018424797 2.866969764

GP2‐C3‐A‐19.asc 214.508 5.987 6.000 5.972 31.0582518 0.008917813 2.439739843

GP2‐C3‐A‐18.asc 215.519 5.997 6.010 5.983 38.47131307 0.011214758 2.979127943

GP2‐C3‐A‐17.asc 216.530 6.008 6.021 5.993 36.79108328 0.011513938 2.330797235

GP2‐C3‐A‐16.asc 217.541 6.018 6.032 6.004 27.97419411 0.004397565 1.63382393

GP2‐C3‐A‐15.asc 218.552 6.029 6.043 6.014 21.30598556 0.004567036 1.339671371

GP2‐C3‐A‐14.asc 219.563 6.039 6.053 6.025 34.18972033 0.007827919 2.264867741

GP2‐C3‐A‐13.asc 220.574 6.050 6.064 6.035 44.24984119 0.019302365 2.039346104

GP2‐C3‐A‐12.asc 221.585 6.061 6.074 6.046 42.14561278 0.008554533 2.317697398

GP2‐C3‐A‐11.asc 222.596 6.071 6.085 6.057 38.98515982 0.005827906 1.676798989

GP2‐C3‐A‐10.asc 223.607 6.082 6.096 6.067 30.05802035 0.006216308 2.139301124

GP2‐C3‐A‐9.asc 224.618 6.092 6.107 6.077 30.32228434 0.010490281 2.888006307

GP2‐C3‐A‐8.asc 225.629 6.103 6.118 6.088 22.78918639 0.003891401 1.474040552

GP2‐C3‐A‐7.asc 226.640 6.113 6.129 6.098 29.01009838 0.003885694 0.979470541

GP2‐C3‐A‐6.asc 227.651 6.124 6.140 6.108 40.65351298 0.006942994 2.19148637

GP2‐C3‐A‐5.asc 228.662 6.134 6.151 6.118 39.80794331 0.002422357 0.911742762

GP2‐C3‐A‐4.asc 229.673 6.145 6.162 6.128 55.80281423 0.017700839 2.785124332

GP2‐C3‐A‐3.asc 230.684 6.155 6.172 6.138 40.50774392 0.015830141 2.542024726

GP2‐C3‐A‐2.asc 231.695 6.166 6.183 6.149 33.34177629 0.012198765 2.290044746

GP2‐C3‐A‐1.asc 232.706 6.177 6.194 6.159 32.68318395 0.009724101 2.118637785

GP2‐C2b‐A‐35.asc 233.861 6.189 6.207 6.170 31.27531117 0.024635838 2.691878453

GP2‐C2b‐A‐34.asc 234.861 6.199 6.217 6.181 35.62971507 0.015598758 2.062251768

GP2‐C2b‐A‐33.asc 235.861 6.210 6.228 6.191 33.62589384 0.011990491 2.604670055

GP2‐C2b‐A‐32.asc 236.861 6.220 6.239 6.201 37.30794726 0.013065179 2.904852177

GP2‐C2b‐A‐31.asc 237.861 6.230 6.250 6.211 33.34632844 0.011103238 3.586026382

GP2‐C2b‐A‐30.asc 238.861 6.241 6.260 6.221 41.22806507 0.007828264 3.388906464

GP2‐C2b‐A‐29.asc 239.861 6.251 6.271 6.231 36.47635097 0.005136662 3.071208201

GP2‐C2b‐A‐28.asc 240.861 6.262 6.282 6.242 47.99527699 0.030896814 3.918931574

GP2‐C2b‐A‐27.asc 241.861 6.272 6.293 6.252 48.67840992 0.039632662 4.07531704

GP2‐C2b‐A‐26.asc 242.861 6.283 6.304 6.262 46.29673662 0.036610906 4.612214952

GP2‐C2b‐A‐25.asc 243.861 6.293 6.314 6.272 46.1747151 0.022578376 3.952430905

GP2‐C2b‐A‐24.asc 244.861 6.304 6.325 6.281 32.66310382 0.003098431 2.492154843

GP2‐C2b‐A‐23.asc 245.861 6.314 6.337 6.291 33.03939155 0.002909108 1.431258596

