Environ. Sci. Technol. 2002, 36, 3354-3361
Measurement of Methane Oxidation in Lakes: A Comparison of Methods D A V I D B A S T V I K E N , * ,† JO ¨ RGEN EJLERTSSON,† AND LARS TRANVIK‡ Department of Water and Environmental Studies, Linko¨ping University, 581 83 Linko¨ping, Sweden, and Department of Limnology, Uppsala University, 752 36 Uppsala, Sweden
Methane oxidation in lakes constrains the methane emissions to the atmosphere and simultaneously enables the transfer of methane carbon to pelagic food webs. Several different methods have been used to estimate methane oxidation, but these methods have not previously been compared. In this study, we present methane oxidation estimates from three different lakes during summer and winter, using methods based on the transformation of added 14CH , the fractionation of natural methane 13C, and the 4 mass balance modeling of concentration gradients. All methods yielded similar results, including similar differences between lakes and seasons. Average methane oxidation rates varied from 0.25 to 81 mg of C m-2 d-1 and indicate that the three methods are comparable, although they to some extent take different processes into account. Critical issues as well as drawbacks and advantages with the used methods are thoroughly discussed. We conclude that methods using the stable isotope or mass balance modeling approach represent promising alternatives, particularly for studies focusing on ecosystem-scale carbon metabolism.
Introduction Lakes are sites of intensive methanogenesis as well as methane oxidation (1, 2), and methane dynamics have implications for both lake food webs and methane emissions. Methane oxidation estimates are crucial for the evaluation of how important methane is as a substrate for pelagic bacteria and for the assessment of to what extent methane produced in lakes reach the atmosphere. There are several ways to estimate methane oxidation in lakes. Some methods are based on incubation of water from different depths using bottles or other containers. In the 14CH transformation method, 14C-labeled methane is added 4 to the bottle, and the transformation to 14CO2 or 14C-labeled biomass can then be measured (3, 4). Alternatively, the change in total methane concentration over time in enclosed samples may be measured using ambient (5-7) or elevated (8, 9) methane concentrations. Other methods employ a whole-lake approach and generally rely on information about the methane flux into or out from the water column. Flux measurements can be combined with concentration gradients in the mass balance modeling of diffusive transport and oxidation of methane within the lake (3, 10). Another approach, more often used * Corresponding author phone: +46 13 282960; fax: +46 13 133630: e-mail:
[email protected]. † Linko ¨ ping University. ‡ Uppsula University. 3354
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in landfills and wetlands than in lakes, is based on the discrimination against stable isotopes (e.g., 13C) in the processes of microbial methanogenesis and methane oxidation (11). The 13C fractionation during methanogenesis results in very low δ13C values of biogenic methane, and the δ13C methane signature is then gradually elevated during methane oxidation since residual methane will become enriched in 13 C. The difference in the methane δ13C value at different depths or in emitted methane along with fractionation factors allows calculation of the percentage of the methane entering the system that gets oxidized (1, 11-15). In general, methane oxidation studies employ only one of these methodological approaches, and to our knowledge, there has been no attempt to compare different approaches using simultaneous measurements at the same sites. Consequently, previous studies provide little guidance when results obtained with different methods are compared or for the choice of methods for future studies. For this reason, we compared the 14CH4 transformation method with mass balance and stable isotope (13C fractionation) approaches in three different lakes and at two contrasting seasons, i.e., summer stratification and under ice during late winter.
