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Geochimica et Cosmochimica Acta 188 (2016) 163–188 www.elsevier.com/locate/gca

Diverse origins of and Subarctic point source emissions identified with multiply-substituted isotopologues

P.M.J. Douglas a,⇑, D.A. Stolper a,b, D.A. Smith a,c, K.M. Walter Anthony d, C.K. Paull e, S. Dallimore f, M. Wik g,h, P.M. Crill g,h, M. Winterdahl h,i, J.M. Eiler a, A.L. Sessions a

a Caltech, Division of Geological and Planetary Sciences, United States b Princeton University, Department of Geosciences, United States c Washington University, Department of Earth and Planetary Sciences, United States d University of -Fairbanks, International Arctic Research Center, United States e Monterey Bay Aquarium Research Institute, United States f Natural Resources , Canada g Stockholm University, Department of Geological Sciences, h Stockholm University, Bolin Center for Research, Sweden i Stockholm University, Department of Physical Geography, Sweden

Received 9 November 2015; accepted in revised form 18 May 2016; Available online 25 May 2016

Abstract

Methane is a potent , and there are concerns that its natural emissions from the Arctic could act as a sub- stantial to anthropogenic global warming. Determining the sources of and the biogeo- chemical processes controlling them is important for understanding present and future Arctic contributions to budgets. Here we apply measurements of multiply-substituted isotopologues, or clumped isotopes, of methane as a new tool to identify the origins of ebullitive fluxes in Alaska, Sweden and the . When methane forms in isotopic equilibrium, clumped isotope measurements indicate the formation temperature. In some microbial methane, however, non- equilibrium isotope effects, probably related to the kinetics of , lead to low clumped isotope values. We iden- tify four categories of emissions in the studied samples: thermogenic methane, deep subsurface or marine microbial methane formed in isotopic equilibrium, freshwater microbial methane with non-equilibrium clumped isotope values, and mixtures of deep and shallow methane (i.e., combinations of the first three end members). Mixing between deep and shallow methane sources produces a non-linear variation in clumped isotope values with mixing proportion that provides new constraints for the formation environment of the mixing end-members. Analyses of microbial methane emitted from lakes, as well as a methanol-consuming methanogen pure culture, support the hypothesis that non-equilibrium clumped isotope values are controlled, in part, by kinetic isotope effects induced during enzymatic reactions involved in methanogenesis. Our results indi- cate that these kinetic isotope effects vary widely in microbial methane produced in Arctic lake sediments, with non- equilibrium D18 values spanning a range of more than 5‰. Ó 2016 Elsevier Ltd. All rights reserved.

Keywords: Methane; Clumped isotope geochemistry; Arctic; cycle; Greenhouse gases

⇑ Corresponding author. Tel.: +1 626 720 1437; fax: +1 (626) 568 0935. E-mail address: [email protected] (P.M.J. Douglas). http://dx.doi.org/10.1016/j.gca.2016.05.031 0016-7037/Ó 2016 Elsevier Ltd. All rights reserved. 164 P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188

1. INTRODUCTION 1999). For example, thermogenic methane typically con- tains greater 13C/12C and D/H ratios relative to microbial Methane (CH4) is a critical atmospheric greenhouse gas, methane (Schoell, 1980). Additionally, stable isotope mea- with 28 times (on a molar basis) the global warming poten- surements can in some cases differentiate between pathways tial of CO2 on a 100-year timescale (Myhre et al., 2013). of microbial methanogenesis (Whiticar et al., 1986; Krzycki Due to its importance to the climate state of the Earth, et al., 1987; Hornibrook et al., 1997, 2000; Whiticar, 1999; the sources of methane to the and how they Conrad et al., 2002; Kru¨ger et al., 2002; Walter et al., 2008; might respond to future are of key concern. Brosius et al., 2012). In particular, hydrogenotrophic One region where natural (i.e., non-anthropogenic) methanogenesis (i.e., methanogens that reduce CO2 with 13 12 methane emissions are of interest and concern is the Arctic, H2) is thought to produce methane with lower C/ C which has been predicted to experience pronounced warm- and higher D/H relative to fermentative methanogenesis ing in the future (Holland and Bitz, 2003; Comiso and Hall, (i.e. methanogens that metabolize acetate or other methy- 2014). Methane emissions from Arctic environments have lated compounds) (Whiticar et al., 1986; Whiticar, 1999). been predicted to increase under a warmer climate However, ambiguities in the isotopic composition of (Christensen et al., 2004; Walter et al., 2006; O’Connor methane can preclude accurate source assignment et al., 2010; Walter Anthony et al., 2012; Thornton et al., (Martini et al., 1996; Prinzhofer and Pernaton, 1997; 2015; Wik et al., 2016), thus acting as a positive feedback Waldron et al., 1998, 1999; Valentine et al., 2004; to global warming (Anisimov, 2007; Schuur et al., 2008, Conrad, 2005). For example, microbial methanogenesis in 2015; Isaksen et al., 2011; Koven et al., 2011). some environments can produce stable isotope composi- Microbial methanogenesis in wetland and lake sedi- tions resembling thermogenic methane (Martini et al., ments is thought to be the dominant source of natural 1996; Valentine et al., 2004). Additionally, multiple factors methane emissions originating in the Arctic, contributing in addition to methanogenic pathway can substantially up to 90% of emissions during the boreal summer (Fisher influence the stable isotope composition of microbial et al., 2011). Consequently, this source has been the pri- methane, including substrate isotopic composition, sub- mary focus of studies of strate limitation, the kinetics of methane production, trans- (Walter et al., 2006; Schuur et al., 2008; Fisher et al., port, and oxidation (Sugimoto and Wada, 1995; Waldron 2011; Isaksen et al., 2011). However, recent studies have et al., 1998, 1999; Whiticar, 1999; Valentine et al., 2004; identified two additional and potentially important sources Conrad, 2005; Penning et al., 2005). These multiple influ- of natural Arctic methane emissions. First, analyses of the ences on methane stable isotope values can complicate isotopic and molecular composition of gases from ebullitive inferences regarding the pathway of methanogenesis in nat- seeps in Alaskan lakes have suggested that many of these ural samples (Conrad, 2005). seeps emit methane from thermogenic or deep subsurface Recently the analysis of multiply-substituted isotopo- microbial sources. Such gases are thought to be transported logues, or ‘clumped isotopes’, has emerged as an additional to the surface by faults, and stored in shallow reservoirs isotopic constraint on the sources of methane (Tsuji et al., underlying and (Walter Anthony 2012; Ono et al., 2014; Stolper et al., 2014a,b; Inagaki et al., 2012). The emission of methane from these deep et al., 2015; Stolper et al., 2015; Wang et al., 2015). sources could be enhanced as permafrost thaws and glaciers Clumped-isotope geochemistry refers to the analysis of melt, which could increase the number of conduits from the abundances of molecules containing multiple rare, 13 12 subsurface reservoirs to the atmosphere (Formolo et al., heavy isotopes (e.g. CH3D and CH2D2). Clumped iso- 2008; Walter Anthony et al., 2012). tope analyses are of interest in part because the proportions Second, methane ebullition has been observed in several of clumped isotope in equilibrated systems are solely locations on the continental shelf and slope of the Arctic a function of temperature-dependent homogeneous phase Ocean (Paull et al., 2007; Westbrook et al., 2009; equilibria (Urey and Rittenberg, 1933; Wang et al., 2004) Shakhova et al., 2010). The sources of these bubbles may and can be used to determine formation or re- be from either the dissociation of gas hydrates or the thaw- equilibration temperatures of a molecule using only a single ing of permafrost inundated by following the phase, as opposed to multiple phases as is typical in stable- last deglaciation (Paull et al., 2007; Westbrook et al., isotope-based geothermometry (Eiler and Schauble, 2004; 2009; Portnov et al., 2013; Frederick and Buffett, 2014). Ghosh et al., 2006; Stolper et al., 2014a,b). See Eiler Methane emitted from the Arctic Ocean shelf may not have (2007, 2011, 2013), and references therein for detailed a significant influence on atmospheric budgets, given evi- reviews of clumped-isotope geochemistry. dence for its efficient oxidation in sediments and the water The first accurate and precise clumped isotope measure- column (Graves et al., 2015; Overduin et al., 2015). Never- ments of methane were achieved on a prototype high- theless, the source and distribution of methane emissions resolution isotope ratio mass spectrometer—the Thermo from the Arctic Ocean remain poorly constrained (Kort Fisher IRMS 253 Ultra (hereafter the ‘Ultra’) (Eiler et al., et al., 2012; Schuur et al., 2015), making it difficult to quan- 2013). Most measurements of methane clumped isotopes titatively evaluate the importance of these sources to the performed with the Ultra report variations in the sum of 13 12 atmospheric methane budget. CH3D and CH2D2, as measured by the quantity D18 Carbon and hydrogen stable isotope measurements are (Stolper et al., 2014a). D18 values represent the relative devi- an important tool for fingerprinting different sources of ation in a sample from the amount of mass-18 methane pre- methane (Schoell, 1980; Whiticar et al., 1986; Whiticar, dicted for a random distribution of isotopes among all P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 165 isotopologues of the sample (for more details see Sec- Wang et al., 2015; Yeung et al., 2015), and preclude, or at tion 2.5). D18 values primarily reflect the anomaly in least complicate, the accurate identification of sample for- 13 CH3D, which makes up 98% of the mass-18 isotopo- mation temperatures. At the same time, non-equilibrium logues in naturally-occurring methane (Stolper et al., clumped isotope signatures have the potential to provide 2014a). In systems that are in internal isotopic equilibrium, valuable new information about chemical kinetics and bio- the D18 value is a unique function of the sample’s formation chemical reaction pathways (Passey, 2015; Stolper et al., or re-equilibration temperature (Stolper et al., 2014a,b), 2015; Wang et al., 2015; Yeung et al., 2015). and is particularly useful in differentiating high temperature This paper provides a focused application of clumped thermogenic from low temperature microbial methane (e.g. isotope analyses to understand the origin of methane emit- Stolper et al., 2015). ted from natural point sources in the Arctic, with a focus on Mixing of gases that differ in their conventional isotopic methane bubble fluxes from lakes in Alaska and Sweden composition (i.e., 13C/12C and D/H) can produce non- and from the Beaufort Sea in the Arctic Ocean. In addition linear variations in clumped isotope indices (including to providing new insights into the methane budgets of these D18)(Fig. 1)(Eiler and Schauble, 2004; Eiler, 2007). Such locations, this study provides an example of how methane mixing effects have been studied for CO2,O2, and CH4 clumped-isotope analyses can be used to understand and and have contributed to the understanding of gas mixing quantify the sources of methane emissions in natural envi- in natural samples (Affek and Eiler, 2006; Yeung et al., ronments. We focus on two key applications of clumped 2012; Stolper et al., 2014b, 2015). In poorly constrained isotopes. First, we apply this technique to differentiate the cases these mixing effects can complicate clear interpreta- contributions of microbial and thermogenic methane to tion of clumped isotope signals, and could be misinter- ebullitive methane fluxes. Second, we explore the factors preted as incorrect formation temperatures. When controlling the clumped-isotope values of microbial clumped isotope data are combined with other isotopic or methane emitted in Arctic environments. We also present gas composition data, however, this phenomenon becomes an analysis of methane produced by a methanogen pure a potentially powerful tool to recognize mixing and con- culture consuming a methanol substrate, which provides strain the properties and relative proportions of end mem- insights into the clumped isotope signature of fermentative bers in mixed gases. pathways of methanogenesis. In some situations, clumped-isotope values of CO2, car- bonate minerals, O2, and CH4 have been shown to deviate 2. METHODS from their thermodynamically predicted equilibrium value in materials where the formation temperature is known or 2.1. Study sites well-constrained (Ghosh et al., 2006; Affek et al., 2007, 2008; Kluge and Affek, 2012; Saenger et al., 2012; Stolper We analyzed a total of 26 samples from 12 lakes and 3 et al., 2014b, 2015; Wang et al., 2015; Yeung et al., 2015). marine localities (Table 1, Fig. 2). Samples were chosen These non-equilibrium clumped isotope values are generally to include a diverse set of Arctic environments with differ- thought to be related to kinetic isotope effects (Kluge and ences in methane flux and conventional stable isotope geo- Affek, 2012; Affek and Zaarur, 2014; Stolper et al., 2015; chemistry. In particular, we selected some samples that

