Organic carbon burial efficiency in lake sediments controlled by oxygen exposure time

and sediment source

Sebastian Sobek,a,b,* Edith Durisch-Kaiser,a,b Roland Zurbrugg,a,b Nuttakan Wongfun,a,c

Martin Wessels,d Natacha Pasche,a,b and Bernhard Wehrlia,b

a Eawag, Swiss Federal Institute of Aquatic Science and Technology, Kastanienbaum, SwitzerlandbEidgenossische Technische Hochschule (ETH), Swiss Federal Institute of Technology Zurich, Institute of Biogeochemistry and

Pollutant Dynamics, Zurich, Switzerlandc United Nations Educational, Scientific and Cultural Organization (UNESCO) International Institute for Hydraulic and Environmental

Engineering (IHE), Institute for Water Education, Delft, The NetherlandsdInstitute for Lake Research, Langenargen, Germany

Abstract

We compared the burial efficiency of organic carbon (buried OC : deposited OC) in a diverse set of 27 differentsediments from 11 lakes, focusing on the potential effects of organic matter source, oxygen exposure, andprotective sorption of OC onto mineral surfaces. Average OC burial efficiency was high (mean 48%), and it wasparticularly high in sediments receiving high input of allochthonous organic matter (mean 67%). Further, OCburial efficiency was strongly negatively related to the oxygen exposure time, again particularly so in sedimentsreceiving high allochthonous loads. On the other hand, OC burial efficiency was not related to the mineral surfacearea, which was used as a proxy of the sorption capacity of the mineral phase for OC. The high OC burialefficiency in many lake sediments can thus be attributed to the frequent and significant input of allochthonousorganic matter to lakes, as well as to a strong dependence of OC burial efficiency on oxygen exposure time. Thisstudy demonstrates that the carbon sink in lake sediments alters the OC export from the continents to the sea andthat the fate of OC in lake sediments (burial vs. mineralization to carbon dioxide and methane) is highly sensitiveto environmental conditions.

Organic carbon (OC) that is deposited onto the surfaceof a sediment will either be mineralized to CO2 or CH4 byheterotrophic microbes or it will be buried in the sedimentsover geological timescales. OC burial in sediments is animportant sink in the global carbon cycle, removing carbonfrom the actively cycling carbon pools. Compared to otherfluxes in the global carbon cycle, OC burial constitutes asmall flux (about 0.1 Pg C yr 1 in marine sediments; IPCC2007), but it has lead to the accumulation of vast stocks offossil carbon. Accordingly, substantial research efforts inoceanography have been directed toward a mechanisticunderstanding of the factors governing OC burial in marinesediments (Burdige 2007).

Studies on accumulation of OC in lakes, on the otherhand, have been more fragmented, and the rates of OCburial reported from different lakes differ by more than twoorders of magnitude (Mulholland and Elwood 1982;Kortelainen et al. 2004; Downing et al. 2008). Dean andGorham (1998) estimated that the annual OC burial in lakesediments could amount to about 50% of the annual OCburial in marine sediments. Considering that lakes coveronly about 2% of Earth’s surface, as compared to 71%covered by ocean, it becomes evident that lake sedimentsrepresent a very efficient sink in the global carbon cycle.However, the reasons for this highly efficient OC burial inlake sediments are poorly understood. Two studies reportrelationships between OC burial and a number of lake andsediment characteristics (Hakanson 2003; Alin and John-

son 2007) but provide no explanations of the mechanismsresponsible for the efficient OC burial in lake sediments.Similarly, a recent study by Downing et al. (2008)demonstrated very high OC burial in small impoundmentssuch as farm ponds, but the mechanisms responsible forthis high OC burial remain unclear. Due to this lack ofmechanistic understanding, it is presently impossible togauge the response of OC burial in lake sediments toclimate change.

Extensive studies on marine sediments have identified awide array of different factors that may contribute to thepreservation of OC in sediments, such as primary pro-duction rate, chemical composition of organic matter,sediment accumulation rate, bottom water oxygen concen-tration, the availability of electron acceptors, characteris-tics of the microbial decomposers, mixing by macro-benthos, oscillations in redox potential, and sorption oninorganic particles (Hedges et al. 1999). Many of thesefactors are interdependent, and their relative importance islikely to shift with time and space. The mechanisms thathave received most attention in marine sediments areoxygen exposure, protective sorption onto mineral surfac-es, and the chemical composition of the organic matter(Burdige 2007).

Several different studies have shown that anoxia favorsOC preservation and the formation of oil precursors inmarine sediments (Demaison and Moore 1980; Gelinas etal. 2001). The oxygen exposure time (OET) has been foundto act as a major regulator of OC preservation in marinesediments (Hartnett et al. 1998; Hedges et al. 1999), as it* Corresponding author: sebastian.sobek@env.ethz.ch

Limnol. Oceanogr., 54(6), 2009, 2243 2254

E 2009, by the American Society of Limnology and Oceanography, Inc.

2243

Eawag_05742

integrates several environmental factors that are related toOC burial (oxygen concentration, primary productivity,sedimentation rate). There are indications that in lakesediments as well, long oxygen exposure time may favor theextent of OC mineralization, thereby lowering OC burial(Marki et al. 2006).

Organic matter can adsorb onto the surfaces of mineralparticles, which limits or inhibits mineralization rates inmarine sediments (Keil et al. 1994; Mayer 1994b). There isevidence that sorption onto mineral surfaces, storage inmeso-sized pores of mineral particles, and association withamorphous metal oxides all contribute to the physicalprotection of organic matter against attacks by microbialexoenzymes (Burdige 2007). Accordingly, a model basedsolely on the physical protection of organic matter bymineral particles could explain the empirically observed OCdecay rates in marine sediments (Rothman and Forney2007). In soils and sediments, the surface area of minerals ispositively related to the OC concentration (Mayer 1994a),and it may therefore be regarded as an indicator of theextent of protective sorption of OC on minerals. Also forlake sediments, there are indications that protectivesorption onto mineral surfaces can contribute to thepreservation of OC (Laskov et al. 2002).

The fate of organic matter in sediments is ultimatelydetermined by its chemical composition, i.e., its molecularstructure (Westrich and Berner 1984). Several studies havedemonstrated that allochthonous (i.e., land plant derived)compounds, as well as microbial membrane remnants, areprone to selective preservation in marine sediments(Burdige 2007). Autochthonous (i.e., internally produced)organic matter, on the other hand, is comparatively easilydecomposed by heterotrophic microbes, and thus it is lessprone to accumulation in sediments (Burdige 2007). A fewstudies have hinted that similar mechanisms are also validfor lacustrine ecosystems (Cranwell 1981; Ho and Meyers1994), and hence the organic matter source may profoundlyaffect OC burial in lake sediments.

The relative importance of oxygen exposure time,sorption onto mineral surfaces, and organic matter sourcefor OC burial in lake sediments has to date not beenstudied systematically. Here, we compare a set of differentlake sediments, varying widely in oxygen exposure time,mineral surface area, and organic matter source, in order tobetter understand the mechanisms behind the effective OCburial in lake sediments. We show that oxygen exposuretime and organic matter source are important regulators ofOC burial in lake sediments, while organic matter sorptionon mineral surfaces plays a subordinate role.

Methods

Site selection We chose sampling sites for lake sedi-ments representing end members of gradients in oxygenexposure time, mineral phase properties, and organicmatter source (Table 1). While we collected quantitativedata on the oxygen exposure time and the mineral surfacearea, the dominating source of organic matter was derivedfrom the literature and resulted in a qualitative groupinginto sediments dominated by autochthonous organic

matter, and sediments dominated by allochthonous organicmatter.