Methods Three small lakes in south central Sweden were sampled. The lakes were chosen to be deep enough to develop an anoxic hypolimnion during summer stratification and to differ from each other in terms of dissolved organic carbon (DOC), total phosphorus (Tot-P), and total nitrogen (Tot-N) concentrations. Illersjo¨n (64°94′96′′ N, 14°52′66′′ W), being eutrophic and oligohumic, was sampled July 14-15, 1999, and March 1, 2000. Mårn (64°95′96′′ N, 15°04′15′′ W) falls into the eutrophic and mesohumic category and was sampled July 27-28, 1999, and March 15, 2000. Lillsjo¨n (65°04′01′′ N, 15°19′83′′ W) is an oligotrophic, polyhumic lake, and samplings were carried out August 24-25, 1999, and March 7, 2000. (For detailed information on lake water chemistry, see ref 16.) Temperature, Oxygen, and Sampling Depths. At each sampling occasion, vertical temperature and O2 profiles were determined using an oxygen probe (Orion, model 835). The sampling depths for measurement of methane concentration and incubation with 14CH4 were selected from the O2 profile to represent oxic and anoxic water layers as well as the oxycline when present. Time constraints allowed sampling of 5-7 depths, ranging from 0.5 m below the surface to 0.5 m above the sediments. CH4 Concentrations. To collect CH4 samples, water was pumped directly from each sampling depth into each of four replicate 330-mL infusion bottles, using a submersible pump (Amazon 10, Awimex International AB, Sweden). Bottles were flushed with at least three bottle volumes of bubble-free water and then immediately capped without headspace using 17 mm thick butyl rubber stoppers (Rubber B.V., The Netherlands). A syringe needle (Microlance 0.6 mm × 25 mm, Becton-Dickinson) attached to a 1-mL plastic syringe (Plastipak, Becton-Dickinson) with the piston removed allowed excess water to escape without intrusion of air into the bottle during the capping procedure. To stop the methane oxidation and preserve samples, pH was raised to above 11 by the addition of 0.5 mL of 4 M NaOH using a plastic syringe (17). Upon return to the laboratory, after creating a 10-mL N2 headspace in each bottle, CH4 was equilibrated between the remaining water and the headspace by vigorous shaking 3 × 60 s. Headspace CH4 was analyzed using gas chromatography (18). The total amount of CH4 in each bottle, and 10.1021/es010311p CCC: $22.00
2002 American Chemical Society Published on Web 06/25/2002
subsequently the CH4 concentration in the lake water, was calculated using Henry’s law describing gas-water partitioning (19). 13C Analyses. CH was collected at the deepest and the 4 shallowest sampling depth, 0.5 m above the sediment and 0.5 m below the surface, respectively. The water was transferred to one 1000-mL infusion bottle per depth according to the procedure described for the methane concentration sampling but with addition of 2.5 mL of concentrated H2SO4 to inhibit further methane oxidation. CH4 was extracted to equilibrium into a 40-mL N2 headspace created in the laboratory. The headspace gas mixture was transferred into 10-mL evacuated exetainers (Labco Limited, U.K.), showing no exchange of methane for long time periods (years) and holding negligible background methane concentrations. One such exetainer per sampling depth was used for the analysis since test analyses showed that replicates generally were within (1‰ (δ units, see below). The samples were analyzed at the Stable Isotope Facility, Department of Agronomy and Range Science, University of CaliforniasDavis, Davis, CA, using a PDZ Europa TGII trace gas analyzer and on-line continuous flow Europa 20/20 isotope ratio mass spectrometer (IRMS). Isotopic data are reported in δ units (‰) relative to the PDB standard (Pee Dee belemnite) according to
δ13C ) ((Rsample/Rstandard) - 1) × 1000
(1)
where R is the 13C/12C ratio. Flux Measurements. Estimates of the methane flux into the water column are necessary for both the 13C fractionation method and the mass balance model approach. The methane release from the sediments was measured in sediment cores kept at ambient temperature in the laboratory. Four cores per lake and sampling occasion were collected in Plexiglas tubes (6.4 cm diameter) using a gravity sediment corer. They were sealed in the field without any headspace, using rubber stoppers. In the laboratory a 50-mL N2 headspace was introduced using syringes. The methane concentration in the headspace was measured 2-3 times weekly during at least one month. The linear increase in methane concentration observed during the first 7-27 d (r2 ) 0.80-1.00) was used to estimate the release rate of CH4 from the sediment to the water column. Methane emission rates were measured during the summer samplings using floating chambers (6.5 L volume, 0.028 m2 area). Two chambers per lake were floating on the lake surface for 6-9.5 h during the daytime. Samples were withdrawn through a rubber septum and transferred to evacuated infusion vials using a syringe. The difference between initial and final methane concentration was used to calculate the methane emission per square meter and day. Test measurements in other lakes as well as emission calculations with data from