AB

13 Fig. 1. Hypothetical examples of non-linear mixing effects for D18 values. Plots show mixing relationships in d C–D18 space (A) and dD–D18 space (B) for mixtures of methane with varying end-member compositions. In these examples the end-member D18 values remain fixed at 3‰ and 6‰, but the d13C and dD values of the isotopically light end-member varies. End-member d13C and dD values are denoted on the plots. 13 13 For mixtures where d C and dD values are relatively similar, mixing in D18 is approximately linear (solid line); as the d C and dD values of the mixing end-members become increasingly widely spaced the non-linearity of mixing in D18 becomes more pronounced (dashed lines). Table 1 163–188 (2016) 188 Acta Cosmochimica et Geochimica / al. et Douglas P.M.J. 166 Sample location, [C1]/[C2], CH4 flux, and CO2 and H2O isotope data. a b 13 Sample Region Latitude (°N) Longitude (°E) [C1]/[C2] CH4 flux 1rdCCO2 (‰, VPDB) Estimated H2O dD 1r (‰, VSMOW) Cake Eater North Slope 71.28 156.64 nd 0.017c 23.39 135h 16 Sukok North Slope 71.07 156.82 655 39.48c 27.35 n/a Lake Q North Slope 70.38 157.35 nd 93400d 37.76 n/a Killarney Fairbanks 64.87 147.90 na 2.5e 1.81 19.82 n/a Goldstream-Hotspot Fairbanks 64.92 147.85 na 6.5e 4.7 19.22 210i 30 Goldstream-Tiny Fairbanks 64.92 147.85 nd 0.116e 17.28 186j 30 Goldstream-A Fairbanks 64.92 147.85 na 0.005e 0.005 24.12 156k 30 Doughnut Fairbanks 64.90 147.91 145 25.9f 21.28 4.07 210i 30 Smith-Hotspot Fairbanks 64.87 147.87 nd 6.7e 4.87 11.03 156k 30 Eyak-1 SE Alaska 60.56 145.67 35,700 0.50c 8.97 n/a Eyak-2 SE Alaska 60.56 145.67 224,000 1.3c 12.9 n/a Eyak-3 SE Alaska 60.56 145.67 137,500 0.51c 10.39 n/a Prince William Sound SE Alaska 60.59 145.70 na nd n/a n/a Katalla SE Alaska 60.18 144.44 nd 66.2c 37.86 n/a ROV 38 m Beaufort 70.48 136.48 11,800 nd n/a 15l 14 Core 400 m Beaufort 70.48 136.48 2310 nd n/a 40m 4 ROV 420 m Beaufort 70.79 135.57 5930 nd n/a 40m 4 Inre Harrsjo¨n Trap 10 Stordalen 68.36 19.05 na 5.14c n/a 94n 2 Inre Harrsjo¨n Trap 4 Stordalen 68.36 19.05 na 4.46c n/a 94n 2 Inre Harrsjo¨n Trap 6 Stordalen 68.36 19.05 na 9.16c n/a 94n 2 Mellersta Harrsjo¨n Trap 21 Stordalen 68.36 19.04 na 1.54g n/a 94n 2 Mellersta Harrsjo¨n Trap 19 Stordalen 68.36 19.04 na 8.34c n/a 94n 2 Mellersta Harrsjo¨n Trap 24 Stordalen 68.36 19.04 na 183.54c n/a 94n 2 Villasjo¨n Trap 34 Stordalen 68.35 19.05 na 29.8c n/a 70o 1 Villasjo¨n Trap 31,34,35 Stordalen 68.35 19.05 na 3.77c n/a 70o 1 Villasjo¨n Trap 31 Stordalen 68.35 19.05 na 41.41c n/a 70o 1 a nd: ethane not detected; na: ethane concentration not analyzed. b Flux estimates for Alaskan samples are in units of L trap 1 day 1 ; for the Stordalen samples they are in units of L m 2 day 1 . c Flux estimate specific to gas analyzed. d Flux measured from the same seep on a different day than gas sampling. e Based on average gas flux for seep class (Hotspot, Tiny, and A-type; Walter Anthony and Anthony, 2013; Lindgren et al., 2016). f Average flux measured between August and October 2011. g Trap specific average flux over six years of measurements. h Estimate based on texture ice dD value in the vicinity of the lake (Meyer et al., 2010). Texture ice is inferred as a likely source of methane formation water given Holocene 14C age of texture-ice organics and the methane sample (Table 2). i Estimate based on dD values (Brosius et al., 2012). Pleistocene ice wedges are inferred as a likely source of methane formation water given the Pleistocene age of this methane sample (Table 2). j Estimate is an average of Pleistocene ice wedge and Holocene ground ice dDvalues(Brosius et al., 2012). The location of these seeps suggests that pore waters include input of thawed ice from both sources. k Estimate based on Holocene ground ice dD values (Brosius et al., 2012). Holocene ice wedges are inferred as a likely source of methane formation water given the Holocene age of these methane samples (Table 2). l Estimate based on average dD of pore water samples in the vicinity of methane sampled from vents and sediments (Paull et al., 2011). m Estimate based on average dD of pore water samples in the vicinity of the sampled gas vent (Paull et al., 2015). n Estimate based on average dD of water samples from Mellersta Harrsjo¨n(n = 10). o Estimate based on average dD of water samples from Villasjo¨n(n = 15). P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 167

Fig. 2. Map of the Arctic showing the location of the studied methane samples (the base map is an open access file from Wikimedia). were likely to contain thermogenic methane, as indicated by Finally, we analyzed three samples from the continental conventional stable isotope, radiocarbon, and gas composi- shelf and slope of the Beaufort Sea in the Arctic Ocean tion measurements (Walter Anthony et al., 2012). (Table 1, Fig. 2). Two samples were collected from an ele- We analyzed ebullitive gas samples from three lakes on vated topographic feature at a water depth of 420 m (Paull the North Slope of Alaska (Lake Sukok, Lake Q, and Cake et al., 2015). One of these samples was collected from gas Eater Lake; Table 1, Fig. 2), a region with a large number bubbles emitted from an active gas vent, and the other of shallow lakes (lakes formed by the thaw of from a gas expansion void in a sediment core collected ice-rich permafrost). This region contains active oil and gas adjacent to the vent. One sample was collected from gas production, and is also underlain by shallow coal seams bubbles emitted from an elevated topographic feature at (Walter Anthony et al., 2012). a water depth of 38 m on the continental shelf (Paull We analyzed a total of six ebullitive gas samples from et al., 2011). four lakes in the vicinity of Fairbanks, AK (Goldstream Lake, Killarney Lake, Smith Lake, and Doughnut Lake; 2.2. Sample collection Table 1, Fig. 2). All of these lakes were formed by thermo- karst erosion, and one of them (Goldstream Lake) is Ebullitive gas samples from Alaskan lakes were collected actively eroding -type permafrost, a variety of from submerged, umbrella-style gas bubble traps, following permafrost that is rich in organic carbon (Walter et al., methods described by Walter et al. (2008), between 2009 2006; Brosius et al., 2012). and 2013. As discussed in Appendix 1, repeat isotopic anal- We analyzed five ebullitive gas samples from southeast yses of these samples did not indicate analytical artifacts Alaska (Table 1, Fig. 2), including three samples from Eyak related to their storage. Bubble traps were fixed in place Lake, a shallow coastal lake next to Cordova, AK. One sam- over discrete points of concentrated gas bubbling. Gas bub- ple is from Prince William Sound (PWS), in close vicinity to ble samples from the Stordalen lakes were collected using Eyak Lake, and one sample is from a stream in the vicinity submerged inverted funnels, as described by Wik et al. of Katalla, AK, about 80 km to the east of Eyak Lake. (2013), in June and July of 2014. These traps were part of We analyzed nine ebullitive gas samples from three inten- a stratified sampling scheme but were not fixed over previ- sively studied, post-glacial lakes (Inre Harrsjo¨n, Mellersta ously identified points of gas, as no sites of continuous, Harrsjo¨n, and Villasjo¨n), within the Stordalen Mire com- coherent bubbling were identified in the Stordalen lakes. plex, a Subarctic peatland underlain by sporadic permafrost All lake ebullitive gas samples were transferred to glass in northern Sweden (Table 1, Fig. 2)(Wik et al., 2013). serum vials and sealed with crimped butyl rubber stoppers. 168 P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188