GP2‐C2b‐A‐22.asc 246.861 6.324 6.346 6.301 36.97744447 0.004617162 1.375531888

GP2‐C2b‐A‐21.asc 247.861 6.335 6.357 6.311 13.76106972 0.002471784 0.265182385

GP2‐C2b‐A‐20.asc 248.861 6.346 6.375 6.321 61.9584278 0.029161194 0.567066205

GP2‐C2b‐A‐19.asc 249.861 6.356 6.405 6.331 19.14165463 0.002826957 0.503745143

GP2‐C2b‐A‐18.asc 250.861 6.367 6.441 6.341 31.85969423 0.006844759 0.311291255

GP2‐C2b‐A‐17.asc 251.861 6.379 6.477 6.352 16.41845364 0.002402339 0.48001144

GP2‐C2b‐A‐16.asc 252.861 6.391 6.502 6.362 33.01892269 0.005895891 1.342117307

GP2‐C2b‐A‐15.asc 253.861 6.404 6.514 6.373 29.45130841 0.00660555 1.840174043

GP2‐C2b‐A‐14.asc 254.861 6.417 6.525 6.383 28.37326243 0.006741037 1.703928083

GP2‐C2b‐A‐13.asc 255.861 6.431 6.539 6.393 35.25434452 0.007398917 1.997965445

GP2‐C2b‐A‐12.asc 256.861 6.450 6.553 6.404 20.55398717 0.00416095 1.233857528

GP2‐C2b‐A‐11.asc 257.861 6.471 6.564 6.415 16.77878804 0.003836589 1.061615609

GP2‐C2b‐A‐10.asc 258.861 6.491 6.573 6.426 28.98292896 0.004212633 1.280664016

GP2‐C2b‐A‐9.asc 259.861 6.508 6.582 6.437 55.07287966 0.004750628 1.049431692

GP2‐C2b‐A‐8.asc 260.861 6.522 6.591 6.449 33.29888929 0.00580206 1.095074721

GP2‐C2b‐A‐7.asc 261.861 6.536 6.600 6.462 25.36166289 0.004429573 1.33798958

GP2‐C2b‐A‐6.asc 262.861 6.549 6.609 6.474 27.72294323 0.004427696 1.79606609

GP2‐C2b‐A‐5.asc 263.861 6.562 6.618 6.487 30.93469163 0.005417395 1.556702521

GP2‐C2b‐A‐4.asc 264.861 6.574 6.627 6.507 26.29600084 0.005087716 1.39099198

GP2‐C2b‐A‐3.asc 265.861 6.585 6.635 6.533 21.66237953 0.0044141 1.415102007

GP2‐C2b‐A‐2.asc 266.861 6.595 6.643 6.546 27.70543334 0.008386134 1.790045825

GP2‐C2b‐A‐1.asc 267.182 6.598 6.645 6.548 35.96594827 0.021994483 2.949078307

GP2‐C2‐72 267.861 6.604 6.651 6.552 44.6402088 0.017005812 3.112316216

GP2‐C2‐71 268.182 6.607 6.654 6.553 67.72737573 0.023618793 4.587055055

GP2‐C2‐70 269.182 6.617 6.662 6.556 82.10952643 0.030765899 4.462465172

GP2‐C2‐69 270.182 6.626 6.670 6.562 60.05623225 0.013134974 4.008789362

GP2‐C2‐68 271.182 6.635 6.678 6.570 50.94545671 0.013547311 3.673649393

GP2‐C2‐67 272.182 6.645 6.687 6.573 45.27681537 0.018127836 3.267446514

GP2‐C2‐66 273.182 6.654 6.695 6.573 68.68851317 0.009604808 3.681726548

GP2‐C2‐65 274.182 6.662 6.704 6.573 70.8924194 0.016963103 4.210723928

GP2‐C2‐64 275.182 6.669 6.712 6.573 43.26283532 0.008996258 2.979333947

GP2‐C2‐63 276.182 6.674 6.720 6.574 49.77094572 0.007856886 2.778714657

GP2‐C2‐62 277.182 6.678 6.728 6.575 43.36500718 0.004448825 2.507076252

GP2‐C2‐61 278.182 6.679 6.736 6.575 49.99374888 0.006540302 2.566497566