the studied lakes showed that diffusive CH4 flux into the chambers dominated and was linear over time during the deployment. Methane Oxidation from 14CH4 Transformation. At each sampling depth, methane oxidation was estimated by the transformation of 14C-labeled CH4 into microbial biomass, dissolved organic carbon (DOC), and dissolved inorganic carbon (DIC). We prepared 14CH4 by growing methanotrophic bacteria (Methanobacterium thermoautotrophicum) in cultures fed with H2 and H14CO3-. The produced 14CH4 was purified by removing CO2 and CO with NaOH and Moleculite (Molecular Products Ltd., Essex, U.K.), respectively (20). Prior to the fieldwork, the purified 14CH4 gas was diluted 1:1000 in N2, and this gas mixture was added to the water samples. Following every preparation of the gas mixture, the CH4 concentration was checked by gas chromatography. At the lake, water from each sampling depth was transferred into six 120-mL infusion bottles using the
submersible pump, as described above. Each bottle was immediately capped without headspace with a 10-mm butylrubber stopper. The stopper was secured using a crimp seal aluminum cap. Thereafter, 0.2 mL of 4 M NaOH was added to two infusion bottles per sampling depth, serving as control bottles with no methanotrophic activity. The NaOH was added through the stopper with a plastic syringe, while 0.2 mL of sample water was removed simultaneously with another syringe to maintain the original pressure in the bottle. Using a gastight glass syringe (SGE Europe Ltd.), 500 µL of the 14CH4 gas mixture was transferred to each infusion bottle. The transfer was carried out holding the bottle upside down so that 500 µL of water could be removed simultaneously to maintain the pressure without interfering with the gas inflow. The volume of the introduced CH4/N2 headspace was a compromise between allowing efficient mixing for the equilibration of CH4 and the desire to induce minimal changes in the concentrations of other ambient gases such as O2 by keeping the headspace as small as possible. The barometric pressure was continuously recorded to allow precise determination of the amount of 14CH4 added to the bottles (additions ranged from 53 to 310 nmol of CH4 per bottle). This procedure of adding 14CH4 as a headspace allowed addition of relatively high amounts of radioactivity to the water phase (22 000-52 000 DPM mL-1, where DPM is decays per minute. The partitioning of CH4 between the headspace and the water was considered in the calculations, and the methane concentration in the samples was increased corresponding to an addition of 0.4-1.8 µM CH4. In bottles with water holding very little natural CH4 (10-100 nM) this change was drastic while in bottles with the highest CH4 levels the addition caused a concentration change of only 0.1-3%. An alternative method is to add water in which 14CH4 is already dissolved, but this results in very low amounts of radioactivity (21) and was consequently not used. When the bottles had been shaken vigorously to equilibrate the 14CH4 between the headspace and the water, they were immersed in net bags to the actual sampling depths for 4-8 h, representing the minimum incubation time yielding reproducible results. Incubation was terminated by the addition of 0.2 mL of 4 M NaOH. The bottles were kept dark and cold (2 °C) for 1-3 d until further processing. In the laboratory, a 20-30-mL subsample from each bottle was filtered through a 0.22-µm mixed cellulose ester filter (Millipore GSWP) to collect bacterial cells. A total of 10 mL of the filtrate was transferred to a 20-mL glass scintillation vial. Thereafter, the filter was rinsed with 5 mL of Milli-Q water. Filters were dissolved in 4 mL of Filter Count scintillation cocktail (Packard BioScience B.V.). The filtrate was purged for 5-7 min with N2 to remove remaining 14CH4. Then 10 mL of Quicksafe A scintillation cocktail (Zinsser Analytic) was added. Radioactivity was measured in a Beckman LS 1801 scintillation counter, correcting quench by the H number method. The filter samples yielded 14C incorporation into cells, while filtrate yielded 14C transformation into DIC and DOC. The specific activity of 14CH4 in the gas mixture added was determined by liquid scintillation counting according to ref 22 using a toluene-based scintillation cocktail (Toluene Scintillator, Packard BioScience B.V.). Specific activities varied between 1.7 × 1013 and 6.4 × 1013 DPM/mol of CH4 depending on the batch of 14CH4 being used each sampling date. The methane transformation rate (MTR; mg of C m-3 d-1) into the different fractions (cells and DIC + DOC) was calculated according to
MTR ) (DPM/DPMadded)[CH4]/t
(2)
where DPM is the incorporated radioactivity corrected for control samples of the same depth. DPMadded represent the VOL. 36, NO. 15, 2002 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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total radioactivity added as 14CH4 to the measured subsample. [CH4] is the natural methane concentration at the studied depth, and t represents the incubation time in days. MTRcells added to MTRDIC+DOC represent the total methane oxidation rate (MOX). Depth integration was performed using simple linear extrapolation between values from adjacent sampling depths. Finally, depth integrated values were normalized to lake surface area. Methane Oxidation from 13C Fractionation. We estimated methane oxidation from three different models of isotope fractionation. First, we used two separate models for open systems at steady state as presented by Happel et al. (12) (eq 3), and Tyler et al. (23) (eq 4):