The three Swedish boreal lakes (Svarttjarn, Gaddtjarn,and Lilla Sangaren) are oligotrophic, humic-rich systems,and the sediments are dominated by allochthonous organicmatter (Von Wachenfeldt and Tranvik 2008). These lakesare small (0.007, 0.07, and 0.24 km2 for Svarttjarn,Gaddtjarn, and Lilla Sangaren, respectively) and shallow,and only one site was sampled within each of the three lakes(Table 1). Lake Baikal (31,494 km2) is the world’s largestlake by volume and very oligotrophic, and the sediments ofLake Baikal are the most highly oxygenated lake sedimentsreported in the literature (Martin et al. 1998). Five sites wereselected in Lake Baikal. While the Posolskaya site receivessome input of allochthonous organic matter and riverineparticles from the Selenga River, the sediments of the fourother sites receive predominantly internally producedmaterial (Muller et al. 2005). In oligotrophic Lake Con-stance (539 km2), we sampled four sites along a gradient ofriverine input from the Rhine River, draining the Alps(Wessels 1998). The site closest to the Rhine River inflowreceives almost exclusively allochthonous matter, while atthe south shore of the central basin, sediments consistpredominantly of autochthonous material. In the northbasin of eutrophic Lake Zug (38.3 km2), we sampled twosites at different depths, which are characterized by differentbottom water oxygen regimes. Due to high internalproduction and limited riverine inflow, sediments of thisbasin are mainly derived from internal production (Meckleret al. 2004). Lake Wohlen (2.5 km2) is a mesotrophicreservoir in the Aare River with an average water retentiontime of roughly 2 d (Albrecht et al. 1998); it consequentlyreceives high riverine input. We sampled Lake Wohlen atfive sites along a transect from the dam (WO-A) to theinflow area (WO-H). Ultra-oligotrophic alpine Lake Brienz(29.8 km2) receives high particle loads from tributaries fed byupstream glaciers, and the deep site (210 m) receives a higherparticle load than the shallow site (20 m) (Muller et al. 2007).Lake Lugano (48.7 km2) is eutrophic, resulting in thesediment being mainly derived from autochthonous sources.A certain proportion of allochthonous matter is present inthe sediment, derived from tributaries draining the alpinecatchment (Hofmann 1996). The north basin of LakeLugano has been meromictic during the past 40 yr, implyingthat the sediments were deposited under permanently anoxicconditions. In eutrophic Lake Kinneret (166 km2), threeshallow sites with increasing distance from the Jordan Riverinflow were sampled, and one site was sampled in the middleof the lake, where the sediments are anoxic for about 6months per year. Sediments in Lake Kinneret are primarilyderived from internal production and have a variable, butsmall degree of allochthonous input from the Jordan River(Koren and Klein 2000). Lastly, tropical Lake Kivu (2370km2) is a eutrophic lake with permanently anoxic bottomwaters. The sediments of Lake Kivu are mainly formed byautochthonous material (Al-Mutlaq et al. 2008).

Sampling For Lakes Baikal, Zug, Brienz, and Lugano,published data on OC burial, OC mineralization, andoxygen pore-water profiles were available (Table 1). The

2244 Sobek et al.

Table1.

La

kes

an

dsa

mp

lin

gsi

tes

of

the

pre

sen

tst

ud

y.

Gro

ssse

dim

enta

tio

nw

as

eith

erca

lcu

late

dfr

om

the

sum

of

OC

bu

ria

la

nd

OC

min

era

liza

tio

n(B

+M

),o

rd

eriv

edfr

om

sed

imen

ttr

ap

s(T

).N

um

ber

ssh

ow

the

mea

n6

95%

con

fid

ence

inte

rva

l,w

her

ea

pp

lica

ble

.n

.d.,

no

td

eter

min

ed.

La

ke*

Sit

eL

ab

elL

ati

tud

e(u

N)

Lo

ng

itu

de

(uE

)D

epth

(m)

Gro

ssse

dim

enta

tio

nO

C(w

t%)

OC

bu

ria

l(g

Cm

22

yr2

1)O

2p

enet

rati

on

dep

th(m

m)

CO

2d

iffu

siv

efl

ux

(gC

m2

2y

r21)

CH

4d

iffu

siv

efl

ux

(gC

m2

2y

r21)

Lil

la San

ga

ren

1C

entr

al

LS

59

.89

97

15

.39

35

17

B+M

216

13

26

12

.36

0.4

276

11

.56

0.2

Gad

dtj

arn

1C

entr

al

GA

59

.85

92

15

.18

34

11

B+M

276

15

76

41

.86

0.2

236

41

.36

0.3

Sv

art

tja

rn1

Cen

tra

lS

V5

9.8

90

61

5.2

57

76

B+M

316

31

46

11

.76

0.2

136

32

.46

0.3

Ba

ika

l2N

ba

sin

cen

tra

lB

A-N

B5

4.4

77

81

08

.62

32

82

0B

+M,

T2

.21

.55

056

2{

n.d

.A

ka

dem

isk

yB

A-A

K5

3.7

36

41

08

.27

95

40

0B

+M1

.30

.22

43

.86

4.6

7{

n.d

.P

oso

lsk

ay

aB

A-P

O5

2.0

77

71

05

.85

76

12

0B

+M2

.56

0.1

6.8

16

.36

1.8

116

3{

n.d

.V

yd

rin

oB

A-V

Y5

1.5

68

71

04

.85

45

65

0B

+M2

.46

0.1

3.0

23

.46

2.8

156

2{

n.d

.S

ba

sin

cen

tra

lB

A-S

B5

1.7

07

81

05

.02

21

14

00

B+M

,T

3.0

60

.12

.32

7.2

60

.41

26

3{

n.d

.C

on

sta

nce

1R

hin

ein

flo

wC

O-I

N4

7.5

55

89

.60

07

14

3B

+M,

T1

.16

0.1

27

46

37

2.0

60

.33

66

14

466

28

La

ng

ena

rgen

CO

-LA

47

.58

11

9.5

17

41

59

B+M

1.7

60

.21

266

14

1.8

60

.12

76

81

36

5C

entr

al

no

rth

CO

-CN

47

.60

26

9.4

59

02

03

B+M

1.7

60

.32

76

56

.36

0.6

336

33

.06

3.9

Cen

tra

lso

uth

CO

-CS

47

.59

96

9.3

57

91

02

B+M

,T

1.8

60

.37

.96

1.7

11

.76

0.2

206

50

.186

0.1

3Z

ug

1,3

50

mZ

G-5

04

7.1

63

98

.49

69

50

B+M

2.8

60

.52

86

30

.46

0.2

13

7{

n.d

.1

20

mZ

G-1

20

47

.12

67

8.4

85

31

20

B+M

3.5

60

.82

66

30

.66

0.3

11

7{

n.d

.W

oh

len

1A

WO

-A4

6.9

64

67

.28

53

17

B+M

1.8

60

.25

696

19

1.4

60

.14

86

71

56

6B

WO

-B4

6.9

67

17

.28

84

13

B+M

2.0

60

.26

896

52

7.3

62

.54

86

15

5C

WO

-C4

6.9

70

37

.29

24

13

B+M

2.0

60

.21

07

26

56

1.4

60

.61

006

44

40

DW

O-D

46

.96

46

7.3

04

28

B+M

1.8

60

.21

14

06

12

20

.96

0.2

16

76

73

31

HW

O-H

46

.96

20

7.3

38

26

B+M

1.1

60

.68

706

28

31

.18

90

.2B

rien

z42

0m

BR

-20

46

.71

57

7.9

73

52

0B

+M0

.66

0.1

176

12

6.3

146

0.5

n.d

.2

10

mB

R-2

10

46

.72

36

7.9

76

92

10

B+M

0.5

60

.12

66

31

4.9

156

2.7

n.d

.L

ug

an

o5

Nb

asi

nL

U4

5.9

92

78

.98

09

26

6T

5.4

61

.13

10

32

n.d

.K

inn

eret

1,6

Jord

an

infl

ow

KI-

IN3

2.8

85

73

5.6

09

07

T1

.66

0.3

726

21

1.2

60

.21

596

23

n.d

.A

tla

bo

rato

ryK

I-L

A3

2.8

66

53

5.5

51

71

3T

1.5

60

.42

36

21

.46

0.3

986

5n

.d.

Tib

eria

sK

I-T

I3

2.8

03

83

5.5

33

31

1T

1.5

60

.41

56

61

.36

0.1

616

12

n.d

.C

entr

al

KI-

C3

2.8

21

83

5.5

89

04

0T

3.9

60

.45

46

20

.76

0.1

316

1n

.d.

Kiv

u1

Ish

un

gu

KIV

U2

2.2

68

02

8.9

89

61

75

T3

.86

0.6

18

04

1n

.d.

*R

efer

ence

s:1

,th

isst

ud

y;

2,

Ma

rtin

eta

l.(1

99

8),

Mu

ller

eta

l.(2

00

5),

Mark

iet

al.