The ebullitive gas sample from the Beaufort shelf vent obtain approximately 50 lmol of CH4. Gases were sampled (38 m water depth) was collected by a Phantom S2 remotely from sealed glass vials and the culture serum bottle using a operated vehicle (ROV) using a gas collection funnel and 5 ml gas tight syringe (Hamilton). The gas from the steel sampling system in 2010, as described in Paull et al. cylinder was sampled by connecting the cylinder to the vac- (2011). This gas sample was transferred underwater to a uum line as described in Stolper et al. (2014a) with a Swa- glass serum vial sealed with a butyl stopper. The gas bubble gelokTM fitting. Gas samples were first exposed to liquid sample from the Beaufort slope vent (420 m water depth) nitrogen to trap H2O, CO2, and H2S. The gases in the head- was collected by the Monterey Bay Aquarium Research space (including CH4,O2, and N2) were then exposed and Institute (MBARI) miniROV using a gas collection funnel transferred to a 20 K cold trap, cooled using a helium cryo- and sampling system in 2012, as described in Paull et al. stat (Janis Research). At this point residual gases, including (2015). This gas sample was transferred underwater to a He and H2, were pumped away. The cold trap was then stainless steel cylinder. The Beaufort slope sediment gas sealed, heated to 80 K, cooled to 45 K, and opened to vac- sample was collected by sampling a gas expansion void uum to remove N2 and O2. This step was repeated until within a gravity core collected at 400 m water depth in <2.67 Pa of gas remained in the cold trap at 45 K, corre- 2012 (Paull et al., 2015). Gas was sampled through the core sponding to a purity of CH4 of 99.8% (Stolper et al., lining using a gas-tight syringe, and was stored in a glass 2014b). The cryostat was then heated to 70 K, and CH4 serum bottle sealed with a butyl stopper. was transferred to a PyrexTM breakseal containing molecular sieve (EM Science; type 5A) immersed in liquid N2. Prior to 2.3. Culture preparation introduction to the mass spectrometer dual inlet, samples were heated with either a heat gun or a heated copper block A pure culture of Methanosarcina acetivorans (Sowers set to 150 °C for 2–3 h to ensure minimal isotopic frac- et al., 1984; Strain DSM 2834; DSMZ GmbH) was grown tionation when transferring CH4 from the molecular sieves on a carbon substrate of methanol in a 1 L glass serum bot- (Stolper et al., 2014a). tle. It was grown under a headspace of N2 gas, at a pressure of 150 kPa, in sterile media (350 mL) containing (g/L): 2.5. Methane stable isotope measurements NaCl (23.4), MgSO47H2O (9.44), NaHCO3 (5.0), KCl 13 (0.8), NH4Cl (1.0), Na2HPO4 (0.6), CaCl22H2O (0.14), Methane dD, d C, and D18 were measured using the cysteine-HCl (0.25), with the addition of 10 mL DSM 141 Ultra, as described in detail by Stolper et al. (2014a). dD Trace Element solution and 10 mL of DSM 141 Vitamin and d13C values are expressed using delta notation relative solution, 5 mL 99.9% MeOH, and 2.5 mL of a 50 mM to Vienna Standard Mean Ocean Water (VSMOW) and H2S solution. The culture bottle was kept in an incubator Vienna Pee Dee Belemnite (VPDB), respectively: at 28 °C and shaken at 35 revolutions per min. Two ali- 2R 2R quots of the headspace gas were sampled after 20 days of d ¼ sample VSMOW ð Þ D 2 1 RVSMOW growth for methane purification and analysis. Filter-sterilized media water was sampled at the same 13R 13R d13C ¼ sample VPDB ð2Þ d 13 time as methane, and the D value was measured using a RVPDB spectroscopic DLT-100 Liquid-Water Isotope Analyzer 2 13 13 12 (Los Gatos Research Inc.), with a precision of <1‰ where R and R are the ratios D/H and C/ C respec- d d13 ‰ (Feakins and Sessions, 2010). The d13C of methanol from tively. D and C data are expressed as per mil ( ) values the same supply as the culture media was measured by com- (Coplen, 2011). D busting an aliquot in a sealed tubed with cupric oxide at Clumped isotope compositions are expressed using 18 800 °C, and then measuring the d13C value of the resulting notation (Stolper et al., 2014a): 18 18 CO2 using Finnigan 252 isotope ratio mass spectrometer. D18 ¼ð R= R 1Þð3Þ We also derivatized a disodium phthalate standard with a known dD value (95.3 ± 1.2‰; from A. Schimmelmann, where 18 13 12 12 University of Indiana) using methanol from the same sup- R ¼ð½ CH3Dþ½ CH2D2Þ=½ CH4ð4Þ ply as the culture media, and using acetyl chloride as the derivatizing agent. We then analyzed the dD value of the The specified isotope ratios are measured from the cor- resulting phthalic acid methyl ester using a ThermoFinni- responding ion beam current ratios, standardized by com- 18 * plus parison with a standard of known composition. R is gan Trace gas chromatograph coupled to a Delta XP iso- 18 tope ratio mass spectrometer via a pyrolysis interface (Jones the R value expected for a random internal distribution d13 d et al., 2008), with a typical precision of <5‰. We calcu- of isotopologues, given the C and D values of the sam- lated the dD value of the methanol methyl-group hydrogen ple (Stolper et al., 2014a), and is expressed as: by mass balance. 18R ¼ 6 ½2R2 þ 4 2R 13R ð5Þ

2.4. Methane purification The factors (‘6’ and ‘4’) in Eq. (5) derive from the sym- metry numbers of the mass 18 methane isotopologues Methane (CH4) was purified from mixed gas samples (Stolper et al., 2014a). D18 data are reported as per mil using the methods described previously by Stolper et al. (‰), where 0‰ refers to a random distribution of methane (2014a,b). For all analyses we sampled enough gas to isotopologues (i.e., 18R=18R*). All samples are referenced P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 169 against a laboratory standard with a D18 value of 2.981 or same region of Alaska (Table 1)(Meyer et al., 2010; ± 0.015‰, as described by Stolper et al. (2014a). D18 values Paull et al., 2011, 2015; Brosius et al., 2012). For the Stor- can be related to equivalent formation temperature (K), dalen Mire samples we applied dD values measured in lake assuming formation in internal isotopic equilibrium, via water samples. Grab samples for water isotope analyses the equation (Stolper et al., 2014a): were collected from Mellersta Harrsjo¨n (10 samples) and Villasjo¨n (15 samples) in acid washed 50 ml polyethylene 106 106 D ¼0:0117 þ 0:708 0:337 ð6Þ bottles in August 2005 and samples were stored cool to 18 T 2 T 2 avoid evaporation before analysis. Water samples were

Because the D18–T relationship is not linear, the error reduced to H2 using chromium oxidation using a Finnigan for inferred temperatures are not symmetric. 2r errors for H-device, and dD values were measured with a Finnigan inferred temperatures reported in Table 2 are the average Delta V isotope-ratio mass spectrometer at the Stable Iso- of the upper and lower errors. For the samples for which tope Laboratory at the Department of Geological Sciences, the inferred temperatures are relevant in this study (i.e. Stockholm University, with a typical precision of ±2‰. samples inferred to have formed in internal isotopic equilib- Average dD values and standard deviations for each lake rium), the difference between upper and lower errors are at are reported in Table 1. We applied water dD measure- most 4 °C, and this asymmetry does not affect our ments from Mellersta Harrsjo¨n to samples from Inre Harrs- interpretations. jo¨n since these two lakes have similar physiographic The samples were analyzed over the course of 5 separate characteristics (Wik et al., 2013). As there are differences measurement periods of 2–15 weeks in duration, spanning in the source of water isotope data between study sites, 14 months in total. These measurement periods were sepa- we apply the largest standard deviation associated with rated by intervals of time when the Ultra was used for other water dD measurements (±30‰ for measurements of Fair- measurements. Ten of the samples analyzed for this study banks area ice wedges; Brosius et al., 2012) as a conserva- were analyzed as replicates, in some cases in multiple mea- tive estimate of uncertainty for methane formation water surement periods. We present measurement uncertainties dD. for individual samples as either two standard errors of the We calculated apparent –methane 13a 2a internal measurement variability for a single measurement ( CO2-CH4 ) and water-methane ( H2O-CH4 ) isotopic frac- (2 SE), or 2 SE of replicate measurements. Reported uncer- tionation factors using the equations: tainties for inferred temperatures are propagated from the 2 13a ¼ 13 =13 ð Þ CO2-CH4 RCO2 RCH4 8 SE errors for D18 values using Eq. (6). External repro- D d d13 r ‰ 2a ¼ 2 =2 ð Þ ducibility for 18, D, and C values (1 ) was 0.38 , H2O-CH4 RH2O RCH4 9 0.22‰ and 0.06‰ respectively. A more detailed description Propagated errors for a values were calculated using the of standardization and external reproducibility is provided individual errors for isotope measurements of CH ,CO, in Appendix 2. 4 2 and H2O. 2.6. Other isotope measurements 2.7. Gas concentration and flux measurements Carbon isotopes of CO contained in gas bubbles from 2 The concentrations of methane and other gases in the the Alaskan lakes were measured at Florida State Univer- Alaskan lake samples were measured at the University of sity, as described by Walter Anthony et al. (2012). Methane Alaska Fairbanks, as described in Walter Anthony et al. radiocarbon abundance for the Alaskan lake and Beaufort (2012). In some samples, ethane concentrations were ana- Sea samples was measured by accelerator mass spectrome- lyzed using the same methodology, and were used to calcu- try (AMS) at either the Woods Hole Oceanographic Insti- late [C1]/[C2] ratios (Table 1). Gas ebullition fluxes tution’s National Ocean Sciences AMS facility or the 1 1 (L gas day trap ; Table 1) were measured via gas vol- University of California at Irvine Keck ume accumulations in bubble traps either manually or using AMS facility (Paull et al., 2011, 2015; Brosius et al., 2012; data loggers over periods ranging from 20 min to 47 days Walter Anthony et al., 2012). Radiocarbon data are (Walter Anthony et al., 2012). In Alaska all samples were expressed as D14C in per mil notation (Stuiver and collected from identified gas seeps, and therefore flux esti- Polach, 1977): mates were not dependent on the area of the traps. For D14C ¼ Fm ekð1950YcÞ 1 ð7Þ some seeps reported gas fluxes are estimates based on mea- surements of seeps from the same region of Alaska with where Fm is the deviation of the sample 14C/12C ratio rela- similar characteristics (Table 1). Gas composition analyses tive to 95% of the 14C/12C ratio of the NBS Oxalic Acid for the Beaufort Sea samples were performed by Isotech standard in the year 1950, k is 1/8267 (the reciprocal of Laboratories (Paull et al., 2011, 2015). the mean-life of 14C), and Yc is the year the sample was Methane concentrations in the Stordalen lake samples collected. were measured at the Scientific Research Station To estimate the dD value of methane formation water (Wik et al., 2013). Gas fluxes were estimated by measuring for the Alaskan and Beaufort Sea samples we relied on pub- gas volume accumulations in bubble traps manually over lished data for the isotopic composition of pore water or periods of 24–72 h. At Stordalen, traps were not placed permafrost ice from either the studied sites (when possible), over identified points of gas bubbling, but instead sampled 7 ...Dulse l eciiae omciiaAt 8 21)163–188 (2016) 188 Acta Cosmochimica et Geochimica / al. et Douglas P.M.J. 170