fopen ) (δs - δb)/((R - 1) × 1000)
(3)
fopen ) (δb - δs)/((δs + 1000)((1/R) - 1))
(4)
where fopen is the fraction of the methane entering the water column that becomes oxidized. δs and δb are the δ13C value of methane at the surface and the bottom, respectively, and R is the isotope fractionation factor. Values of R were estimated experimentally for each lake at 5 and 20 °C, according to Coleman et al. (24). Briefly, water column composite lake water was transferred to 118-mL infusion bottles with a methane-amended headspace (0.01 atm CH4 initially, n ) 4 for each lake and temperature). Changes in methane concentration and δ13C signature in the bottles were monitored over time allowing calculation of R values (24). Bottles were incubated under both oxic and anoxic conditions, but no consumption of methane was detected in the anoxic bottles, and thus no anoxic R values could be determined. Obtained R values from the oxic bottles were similar regardless of lake and temperature (average values were between 1.0184 and 1.0208), and we used a value of 1.02 to estimate the fraction of the methane being oxidized. The oxidized methane fractions needed to be combined with values of the methane flux through the system to get estimates of the lake area methane oxidation (MOX; mg of C m-2 d-1). Under the open steady-state system assumption, the methane release rate from the sediments (representing the input rate to the water) was combined with fopen according to
MOX ) fopen × flux from sediments
(5)
The flux from the sediments could also be indirectly estimated from methane emissions and fopen since the emitted methane represents the fraction escaping oxidation, i.e., flux from lake surface ) sediment flux × (1 - fopen). Therefore, to get an additional estimate of the methane oxidation, we also did the following calculation during the summer when methane emissions were measured:
MOX ) fopen × flux from lake surface/(1 - fopen)
(6)
The assumption of an open steady-state system may be questionable, especially during the wintertime when a 2070-cm ice layer covered the lakes. Therefore, we also used the Rayleigh model for closed systems (13)
ln(1 - fclosed) ) [ln(δb + 1000) - ln(δs + 1000)]/[R - 1] (7) to calculate the fraction of the methane being oxidized under closed system conditions (fclosed). Values of fclosed were multiplied with methane flux from the sediments to yield the total depth integrated methane oxidation. Equation 7 is based on the assumption that no methane leaves the system, and it was therefore not used with emission values. 3356
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Methane Oxidation from Mass Balance Modeling. To estimate the methane oxidation from concentration measurements, a mass balance model was developed in STELLA for Research 5.1.1. for Windows. The model considered the water column to consist of horizontal layers being 0.25 m thick. A simple and generalized cone-shaped lake morphometry, with a bottom plane radius of 50 m and a surface plane area corresponding to actual lake area, was used. The measured flux rates from the sediment cores were used as methane input rates to the water column from anoxic sediments, i.e., sediments overlain with anoxic water as determined from the measured O2 profiles. The methane flux from oxic sediments (i.e., overlain with oxic water) was varied from 100 to 0% of the flux from anoxic sediments to simulate the model sensitivity to potential methane oxidation in oxic sediment layers. It was assumed that the methanogenesis occurring in the water could be neglected in the model. The horizontal transport of methane within each water layer was assumed to be instantaneous, while the vertical transport between the layers was calculated from Fick’s first law using diffusion coefficients representing a combination of molecular and turbulent diffusion (25, 26). The model was run with diffusion coefficients ranging from 1 × 10-8 to 1 × 10-5 m2 s-1 representing literature values from lake hypolimnia (25-27). Sensitivity analysis with regard to diffusion coefficients was performed by running model scenarios with different diffusion coefficients, including both the same diffusion coefficients at all depths and a 10-1000-fold decrease in the diffusion coefficient upon increased temperature differences between water layers. Methane oxidation was modeled as removal of a certain fraction of the methane in each layer. We simulated the measured methane concentrations during 120-150 days representing the approximate time since lake circulation occurred. The modeled methane oxidation represents the sum of the methane oxidized in all layers when the best possible fit to measured concentrations was obtained for each diffusion coefficient and methane flux setting.