(20

06

),M

ark

i(2

00

7);

3,

Mark

iet

al.

(20

09);

4,

Mu

ller

eta

l.(2

00

7);

5,

Ho

fman

n(1

99

6);

6,

Ko

ren

an

dK

lein

(20

00

).{

To

tal

org

an

icca

rbo

no

xid

ati

on

,M

ark

iet

al.

(20

06)

an

dM

ark

iet

al.

(20

09).

OC burial efficiency in lake sediments 2245

sediments of the other lakes were sampled with a gravitycorer, resulting in ,30 100-cm-long sediment cores. Onecore from each site was sliced at 0.5 2-cm intervals,depending on the expected sedimentation rate. Thesesamples were then analyzed for bulk sediment properties(water content, elemental composition, mineral surfacearea). An additional 2 3 cores were taken at each site forthe measurement of the oxygen penetration depth usingmicrosensors, as described in the following section. Thesecores were stored in the dark until measurement, and carewas taken to minimize temperature change. Furthermore, 23 cores equipped with side ports were taken at each site inorder to sample methane in the sediment pore-water.Sampling was repeated in order to cover seasonal variationsin oxygen and methane pore-water concentrations. LakeWohlen was sampled three times at the site closest to thedam (WO-A), and once along the riverine input gradient.The other lakes (Swedish boreal lakes, Lake Constance,Lake Kinneret) were sampled twice (Table 1). Lake Kivuwas sampled once as described already, but due topermanently anoxic bottom waters, no cores for themeasurement of oxygen profiles were taken.

Pore-water analyses Profiles of oxygen concentrationin the sediment pore-water were measured using oxygenmicro-optodes (tip size ,50 mm; PreSens) mounted on acomputer-controlled micromanipulator (Newport), whichmoved the micro-optodes vertically in step sizes of 0.1 0.2mm. Measurement commenced usually 1 4 h after retriev-ing the core; hence, bottom water oxygen concentrationswere probably similar to in situ conditions. For measure-ment, most of the water overlying the sediment wascarefully siphoned off, leaving about 5 cm of water columnabove the sediment. In each core, three oxygen profileswere recorded. Measurements were conducted as close to insitu temperature as possible; occasionally observed moder-ate temperature increases during measurement are notexpected to have affected the measured profiles to any largeextent during the short time of measurement. The similarityof diffusive boundary layer thickness observed in the cores(mean 6 SD, 0.64 6 0.32 mm) with values typicallyreported from benthic lander measurements of lakesediments (range 0.2 1 mm; Marki et al. 2009) indicatesthat the artificial turbulence conditions inside the core didnot seem to have any major effect on our estimates ofoxygen flux across the sediment water interface. Theoxygen sensors were calibrated using water-saturated airand an oxygen-free solution (1 : 1 mixture of 0.1 mol L 1

sodium ascorbate and 0.1 mol L 1 NaOH). Analyticalprecision was 60.5%. The oxygen penetration depth wascalculated as the difference in distance between thesediment water interface (defined from the shape and thestandard deviations of the oxygen profile; Archer et al.1989) and the depth of onset of anoxia.

Samples for the measurement of dissolved CH4 insediment pore-water were taken using a core liner withside ports (1-cm distance between ports). From each core,eight samples were taken, covering between 0 and 15 cm ofsediment depth. From each layer, 2 mL of sediment wereextracted through a side port using a plastic syringe with a

cut-off tip, and transferred to a 25-mL glass vial prefilledwith 4 mL of 2.5% NaOH. The vial was sealed immediatelyusing a gas-tight butyl-rubber stopper and an aluminumcrimp seal, shaken, and then stored upside down untilanalysis. Quantification of CH4 was accomplished byinjecting 500 mL of equilibrated headspace from the glassvials into a Carlo Erba HRGC 5160 gas chromatographequipped with a J&W GSQ column (30 m 3 0.53 mm) anda flame ionization detector (FID). Known amounts ofstandard gas (Scotty, Supelco) were injected in quadrupli-cate and served for quantification. Analytical precision was65%.

Sediment analyses Water content of the sediment wasmeasured by weighing samples both wet and after freezedrying. Contents of total carbon and nitrogen weremeasured by high-temperature catalytic oxidation using aLECO CHNS-932. Inorganic carbon concentrations weremeasured on a coulometer after acidification with 2 molL 1 perchloric acid (UIC). The organic carbon (OC)content was then calculated as the difference between totaland inorganic carbon. Analytical precision was 61%.

Dry bulk density (r) of the sediment was calculated fromthe OC content (Muller et al. 2005), assuming that thesediment is a two-phase mixture between silicate andcarbonate minerals (density about 2.65 g cm 3) andorganic matter (density about 1 g cm 3):

r (g cm 3)~{0:0523|OC (%)z2:65 ð1Þ

We also measured the dry bulk density in 45 samples fromdifferent sediments using a pycnometer. The differencebetween calculated and measured density was on average4% and did not affect the estimates of OC burial.

From bulk dry density (r, g cm 3) and water content(wc, %), we then calculated porosity (W) as follows:

W~wc

(wcz(1{wc):r)ð2Þ

The mineral surface area (MSA) was determined by meansof N2 adsorption at 196uC on a Sorptomatic 1990(Thermo Electron Corporation), according to the BETmethod (named after Brunauer, Emmett, and Teller 1938).Organic matter was removed by thermal oxidation at350uC for 12 h (Mayer 1999). To remove water vapor priorto adsorption analysis, each sample was evacuated at 100uCuntil pressure was ,0.02 Pa, and then evacuated at 100uCfor another 2 h. For calculation of BET parameters, sixpoints within the linear part (relative pressure [p : p0] 0.050.3) of the adsorption isotherm were used. MSA at sites inlakes Baikal and Brienz was measured on archivedsediment samples.

Sedimentation rates were determined from depth profilesof 210Pb and/or 137Cs, analyzed by gamma spectrometryusing germanium detectors (Canberra). The sedimentationrate was corrected for compaction of sediment according toLu (2007). At some sites with very heterogeneous sedimen-tation regime in lakes Constance and Wohlen, the depthprofiles of 137Cs and/or 210Pb could not be used for dating.

2246 Sobek et al.

At the site close to the inflow of the Rhine River inLake Constance (CO-IN), the sedimentation rate wasdetermined from the depth difference of a stratigraphicmarker (the August 2005 extreme flood event) at twoconsecutive years. In Lake Wohlen, sedimentation rateswere derived from water-depth surveys conducted bythe hydropower company (BKW FMB Energie) in 1990and 2004. The difference in standardized water depthbetween 1990 and 2004 represents the sedimentation rateduring this period. For each of the coring sites, thesedimentation rates of two to four nearby depth-surveylocations were averaged to represent the sedimentation rateof the coring site.

Calculations The burial efficiency of organic carbon(OC BE, %) was calculated as the ratio between OC burial(i.e., mean mass accumulation rate in the sediment, g Cm 2 yr 1) and OC gross sedimentation (i.e., mean massdeposition rate onto the sediment surface, g C m 2 yr 1).Gross sedimentation was either derived from sedimenttraps, if such data were available, or calculated as the sumof OC burial and OC mineralization (Table 1). OCmineralization (g C m 2 yr 1) was calculated from pore-water profiles of oxygen and methane using Fick’s first lawof diffusion. The methane profiles observed in this studygenerally exposed a strong quasi-linear decrease of methaneconcentrations over the top 4 or 5 cm of sediment,probably induced by intense methane oxidation at theoxic anoxic boundary (data not shown). Methane fluxeswere calculated over this gradient and therefore includemethane oxidation. Oxygen fluxes were converted tocarbon dioxide fluxes by using a respiratory quotient of0.9 (Graneli 1979), and total OC mineralization was thencalculated as the sum of CO2 and CH4 flux from thesediment to the water column. Oxygen exposure time wascalculated by dividing the mean oxygen penetration depthby the sedimentation rate.