Table 2 Methane isotope data. 13 a b c 14 Sample n dD(‰, VSMOW) 2 SE d C(‰, VPDB) 2 SE D18 (‰) 2 SE Inferred temperature (°C) 2SE D C(‰) Cake Eater 2 371.4 0.22 64.00 0.01 0.4 0.45 n/a 394.3 Sukok 1 193.1 0.20 46.31 0.01 4.1 0.46 102 23 997.6 Lake Q 1 238.3 0.24 59.31 0.01 6.8 0.50 9 14 1000 Killarney 2 312.5 0.66 88.76 0.01 9.6 0.66 61 15 907.7 Goldstream-Hotspot 2 383.1 0.26 77.59 0.26 2.0 0.70 268 91 971.2 Goldstream-Tiny 1 369.3 0.24 64.34 0.01 1.1 0.44 412 130 nd Goldstream-A 1 332.8 0.24 61.89 0.01 0.2 0.46 905 n/a 314.9 Doughnut 1 302.4 0.24 55.50 0.01 6.0 0.48 29 16 984.1 Smith-Hotspot 1 362.2 0.24 62.73 0.01 0.7 0.50 549 246 265.3 Eyak-1 2 172.4 0.34 46.81 0.08 6.2 0.48 24 14 851.0 Eyak-2 2 203.5 0.26 60.74 0.02 9.1 0.80 47 19 nd Eyak-3 2 242.6 0.24 73.83 0.01 8.4 0.50 31 12 384.4 Prince William Sound 2 151.0 0.24 34.34 0.08 4.8 0.50 73 20 nd Katalla 1 171.0 0.22 40.80 0.01 6.1 0.48 27 15 987.1 ROV 38 m 2 228.6 1.30 83.02 0.04 6.9 0.43 5 11 997.0 Core 400 m 1 212.1 0.24 65.32 0.01 7.1 0.44 0 11 nd ROV 420 m 2 210.3 0.24 65.21 0.12 6.9 0.46 5 12 995.0 Inre Harrsjo¨n Trap 10 1 310.3 0.22 68.04 0.01 2.8 0.43 187 35 nd Inre Harrsjo¨n Trap 4 1 285.9 0.23 77.61 0.01 5.4 0.49 50 17 nd Inre Harrsjo¨n Trap 6 1 311.6 0.25 68.28 0.01 1.9 0.49 271 65 nd Mellersta Harrsjo¨n Trap 21 1 288.1 0.21 71.03 0.01 4.4 0.44 90 20 nd Mellersta Harrsjo¨n Trap 19 1 282.2 0.23 68.01 0.01 4.6 0.45 79 19 nd Mellersta Harrsjo¨n Trap 24 1 293.1 0.25 68.01 0.01 5.0 0.48 64 18 nd Villasjo¨n Trap 34 1 300.7 0.21 65.49 0.01 3.7 0.50 126 28 nd Villasjo¨n Trap 31,34,35 1 314.9 0.23 66.60 0.01 2.5 0.45 215 44 nd Villasjo¨n Trap 31 1 312.7 0.25 62.32 0.01 1.8 0.47 291 69 nd Methanosarcina acetivoransd 2 346.7 0.28 30.23 0.16 5.4 0.46 n/a nd a Values relative to stochastic distribution of isotopologues. b Italics denote temperatures inferred to be implausible for methane formation for a given sample, which reflect mixing or non-equilibrium isotope effects. c Errors for inferred temperatures are average of upper and lower temperature estimates since D18 –T relationship is not linear. d Grown at 28 °C. P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 171 overall ebullition within the area of the trap. To account for dD–d13C range of fermentative microbial methane (Fig. 3). scaling effects related to the area of the traps, for these sam- The Stordalen Mire samples display a negative trend in dD– ples we report flux in terms of L gas day1 m2 (Table 1). d13C space, while most of the Fairbanks area samples dis- In most cases we used the flux estimate for the actual sam- play a positive trend. The low d13C(88.8‰) and dD ple analyzed, but in one case where a sample-specific flux (313‰) value of the sample from Killarney Lake are estimate is not available we adopted the six-year average anomalous relative to typical values of microbial methane flux for that trap (Table 1). In all samples methane flux (Whiticar et al., 1986). was calculated by multiplying the total gas flux by the mea- sured methane concentration. 3.2. Methane clumped isotope data

3. RESULTS The D18 values of the studied samples varied widely from 0.4‰ to +9.6‰ (Table 2, Fig. 4). For comparison, forma- 3.1. Methane dD and d13C data tion of methane from 0 to 100 °C in internal isotopic equi- librium would correspond to a D18 range of 7.1–4.2‰ 13 Methane dD and d C values (Table 2) measured on the respectively. The observed range of D18 is much wider than Ultra differed by variable amounts from previous measure- this, and corresponds to apparent equilibrium temperatures ments of the samples from Alaska and the Beaufort Sea, ranging from 61 °C to non-real temperatures (i.e., nega- with an average deviation of 2±9‰ for dD and 1.1 tive values of D18 do not have equivalent equilibrium tem- ± 0.5‰ for d13C. As discussed in Appendix 1, these differ- peratures). Thus both the high and low ends of the range ences are likely caused by interlaboratory measurement of D18 values cannot be interpreted in the context of appar- artifacts, and do not reflect changes in samples due to stor- ent equilibrium formation temperatures, as discussed below age. The interlaboratory differences are minor relative to (Sections 4.3–4.5). the range of variability in the samples, and do not influence In specific geographic regions in Alaska we found a sim- the interpretations presented here. The dD values of these ilarly wide range of D18 values: D18 ranged from 4.8‰ to samples ranged from 151‰ to 383‰, and d13C values 8.4‰ in Southeast Alaska, from 0.2‰ to 9.6‰ in the Fair- ranged from 34.3‰ to 88.8‰ (Table 2; Fig. 3). The banks region, and from 0.4‰ to 6.8‰ on the North samples from southeast Alaska, the Beaufort Sea, and Slope. These data indicate significant differences in the ori- two of the samples from the Alaskan North Slope (Lake gin of regional ebullitive methane emissions. The Stordalen Sukok, Lake Q) display relatively high dD values lake samples also displayed a wide range of D18 values, (>250‰), and conform to a broad positive relationship from 1.8‰ to 5.4‰. In contrast, the three samples from 13 in dD–d C space spanning the typical ranges of thermo- the Beaufort Sea displayed a small range of D18 values, genic and hydrogenotrophic microbial methane (Fig. 3; 6.9–7.1‰. These values correspond to a temperatures of note reversed y-axis) (Whiticar et al., 1986). In contrast, 0–5 (±13) °C, consistent with equilibrium formation at sea- the samples from the Fairbanks area and the Stordalen floor temperatures of 1.5–1 °C(Fig. 5). Mire, as well as from Cake Eater Lake on the North Slope, The studied samples define two groups in a plot of D18 display low dD values (<250‰) and cluster in the typical vs. dD(Fig. 4). One subset, comprising samples from south- east Alaska, the Beaufort Sea, and two of the samples from the Alaskan North Slope (Lake Sukok, Lake Q), is defined by both elevated dD values (>250‰) and D18 values (>4‰). We interpret these samples to have either formed in isotopic equilibrium, or through mixing of isotopically distinct end-members that each formed in isotopic equilib- rium (Fig. 5). The other subset, comprising the samples from the Fairbanks area and the Stordalen Mire, as well as from Cake Eater Lake on the North Slope, is defined by lower dD(<250‰) and D18 values (<6‰)(Fig. 4). We interpret these samples to represent microbial methane that did not form in isotopic equilibrium. These D18 values, if interpreted as formation temperatures, would indicate temperatures >29 °C that are not plausible for microbial methane in Arctic lake sediments. The two groups of sam- 13 ples are less clearly distinguished in D18-d C composition space (Fig. 4), but samples inferred to form in isotopic equi- librium or through mixing generally have higher d13C val- ues, whereas samples with non-equilibrium D18 values generally have lower d13C values (Fig. 4). The Doughnut Lake sample from the Fairbanks region is ambiguous in 13 that it plots with the equilibrium samples in d C–D18 space, but with the non-equilibrium samples in dD–D space. In Fig. 3. Methane dD and d13C values overlaid on empirical 18 addition, the sample from Killarney Lake (Fairbanks) is methane. Source fields derived from Whiticar et al. (1986). 172 P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188

AB

13 Fig. 4. Scatter plots of methane D18 versus dD (A) and d C (B). All error bars are 2 SE as described in Section 2.5. Error bars for dD and d13C are smaller than the symbols. Two groups of data described in Section 3.2 are circled.

AB

13 Fig. 5. Scatter plots of D18-derived temperature versus (A) d C and (B) dD for methane samples with inferred equilibrium or mixing- influenced D18 values. Specific samples referred to in the text are indicated. The solid gray line indicates the modeled non-linear mixing line (see Section 4.4) for samples from the Eyak Lake (‘‘e”). The dashed line indicates a temperature of 5 °C, an assumed lower limit to methanogenesis in Arctic environments. anomalous given its low dD(312‰) and d13C(88.8‰) ized ebullitive methane flux from the Swedish lakes spanned 1 2 values, but high D18 value (9.6‰) (see Section 4.3.1). two orders of magnitude, from 1.5 to 183 L CH4 day m (Table 1). 3.3. Methane flux and radiocarbon data Methane D14C values also spanned a substantial range (Table 2; Figs. 6 and 7) from 265‰ (equivalent to 2420 Methane ebullitive flux measurements from lacustrine 14C years before present) to 1000‰ (no detectable radio- seeps in Alaska spanned eight orders of magnitude, from carbon; >50,000 14C years before present). It is important 1 1 14 .005 to 93,456 L CH4 day trap (Table 1). Area normal- to note that methane C ages do not necessarily indicate P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 173

A B

CD

E F

d d13 d D d13 D 2a D 13a D D14 D Fig. 6. Scatter plots of (A) D vs. C; (B) D vs. 18; (C) C vs. 18; (D) H2O-CH4 vs. 18 (E) CO2-CH4 vs. 18; and (F) C vs. 18 for lacustrine microbial methane samples displaying non-equilibrium D18 values. Linear regression statistics for significant correlations for subsets of data either from Alaska or from the Stordalen Mire are shown; in (E) the sample from Doughnut Lake (upper right side of the plot) is an outlier and is not included in the regression model. 174 P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188

A B

C D

13 13 Fig. 7. Isotope and gas composition mixing models for methane from Eyak Lake and Prince William Sound. (A) d C vs. dD; (B) d C vs. D18; 13 14 13 (C) d C vs. D C; (D) d C vs. [C1]/[C2]. The circle in (A) and (C) indicates the inferred composition of the high-temperature Eyak Lake end- 13 14 14 member based on d C–D C and dD–D C mixing lines. The gray area in (B) indicates the high-temperature end-member D18 values implied 13 13 14 13 by the d C value (38.1‰) inferred from the d C–D C mixing line (C). The dashed line in (B) indicates the D18 and d C value implied by the model if the low-temperature end-member formed in equilibrium at 5 °C. Equilibrium formation at higher temperatures or non- equilibrium kinetic isotope effects would imply lower d13C values. The dashed line in (C) indicates a D14C composition of 1000‰ (i.e. no radiocarbon). D14C data is not available for the PWS sample and its d13C value is plotted on the y-axis in (C). The mixing curve in (D) is one of many possible curves that fits the data from samples Eyak-1 and Eyak-3, but is representative of the general shape of these curves. d13C and 12 [C1]/[C2] end-members for this curve are 90‰ and 1 10 for the low-temperature end-member, and 20‰ and 25,000 for the high- temperature end-member. The Katalla sample data are plotted for reference only and are not included in the models. the age of methane formation, since in many cases recently the dD value of the methyl group of methanol was 156 formed methane can be produced from aged carbon that is ±8‰. The high d13C of the methane is likely the result of depleted in 14C (e.g. Walter et al., 2006, 2008; Brosius et al., Rayleigh fractionation of the culture media methanol, 2012). and suggests that the methanogens consumed most of this carbon substrate. The D18 value for this sample, 5.4 3.4. Methylotrophic methanogen culture ± 0.5‰, is the lowest yet observed. This observation sug- gests that cultures of fermentative methanogens produce Methane sampled from the M. acetivorans culture had a substantial non-equilibrium effects in D18, similar to or low dD value (347‰), but a high d13C value (30.2‰). greater (i.e., further from equilibrium) than those observed The dD value of water in the culture media was 82 in cultures of hydrogenotrophic methanogens (Stolper ±1‰, the d13C value of the methanol was 25.69‰, and et al., 2015; Wang et al., 2015). P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 175