Results All lakes were thermally stratified during summer with low oxygen concentrations in the hypolimnetic water (Figure 1). During winter, O2 was present throughout the water column, except in water very close to the sediments. Methane concentrations in all lakes showed a similar pattern with concentrations of 30-160 µM close to the sediments and a drastic decrease usually within a few meters to between 0.03 and 0.5 µM in the surface water. The methane oxidation at different depths as measured by 14CH4 transformation was generally greatest in the hypolimnion where methane concentrations were high, regardless of whether O2 was present or not (Figure 1). Individual measurements of 14CH4 transformation rates ranged from 0.001 to 39 mg of C m-3 d-1. The δ13C methane signatures differed a lot between bottom and surface waters (Table 1). Assuming that bottom water signatures represent methane not being subjected to oxidation, the difference indicates that 57-100% of the methane produced in lake sediments or water was oxidized before reaching the lake surface (Table 1). Consistent differences were found between the equations used. The lowest estimates were given by the equation for closed systems (eq 7). Among the two open steady-state system equations, eq 4 yielded the highest estimates. Both eq 3 and eq 4 suggest that 100% of the methane was oxidized during winter. Regardless of the equation used, a larger fraction was oxidized in Mårn and Lillsjo¨n than in Illersjo¨n. The methane flux results (Table 1) yield a similar picture with highest methane emissions relative to sediment flux in Illersjo¨n.
FIGURE 1. Depth profiles of temperature (line), O2 concentration (gray circles), methane concentration (open squares), and methane oxidation from 14CH4 transformation measurements (black triangles) in the three studied lakes. Error bars denote the full range of the measurements (n ) 4). Note the expanded scales for the methane oxidation in Lillsjo1 n, illustrating very low yet measurable rates. All different approaches to measure methane oxidation yielded estimates in a similar range (Table 2). The 14CH 4 transformation method was most variable, both within and between lakes, and yielded highest average estimates during summer in Illersjo¨n and Mårn as compared to other approaches. During winter, all methods yielded similar results in Illersjo¨n, while the 14CH4 transfor-
mation method yielded the lowest estimates in Mårn during winter and in Lillsjo¨n during both summer and winter. Regarding differences between lakes, all approaches showed a similar pattern with greatest methane oxidation rate in Illersjo¨n during summer, followed by similar rates in Mårn and in Illersjo¨n during winter, and lowest rates in Lillsjo¨n (Table 2). VOL. 36, NO. 15, 2002 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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TABLE 1. δ13C Methane Signatures, Percentage of the Methane That Was Oxidized within the Lake As Estimated from the δ13C Values, and Measured Methane Fluxes from Sediment and Lake Surface, Respectively Illersjo1 n July 1999 methane signature 0.5 m below surface (n ) 1) δ13C methane signature 0.5 m above sediment (n ) 1) percentage CH4 oxidizeda open steady-state system eq 3 eq 4 closed system eq 7 CH4 flux from sediment (mg of C m-2 d-1, n ) 4)b CH4 flux from surface (mg of C m-2 d-1, n ) 2)b δ13C
Lillsjo1 n
Mårn
March 2000
July 1999
March 2000
July 1999
March 2000
-55.3 -71.9
-58.0 -73.8
-51.5 -70.7
-44.9 -70.9
-57.2 -79.2
-56.5 -80.6
83 90 59 28.8 ( 3.2 9.64 ( 3.90
79 86 57 12.6 ( 1.4 nd
95 >100 64 12.7 ( 2.0 1.04 ( 0.02
>100 >100 75 13.6 ( 6.0 nd
>100 >100 69 8.1 ( 0.8 0.43 ( 0.01
>100 >100 73 6.8 ( 1.0 nd
a Calculated using R ) 1.02. Equations 3 and 4 represent two different open steady-state models, while eq 7 refers to the Rayleigh closed system model. See text for details. b Average ( 1 SD.