GP2‐C2‐60 279.182 6.679 6.745 6.576 58.66930708 0.014979308 3.337192446

GP2‐C2‐59 280.182 6.679 6.754 6.579 79.5661192 0.019331873 3.202709374

GP2‐C2‐58 281.182 6.683 6.763 6.585 43.15805545 0.006897762 2.938441011

GP2‐C2‐57 282.182 6.696 6.773 6.593 46.74568751 0.007978511 2.646585596

GP2‐C2‐56 283.182 6.711 6.783 6.603 36.65034003 0.006536232 2.371343012

GP2‐C2‐55 284.182 6.725 6.793 6.619 31.7816071 0.004478843 1.924913124

GP2‐C2‐54 285.182 6.738 6.804 6.642 17.90619253 0.002298661 0.896123671

GP2‐C2‐53 286.182 6.750 6.814 6.663 42.44915632 0.007608287 2.017697538

GP2‐C2‐52 287.182 6.764 6.824 6.684 28.90216335 0.005190476 1.359426251

GP2‐C2‐51 288.182 6.778 6.835 6.706 22.4522173 0.003618797 1.052272807

GP2‐C2‐50 289.182 6.792 6.846 6.727 20.28526106 0.002935152 0.809940491

GP2‐C2‐49 290.182 6.805 6.858 6.748 21.1823095 0.002085117 0.537767199

GP2‐C2‐48 291.182 6.819 6.870 6.767 22.94064888 0.002327246 0.504452133

GP2‐C2‐47 292.182 6.834 6.884 6.784 27.1097437 0.003549846 0.746665558

GP2‐C2‐46 293.182 6.849 6.899 6.798 14.81493267 0.001884526 0.463585712

GP2‐C2‐45 294.182 6.865 6.915 6.809 20.10508476 0.002915715 0.73225136

GP2‐C2‐44 295.182 6.881 6.932 6.818 25.14116329 0.00298981 0.804587801

GP2‐C2‐43 296.182 6.897 6.950 6.826 11.79281088 0.002826021 0.600660095

GP2‐C2‐42 297.182 6.913 6.968 6.834 15.22651086 0.003377859 0.68435653

GP2‐C2‐41 298.182 6.930 6.987 6.842 12.09575324 0.00270666 0.540872711

GP2‐C2‐40 298.682 6.939 6.997 6.846 14.33294507 0.002923236 0.870305488

GP2‐C2‐39 299.182 6.947 7.006 6.850 21.96957171 0.007839146 1.446635182

GP2‐C2‐38 299.682 6.957 7.015 6.854 27.93467413 0.004246354 1.998538898

GP2‐C2‐37 300.182 6.966 7.024 6.858 23.56315728 0.004565036 2.025456393

GP2‐C2‐36 300.682 6.975 7.033 6.862 21.94151852 0.004652877 1.681366446

GP2‐C2‐35 301.182 6.984 7.043 6.866 19.22391496 0.002291255 1.542528601

GP2‐C2‐34 301.682 6.994 7.052 6.870 18.60512947 0.002549503 1.866087766

GP2‐C2‐33 302.182 7.003 7.062 6.874 17.35404555 0.003347773 1.506226095

GP2‐C2‐32 302.682 7.013 7.072 6.878 20.14925168 0.002005166 0.987614236

GP2‐C2‐31 303.182 7.023 7.082 6.882 33.77284895 0.014370893 2.637525666

GP2‐C2‐30 303.682 7.034 7.091 6.885 36.28764497 0.04240158 3.233623479

GP2‐C2‐29 304.182 7.044 7.101 6.889 41.55106932 0.015492718 3.659724708

GP2‐C2‐28 304.682 7.055 7.111 6.893 43.29281594 0.085757173 3.788144537

GP2‐C2‐27 305.182 7.066 7.120 6.897 43.73261664 0.04484864 3.195028144

GP2‐C2‐26 305.682 7.077 7.130 6.901 41.20995899 0.014894526 3.20740141