Statistics We used partial least squares regression(PLS; Hoskuldsson 1988) in order to determine the waydifferent variables perform as predictors of OC burialefficiency. A PLS regression places uncorrelated latentcomponents (i.e., orthogonal axes) into the X data space inorder to maximally explain the variability in the Y data.Compared to ordinary multiple linear regression, PLS isrelatively insensitive against the interdependence of Xvariables on each other, and against deviations fromnormality. Also, the PLS algorithm is very tolerant tomissing values. The performance of the PLS model isexpressed in the terms R2Y and Q2. R2Y is comparable toR2 in linear regression, and Q2 is a measure of thepredictive power of the model. Using a permutation test,R2Y was corrected for the intrinsic ‘‘background correla-tion’’ of the data, i.e., the baseline in R2Y that is notindicative for any correlations between variables, but isonly due to chance. Highly skewed variables (skewness .2.0 and min : max ratio , 0.1) were logarithmicallytransformed prior to modeling in order to increase modelperformance. All PLS modeling was done on the SIMCA-P+ 12.0 software (Umetrics).

Results

In the studied 27 lake sediments, OC burial rangedbetween 0.2 and 1140 g C m 2 yr 1 (median 27, mean 192 gC m 2 yr 1), and OC mineralization ranged between 5.3and 196 g C m 2 yr 1 (median 40, mean 58 g C m 2 yr 1).Consequently, organic carbon burial efficiencies (OC BE;OC burial : OC deposition, see Methods section) variedgreatly, covering a range from 3% to 93% (median andmean, 48%). Oxygen penetration depths in the sedimentsoverlain by oxygenated water varied between 0.4 and .50mm, and sedimentation rates covered over three orders ofmagnitude (0.02 79 mm yr 1). This resulted in oxygenexposure times (OET) ranging from essentially zero in lakeswith permanently anoxic bottom waters to .2000 yr atAkademisky Ridge in Lake Baikal (median OET 0.5 yr,mean 93 yr). Also, the mineral surface area (MSA) wasvariable among the different lake sediments; values werebetween 5.7 and 86 m2 g 1 (median 21.6, mean 30.3 m2

g 1). Hence, the broad diversity of lake sediments includedin this analysis ensures that general conclusions can bedrawn regarding the influence of OET and MSA on OCBE.

The partial least squares regression (PLS) explained asignificant fraction of the variability in OC BE between sites(R2Y 5 0.83; R2Ycorrected 5 0.68; Q2 5 0.69) and provided acomprehensive overview of the correlation structures in ourdata set (Fig. 1). The results of the PLS analysis show theimportance of the different X variables in explaining the Y

Fig. 1. Partial least squares regression (PLS) loadings plot,depicting the relationships between the different X variables(closed circles) and OC burial efficiency (open circle). The modelexplains 84% of the variability in OC burial efficiency; whencorrected for background correlation, the degree of explanation is68%. Variables situated along the same directional axis correlatepositively with each other; variables situated at opposite ends ofthe plot correlate negatively with each other; variables situated inthe center of the plot are poor predictors of OC burial efficiency.The horizontal axis explains about three times as much of thevariability in OC burial efficiency as compared to the vertical axis.Abbreviations are as follows: OET, oxygen exposure time; MSA,mineral surface area; Sed R, linear sedimentation rate.

OC burial efficiency in lake sediments 2247

variable (i.e., OC BE), and the relationships of the Xvariables with each other. Variables are positively correlatedif they plot close to each other, while they are negativelycorrelated if they are placed at opposite ends of the plot.Variables in the center of the plot are at most poorly relatedto the variables at the outer ends of the plot area. The firstcomponent (horizontal axis in Fig. 1) explained roughlythree times as much of the variance in the data set as thesecond component (vertical axis in Fig. 1), and it is thereforeof higher importance when interpreting the plot.

The OC BE was strongly positively correlated with OCburial and the sedimentation rate (Fig. 1). Also, theOC : MSA ratio, expressing the organic loading of the mineralsurface area, was positively related to OC BE. On the otherhand, OET and water depth were negatively related to OC BE(along the first component), as well as OC mineralization andannual mean bottom water temperature (along the secondcomponent). The OC concentration, the molar C : N ratio,and the MSA were at most weakly related to OC BE.

A closer look at the negative relationship between OETand OC BE revealed that the different lake sedimentsfollowed two different relationships (Fig. 2). Sedimentsthat receive significant input of autochthonous material(BA-AK, BA-SB, BA-NB, BA-VY, KI-LA, KI-TI, ZG-50,ZG-120, LU and KIVU; see Table 1) grouped around theOET OC BE regression line for marine sediments reportedby Hartnett et al. (1998). Sediments that receive asignificant input of allochthonous material followed adifferent relationship with steeper slope (OC BE 5 16.73 log[OET] + 61.2; R2 5 0.81; p , 0.0001; n 5 14).

When comparing the OC concentration with the mineralsurface area in individual sediment layers, we found a weakpositive relationship (Fig. 3A). On the other hand, we didnot find a relationship between OC BE and mean MSA forour 27 different sediment sites (linear regression R2 5 0.06;p 5 0.24; Fig. 3B), indicating that MSA is not an importantregulator of OC BE in the studied sediments.

No distinct relationship between latitude and OC BEwas observed in our data set (data not shown). However,we found that the annual mean bottom water temperaturewas positively related to OC mineralization in lakesediments, in particular in the range of 3uC to 10uC(Fig. 4), and thereby negatively related to OC BE (Fig. 1).

The OC BE was calculated from OC burial and OCmineralization, which in turn were calculated from severaldifferent parameters (see Methods). Our data showed thatthe magnitude of OC BE was most strongly influenced byOC burial, which in turn was most strongly influenced bythe sedimentation rate (Fig. 1). The sedimentation ratealone explained 67% of the variability in OC BE (Fig. 5;OC BE 5 32.1 + 27.9 3 log(sedimentation rate); R2 5 0.67;p , 0.0001; n 5 27).

Discussion

Organic carbon burial efficiency in lake sediments Ourresults show that in many lake sediments, OC burialefficiency is high (mean 48%). This applies particularly tosediments receiving significant input of allochthonousmatter, where average OC BE was 66%. In sediments that

are predominantly composed of autochthonous matter, onthe other hand, average OC BE was 22%. These averagevalues only reflect a qualitative trend due to the limitedamount of data, and because autochthonous and allochtho-nous sediments were distinguished qualitatively based on thepublished literature. The C : N ratio, which is frequently usedas a quantitative indicator of organic matter source, was notfound to be related to the OC burial efficiency in the presentanalysis (Fig. 1). This could possibly be attributable to thevery large differences between the studied sediments in termsof organic matter sources, degradation pathways, andmicrobial decomposers, all of which may affect the C : Nratio in different ways. This implies that in a cross-systemcomparison of very different sediments, the C : N ratio maynot be a reliable indicator of organic matter source.Furthermore, 50% of the C : N ratio data were within anarrow interval (9.9 11.4), potentially occluding any statis-tical effect of the C : N ratio. Nevertheless, the largedifference in mean OC BE between different organic mattersources illustrates that allochthonous inputs to lake sedi-ments stimulate OC burial and hamper OC mineralization.Further, these data indicate that the fate of allochthonousorganic matter in lake sediments is primarily burial.Autochthonous organic matter, on the other hand, is lessprone to burial and, consequently, primarily fuels microbialrespiration in the sediments. Based on a very diverse data set(Table 1), these conclusions are most probably valid for lakesediments in general. Overall, our data show that roughlyhalf of the OC deposited on lake floors may be buried in thesediments, illustrating that lakes are important modifiers ofcarbon export from the continents to the ocean, andhighlighting the role of lake sediments as significant sinksin the global carbon cycle (Cole et al. 2007).

The effect of oxygen exposure time on organic carbonburial efficiency The OC burial efficiency was found to bestrongly negatively related to the oxygen exposure time(Fig. 2). While the lake sediments derived from mainlyautochthonous sources followed a similar trend as marinesediments (Hartnett et al. 1998), the OC BE in lakesediments derived from mainly allochthonous sources hada much stronger response to changes in OET (Fig. 2). Ofthe 27 different sediments in the present data set, there wereonly two exceptions to this pattern, both in Lake Kinneret.The sediment in the inflow area of the Jordan River (KI-IN) had a comparatively low OC BE (Fig. 2). Possibly, theallochthonous inputs from the river to this sediment arediluted by the deposition of autochthonous matter derivedfrom the high phytoplankton production in this eutrophiclake (Ostrovsky and Yacobi 1999). Further, this site isshallow (7-m depth), and the oscillating redox conditions inthe top sediment probably result in frequent sedimentmixing, which may significantly promote OC mineraliza-tion (Hulthe et al. 1998). On the other hand, OC BE in thecentral basin of Lake Kinneret (KI-C) was comparativelyhigh (Fig. 2), given that the main OC source is autochtho-nous material (Ostrovsky and Yacobi 1999). However,lateral transport of sediment from shallow to deeper areas(i.e., focusing) is a significant process in Lake Kinneret dueto the frequent and regular occurrence of strong internal

2248 Sobek et al.

waves. Hence, sediment at KIN-C has a relatively longpredepositional history and is consequently relativelydegraded (Ostrovsky and Yacobi 1999), which may helpto explain the high OC BE at this site.