Interpretation of this low D18 value is complicated. The ±24°C. This inferred temperature is within the range at D18 value of the methane is controlled by both the isotope which thermogenic methane typically forms (60 to effects associated with the hydrogenation of the methanol- 300 °C), and would imply generation of gas during initial derived methyl group to methane, as well as the initial iso- catagenic breakdown of organic macromolecules to oil and topic order of the methyl group (Stolper et al., 2015; Wang gas (Hunt, 1979; Quigley and Mackenzie, 1988; Clayton, et al., 2015). We do not know the clumped isotope composi- 1991; Seewald, 2003). We note that D18 data for other ther- tion of the methanol consumed in this experiment, which mogenic methane samples have yielded temperatures could have influenced the D18 value of the methane. Further- >140 °C(Stolper et al., 2014b; Wang et al., 2015), except more, the results of this experiment, while informative for dominantly thermogenic gases from the Antrim Shale regarding D18 values in fermentative methane at a first- (95–115 °C) (Stolper et al., 2015). The elevated dD order, may not be particularly representative of fermentative (193‰) and d13C values (46.3‰), low D14C value methanogenesis in freshwater environments, for three rea- (998‰) of the Lake Sukok sample are also consistent with sons. First the cultured taxon was isolated from a marine a thermogenic origin. Furthermore, Walter Anthony et al. ecosystem (Sowers et al., 1984), and was grown in a salt (2012) showed that the hydrocarbon geochemistry and iso- water medium. We used this taxon as an initial test of fer- topes of the Sukok Lake ebullition seep closely matched mentative methanogenesis because it was readily available. data from an adjacent petroleum production well. A recent Second, the carbon substrate for the culture was methanol, study of pore water geochemistry and geobiology from whereas acetate is the dominant carbon substrate for fer- Lake Sukok also concluded that most or all of the methane mentative methanogenesis in most freshwater ecosystems found in its sediments is thermogenic in origin, and that (Whiticar et al., 1986), and differences in 13C isotopic frac- there is very little methanogen activity in Lake Sukok sed- tionation between methanogens grown with acetate and iments based on the abundance of both genetic markers and methanol on the order of 50‰ have been documented in pre- lipid biomarkers (Matheus Carnevali et al., 2015). vious studies (Krzycki et al., 1987). Third, the genera Metha- nosarcina has differences in its methanogenic pathway as 4.2. Equilibrium microbial methane compared to the genera Methanosaeta (Smith and Ingram- Smith, 2007), which is the dominant aceticlastic methanogen We interpret the clumped isotope data from the three in most freshwater environments (Borrel et al., 2011). Previ- Beaufort Sea samples, as well as the sample from Lake Q ous studies of hydrogenotrophic methane produced by in Alaska, to be indicative of microbial methane generated Methanosarcina barkeri produced lower D18 values than in internal isotopic equilibrium. There are three lines of evi- other hydrogenotrophic methanogens (Stolper et al., 2015; dence for this conclusion. First, the D18 values for these Wang et al., 2015). Therefore the metabolic pathway of samples (6.8–7.1‰) imply formation temperatures between Methanosarcina could produce more pronounced non- 0–9 ± 13 °C(Fig. 5), which is within error of ambient envi- equilibrium effects in D18 than that of other methanogens. ronmental temperatures, and well below the lower limit of thermogenic methane formation (60 °C; Hunt, 1979; 4. DISCUSSION Seewald, 2003). Second, the dD(210‰ to 238‰) and d13C(59.3‰ to 83‰) values of all four gases are within 13 Based on the D18, dD, and d C values summarized the typical range of microbial methane (Table 2; Fig. 3; above, supplemented in some cases with D14C values and (Whiticar et al., 1986). Third, research to date indicates that ratios of methane to ethane concentrations ([C1]/[C2]), we microbial methane formed in marine and deep subsurface divided the studied samples into four categories of methane settings, produces equilibrium clumped isotope signatures sources: thermogenic methane, equilibrium microbial that reflect their formation environment (Stolper et al., methane, non-equilibrium microbial methane, and mixtures 2014b, 2015; Inagaki et al., 2015; Wang et al., 2015). of methane from deep and shallow sources. The basis for this categorization is discussed below. We primarily inter- 4.2.1. Microbial methane from the Beaufort shelf and slope pret D18 values as an indicator of equilibrium or non- The three methane samples from the Beaufort Sea slope equilibrium isotope fractionation at the time of methane and shelf vents and sediment core indicate consistently low formation, although we do discuss post-formation isotope formation temperatures, from 0 to 5 (±13) °C. These tem- effects related to mixing and gas-phase diffusion in Sections peratures are within error of bottom water temperatures 4.3.1 and 4.4. A key limitation of our interpretation is that at these sites (1.5–1 °C; Paull et al., 2011, 2015). The we do not have constraints on how methane oxidation D18 data are consistent with methane formation in sedi- influences D18 values. Previous research has suggested, how- ments or sub-permafrost environments, and do not support ever, that methane oxidation does not strongly influence the a dominant contribution from thermogenic methane or isotopic composition of methane bubbles emitted from deep microbial methane formed in warm environments lakes (Walter et al., 2008). (>18 °C). Overall, our results from the Beaufort shelf are consistent with previous clumped-isotope analyses of mar- 4.1. Thermogenic methane ine methane seeps from the Santa Barbara Basin and the Santa Monica Basin, which indicated formation tempera- The methane sampled from Lake Sukok on the North tures (6–16 °C), within error of bottom water temperatures Slope of Alaska displayed a D18 value of 4.1 ± 0.5‰, corre- (Stolper et al., 2015). Similarly, analyses of gas hydrate and sponding to an apparent equilibrium temperature of 102 sediment core void gas from the North Cascadia Margin 176 P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 indicated relatively low formation temperatures between 12 bial methane produced in freshwater sediments analyzed to and 42 °C(Wang et al., 2015). date have displayed low, non-equilibrium D18 values The Beaufort Sea samples exhibit similar D18 values in (Stolper et al., 2015; Wang et al., 2015). We infer that the spite of large differences in water depth and vent type. low temperatures of methane generation, combined with The 38 m water depth methane vent is inferred to be a the lack of radiocarbon, are consistent with methane emit- -like formation associated with melting permafrost ted from Lake Q being produced by methanogens consum- (Paull et al., 2007, 2011). This sample contains negligible ing fossil carbon in coal seams known to underlie the lake radiocarbon (997‰ D14C; Table 2), in contrast to nearby (Walter Anthony et al., 2012). Microbial coal-bed methane sedimentary organic matter that contains more radiocarbon has been documented in other regions of Alaska (Dawson (960 to 831‰ D14C; Paull et al., 2011). This difference in et al., 2012), and is an important category of coal-bed D14C between methane and sedimentary organic matter is methane globally (Strazpoc´ et al., 2011). Furthermore, a probably caused by the migration of methane from deeper recent study found evidence for methane formed in subsurface horizons that contain ancient carbon, possibly clumped-isotope equilibrium at 70 °C in a coal deposit as a result of dissociating gas-hydrates or permafrost in deep marine sediments (Inagaki et al., 2015). D (Paull et al., 2007, 2011). The 18 data are consistent with Methane from Doughnut Lake has a D18 value of 6.0‰, this interpretation, but argue against a high-temperature indicating an apparent temperature of 29 ± 15 °C(Fig. 5). origin for methane from gas hydrates. Permafrost extends This result is ambiguous, as it could reflect either equilibrium up to 700 m below the seafloor in this area (Paull et al., methane formation by deep subsurface methanogens, or 2011), and it is possible that methane could be forming in methane formation in lake sediments with a relatively small relatively deep sub-permafrost environments that maintain non-equilibrium isotope effect (Fig. 6; Section 4.3). Given temperatures near 0 °C. this ambiguity we include the Doughnut Lake sample in The 420 m vent on the Beaufort Shelf is classified as a our discussion of non-equilibrium microbial methane below. mud volcano, and is not associated with permafrost (Paull et al., 2015). The isotopic and ionic chemistry of 4.3. Non-equilibrium microbial methane water venting from the volcano suggest a contribution of fluid derived from smectite to illite dehydration Six of the methane samples from lakes in Alaska (Paull et al., 2015), which is thought to occur at tempera- (Goldstream-Hotspot, Goldstream-Tinies, Goldstream- tures of 60 °C or greater (Jennings and Thompson, 40A, Smith, Cake Eater, and Doughnut), and all of the 1986), although the water chemistry also implies a contribu- Stordalen samples, have dD(285‰ to 383‰) and tion from seawater and groundwater of meteoric origin to d13C(55.5‰ to 77.6‰) values (Fig. 6A) typical of the fluid emanating from the mud volcano (Paull et al., microbial methane, but low D18 values (6‰ to 0.4‰) 2015). Our clumped isotope data rule out a high formation (Table 2, Fig. 6B and C). These D18 values would require temperature for the methane at this mud volcano, and implausible temperatures for methanogenesis in lake sedi- instead imply microbial methanogenesis in sediments or ments (29–905 °C; negative D18 values do not correspond the shallow subsurface. Methane sampled from a nearby to any temperature) if interpreted as equilibrium values D d13 d sediment core is similar in its 18, C, and D values (Table 2), and almost certainly do not reflect formation of (Table 2), further suggesting a shallow source for the mud methane in internal isotopic equilibrium. Instead, the low volcano methane. It is possible that the methane was orig- D18 values for these samples are consistent with previous inally formed in the shallow subsurface, was subsequently studies that showed microbial methane produced in fresh- buried to a greater depth where clay dehydration took water sediments, cow rumen, and in pure cultures of hydro- place, and then both the methane and clay-dehydration genotrophic methanogens have low D18 values that are not waters were exhumed to form the modern mud volcano. in equilibrium with their formation environment (Stolper Heating of buried methane to temperatures around 60 °C et al., 2014a, 2015; Wang et al., 2015). D would most likely have not reset its 18 value, as a previous Previous studies have proposed that non-equilibrium study implied that internal isotopic re-equilibration does D18 values in microbial methane primarily represent kinetic not occur at this temperature (Stolper et al., 2014b). isotope effects related to the differential reversibility of the enzymatic reactions involved in methanogenesis (Stolper 4.2.2. Deep subsurface microbial methane emitted from et al., 2015; Wang et al., 2015). In other words, this hypoth- Alaskan lakes esis proposes that kinetic isotope effects manifest in D18 val- We interpret the clumped-isotope measurement from ues, as well as in dD and d13C values, are determined by the one of the Alaskan lakes, Lake Q, to indicate emission of extent to which the reactions of methanogenesis operate subsurface microbial methane formed in internal isotopic near thermodynamic reversibility, which controls the estab- D equilibrium. Methane emitted at Lake Q has a 18 value lishment of isotopic equilibration between methane and its of 6.8 ± 0.5‰, equivalent to a formation temperature of metabolic precursors (Blair, 1998; Valentine et al., 2004; 9±13°C(Fig. 5). This inferred temperature is within error Penning et al., 2005). The ‘reversibility of methanogenesis’ (2 SE) of the estimated mean annual temperature at the lake is related to chemical potential gradients between methane (0 °C). The methane from this seep, however, contains no and its precursors. Faster rates of methanogenesis at high detectable radiocarbon (Table 2), arguing against microbial chemical potential gradients are interpreted to correlate methanogenesis in lake sediments. In addition, as discussed with less reversible reactions, larger kinetic isotope effects, in detail below (Sections 4.3 and 4.5), all samples of micro- and lower D18 values (Valentine et al., 2004; Penning P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 177 et al., 2005; Stolper et al., 2015; Wang et al., 2015). Other lakes (Fig. 6C; R2 = 0.77); the sample from Doughnut Lake factors in addition to the rate of methanogenesis, including does not conform and is not included in the regression differences in metabolic pathways between methanogen model. This relationship could also indicate kinetic isotope D 13a taxa, the relative abundance of methanogenesis reactants effects that influence both 18 and CO2-CH4 (Valentine and products in the environment, and the allocation of car- et al., 2004; Penning et al., 2005; Stolper et al., 2015), sim- bon for growth as opposed to methane generation, could D 2a ilar to the relationship between 18 and H2O-CH4 described also be influential in the reversibility of methanogenesis above. Indeed, such a relationship is predicted by a model and related isotope effects (Valentine et al., 2004; Stolper of kinetic isotope effects in methane, described in Stolper et al., 2015; Wang et al., 2015). et al. (2015). While we do not have CO2 isotope data for In the context of this hypothesis, we propose two expla- the Stordalen lake samples, these samples display a negative D 13 nations for the substantial variability of 18 values relationship between methane d C and D18 (Fig. 6C) that observed in the microbial methane from the Alaskan and would be consistent with the pattern observed in the Alas- 13 Swedish lakes. First, it could indicate differences in the kan lakes if CO2 d C values are relatively constant in these extent of kinetic fractionation exhibited by methanogenesis samples. D between samples. This would imply that the highest 18 Among the Alaskan lake methane samples, those with ‰ 14 value (Doughnut Lake; 6 ) corresponds to a high degree low D C(<970‰) display higher D18 values than samples D 14 of reversibility, and the lowest 18 value (Cake Eater Lake; with high D C(>400‰)(Fig. 6F; note that we do not 0.4‰) corresponds to low reversibility. Alternatively, the have D14C data for the Goldstream-Tinies sample). This D range in 18 values could represent variable mixtures of two pattern could indicate a greater degree of reversibility in distinct sources of microbial methane. For example, mixing methanogenesis sustained by older, more refractory carbon of microbial methane formed in isotopic equilibrium, possi- that is inherently more difficult to degrade, which would bly in deep subsurface environments, with non-equilibrium limit rates of methanogenesis. Alternatively, this pattern methane formed in lake sediments, would produce methane could be explained by variable mixtures of 14C-depleted D samples with intermediate non-equilibrium 18 values. In methane, formed in isotopic equilibrium in the deep subsur- this scenario, the non-linearity of mixing would be mini- face, with relatively 14C-enriched methane that is formed 13 mized if the dD and d C values of the end-members were out of isotopic equilibrium in lake sediments. d similar (Fig. 1). A strong positive correlation between D The wide range of D18 values in the microbial lacustrine D and 18 in the Stordalen Mire samples (Fig. 6B; methane samples indicates that kinetic isotope effects asso- 2 R = 0.86) is suggestive of a mixing relationship between ciated with methanogenesis vary substantially in the studied isotopically distinct methane reservoirs. However, correla- Arctic lakes. Invariably there is some degree of mixing of d13 D 2 tions between C and 18 (Fig. 6C; R = 0.46), and methane in lake sediments, but our results are not consis- 13 2 between dD and d C(Fig. 6A; R = 0.37), are weaker for tent with simple mixing between an equilibrium end- this group of samples, suggesting that if such mixing member and a non-equilibrium end-member with a con- occurred, it was modulated by other isotopic effects. We stant D18 value. Instead the observed trends, and in partic- also note that there are no currently known sources of deep D 2a 13a ular relationships between 18 and H2O-CH4 and CO2-CH4 subsurface microbial methane in the Fairbanks area or in values (Fig. 6D and E), are consistent with methane being the Stordalen Mire complex. produced in these lakes with a variety of non-equilibrium Previous studies (Stolper et al., 2015; Wang et al., 2015) D18 values, which would imply a spectrum of kinetic isotope have noted a negative correlation between non-equilibrium effects. D 2a 18 and H2O-CH4 values, an association that is consistent with the hypothesis that microbial methane isotope frac- 4.3.1. High D18 in microbial methane from Lake Killarney tionation is controlled by the reversibility of methanogene- The methane sampled from Lake Killarney has an unex- sis (Valentine et al., 2004). We also observe a negative pectedly high D18 value of 9.6 ± 0.7‰ (2 SE of two replicate D 2a correlation between 18 and H2O-CH4 in the non- measurements), which corresponds to an equilibrium for- equilibrium methane samples (R2 = 0.34), although there mation temperature of 61 ± 15 °C. This temperature is is substantial scatter in this relationship (Fig. 6D). If the clearly unrealistic for methanogenesis (Fig. 5), and the data are subdivided into the Alaskan and Stordalen sam- anomalously high D18 value is in the opposite direction of D 2a ples, however, the correlation between 18 and H2O-CH4 previously observed non-equilibrium effects (Stolper et al., 2 for each sample set is much stronger (Fig. 6D, R = 0.85 2014b, 2015; Wang et al., 2015), which produce lower D18 and 0.72, respectively). The different regression lines for values than expected for a given temperature. Currently, these two sample groups could be caused by differences in we cannot account for this result, but we suggest three pos- the source of water dD data. Namely, for the Alaskan sam- sible explanations. First, this high D18 value could reflect ples we applied dD measurements of permafrost ice, but for mixing of thermogenic and microbial methane (Fig. 1). the Stordalen samples we applied measurements of lake However, the highly depleted d13C value of this sample water. Overall, the negative correlations between D18 and (88.8‰) makes such mixing seem unlikely, as it would 2a H2O-CH4 values are consistent with the hypothesis that require that the microbial end-member have an even lower the degree of reversibility during methanogenesis at least d13C value, which would be anomalous for microbial partially controls D18 in the studied lakes. methane in freshwater environments (Fig. 3). D We also observe a positive correlation between D18 and Second, the high 18 value could be the result of 13a methane oxidation, whose effects on D values have not CO2-CH4 values (Fig. 7E) in five samples from Alaskan 18 178 P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 yet been directly observed. However, methane oxidation fore we calculated a second model that omits this sample tends to cause enrichment of residual methane in both dD (Fig. 7A and B). While the two models differ slightly, qual- and d13C(Whiticar, 1999), and – given the especially low itatively the results are similar. A key assumption of these d13C signature of this sample – it is unlikely that it has mixing models is that mixing is conservative and involves undergone significant oxidation. Third, the high D18 value only two-end members. The mixing models provide a good could be the result of diffusive isotopic fractionation. The fit (within 0.5‰ in D18) to samples Eyak-1, Eyak-3, and effects of gas-phase diffusion on clumped isotope composi- PWS, but a less good fit (within 0.8‰ in D18) to sample tions have been described in detail for mass-47 CO2 and Eyak-2 (Fig. 7B), although this difference is within the 2 mass-4 H2 by Eiler and Schauble (2004) and Eiler (2013), SE analytical error of this sample. The mixing models con- 13 respectively. In brief, diffusive isotopic fractionation of strain the possible combinations of D18, d C and dD values methane in air would be expected to lower both dD and for the mixing end-members, but not their specific values. d13C values in the diffused gas by approximately 14‰, Specifically, the models suggest that in order for the low- but increase D18 values by approximately 1.5‰. While this temperature end-member to have an equilibrium formation effect will require empirical validation, and does not take temperature above 5 °C, it would require that its d13C into account the likely importance of liquid-phase diffusion value be less than 90‰ (Fig. 7B), which is anomalously in this environment, to a first-order it is consistent with the low compared to other samples from freshwater ecosystems 13 high D18 and low dD and d C values observed at Killarney (Whiticar, 1999). As discussed above, microbial methane in Lake. It is currently unclear why diffusion would impart a most lakes expresses non-equilibrium D18 values lower than significant effect on methane emitted at Killarney Lake that equivalent to their formation temperature, but in this and not the other sites in this study, with the possible excep- case a low non-equilibrium D18 value would require a tion of Eyak Lake as discussed below. d13C value even lower than 90‰. Alternatively, the Lake Eyak low-temperature end-member may be characterized 4.4. Mixtures of thermogenic and microbial methane by a higher than equilibrium D18 value, as observed at Kil- larney Lake, which could be caused by diffusion or another The isotopic compositions of the five samples from undetermined post-formation process. Southeast Alaska (Eyak-1, -2, and -3; PWS; Katalla) sug- Additional measurements, including radiocarbon and gest that they contain variable mixtures of methane from gas composition data, provide further constraints on gas high- and low-temperature formation environments. Such mixing at Eyak Lake. If we assume that the D14C value mixing was previously identified for a larger set of methane of the high-temperature end-member is 1000‰ (i.e. it con- samples from Lake Eyak and Prince William Sound by tains no radiocarbon), the d13C of the high-temperature Walter Anthony et al. (2012) on the basis of evidence for end-member can be constrained by the intersection of a linear correlations between D14C, d13C and dD values. That D14C value of 1000‰ and the D14C–d13C mixing line for study suggested that the mixing end-member with high d13C samples Eyak-1 and Eyak-3 (Fig. 7C). This constraint and dD values, and a low D14C value, was thermogenic in implies a high-temperature end member d13C value of origin. 38.1 ± 1‰, although this estimate is based on only two The D18 values for the Lake Eyak and Prince William radiocarbon measurements, which limits its accuracy. This Sound (PWS) samples in this study are consistent with mix- inferred high-temperature end-member d13C value is lower ing between methane with distinct dD and d13C values. than the d13C value for sample PWS (34.3‰)(Fig. 7C). 13 These samples form a parabolic trajectory in d C–D18 This difference suggests that either (1) the high- 13 and dD–D18 space (Fig. 7B) that is characteristic of mix- temperature methane emitted at Eyak Lake differs in d C tures in which the end-member dD and d13C values differ from the high-temperature methane emitted in the PWS widely (Fig. 1). The D18 value for sample PWS indicates a sample, despite their close proximity (see Fig. 6 in Walter formation temperature of 73 ± 20 °C(Table 2; Fig. 5), Anthony et al., 2012); or (2) that the first assumption is which is a plausible, but low, temperature for thermogenic invalid and there are more than two low-temperature end- methane formation (Hunt, 1979; Seewald, 2003). In con- members with distinct D14C values; or (3) that sample trast, sample Eyak-1 indicates a temperature of 24 ± 15 ° PWS underwent post-formation isotopic fractionation, C, which is too low for a thermogenic source, and samples such as oxidation, that led to a higher d13C value. Eyak-2 and Eyak-3 indicate temperatures of 47 ± 19 and If the d13C(38.1‰) value for the high-temperature 31 ± 12 °C respectively (Table 2), which are implausible end-member inferred from the D14C mixing-line discussed for methane formation by any mechanism in these environ- above is correct, this in turn implies that the D18 of the ther- ments (Fig. 5). The high D18 values and low corresponding mogenic end-member is approximately 5.2 ± 0.5‰ apparent temperatures for the Lake Eyak samples can be (Fig. 7B), indicating a temperature of 57 ± 19 °C. This is understood, however, as a consequence of mixing between an anomalously low temperature for thermogenic methane thermogenic and microbial methane that differ in their generation, suggesting an extremely low maturity source 13 13 D18, d C and dD values. (Seewald, 2003), despite the relatively high d C value. We calculated a best-fit mixing model (described in One possible explanation is that the high-temperature 13 detail in Appendix 3) to the D18, d C and dD values from end-member is not thermogenic in origin, and instead is the Lake Eyak and PWS samples. As discussed below, there deep surface microbial methane. is some evidence that the PWS sample does not conform to Comparing our results with [C1]/[C2] data for the Lake the same mixing trend as the Lake Eyak samples, and there- Eyak samples indicates further complexity in the gas mixing P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 179 relationships in this region. While sample Eyak-2 is inter- 13 mediate in dD and d C values, it has the highest [C1]/ [C2] value (Fig. 7D). This implies that the assumption of conservative, two end-member mixing is incorrect, and sug- gests that either (1) there are more than two mixing end- members or (2) that ethane oxidation is occurring and dis- proportionately affected sample Eyak-2. Furthermore, the relatively high [C1]/[C2] value for sample Eyak-1 implies that the high-temperature end-member has a [C1]/[C2] ratio greater than 1 104 (Fig. 7D), which is anomalously high for thermogenic methane (Bernard et al., 1978; Whiticar, 1999). These data also suggest that the high-temperature end-member is likely microbial methane, potentially pro- duced in coal beds that occur in Southeast Alaska (Dawson et al., 2012; Walter Anthony et al., 2012). Ultimately, the high D18 values of methane in the vicin- ity of Lake Eyak confirm that mixing between isotopically distinct end-members is occurring, and has the potential to provide new insights into the formation environment of the mixing end-members. However, comparison with gas composition data suggests that the mixing processes occurring in this system are more complex than can be ade- quately resolved within the scope of this paper. Methane sampled from Katalla, 80 km to the east of D D Lake Eyak, has a similar isotopic signature to sample Fig. 8. Compilation of microbial methane 18 and 13CH3D data, D D Eyak-1 (Fig. 7A and B). The Katalla methane dD and comparing the deviation in measured 18 or 13CH3D values relative d13C values plot within the thermogenic methane field to the expected value if the methane formed in internal isotopic equilibrium vs. the deviation in measured 2a relative to the (Table 2, Fig. 3), but the inferred clumped-isotope temper- H2O-CH4 value expected in heterogeneous phase isotopic equilibrium (for ature of 27 ± 15 °C is not consistent with pure thermogenic definitions of axis parameters see Eqs. (10) and (11)). Data are from methane (Fig. 5). Furthermore, the Katalla sample contains this study, Stolper et al. (2015), and Wang et al. (2015). Data from no detectable ethane. This suggests that the methane emit- Wang et al. (2015) (open points) were measured as D13CH3D. The ted at Katalla is predominantly microbial in origin, and solid line indicates values predicted by a model of the isotopic either represents a mixture of high- and low-temperature composition of methane formed by hydrogenotrophic methano- microbial methane with distinct dD and d13C values, or gens as a function of the reversibility of methyl-coenzyme M methane with a single source forming around 27 °C with reductase (Stolper et al., 2015), with reversibility decreasing away 13 2a highly enriched dD and d C values. The relatively low from the origin. The gray triangle represents the H2O-CH4 value for 13 the water-derived hydrogen atoms in the methylotrophic culture d C value of CO2 in the Katalla sample (37.9‰, Table 1) also suggests that this sample may have undergone methane sample under two assumptions: (a) 50% of methane hydrogen atoms are derived from water; and (b) there is no D/H fraction- oxidation (Whiticar, 1999). ation between methyl group hydrogen and methane. Representa- tive x and y error bars are indicated in the upper left corner. 4.5. D18 variability in microbial methane