TABLE 2. Depth Integrated Methane Oxidation Rates from Different Approaches in Three Lakes water column methane oxidation (mg of C m-2 d-1) for each lake and season Illersjo1 n approach 14CH
4
transformationa
n ) 4 bottles per sampling depth) 13C fractionationa,b flux from sediment cores (n ) 4 sediment cores) flux from lake surfaced: (n ) 2 floating chambers) mass balance modelg
eq 3 eq 4 eq 7 eq 3 eq 4
Lillsjo1 n
Mårn
July 1999
March 2000
July 1999
March 2000
52 ( 30 24 ( 2.6 26 ( 2.8 17 ( 1.9 46 ( 19 81 ( 33 20-33
July 1999
March 2000
8.7 ( 0.7
21 ( 10
3.1 ( 0.1
0.25 ( 0.03
0.32 ( 0.15
10 ( 1.1 11 ( 1.2 7.2 ( 0.8 nde nde 8-18
12 ( 1.9 13 ( 2.0c 8.1 ( 1.3 20 ( 0.4 ndf 8-19
14 ( 6.0c 14 ( 6.0c 10 ( 4.5 nde nde 8-20
8.1 ( 0.8c 8.1 ( 0.8c 5.6 ( 0.6 ndf ndf 5-12
6.8 ( 1.0c 6.8 ( 1.0c 5.0 ( 0.8 nde nde 4-10
a Mean values ( SD. b Equations 3 and 4 represent two different open steady-state models, while eq 7 refers to a closed system model. Error estimates are based on flux rate variation. Approximately (10% should be added to consider potential errors in the δ13C signatures and R-values. c Equal to sediment flux assuming that 100% of the methane is oxidized (see Table 1). d nd denotes no data. e Flux from lake surface not measured during winter due to ice on lakes. f Calculation not possible since 13C fractionation indicates that 100% or more of the methane gets oxidized (see Table 1). g Based on concentration gradients and flux from sediment cores. Reported ranges include the total combined variation from the sensitivity analyses regarding diffusion coefficients and methane input from oxic sediments. See text for details.
The mass balance modeling yielded a diffusion coefficient range of about 2 orders of magnitude, within which it was possible to get a good fit with measured concentrations (Figure 2 A,B). Within this range, the methane oxidation was insensitive to diffusion coefficients and moderately sensitive to the input from oxic sediments (Figure 2C). Since these factors are unknown, we report the whole range given by the sensitivity analysis (Table 2). The sensitivity to the flux from oxic sediments is to be expected since a higher flux from oxic sediments results in a higher total flux of methane into the lake. In general terms, the most critical factor in the model was the methane flux. Methane oxidation estimates from both the concentration gradient model and the 13C fractionation approach were directly proportional to the flux values used in calculations.
Discussion In this study, several widely different approaches yielded similar estimates of methane oxidation as well as similar relative differences between different sites and sampling occasions. All approaches indicated higher methane oxidation rates in the two nutrient-rich lakes (Illersjo¨n and Mårn) than in the oligotrophic lake (Lillsjo¨n) as well as higher methane oxidation rates during summer than during winter, especially in the nutrient-rich lakes (Table 2). The difference between seasons was probably not caused by temperature since most of the methane oxidation occurred at depths having similar temperatures both seasons. More likely, differences between lakes as well as between seasons reflect differences in primary production and overall microbial carbon metabolism, being most extensive in nutrient-rich lakes during the summer. 3358
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14CH
4 Transformation Approach. Individual measurements of 14CH4 transformation during this study (Figure 1) are within the range of previously reported estimates of methane oxidation in lakes (0-207 mg of C m3 d-1 (4-6, 8, 28-31). There was considerable variation in measurements at some depths (Figure 1). If all potential errors related to the methodology interact, we estimate that maximum variability would be (25%. Thus, the observed variation at some depths cannot be fully explained by measurement procedures. Another potential source of variability is that water was sampled from a steep gradient in the methane oxidation profile. This is highly plausible since methane oxidation is often restricted to narrow horizontal zones in the water column (4, 17, 28, 32). The addition of 14C-labeled methane substantially increased methane concentrations in the bottles with low levels of ambient methane (see Methods section). Possibly, this resulted in overestimated methane oxidation rates from these depths. However, at depths having high methane concentrations as well as the highest methane oxidation, methane additions were proportionally small. Thus, the effect of methane addition on the depth integrated rates was most likely minor. For comparison of depth integrated methane oxidation rates with previous studies, Rudd and Taylor (3) and Striegl and Michmerhuisen (30) used bottle incubation techniques and reported methane oxidation per lake area unit to be 33 and 10-700 mg of C m-2 d-1, respectively. This is in the same range as our estimates from Illersjo¨n and Mårn. Whole-Lake Approaches. The measured 13C methane signatures seem reasonable as compared to previous studies (11, 14) and indicate that extensive methane oxidation occurs in all the studied lakes despite the low 14CH4 transformation
FIGURE 2. Results from the mass balance model based on concentration gradients. Data are from Mårn during summer, and the model was run for 120 d. Modeled concentration profiles with different diffusion coefficients (kd) vs observed methane concentrations ([CH4]; diamonds) are shown both without any methane oxidation (A) and with methane oxidation in the model (B). This illustrates that the model could not predict the concentration profile without any methane oxidation and that a good fit was possible only with a part of the kd-range tried. (Panels A and B show selected [CH4] only. For all observations, see Figure 1.) Methane oxidation estimates were more sensitive to the methane flux from oxic sediments (sedfluxox) than to kd (C). sedfluxanox represents methane flux from sediments overlain with anoxic water as measured in the sediment cores (see text for details).