GP2‐C2‐25 306.182 7.088 7.139 6.905 43.72278396 0.028023853 3.611152213

GP2‐C2‐24 306.682 7.099 7.149 6.909 47.20237281 0.029665873 3.996931549

GP2‐C2‐23 307.182 7.110 7.159 6.913 37.98026324 0.016460898 2.872179799

GP2‐C2‐22 307.682 7.121 7.169 6.917 36.880958 0.026304112 2.673709537

GP2‐C2‐21 308.182 7.132 7.179 6.921 33.93122704 0.01561364 2.582259749

GP2‐C2‐20 308.530 7.140 7.186 6.923 37.41829182 0.005627804 2.784273928

GP2‐C2‐19 309.530 7.163 7.206 6.930 42.89982487 0.004290627 3.100575939

GP2‐C2‐18 310.530 7.186 7.227 6.942 57.24780007 0.022918038 4.52299605

GP2‐C2‐17 311.530 7.208 7.248 6.960 52.58069919 0.050628484 4.238820766

GP2‐C2‐16 312.530 7.230 7.269 6.964 54.34688575 0.036173992 4.239532159

GP2‐C2‐15 313.530 7.252 7.290 6.964 59.22036203 0.092941529 4.012540643

GP2‐C2‐14 314.530 7.273 7.309 7.007 61.85635689 0.112128188 4.244236972

GP2‐C2‐13 315.530 7.295 7.320 7.147 38.29567273 0.131383905 2.011009322

GP2‐C2‐12 316.530 7.305 7.331 7.282 82.09213141 0.0977279 2.866279082

GP2‐C2‐11 317.530 7.315 7.341 7.301 72.14126867 0.099473532 4.215875867

GP2‐C2‐10 318.530 7.325 7.352 7.301 53.81732372 0.043946918 3.447623461

GP2‐C2‐9 319.530 7.335 7.363 7.305 77.67197406 0.041048719 4.033868411

GP2‐C2‐8 320.530 7.345 7.374 7.316 57.31979184 0.029658979 3.201747718

GP2‐C2‐7 321.530 7.354 7.385 7.325 43.17988094 0.012673409 3.009766012

GP2‐C2‐6 322.530 7.364 7.394 7.333 40.66200257 0.024822077 2.431084794

GP2‐C2‐5 323.530 7.374 7.404 7.344 45.3105078 0.007866419 3.025504496

GP2‐C2‐4 324.530 7.383 7.415 7.355 67.4726856 0.018874867 3.071405908

GP2‐C2‐3 325.530 7.393 7.426 7.364 46.99109342 0.008007523 3.17628259

GP2‐C2‐2 326.530 7.402 7.437 7.373 40.67318785 0.006143072 1.913105147

GP2‐C2‐1 327.530 7.411 7.447 7.384 41.50445086 0.006460658 2.179326989

GP2‐C1‐A‐41.asc 405.465 8.318 8.350 8.280 35.27465383 0.043331198 3.501537556

GP2‐C1‐A‐40.asc 406.465 8.335 8.368 8.298 39.35638499 0.028215652 4.757173833

GP2‐C1‐A‐39.asc 407.465 8.352 8.385 8.314 37.93851869 0.017455925 3.578738936

GP2‐C1‐A‐38.asc 408.465 8.369 8.403 8.331 43.94147041 0.032923121 4.029522002

GP2‐C1‐A‐37.asc 409.465 8.386 8.420 8.348 33.71200782 0.018003376 2.76236208

GP2‐C1‐A‐36.asc 410.465 8.403 8.438 8.365 38.37880091 0.035576618 3.532003837

GP2‐C1‐A‐35.asc 411.465 8.420 8.455 8.382 36.04539788 0.025910358 2.210940911

GP2‐C1‐A‐34.asc 412.465 8.438 8.472 8.399 48.93023412 0.015398437 2.386929041

GP2‐C1‐A‐33.asc 413.465 8.455 8.490 8.416 31.66010664 0.005730969 2.50463627

GP2‐C1‐A‐32.asc 414.465 8.472 8.507 8.432 32.38293655 0.003734435 2.243380427