We compared our dataset for microbial methane emis- Measurements performed at the Massachusetts Institute of sions from the Arctic and for the methylotrophic methano- Technology (MIT) by Wang et al. (2015) (unfilled symbols gen culture experiment with existing clumped-isotope data in Fig. 9) were reported as D13CH D, as these measurements for microbial methane (Stolper et al., 2015; Wang et al., 3 2 were made using a spectroscopic method that only measures 2015). Fig. 8 depicts deviations in aH O-CH and D18 (or 13 12 2 4 the abundance of CH3D(Ono et al., 2014). CH2D2 is D13CH3D) relative to their equilibrium values at the esti- assumed to have a minor influence on D18 values in most mated temperature of methane formation, following natural samples (Stolper et al., 2014b), and our analysis Stolper et al. (2015), and were calculated as follows: treats deviations from equilibrium D and D values 2 3 13CH3D 18 18R as comparable at the scale of variability depicted here. 18 4 R m 5 DD values were calculated as in Eq. (10), but substi- DD18 ¼ 1 1000 ð10Þ 13CH3D 18R 13CH3D 13CH3D * 18 18 * 18R e tuting R/ R for R/ R . Equilibrium values ! for 13CH3DR/13CH3DR* were derived from the calculations 2a H2O-CH4;m of Webb and Miller (2014). Water dD data for culture sam- D2a ¼ 1 1000 ð11Þ H2O-CH4 2a H2O-CH4;e ples were not presented in Wang et al. (2015), so we assumed a value of 50‰ as an estimate for laboratory water at MIT 18 18 * 2a Equilibrium values for R/ R and H2O-CH4 were (Bowen et al., 2007). D 2a based on the temperature dependence of 18 and H2O-CH4 Several key patterns emerge from this compilation. presented by Stolper et al., 2014a, and 2015, respectively. First, all marine samples cluster near the defined equilib- 180 P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188