rates in Lillsjo¨n (Tables 1 and 2). Our estimates of isotope fractionation factors are also in the same range as several other measurements (11, 24, 33). In lake water, the concentrations of methane generally range from 100 and occasionally up to 1000 µM (4, 6, 28-30, 32, 34). Both this range and the methane concentration profiles reported correspond well with our results. Diffusive emission from the surface of the lakes ranged from 0.4 to 9.6 mg of C m-2 d-1, which is in within the range of 0.4-29 mg of C m-2 d-1 found in previous studies (32, 35-39). However, our measurements of methane flux from the sediments (6.8-28.8 mg of C m-2 d-1) are lower than most previous estimates (59-291 mg of C m-2 d-1) (3, 8, 32, 40-42). Hence, it may be hypothesized that the sediment core experiments underestimated sediment flux. Although we took care to achieve undisturbed sediment cores, possible reasons for biased methane flux include disturbance of the sediment during the sampling procedure, both by mechanical disturbance and by changes in barometric pressure. Underestimated flux from the sediment is suggested also by methane oxidation estimates from the 13C fractionation approach, which were about twice as high when methane emission rates from the lake surface were used instead of the sediment flux rates. In the whole-lake approaches (13C fractionation and mass balance modeling), lake area integrated methane oxidation is directly proportional to the sediment flux. This sensitivity to flux rates should be carefully considered in future studies. In situ flux measurements are probably more appropriate than flux measurements from sediment cores but could unfortunately not be performed in this study for practical reasons. The comparison of the different equations in the 13C fractionation method reveals that the choice of equation can be more important for the results than potential errors in the δ13CH4 signatures or in the R value. The closed system equation (eq 7) consistently yielded lower values of methane oxidation than the equations for open systems at steadystate (eqs 3 and 4) (Tables 1 and 2). It is likely that the closed system model underestimates the methane fraction being oxidized by not taking the continuous supply of 13C-depleted methane into account (13). On the other hand, the open steady-state equations frequently suggested that more than 100% of the methane was oxidized (Table 1). This is obviously an overestimate since some methane was present in the surface water. Interestingly, none of the open steady-state equations worked during winter, when lakes presumably behave more like a closed system than during summer. There is usually a gradual buildup of methane in a stratified water column, and if the lake has not reached steady state, it will probably behave like a system being somewhere between completely closed and completely open. Then, the most plausible methane oxidation estimate will be intermediary to the values yielded from the closed system and the open steady-state equations, respectively. Hence, it seems appropriate to always use equations for both those situations simultaneously in lake studies. Not only the flux rates but also the methane flux patterns within lakes are critical for the whole-lake approaches. In stratified lakes, the main source of surface water methane may depend on lake morphometry. The epilimnetic CH4 represents a mixture of methane coming from the hypolimnion and from the epilimnetic sediments (the hypolimnetic pathway and the epilimnetic sediment pathway, respectively, in Figure 3). Hence, the epilimnetic δ13CH4 signature reflects fractionation (e.g., oxidation) in both the water column and the epilimnetic surface sediments. If the area of the epilimnetic sediments is large as compared to the area of the metalimnion, most surface water methane may have originated in epilimnetic sediments. In such cases, methane oxidation estimates from the 13C fractionation method will VOL. 36, NO. 15, 2002 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 3. Illustration of methane dynamics in a lake during summer stratification. Methane is exported from anoxic sediments into the lake where it either accumulates in anoxic bottom waters, gets oxidized in a zone of extensive net methane consumption in anoxic or oxic water layers and in oxic sediments, or reaches well-mixed surface water and gets emitted to the atmosphere. The picture shows only net fluxes and not specific microbial processes (e.g., methanogenesis or anoxic and oxic methane oxidation). The zone of net methane consumption indicates where most of the methane is oxidized, although some methane oxidation may occur at lower rates outside that zone. The “epilimnetic sediment pathway” and the “hypolimnetic pathway” denote different routes of methane into the epilimnion. be biased by methane oxidation in epilimnetic surface sediments. On the other hand, if the metalimnetic area is large as compared to the eplimnetic sediment area, methane produced in hypolimnetic sediments will constitute a larger fraction of the surface water methane. Then, estimates from the 13C fractionation method will primarily reflect the water column methane oxidation. Given sufficient knowledge about the flux patterns, the role of both hypolimnetic and epilimnetic sediments could, of course, be investigated by collecting additional sediment methane samples. The mass balance model is also affected by the flux pattern due to its