Apart from these exceptions, our data show thatallochthonous inputs to lake sediments both trigger a highOC BE, and result in a greater sensitivity of the OC towardoxic degradation. This effect is most likely due to the organicmatter characteristics and not the mineral phase character-istics of the imported allochthonous matter. The lack of apositive relationship between OC BE and mineral surfacearea in lake sediments (Fig. 3B) indicates that mineral phaseproperties have subordinate importance for OC burial in lakesediments. Further, enhanced OC burial efficiency inallochthonous sediments is both observed in mineral-poorsediments with slow sedimentation rates (e.g., boreal lakes),and in mineral-rich sediments with high sedimentation rates(e.g., Brienz, Constance-inflow, Wohlen; Table 1; Figs. 2, 5).This strongly suggests that the high OC BE in allochthonoussediments is not primarily caused by a high rate ofsedimentation of mineral particles per se, but rather by therecalcitrance of allochthonous organic matter.

Several studies have shown that while the degradation ofautochthonous OC is independent of oxygen availability,

the less reactive allochthonous OC is mineralized muchfaster under oxic than under anoxic conditions (Kristensenet al. 1995; Hulthe et al. 1998; Bastviken et al. 2004b). First,allochthonous OC is generally older than autochthonousOC (Mollenhauer and Eglinton 2007) and has consequentlyto a higher degree been exposed to predepositionaldegradation and transformation processes. Second, al-lochthonous OC is typically rich in molecules that arerelatively resistant to anaerobic oxidation, e.g., long-chained aliphatics, lignin, and humic matter (Zehnder andSvensson 1986; Emerson and Hedges 1988). Only in thepresence of molecular oxygen can this aged, structurallycomplex allochthonous OC be exposed to the powerfulattack by oxygenases (synthesized by aerobic bacteria) andby reactive oxygen species such as H2O2 and radicalintermediates (Zehnder and Svensson 1986; Stumm andMorgan 1996). Furthermore, the activity of phenol oxidaseis strongly inhibited under anoxic conditions, leading to anenrichment in phenolic compounds that in turn inhibitorganic matter degradation by hydrolases (Freeman et al.2001). Hence, the primary attack of the OC is compara-tively weaker in the absence of oxygen, which mayrepresent the rate-limiting step of the degradation ofallochthonous OC in lake sediments. Intriguingly, even

Fig. 2. Plot of oxygen exposure time against OC burial efficiency for the 27 different lake sediments. Open circles represent sitesreceiving sediment from mainly autochthonous sources; closed circles represent sites receiving sediment from mainly allochthonoussources. The solid line shows the linear regression for mainly allochthonous sediments (closed circles), excluding KI IN (see Discussion):OC BE 5 61.2 16.7 3 log(OET); R2 5 0.81; p , 0.0001; n 5 14. The dashed line gives the relationship for marine sediments accordingto Hartnett et al. (1998). Linear regression for the mainly autochthonous sediments (open circles, excluding KI C; see Discussion) returnsOC BE 5 23.3 4.39 3 log(OET); R2 5 0.49; p , 0.05; n 5 12 (line not shown for clarity). The error bars show the 95% confidenceinterval; for some of the literature data, no error bars could be calculated. Maximum OC burial efficiency is 100%, even though someconfidence intervals exceed 100% mathematically. Abbreviations are as in Table 1.

OC burial efficiency in lake sediments 2249

the OC of ancient sediments (kyr Myr) can readily bemineralized by aerobic bacteria if re-exposed to oxygen(Moodley et al. 2005; Schillawski and Petsch 2008). Toconclude, the greater effect of OET on the fate of OC inlake sediments with a high proportion of allochthonouscompounds may be attributed to the restricted mineraliza-tion of allochthonous OC under anoxic conditions.

The absence of a mineral surface area effect on organiccarbon burial efficiency No positive relationship wasobserved between the OC BE and the mineral surface area(Fig. 3B), although such a correlation could have beenexpected based on frequent reports on the importance ofprotective mineral sorption for OC preservation in marinesediments (Keil et al. 1994; Mayer 1994b; Rothman andForney 2007). The lack of a MSA effect on OC BE maypossibly be attributable to the relatively high organicmatter loading of the mineral surfaces in many lakesediments. The OC : MSA ratio in our lake sediments wason average 1.7 mg m 2, as compared to a range of 0.5 1 mgm 2 frequently found in marine sediments (Mayer 1994b).Furthermore, we suspect that the large effect of OET onOC BE, in particular in sediments dominated by allochtho-nous substances, may result in a comparatively little effectof MSA on OC BE in lake sediments as opposed to marinesediments. Hence, in spite of the obvious fact that organicmatter sorbs onto mineral surfaces also in lake sediments,the frequently high organic matter loading, as well as thepronounced importance of OET, may mask a potential roleof MSA in regulating the OC BE in the present analysis.

Relationships of organic carbon burial efficiency withother variables Contrary to the study of the earth’s largelakes by Alin and Johnson (2007), our data did not indicatea positive relationship between OC BE and latitude (notshown). Notably, Alin and Johnson (2007) defined the OCBE as the ratio between OC burial and primary production,while in the present study, OC BE is defined as the ratiobetween OC burial and OC deposition onto the sediment.

A direct comparison of OC BE in the present study and theone by Alin and Johnson (2007) is therefore not possible.

We observed a negative relationship between annual meanbottom water temperature and OC BE (Fig. 1). Closerexamination of this relationship shows that OC mineraliza-tion was positively related to annual mean bottom watertemperature in the 3 10uC interval (Fig. 4), as observed inhypolimnetic sediments of mono- and dimictic lakes.Although the relationship is not very strong, it is inaccordance with Den Heyer and Kalff (1998), who showedthat mineralization rates in lake sediments are sensitive totemperature. The flattening of the relationship toward highertemperatures may partially be related to seasonally andpermanently anoxic bottom waters in two of the five warm-water sites (Kinneret central and Kivu), potentially resultingin comparatively low mineralization rate at these sites.

We further found that water depth was weakly negativelyrelated to OC BE (Fig. 1). This relationship is probablyattributable to two effects. First, annual mean bottom watertemperatures are generally colder in deep lakes than inshallow lakes, and this hampers mineralization and thereforetriggers OC BE (Fig. 4). Second, OC degradation ratesdecrease exponentially with increasing OC age (Middelburget al. 1993), implying that degradation rates may be higherfor sinking particles, which are comparatively young,compared to sediments, which are comparatively old.Accordingly, sediment trap studies at a 1400-m-deep site inLake Baikal showed that about 30% of the particulate OCsinking out of the mixed surface layer is mineralized duringsinking to the sediment surface (Muller et al. 2005). Hence, itis likely that predepositional degradation in the watercolumn is more intense for deeper lakes. High predeposi-tional degradation reduces OC deposition on the sedimentsurface, and consequently stimulates OC BE as defined here.

Predictability of organic carbon burial efficiency The PLSmodel (Fig. 1) explained 68% of the variability in OC BE, andit had a high predictive power (Q2 5 0.69). However, the PLSmodel is based on many variables, several of which are not

Fig. 3. (A) Relationship between mineral surface area and OC for individual sediment layersin the different lake sediments. (B) Mineral surface area against OC burial efficiency in differentlake sediments. Open circles represent sites receiving sediment from mainly autochthonoussources; closed circles represent sites receiving sediment from mainly allochthonous sources. Thepoints show the mean, vertical error bars show the 95% confidence interval, and horizontal barsshow the range of mineral surface area in each sediment core.