AB

Fig. 9. Scatter plot of log CH4 flux vs. D18 for (A) Alaskan lacustrine seep samples and (B) Stordalen lake samples. The Alaskan samples were collected at localized methane seeps and their fluxes are calculated on a per trap basis. The Stordalen samples were not collected at specific sites of methane seepage, and their flux is normalized to the area of the trap. A positive linear regression fit for microbial methane samples from Alaska (excluding samples where mixing or diffusion effects have likely altered primary D18 values) is shown in (A).

2a rium values, while all other sample categories show vari- methanol results in a much larger H2O-CH4 value of 13.5 D 2a ability in 18 and H2O-CH4 , with values that deviate sub- (not plotted because it does not fit on the scale of Fig. 8). stantially from equilibrium (Fig. 8). This difference has This calculation depends on the assumption that there is been noted previously (Stolper et al., 2015; Wang et al., no hydrogen isotope fractionation between methyl group 2015), and may be related to either slower rates of methano- substrates and methane. We are aware of one isotopic label- genesis in marine environments, or to anaerobic oxidation ing study that suggests minimal hydrogen isotope fraction- reactions causing the isotopic equilibration of methane, as ation between acetate and methane during fermentative suggested for the equilibration of d13C values (Yoshinaga methanogenesis (Pine and Barker, 1956). We note however, et al., 2014; Stolper et al., 2015). that differences between the aceticlastic and methylotrophic Second, the methylotrophic methanogen culture ana- pathways could lead to larger hydrogen isotope fractiona- lyzed in this study is clearly distinct from previous hydroge- tions in methyl hydrogen from methanol. While not well notrophic methanogen cultures, in that it exhibits much constrained, this calculation suggests that it is possible that D2a D2a DD lower H2O-CH4 values relative to its departure from equi- the differences in H2O-CH4 – 18 space between the hydro- librium D18. This difference could be related to different genotrophic and methylotrophic methanogen cultures sources of hydrogen, since fermentative methanogenesis is could be a result of their differing hydrogen sources. 2a thought to derive 75–50% of its hydrogen atoms from Alternatively, kinetic isotope effects for both H2O-CH4 methyl groups of substrate molecules (Pine and Barker, and D18 could differ between different pathways of 1956; Schoell, 1980; Sugimoto and Wada, 1995; de Graaf methanogenesis. Such differences could be caused by differ- et al., 1996; Waldron et al., 1999; Chanton et al., 2006), ences in kinetic isotope effects associated with the enzymes whereas hydrogenotrophic methane derives its hydrogen used by different methanogenesis pathways, and may be atoms either from water or from H2 that is assumed to be especially important with respect to the distinctive metabo- in isotopic equilibrium with water (Daniels et al., 1980; lism of the genus Methanosarcina (Smith and Ingram- Schoell, 1980; Balabane et al., 1987; Sugimoto and Wada, Smith, 2007). Furthermore, relatively lower D18 values in 1995; Valentine et al., 2004). fermentative methane could be caused by an inherited If we assume that 50% of the hydrogen in the fermenta- kinetic clumped isotope signature in the methyl group of tive culture methane is derived from the substrate metha- the substrate molecule (i.e. acetate or methanol) (Wang nol, and that there is no isotopic fractionation between et al., 2015). Whatever its cause, the difference in trajecto- methanol and methane, by mass balance the 2a value D2a DD H2O-CH4 ries followed in a plot of H2O-CH4 vs. 18 potentially for the remaining two methane hydrogen atoms is 2.01. provides a means of distinguishing fermentative and hydro- Plotting this value in Fig. 8 (with a gray triangle) brings genotrophic methane. the methylotrophic culture much closer to the data from Third, the hydrogenotrophic culture samples are also the hydrogenotrophic methanogen experiments. Assuming clearly distinct from freshwater methane samples (Fig. 8). that 75% of the hydrogen atoms are from the substrate This suggests that non-equilibrium isotope fractionation P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 181 in freshwater methanogenesis follows a trajectory in low-temperature formation environments. Our results are D2a DD H2O-CH4 – 18 space that is distinct from that of the stud- consistent with the finding of Walter Anthony et al. ied hydrogenotrophic methanogen cultures. Comparison (2012) that some ebullitive seeps in Alaskan lakes emit with the methylotrophic culture suggests that the trajectory methane from deep subsurface reservoirs of either thermo- in freshwater methane may be related, at least in part, to genic or microbial origin. Comparing D18 results with fermentative methanogenesis, which is inferred to be dom- methane flux estimates makes clear that some seeps associ- inant in many freshwater ecosystems (Whiticar et al., 1986; ated with deep subsurface reservoirs emit methane at signif- Whiticar, 1999). As discussed above, this trajectory may be icantly higher flux than the bubble fluxes of microbial in part controlled by differences in the hydrogen source methane produced in lake sediments (Fig. 9). While this between hydrogenotrophic and fermentative methanogens. does not constrain the relative fluxes of these different Fourth, a model of kinetic isotope effects in methano- methane sources to the atmosphere, it does highlight that genesis, described in detail in Stolper et al. (2015), fits some deep subsurface methane reservoirs can contribute to large of these data (Fig. 9B), and predicts the general trend point sources of natural methane emissions. The D18 of observed. There are, however, also clear deviations from methane samples from the Beaufort Shelf and Slope are the model prediction. For example, some hydrogenotrophic consistent with formation in low temperature shallow envi- culture samples exhibit higher DD18 values and lower ronments, and imply that high temperature methane reser- D2a voirs need not be invoked to explain high-flux methane H2O-CH4 values than the model prediction. In contrast, some freshwater and serpentinization samples, as well as point sources in the Arctic Ocean. the fermentative culture sample, exhibit lower DD18 values Arguably the most important methane-related feedbacks D2a to global warming will be associated with microbial and higher H2O-CH4 values than the model prediction. These discrepancies are almost certainly related to the sim- methane emissions from wetlands, lakes, and other surficial plicity of the model, which assumes a single kinetic isotope aquatic environments (O’Connor et al., 2010; Fisher et al., D effect in methanogenesis during hydrogenation of a methyl 2011). Our understanding of non-equilibrium 18 signa- group to generate methane by methyl-coenzyme M reduc- tures in microbial methane is currently incomplete, but tase. Increased model complexity, through the addition of the available data are consistent with the hypothesis that D kinetic isotope effects at other reaction steps, could poten- the reversibility of methanogenesis influences 18 values. tially accommodate this complexity, but is beyond the In the Fairbanks, North Slope and Stordalen Mire lakes D scope of this paper. Additionally, differences in the frac- the large variability in 18 values suggest a wide range of tional contribution of hydrogen atoms from water, differen- kinetic isotope effects associated with methanogenesis tial kinetic isotope effects of enzymes in different pathways (Fig. 7), as well as possible isotope effects related to D of methanogenesis, or inherited non-equilibrium clumped methane diffusion or oxidation leading to high 18 values isotope values from methyl substrates could influence the at Killarney Lake. Future studies of pure cultures and nat- expression of D and 2a values in fermentative ural methane samples will further illuminate the controls on 18 H2O-CH4 D microbial methane and contribute to deviations from the non-equilibrium 18 values, and this measurement could model prediction. become a useful indicator of methanogenesis biochemistry and its response to environmental change. 4.6. Implications for natural Arctic methane emissions In seeps emitting microbial methane from Alaska, excluding samples from Southeast Alaska and Killarney Understanding the future responses of methane emis- Lake where mixing or diffusion probably cause elevated D sions in the Arctic is an important component of predicting 18 values, we observe a positive correlation between D carbon cycle feedbacks to anthropogenic greenhouse warm- methane flux and 18 (Fig. 9A). We suggest that within this ing (Schuur et al., 2008; O’Connor et al., 2010; Koven et al., sample set, stronger kinetic isotope effects during microbial D 2011). The data presented in this study demonstrate that methanogenesis, which cause lower non-equilibrium 18 clumped-isotope analyses can help to distinguish microbial values, are associated with lower fluxes. One possible expla- and thermogenic methane, can differentiate between differ- nation for this association relates to differences in the ent sources of microbial methane (i.e. deep vs. shallow source and transport mechanism for different categories methanogens), can identify mixtures of methane with differ- of methane seeps. Walter et al. (2008) hypothesized that ent origins, and can provide new insights into the properties high-flux ‘hot-spot’ seeps in thermokarst lakes that exhib- ited older 14C ages represented conduits that integrated of those mixtures. Temporal monitoring of D18 values, in tandem with other isotopic measurements, could prove methane production across a relatively large volume of especially valuable in understanding how the relative flux deep, Pleistocene-aged sediments. In contrast, lower-flux 14 of different methane sources vary with changing environ- seeps with younger C ages emitted methane produced in mental conditions. a relatively small volume of shallow sediments. D The clumped-isotope data presented in this study con- The 18 data suggests that methane being emitted from firms the presence of diverse sources of methane in lakes high-flux seeps is produced with reduced kinetic isotope from three regions of Alaska. On the North Slope, thermo- effects, possibly indicating slower rates of growth in deeper genic methane, coal-bed microbial methane, and lake sedi- environments with limited substrate availability. This pat- D ment microbial methane are emitted from seeps within tern is also consistent with the observation of higher 18 14 100 km of one another. In Southeastern Alaska, the studied values in methane with older C ages (Fig. 7F). If this is seeps emit variable mixtures of methane from high- and the case, it would imply that the high fluxes of methane 182 P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 from these ‘hot-spot’ seeps is primarily controlled by the of methanogenesis. Both methane analyses from these lakes large source volume of methane producing sediments, and a pure culture of a methylotrophic methanogen, how- 2a D despite relatively slow kinetics of methanogenesis. We do ever, follow a trajectory in H2O-CH4 – 18 space that differs not observe a correlation between flux and D18 in microbial from that for cultures of hydrogenotrophic methanogens, methane from the Stordalen lake samples. This suggests which could either reflect differential effects of methanogen- that in these glacial lakes in discontinuous permafrost, esis pathway on D18 values, or differences in apparent where there are not clearly defined methane seeps, there is hydrogen isotope fractionation related to the source of no apparent relationship between methane flux and the methane hydrogen. We observe a wide range of non- kinetics of methanogenesis. equilibrium D18 values in ebullitive methane fluxes, span- ning a range of about 5‰, implying that kinetic isotope 5. CONCLUSIONS effects during methanogenesis are highly variable in lacus- trine environments. We have presented a survey of the clumped isotope com- position of methane emissions from Arctic environments, ACKNOWLEDGMENTS alongside measurements of dD, d13C, and D14C. Our analysis of methane from lake ebullition seeps in Alaska indicates a Thanks to Nami Kitchen and Yanhua Shuai for help with diverse set of origins, including thermogenic methane, mixed clumped isotope measurements, Kat Dawson for help with culture microbial and thermogenic methane, microbial methane preparation, Fenfang Wu for help with the water isotope measure- ment, Reto Wijker for help with the methanol dD measurement, formed in isotopic equilibrium in marine and coal-bed envi- Max Lloyd for performing the methanol d13C measurement, and ronments, and microbial methane produced in lake sedi- Uri Ryb for help with developing the isotope mixing model. Dave ments exhibiting non-equilibrium clumped isotope effects. Valentine provided helpful discussions on the results of the culture Our results confirm that some lacustrine seeps emit methane experiment. The development of the Ultra was funded by NSF- formed in deep subsurface environments at temperatures EAR, and PMJD was supported in part by Royal Dutch Shell. ranging from 9 ± 14 to 102 ± 23 °C. D18 values from seeps on the Beaufort Shelf indicate low formation temperatures consistent with methane formation in sediments or sub- APPENDIX 1: INTERLABOROTORY COMPARISON D 13 permafrost environments. While 18 values of coal-bed OF METHANE dD AND D C DATA and marine microbial methane indicate plausible equilib- rium formation temperatures, microbial methane produced Aliquots of the methane samples from the Alaskan lakes in lake sediments in Alaska and Sweden are characterized and Beaufort Sea were previously analyzed for dD and d13C D by low 18 values indicating non-equilibrium isotope effects. using a gas chromatography-isotope ratio mass spectrome- Mixing between isotopically-distinct methane sources pro- try method at either Florida State University, the Univer- D duces a distinctive non-linear trajectory in 18 values that sity of Alaska, or Isotech Laboratories (Paull et al., 2011, can be used to help characterize the mixing end-members. 2015; Brosius et al., 2012; Walter Anthony et al., 2012). D 2a d d13 Comparison of 18 and H2O-CH4 data from microbial The D and C values measured using the Ultra are typ- methane produced in lake sediments supports the hypothe- ically depleted in dD and d13C relative to the previous mea- sis that non-equilibrium D18 values are controlled, at least surements, with an average deviation of 2±8‰ for dD in part, by kinetic isotope effects related to the reversibility and 1.1 ± 0.5‰ for d13C(Fig. A1). We ascribe this