sensitivity to the flux from oxic sediments (Figure 2C). Obviously, this method would benefit from detailed methane concentration profiles. However, Figure 2A,B shows that it is possible to get at least a rough estimate of the methane oxidation from only three measurements in a concentration gradient, the rate of methane input, and some basic system assumptions, such as the flux from oxic sediments and the realistic time period to be modeled. Reliable flux estimates may therefore be more important than very detailed concentration gradients. In stratified lakes, there may be a considerable time delay between release of methane from hypolimnetic sediments and its entry into surface waters. Consequently, flux rates and the 13C methane signature in the bottom water become largely uncoupled from the conditions pertaining to the surface water methane. This time delay complication is avoided by the assumption of steady-state methane dynamics, but ideally such an assumption should be verified by consecutive concentration measurements throughout a depth profile as well as by consecutive measurements of the 13C isotopic signatures. As indicated by the model used to estimate methane oxidation from concentration gradients, methane dynamics in dimictic lakes approach steady state throughout a stratification period since the buildup of methane in the hypolimnion steepens the concentration gradient which in turn increases the flux through the water column. Late during the stratification period, the flux from the sediment is probably relatively small as compared to the pool of hypolimnetic methane driving the upward flux, which makes it reasonable to assume steady-state dynamics. Comparison of Methods. All tested approaches yielded similar estimates of lake methane oxidation, and they all share a few common features apart from those being obvious in the method description: None of the methods consider ebullition since bubbles of methane presumably pass the 3360
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water column too rapidly to make any significant contribution to water column methane dynamics. In addition, all methods can account for both oxic and anoxic methane oxidation, the latter presumably being more important in lakes rich in sulfate. The 13C fractionation method may however require an additional R value for anoxic methane oxidation (43). Interestingly, although anoxic methane oxidation was measured in situ, we could not detect any anoxic methane consumption when determining R values. In these laboratory incubations, we used aged lake water and monitored methane concentrations with time. Potentially, the use of freshly sampled water is critical for such incubations. Despite the common features outlined above, there are fundamental differences between the approaches. The 14CH 4 transformation method yields the instantaneous methane oxidation rates at discrete depths. It also gives the gross methane oxidation (CH4 consumption only). The wholelake approaches, on the other hand, integrate methane oxidation rates between sampling depths as well as back in time and return the net methane oxidation (CH4 consumption minus production). The difference between gross and net methane oxidation rates may be tiny if the methane formation largely occurs in the sediments and is negligible in the water column (32), and this is often assumed to be the case in bottle incubation approaches (5, 6). The instantaneous and spatially discrete versus the spatially and temporally integrative characteristics of the used approaches could however cause the results to differ. Potentially, this explains why the whole lake approaches consistently yielded higher methane oxidation rates than the 14CH4 transformation method during winter (Table 2). Practical advantages with the 14CH4 transformation method include that it can detect very low transformation rates at specific depths and that it is theoretically simple and straightforward. It can also provide information about the bacterial growth efficiency of methane oxidizers. The method is fast if 14CH4 can be bought already made, but with 14CH4 production included the method becomes quite tedious. The whole-lake approaches are very sensitive to flux estimates, but with some information about the flux patterns, these methods represent convenient ways to estimate whole system methane oxidation. In studies demanding only limited or relatively easily measured flux information, such as methane emissions from the lake surface, the 13C fractionation approach could potentially be very useful. Thus, the presented whole-lake approaches represent promising alternatives to
estimate lake methane oxidation, particularly when questions concerning whole system carbon metabolism are in focus.
Acknowledgments We thank Jenny Gro¨nesjo¨, David Kvick, Dan Lindmark, Annika Fredriksson, and David Harris for invaluable practical assistance. Håkan Olsson kindly provided information about the sampled lakes. We also thank Gunnar Bo¨rjesson and Bo Svensson for generously sharing their knowledge and for inspiring discussions. The contribution of four anonymous reviewers substantially improved the manuscript. This study was funded by the Swedish Natural Science Research Council.
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Received for review December 3, 2001. Revised manuscript received May 2, 2002. Accepted May 15, 2002. ES010311P
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