2250 Sobek et al.

easily assessed. Our analysis shows that the sedimentationrate alone explained 67% of the variability in OC BE (Fig. 5).Hence, the sedimentation rate is the statistically mostimportant predictor of OC burial efficiency in our data set.However, it is not evident what kind of mechanism could linkthe yearly increase in sediment thickness to the extent of OCmineralization or preservation; instead, we attribute the highpredictive power of sedimentation rate to the fact that it is themost important factor in the calculation of OET and OCburial, which in turn can be mechanistically linked to the OCburial efficiency. As illustrated by the confidence bands of theregression line in Fig. 5, there is considerable uncertainty inthe regression slope, as well as great deviations from theregression line for some of the sediments. Hence, predictionsof OC BE from the sedimentation rate may suffer from a lackof accuracy. Inclusion of other easily available data (watertemperature, water column depth) into a multiple linearregression model did not contribute significant additionalexplanatory power. However, an analysis of the residuals ofthe linear regression between the sedimentation rate and OCBE (Fig. 5) revealed that 75% of the positive residuals wereassociated with sediments dominated by allochthonousinputs, while 82% of the negative residuals were associatedwith sediments dominated by autochthonous inputs. Thisdifference in residual direction between allochthonous andautochthonous sediments was statistically significant (t-test, t5 2.78, df 5 25, p 5 0.010), implying that allochthonoussediments tend to have a higher OC BE at a certainsedimentation rate, while autochthonous sediments tend tohave a lower OC BE at a certain sedimentation rate. It istherefore likely that quantitative information on the source ofthe sediment (autochthonous vs. allochthonous) will greatlyenhance the predictability of OC BE in lake sediments.

Comparison with marine sediments The average OC BEin the studied lake sediments (48%) was considerably higherthan the average OC BE for different marine sediments

(29%; Burdige 2007). The range in OC BE in the studied lakesediments, however, was similar to that found in marinesediments (Burdige 2007), except that very low OC BEs(,3%) were absent in the lake sediments. Also, the ranges ofOET and MSA in the studied lake sediments werecomparable to marine sediments (Mayer 1994a,b; Hartnettet al. 1998). Since the gradients in OC BE, OET, and MSAare similar in lake and marine sediments, the potentialmechanisms regulating OC BE may be compared.

In marine sediments, both OET and MSA were found to berelated to OC burial and OC BE (Keil et al. 1994; Hartnett etal. 1998), while in lake sediments, our data suggest a majorrole of OET and allochthonous OC, and a minor role of MSAfor OC BE (Figs. 2, 3). However, there are indications thatthe mechanisms regulating OC BE in lake and marinesediments are fundamentally similar. Short OET and highallochthonous OC inputs do not only trigger high OC BE inlake sediments, but were also reported to give rise to the veryhigh OC BE values in sediments of the Bengal Fan in theIndian Ocean (Galy et al. 2007). Further, allochthonousorganic matter in the ocean is to a far greater extent prone toburial in the sediments than autochthonous organic matter(Burdige 2007), similar to lake sediments (this study). Also, iflake sediments resemble open-ocean sediments (long OETand mainly autochthonous OC), they display OC BE valuessimilar to open-ocean sediments (e.g., BA-AK, 3%). The maindifference in the geochemistry of marine and freshwatersediments is the concentration of sulfate. Because it is the rateof fermentation that kinetically limits both sulfate reductionand methanogenesis (Postma and Jakobsen 1996), thedifference in sulfate concentration should not result in adifferent extent of overall OC mineralization in marine vs.freshwater sediments. From this point of view, it makes sensethat the mechanisms regulating OC BE in marine andfreshwater sediments appear to be similar.

Fig. 4. Relationship between the annual mean bottom watertemperature and the OC mineralization in the different lakesediments. Open circles represent sites receiving sediment frommainly autochthonous sources; closed circles represent sitesreceiving sediment from mainly allochthonous sources. Errorbars show the 95% confidence interval.

Fig. 5. Relationship between the OC burial efficiency andthe sedimentation rate. The solid line shows the linear regression:OC BE 5 32.1 + 27.9 3 log(sedimentation rate); R2 5 0.67; p ,0.0001; n 5 27. Open circles represent sites receiving sedimentfrom mainly autochthonous sources; closed circles represent sitesreceiving sediment from mainly allochthonous sources. Thedashed lines show the 95% confidence bands.

OC burial efficiency in lake sediments 2251

Hence, we propose that for both marine and freshwatersediments, the specific characteristics in terms of OET,mineral surface area, and organic matter source willdetermine the different mechanisms that will be the mostimportant regulator of OC BE. Lakes receive frequently highinputs of allochthonous OC (Sobek et al. 2007), and theOET tends to be shorter in lake sediments (Fig. 2) than inopen-ocean sediments (Hartnett et al. 1998). Hence, OCsource and OET have a comparatively large influence on OCBE in lake sediments. Open-ocean sediments receive mainlyautochthonous OC, and the OET is in most cases longerthan in lake sediments. Therefore, the effect of OC sourceand OET may be moderate in open-ocean sediments, and theprotective sorption of potentially bioavailable autochtho-nous OC on mineral surfaces may be more important (Keilet al. 1994). To conclude, the high average OC BE in lake ascompared to marine sediments is probably attributable tothe frequently sizable allochthonous OC inputs to lakes, aswell as to the frequent occurrence of suboxic conditions inbottom waters of lakes.

Effects of environmental change on organic carbon burialefficiency and methanogenesis OC burial in lake sedimentsis an important sink in the global carbon cycle (Dean andGorham 1998). Likewise, methanogenesis in lake sedimentsconstitutes an important source of atmospheric methane(Bastviken et al. 2004a). Thus, lake sediments are importantplayers in the global carbon cycle because they are able to actas both a sink and a source. Our analysis shows that therelative proportions of allochthonous OC and autochtho-nous OC, in concert with the oxygen exposure time, largelydetermine if the deposited OC is buried or mineralized(Fig. 2). Also, the bottom water temperature had adiscernible effect on OC mineralization, and thus OC BE(Fig. 4). The proportion of different OC sources, oxygenavailability, and temperature is dependent on environmentalconditions. Hence, it is evident that environmental changewill affect the role of lake sediments in the carbon cycle.

Eutrophication increases the input of autochthonous OCto the sediment, which is to a far greater extent mineralizedthan buried in the sediments. Oxygen consumption duringOC mineralization leads to anoxic bottom waters, which istypically observed in eutrophic stratified lakes. As anoxicconditions do not impede the degradation of autochthonousOC (Kristensen et al. 1995), eutrophication thereby stimulatesmethanogenesis in hypolimnetic sediments. While methanediffusing out of the sediment will probably be oxidized,methane ebullition could, dependent on water-column depth,result in the emission of methane from the lake to theatmosphere (McGinnis et al. 2006). Hence, if a lake is subjectto eutrophication, the OC BE is likely to decrease, but themethane emission to the atmosphere is likely to increase.

Climate change has the capacity to alter terrestrialvegetation, soils, and hydrology, and it can thus modifythe export of OC from catchments to lakes. The increasedterrestrial OC export reported from some regions (e.g.,northern Europe) has resulted in a concomitant increase inthe sedimentation of allochthonous OC in lakes (VonWachenfeldt et al. 2008). Increased allochthonous OC inputto the sediments has probably resulted in a higher OC BE in

the lakes of such regions. In regions where terrestrial OCexport has decreased (e.g., Ontario; Schindler et al. 1997),the OC BE in lake sediments has probably been reduced.

Climate change will further alter the thermal propertiesof lakes; while surface waters are expected to experiencesubstantial heating, hypolimnetic waters will probably onlywarm moderately or not at all (De Stasio et al. 1996). Thishas two implications with respect to the fate of sedimentOC. On one hand, higher epilimnetic temperatures willpromote OC mineralization, and thereby reduce OC BE, inepilimnetic sediments (Fig. 4). On the other hand, anincreased temperature difference between epilimnetic andhypolimnetic waters implies prolonged periods of stratifi-cation, which in turn have the potential to greatly increasethe oxygen deficiency in bottom waters (Jankowski et al.2006). The strong relationship between OC BE and OET(Fig. 2) suggests that an increasing hypolimnetic oxygendeficiency would result in a concomitant increase in the OCBE of hypolimnetic sediments in the future.