GP2‐C1‐A‐31.asc 415.465 8.490 8.525 8.448 26.45431845 0.004544111 1.638699563

GP2‐C1‐A‐30.asc 416.465 8.507 8.543 8.465 17.4689818 0.003812606 0.723102369

GP2‐C1‐A‐29.asc 417.465 8.524 8.561 8.481 17.65810794 0.003025329 0.519180804

GP2‐C1‐A‐28.asc 418.465 8.541 8.579 8.498 27.74853267 0.002525957 1.969649503

GP2‐C1‐A‐27.asc 419.465 8.559 8.597 8.515 20.63490095 0.003731395 1.213776338

GP2‐C1‐A‐26.asc 420.465 8.576 8.614 8.532 21.50287485 0.002615001 0.558959575

GP2‐C1‐A‐25.asc 421.428 8.591 8.630 8.548 30.08315234 0.004713102 0.79262989

GP2‐C1‐A‐24.asc 422.392 8.609 8.648 8.564 18.30775565 0.0035262 1.052377677

GP2‐C1‐A‐23.asc 423.355 8.631 8.672 8.580 15.25931952 0.002325538 0.870366286

GP2‐C1‐A‐22.asc 424.318 8.643 8.683 8.595 22.4165427 0.003014541 1.016064408

GP2‐C1‐A‐21.asc 425.282 8.652 8.683 8.609 67.74953147 0.006150556 2.406818428

GP2‐C1‐A‐20.asc 426.245 8.661 8.704 8.626 44.39616382 0.019994085 2.780263519

GP2‐C1‐A‐19.asc 427.245 8.772 8.832 8.649 34.15318489 0.035947157 3.610488545

GP2‐C1‐A‐18.asc 428.245 8.918 8.996 8.670 34.96763445 0.034728171 2.571146567

GP2‐C1‐A‐17.asc 429.245 8.994 9.066 8.676 32.18635576 0.043956506 3.163833631

GP2‐C1‐A‐16.asc 430.245 9.007 9.066 8.708 32.43455558 0.027373598 2.652852278

GP2‐C1‐A‐15.asc 431.245 9.017 9.068 8.820 42.24612845 0.040681071 4.667804009

GP2‐C1‐A‐14.asc 432.245 9.036 9.086 8.957 47.34214782 0.019403158 3.941568358

GP2‐C1‐A‐13.asc 433.245 9.052 9.103 9.020 35.35828472 0.011193389 4.000049886

GP2‐C1‐A‐12.asc 434.245 9.066 9.116 9.022 44.76515171 0.036029781 4.134270809

GP2‐C1‐A‐11.asc 435.245 9.079 9.128 9.026 35.83773723 0.038830543 2.781784785

GP2‐C1‐A‐10.asc 436.245 9.093 9.142 9.045 42.59343914 0.060429535 4.384733561

GP2‐C1‐A‐9.asc 437.245 9.108 9.156 9.062 40.25650962 0.018993353 4.37394224

GP2‐C1‐A‐8.asc 438.245 9.122 9.170 9.075 32.58732615 0.007015827 3.745139083

GP2‐C1‐A‐7.asc 439.245 9.136 9.183 9.089 32.29385332 0.009656523 4.125459126

GP2‐C1‐A‐6.asc 440.245 9.150 9.197 9.104 34.05508682 0.012949773 5.48904903

GP2‐C1‐A‐5.asc 441.245 9.164 9.211 9.118 36.85252029 0.014217319 4.068088821

GP2‐C1‐A‐4.asc 442.245 9.178 9.225 9.132 38.81597468 0.009830936 3.561790728

GP2‐C1‐A‐3.asc 443.245 9.192 9.238 9.146 33.50405395 0.005127343 3.803975332

GP2‐C1‐A‐2.asc 444.245 9.206 9.252 9.160 34.2065998 0.003981463 3.634183554

GP2‐C1‐A‐1.asc 445.245 9.220 9.266 9.174 36.34387194 0.005042247 4.030335282

GP2‐A2‐20 561.973 10.861 10.939 10.669 25.87314358 0.004226308 1.216069666

GP2‐A2‐19 562.921 10.873 10.950 10.671 45.42067298 0.007142041 2.356100138