Further, prolonged anoxia will not only stimulate OCburial, but it will also stimulate methanogenesis. We testedthe potential stimulation of methanogenesis as a result ofoxygen deficiency by combining data from this study withdata from meso- to hypereutrophic lakes and reservoirs inFinland (Huttunen et al. 2006). We found that withdecreasing oxygen penetration depth into the sediment,diffusive CH4 flux from the sediment increased (Fig. 6).Even if the relationship was weak (R2 5 0.28), theregression slope was significantly different from zero (p 50.023), illustrating the negative coupling between oxygenavailability and methane flux from the sediment in a verydiverse set of sediments. Hence, prolonged anoxia will notonly trigger increased OC BE, but it will at the same timegive rise to increased methane emission from the sediment.Given this whole array of potential climate-change effectson OC BE, it is not possible to gauge the net feedback toclimate change with any certainty. However, due to the,20-fold greater global warming potential of CH4 ascompared to CO2, it takes only a very little increase inmethane emission to offset any potential future increase ofthe OC sink in lake sediments.

The high OC BE, particularly of allochthonous OC, inlake sediments illustrates the importance of lakes asmodifiers of carbon export from land to sea. As the meanOC BE for allochthonous lake sediments was 66%, we mayinfer that, on average, on the order of two thirds of theallochthonous OC deposited onto lake sediment is buried.The remainder is mineralized to CO2 and CH4 and mayeventually reach the atmosphere. In that respect, lakesediments could not only act as OC sinks, but they couldalso act as transformers of terrestrial organic carbon toatmospheric CO2 and CH4. This is particularly importantin the case of methane because the transformation of OC toCH4 along the flow path from land to sea is largelyconfined to lake sediments. The channeling of OC intoburial carbon dioxide or methane is dependent on the OCsource, oxygen exposure time, and temperature, all ofwhich are sensitive to environmental change (eutrophica-tion and climate change). While the present studydemonstrates that environmental change will substantially

2252 Sobek et al.

affect the OC BE of lake sediments, further studies areneeded in order to quantify the overall effect of environ-mental changes on OC BE.

AcknowledgmentsWe thank Andreas Brand, Jakob Frommer, Cristian Gudasz,

Lucia Klauser, Ilia Ostrovsky, Tonya del Sontro, MichaelSchurter, and Alois Zwyssig for help with sampling and analyses,and Beat Muller, Martin Marki, and Michael Sturm for sharingdata and sediment samples. This study was supported by the SwissNational Science Foundation (grants 200021 112274 and 200020120112).

References

ALBRECHT, A., R. REISER, A. LUCK, J. M. A. STOLL, AND W.GIGER. 1998. Radiocesium dating of sediments from lakes andreservoirs of different hydrological regimes. Environ. Sci.Technol. 32: 1882 1887.

ALIN, S., AND T. C. JOHNSON. 2007. Carbon cycling in large lakesof the world: A synthesis of production, burial, and lakeatmosphere exchange estimates. Glob. Biogeochem. Cycles21: GB3002, doi: 10.1029/2006GB002881.

AL MUTLAQ, K. F., L. J. STANDLEY, AND B. R. T. SIMONEIT. 2008.Composition and sources of extractable organic matter froma sediment core in Lake Kivu, East African rift valley. Appl.Geochem. 23: 1023 1040.

ARCHER, D., S. EMERSON, AND C. R. SMITH. 1989. Directmeasurement of the diffusive sublayer at the deep sea floorusing oxygen microelectrodes. Nature 340: 623 626.

BASTVIKEN, D., J. J. COLE, M. L. PACE, AND L. J. TRANVIK. 2004a.Methane emissions from lakes: Dependence of lake characteristics, two regional assessments, and a global estimate. Glob.Biogeochem. Cycles 18: GB4009, doi: 10.1029/2004GB002238.

, L. PERSSON, G. ODHAM, AND L. J. TRANVIK. 2004b.Degradation of dissolved organic matter in oxic and anoxiclake water. Limnol. Oceanogr. 49: 109 116.

BRUNAUER, S., P. H. EMMETT, AND E. TELLER. 1938. Adsorption ofgases in multimolecular layers. J. Am. Chem. Soc. 60:309 319.

BURDIGE, D. J. 2007. Preservation of organic matter in marinesediments: Controls, mechanisms, and an imbalance insediment organic carbon budgets? Chem. Rev. 107: 467 485.

COLE, J. J., AND oTHERS. 2007. Plumbing the global carbon cycle:Integrating inland waters into the terrestrial carbon budget.Ecosystems 10: 171 184.

CRANWELL, P. A. 1981. Diagenesis of free and bound lipids interrestrial detritus deposited in a lacustrine sediment. Org.Geochem. 3: 79 89.

DEAN, W. E., AND E. GORHAM. 1998. Magnitude and significanceof carbon burial in lakes, reservoirs, and peatlands. Geology26: 535 538.

DEMAISON, G. J., AND G. T. MOORE. 1980. Anoxic environmentsand oil source bed genesis. Org. Geochem. 2: 9 31.

DEN HEYER, C., AND J. KALFF. 1998. Organic matter mineralization rates in sediments: A within and among lake study.Limnol. Oceanogr. 43: 695 705.

DE STASIO, B. T. J., D. K. HILL, J. M. KLEINHANS, N. P. NIBBELINK,AND J. J. MAGNUSON. 1996. Potential effects of global climatechange on small north temperate lakes: Physics, fish, andplankton. Limnol. Oceanogr. 41: 1136 1149.

DOWNING, J. A., J. J. COLE, J. J. MIDDELBURG, R. G. STRIEGL, C. M.DUARTE, P. KORTELAINEN, Y. T. PRAIRIE, AND K. A. LAUBE.2008. Sediment organic carbon burial in agriculturallyeutrophic impoundments over the last century. Glob. Biogeochem. Cycles 22: GB1018, doi: 10.1029/2006GB002854.

EMERSON, S. R., AND J. I. HEDGES. 1988. Processes controlling theorganic carbon content of open ocean sediments. Paleoceanography 3: 621 634.

FREEMAN, C., N. OSTLE, AND H. KANG. 2001. An enzymatic ‘latch’on a global carbon store. Nature 409: 149.

GALY, V., C. FRANCE LANORD, O. BEYSSAC, P. FAURE, H.KUDRASS, AND F. PALHOL. 2007. Efficient organic carbonburial in the Bengal fan sustained by the Himalayan erosionalsystem. Nature 450: 407 410.

GELINAS, Y., J. A. BALDOCK, AND J. I. HEDGES. 2001. Organiccarbon composition of marine sediments: Effect of oxygenexposure on oil generation potential. Science 294: 145 148.

GRANELI, H. W. 1979. A comparison of carbon dioxideproduction and oxygen uptake in sediment cores from foursouth Swedish lakes. Holarctic Ecol. 2: 51 57.

HAKANSON, L. 2003. Quantifying burial, the transport of matterfrom the lake biosphere to the geosphere. Int. Rev. Hydrobiol. 88: 539 560.

HARTNETT, H. E., R. G. KEIL, J. I. HEDGES, AND A. H. DEVOL. 1998.Influence of oxygen exposure time on organic carbon preservation in continental margin sediments. Nature 391: 572 574.

HEDGES, J. I., F. S. HU, A. H. DEVOL, H. E. HARTNETT, E.TSAMAKIS, AND R. G. KEIL. 1999. Sedimentary organic matterpreservation: A test for selective degradation under oxicconditions. Am. J. Sci. 299: 529 555.

HO, E. S., AND P. A. MEYERS. 1994. Variability of early diagenesisin lake sediments evidence from the sedimentary geolipidrecord in an isolated tarn. Chem. Geol. 112: 309 324.

HOFMANN, A. 1996. Geochemical characteristics and processes ofparticulate matter transport in the north basin of LakeLugano (Switzerland, Italy). Ph.D. thesis. University ofGeneva (written in French).

HOSKULDSSON, A. 1988. PLS regression methods. J. Chemometr. 2:211 228.

Fig. 6. The relationship between oxygen penetration depthinto the sediment and diffusive CH4 flux from the sediment to thewater column. Circles represent data from this study (Swedishboreal lakes, Lake Constance, Lake Wohlen); the open circlerepresents a site receiving sediment from mainly autochthonoussources, and the closed circles represent sites receiving sedimentfrom mainly allochthonous sources. The gray squares show datafrom eight meso and hypereutrophic lakes and reservoirs inFinland (Huttunen et al. 2006). The solid line represents a linearregression for all data in the plot (log CH4 flux 5 1.91 0.15 3oxygen penetration; R2 5 0.28; p , 0.05; n 5 18).

OC burial efficiency in lake sediments 2253

HULTHE, G., S. HULTH, AND P. O. J. HALL. 1998. Effect of oxygenon degradation rate of refractory and labile organic matter incontinental margin sediments. Geochim. Cosmochim. Acta62: 1319 1328.

HUTTUNEN, J. T., T. S. VAISANEN, S. K. HELLSTEN, AND P. J.MARTIKAINEN. 2006. Methane fluxes at the sediment waterinterface in some boreal lakes and reservoirs. Boreal Environ.Res. 11: 27 34.

IPCC. 2007. Climate change 2007: The physical science basis.Contribution of Working Group I to the Fourth AssessmentReport of the Intergovernmental Panel on Climate Change.Cambridge Univ. Press.

JANKOWSKI, T., D. M. LIVINGSTONE, H. BUHRER, R. FORSTER, AND

P. NIEDERHAUSER. 2006. Consequences of the 2003 Europeanheat wave for lake temperature profiles, thermal stability, andhypolimnetic oxygen depletion: Implications for a warmerworld. Limnol. Oceanogr. 51: 815 819.

KEIL, R. G., D. B. MONTLUCON, F. G. PRAHL, AND J. I. HEDGES.1994. Sorptive preservation of labile organic matter inmarine sediments. Nature 370: 549 552.

KOREN, N., AND M. KLEIN. 2000. Rate of sedimentation in LakeKinneret, Israel: Spatial and temporal variations. Earth Surf.Proc. Land. 25: 895 904.

KORTELAINEN, P., H. PAJUNEN, M. RANTAKARI, AND M. SAARNISTO.2004. A large carbon pool and small sink in boreal Holocenelake sediments. Glob. Change Biol. 10: 1648 1653.

KRISTENSEN, E., S. I. AHMED, AND A. H. DEVOL. 1995. Aerobic andanaerobic decomposition of organic matter in marine sediment:Which is fastest? Limnol. Oceanogr. 40: 1430 1437.

LASKOV, C., W. AMELUNG, AND S. PEIFFER. 2002. Organic matterpreservation in the sediment of an acidic mining lake.Environ. Sci. Technol. 36: 4218 4223.

LU, X. 2007. A note on removal of the compaction effect for the210Pb method. Appl. Radiat. Isotopes 65: 142 146.

MARKI, M. 2007. Biogeochemical processes in surface sedimentsof lakes a microscale approach. Ph.D. thesis. Swiss FederalInstitute of Technology Zurich (ETH).

, B. MULLER, C. DINKEL, AND B. WEHRLI. 2009. Mineralization pathways in lake sediments with different oyxgen andorganic carbon supply. Limnol. Oceanogr. 54: 428 438.

, , AND B. WEHRLI. 2006. Microscale mineralizationpathways in surface sediments a chemical sensor study inLake Baikal. Limnol. Oceanogr. 51: 1342 1354.

MARTIN, P., L. GRANINA, K. MARTENS, AND B. GODDEERIS. 1998.Oxygen concentration profiles in sediments of two ancientlakes: Lake Baikal (Siberia, Russia) and Lake Malawi (EastAfrica). Hydrobiologia 367: 163 174.

MAYER, L. M. 1994a. Relationships between mineral surfaces andorganic carbon concentrations in soils and sediments. Chem.Geol. 114: 347 363.

. 1994b. Surface area control of organic carbon accumulation in continental shelf sediments. Geochim. Cosmochim.Acta 58: 1271 1284.

. 1999. Extent of coverage of mineral surfaces by organicmatter in marine sediments. Geochim. Cosmochim. Acta 63:207 215.

MCGINNIS, D. F., J. GREINERT, Y. ARTEMOV, S. E. BEAUBIEN, AND

A. WUEST. 2006. Fate of rising methane bubbles in stratifiedwaters: How much methane reaches the atmosphere? J.Geophys. Res. 111: C09007, doi: 10.1029/2005JC003183.

MECKLER, A. N., C. J. SCHUBERT, G. L. COWIE, S. PEIFFER, AND M.DITTRICH. 2004. New organic matter degradation proxies:Valid in lake systems? Limnol. Oceanogr. 49: 2023 2033.

MIDDELBURG, J. J., T. VLUG, AND F. VANDERNAT. 1993. Organicmatter mineralization in marine systems. Glob. Planet.Change 8: 47 58.

MOLLENHAUER, G., AND T. I. EGLINTON. 2007. Diagenetic andsedimentological controls on the composition of organicmatter preserved in California Borderland Basin sediments.Limnol. Oceanogr. 52: 558 576.

MOODLEY, L., J. J. MIDDELBURG, P. M. J. HERMAN, K. SOETAERT,AND G. J. DE LANGE. 2005. Oxygenation and organic matterpreservation in marine sediments: Direct experimental evidence from ancient organic carbon rich deposits. Geology 33:889 892.

MULHOLLAND, P. J., AND J. W. ELWOOD. 1982. The role of lake andreservoir sediments as sinks in the perturbated global carboncycle. Tellus 34: 490 499.

MULLER, B., M. MARKI, M. SCHMID, E. G. VOLOGINA, B. WEHRLI,A. WUEST, AND M. STURM. 2005. Internal carbon and nutrientcycling in Lake Baikal: Sedimentation, upwelling, and earlydiagenesis. Glob. Planet. Change 46: 101 124.

, AND oTHERS. 2007. Present and past bio availablephosphorus budget in the ultra oligotrophic Lake Brienz.Aquat. Sci. 69: 227 239.

OSTROVSKY, I., AND Y. Z. YACOBI. 1999. Organic matter andpigments in surface sediments: Possible mechanisms of theirhorizontal distributions in a stratified lake. Can. J. Fish.Aquat. Sci. 56: 1001 1010.

POSTMA, D., AND R. JAKOBSEN. 1996. Redox zonation: Equilibriumconstraints on the Fe(III)/SO4 reduction interface. Geochim.Cosmochim. Acta 60: 3169 3175.

ROTHMAN, D. H., AND D. C. FORNEY. 2007. Physical model for thedecay and preservation of marine organic carbon. Science316: 1325 1328.

SCHILLAWSKI, S., AND S. T. PETSCH. 2008. Release of biodegradabledissolved organic matter from ancient sedimentary rocks. Glob.Biogeochem. Cycles 22: GB3002, doi: 10.1029/2007GB002980.

SCHINDLER, D. W., P. J. CURTIS, S. E. BAYLEY, B. R. PARKER, K.G. BEATY, AND M. P. STAINTON. 1997. Climate inducedchanges in the dissolved organic carbon budgets of boreallakes. Biogeochemistry 36: 9 28.

SOBEK, S., L. J. TRANVIK, Y. T. PRAIRIE, P. KORTELAINEN, AND J. J.COLE. 2007. Patterns and regulation of dissolved organiccarbon: An analysis of 7,500 widely distributed lakes. Limnol.Oceanogr. 52: 1208 1219.

STUMM, W., AND J. J. MORGAN. 1996. Aquatic chemistry: Chemicalequilibria and rates in natural waters, 3rd ed. Wiley Interscience.

VON WACHENFELDT, E., S. SOBEK, D. BASTVIKEN, AND L. J.TRANVIK. 2008. Linking allochthonous dissolved organicmatter and boreal lake sediment carbon sequestration therole of light mediated flocculation. Limnol. Oceanogr. 53:2416 2426.

, AND L. TRANVIK. 2008. Sedimentation in boreal lakesthe role of flocculation of allochthonous dissolved organicmatter in the water column. Ecosystems 11: 803 814.

WESSELS, M. 1998. Late glacial and postglacial sediments in LakeConstance (Germany) and their palaeolimnological implications. Arch. Hydrobiol. Suppl. 53: 411 449.

WESTRICH, J. T., AND R. A. BERNER. 1984. The role of sedimentaryorganic matter in bacterial sulfate reduction: The G modeltested. Limnol. Oceanogr. 29: 236 249.

ZEHNDER, A. J. B., AND B. H. SVENSSON. 1986. Life without oxygenwhat can and what cannot? Experientia 42: 1197 1205.

Associate editor: Bo Thamdrup

Received: 26 February 2009Accepted: 26 June 2009Amended: 28 July 2009

2254 Sobek et al.