GP2‐A2‐18 563.869 10.885 10.960 10.671 63.31953065 0.008757691 1.256568222

GP2‐A2‐17 564.817 10.898 10.972 10.672 56.73202723 0.01091523 1.492370571

GP2‐A2‐16 565.765 10.910 10.983 10.676 40.87606363 0.00635269 1.605289571

GP2‐A2‐15 566.823 10.924 10.996 10.683 38.83613104 0.003175579 1.474818955

GP2‐A2‐14 567.882 10.938 11.008 10.692 35.96196964 0.009082052 1.4201522

GP2‐A2‐13 568.940 10.952 11.020 10.704 56.99093127 0.023592805 1.960889336

GP2‐A2‐12 569.999 10.967 11.034 10.719 44.12804536 0.01588191 1.57731392

GP2‐A2‐11 571.057 10.981 11.048 10.735 37.78741306 0.015913841 2.058517607

GP2‐A2‐10 572.116 10.995 11.062 10.762 88.09228856 0.015803841 1.258644931

GP2‐A2‐9 573.174 11.009 11.076 10.795 32.39816763 0.011010477 1.484428991

GP2‐A2‐8 574.177 11.023 11.090 10.826 47.76647211 0.024553857 2.154422284

GP2‐A2‐7 575.180 11.036 11.104 10.856 36.7653929 0.020457749 1.80860363

GP2‐A2‐6 576.183 11.050 11.117 10.887 38.29433981 0.029721848 1.886765859

GP2‐A2‐5 577.187 11.063 11.131 10.917 33.04196165 0.024780699 1.889349733

GP2‐A2‐4 578.190 11.077 11.146 10.948 31.03107402 0.014766738 1.960029696

GP2‐A2‐3 579.193 11.090 11.160 10.980 44.74750896 0.022693771 2.227064728

GP2‐A2‐2 580.196 11.104 11.174 11.011 27.58797672 0.015610586 1.773335616

GP2‐A2‐1 581.199 11.119 11.189 11.038 33.18849917 0.02358146 1.929134808

GP2‐CA‐101 581.200 11.119 11.189 11.038 25.674624 0.007987363 0.980446582

GP2‐CA‐100 581.300 11.120 11.190 11.041 23.62305716 0.005731417 0.788058414

GP2‐CA‐99 581.400 11.122 11.192 11.044 28.02286015 0.007026981 0.752230013

GP2‐CA‐98 581.500 11.123 11.193 11.046 22.55358546 0.005141091 0.614263041

GP2‐CA‐97 581.600 11.124 11.195 11.048 22.95781888 0.003654059 0.667440647

GP2‐CA‐96 581.700 11.126 11.196 11.051 19.90916345 0.003870746 0.532381085

GP2‐CA‐95 581.800 11.127 11.198 11.053 20.36286933 0.004797349 0.550641417

GP2‐CA‐94 581.900 11.129 11.199 11.056 17.4916998 0.004230207 0.663521536

GP2‐CA‐93 582.000 11.130 11.201 11.058 17.07134259 0.004834542 0.604096826

GP2‐CA‐92 582.100 11.132 11.202 11.060 21.88280413 0.004721372 0.656114629

GP2‐CA‐91 582.200 11.133 11.203 11.062 21.13923422 0.004399551 0.867905208

GP2‐CA‐90 582.300 11.135 11.205 11.064 30.2998794 0.006399548 1.117221703

GP2‐CA‐89 582.400 11.136 11.206 11.067 32.65719624 0.005954663 1.167009159

GP2‐CA‐88 582.500 11.138 11.208 11.069 29.99703217 0.005225375 1.091762636

GP2‐CA‐87 582.600 11.139 11.209 11.071 31.32529342 0.005668991 1.105728315

GP2‐CA‐86 582.700 11.141 11.211 11.073 29.80626595 0.005955304 1.119931553

GP2‐CA‐85 582.800 11.142 11.212 11.075 28.54659595 0.006515906 1.11229583

GP2‐CA‐84 582.900 11.144 11.214 11.077 29.81552796 0.006152927 1.065194034

GP2‐CA‐83 583.000 11.145 11.215 11.079 31.92470455 0.007173595 1.183595454

GP2‐CA‐82 583.100 11.147 11.216 11.081 29.95555037 0.007014509 1.233942546

GP2‐CA‐81 583.200 11.148 11.218 11.083 30.60586422 0.007247698 1.376785452

GP2‐CA‐80 583.300 11.150 11.219 11.084 30.65798254 0.006083765 1.287949178

GP2‐CA‐79 583.400 11.152 11.221 11.086 30.5018602 0.007464503 1.477715737

GP2‐CA‐78 583.500 11.153 11.222 11.088 31.60643041 0.006490283 1.684356906

GP2‐CA‐77 583.600 11.155 11.224 11.090 35.86114505 0.006662259 1.857163197

GP2‐CA‐76 583.700 11.156 11.225 11.091 36.17257687 0.007533815 2.039527085

GP2‐CA‐75 583.800 11.158 11.227 11.093 39.20098663 0.009340226 1.962589817

GP2‐CA‐74 583.900 11.160 11.228 11.095 35.25655318 0.013013647 2.174340476

GP2‐CA‐73 584.000 11.161 11.230 11.096 32.40944616 0.017528901 2.429388765

GP2‐CA‐72 584.100 11.163 11.231 11.098 35.33796705 0.01589698 2.369823539

GP2‐CA‐71 584.200 11.164 11.233 11.100 39.88189921 0.011592788 2.381565144

GP2‐CA‐70 584.300 11.166 11.234 11.101 39.72021504 0.010175053 2.370295667

GP2‐CA‐69 584.400 11.168 11.236 11.103 32.06534925 0.006945775 2.226692757

GP2‐CA‐68 584.500 11.169 11.237 11.104 27.67432126 0.006782182 2.123444928

GP2‐CA‐67 584.600 11.171 11.239 11.105 26.80402363 0.009043628 2.270125427

GP2‐CA‐66 584.700 11.173 11.240 11.107 26.54247544 0.010901571 2.345965813

GP2‐CA‐65 584.800 11.174 11.242 11.108 26.40559674 0.010745798 2.41729671

GP2‐CA‐64 584.900 11.176 11.244 11.110 26.45052781 0.012161846 2.465426759

GP2‐CA‐63 585.000 11.177 11.245 11.111 27.33425755 0.012838478 2.542417805

GP2‐CA‐62 585.100 11.179 11.247 11.112 27.28874166 0.012284745 2.52749868

GP2‐CA‐61 585.200 11.181 11.249 11.114 27.61366095 0.016797335 2.676491431

GP2‐CA‐60 585.300 11.182 11.250 11.115 29.01133859 0.014769844 2.735797336

GP2‐CA‐59 585.400 11.184 11.252 11.116 31.6006904 0.016227324 2.750881976

GP2‐CA‐58 585.500 11.185 11.254 11.117 34.51185672 0.028920294 3.149244479

GP2‐CA‐57 585.600 11.187 11.255 11.119 37.72677111 0.041904988 3.670961044

GP2‐CA‐56 585.700 11.189 11.257 11.120 38.23581724 0.039591828 3.57011847

GP2‐CA‐55 585.800 11.190 11.259 11.121 35.72969113 0.036848429 3.593391007

GP2‐CA‐54 585.900 11.192 11.260 11.122 33.19344556 0.033830175 3.353151371

GP2‐CA‐53 586.000 11.193 11.262 11.123 30.49685003 0.028154748 3.221133309

GP2‐CA‐52 586.100 11.195 11.264 11.125 28.9109493 0.025081127 3.017513287