AB

Fig. A1. Comparison of d13C (A) and dD (B) values for samples in this study measured on the Ultra and in external laboratories. The solid black line indicates a 1:1 relationship, and the dashed line indicates the linear regression fit for the data. One outlier sample (Goldstream 40A) is indicated by a filled symbol, and is not included in the linear regression fit. P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 183 difference to interlaboratory measurement artifacts. The out the session (Fig. A2A). In this session we also tested the Ultra measurements are anchored to off-line combustion observed dependence by measuring gases heated at 200 °C, and water reduction techniques, coupled with dual inlet in which we observed a linear relationship between D18 on mass spectrometry, performed in the laboratories of A. d18 with the same slope as the relationship for the gases Schimmelmann at Indiana University (Stolper et al., heated at 500 °C(Fig. A2A). 2014a). The techniques used in most conventional stable This effect appears to be similar to the dependence of D47 isotope laboratories have other bases for standardization, to bulk isotopic composition in CO2 clumped isotope stud- and the methane isotope community as a whole is currently ies (Huntington et al., 2009; Dennis et al., 2011). We do not organizing a broader interlaboratory approach to standard- know the origin of this effect, but hypothesize it is related to ization. Thus, we do not believe we can currently resolve background effects that were not present in previous studies these discrepancies in our study, but they should be resolv- or ion scrambling that has changed from the previous ses- 18 able in the near future. In any event, these differences do sions. Based on this observed dependence of D18 on d not affect the interpretation of the results presented here. we applied a heated gas correction, similar to that applied As all of our measurements are internally referenced to in analyses of mass 47 CO2 (Dennis et al., 2011), using the same standard, issues of inaccuracy in dDord13Cof the equation: a few per mil make no difference to the D measurements 18 D ¼ D ðd18 m þ bÞðA2Þ beyond the stated error of the measurement. The lower 18HG 18M d d13 D and C values measured by the Ultra are not consis- where D18HG is the corrected value, D18M is the raw mea- tent with gas-phase diffusion-related fractionation caused sured value, and m and b are slope and intercept parameters by leakage of gas during storage, which would lead to both defined for each measurement period by the relationship d d13 18 the D and C values of residual methane being higher by between D18M and d for heated gases (Fig. A2). Our basis the same amount (Criss, 1999). Additionally, oxidation for a constant set of parameters for a given measurement during storage should have led to increases in dD and period is that the values for m and b remained constant over d13C as well, although by different amounts (Whiticar, the course of the most recent, 15 week measurement period 1999). where the slope was most prominently observed (Fig. A2A). For one sample (Goldstream 40A) we observe much lar- For the sake of internal consistency, and because doing so ger deviations between the previously measured isotope val- improved the reproducibility of samples analyzed in multi- ues (difference of 64‰ in dD and 7.3‰ in d13C). While ple measurement periods, we corrected all other measure- we are uncertain of the cause of this discrepancy, we pro- ment periods in this study following this protocol ceed with an interpretation of this sample based on the (Fig. A2B). We note, however, that the evidence for this stable isotope measurements made using the Ultra (with dependence is not as strong in some of these measurement the simple reasoning that at least we know these values periods (Fig. A2B). For example, in one measurement per- apply directly to the aliquot of gas for which D18 was iod (April 2014) we did not measure a heated gas depleted measured). in d18 (d18 < 20‰ relative to the internal reference stan- dard). The heated gas correction is therefore less certain APPENDIX 2: STANDARDIZATION AND ERROR for this session for methane with d18 values below 20‰. ESTIMATES FOR CLUMPED ISOTOPE Subsequent replicate analyses of two samples measured in MEASUREMENTS this measurement period (Goldstream Hotspot; Killarney Lake) indicate a 2SE uncertainty of 0.7‰. This uncertainty In each session we measured methane with different iso- is larger than that of other replicate measurements, but topic compositions equilibrated on a nickel catalyst at 500 ° does not affect the interpretation of these samples. C to determine whether D18 values were dependent on aver- To ensure accuracy and precision of our measurements, age molecular methane isotopic composition. These especially in the context of the newly applied correction, the methane samples ranged from 78‰ to 340‰ in dD, external precision of measurements was monitored by ana- from 34‰ to 42‰ in d13C, and from 121‰ to 198‰ lyzing a standard differing in dD (+56‰), d13C (+33‰), in d18. d18 is defined as: and d18 (+92‰) relative to the laboratory internal stan- dard. External precision for D across all measurements d18 ¼ 18R =18R 1 ðA1Þ 18 sample standard was ±0.38‰ (1 standard deviation, r; n = 16), and is offset and is expressed in per mil (‰) notation. The standard for in D18 by 0.06‰ from the long-term average of the stan- d18 values is the laboratory internal methane standard, dard over 2.5 years of measurements (1.6‰). The standard which has a defined value of 0‰ (see Section 2.5). In previ- deviation for measurements of this external standard was ous studies, it was demonstrated that there was not a signif- larger than previously observed in studies from this instru- ‰ ‰ icant dependence of D18 values on the bulk isotopic ment (±0.19 in Stolper et al., 2014b; ±0.23 in Stolper composition of the gases (Stolper et al., 2014a,b, 2015). et al. (2015), for unknown reasons. For this reason we However, in some of the measurement periods for this applied conservative, 2 SE uncertainties to our D18 values. study a linear dependence of D18 on the bulk composition In two sessions we observed drift in the standard used to of the sample (indicated by d18 values) was apparent normalize data from a measurement session to a unified dD (Fig. A2). In particular in the final measurement period, and D18 reference frame (Stolper et al., 2014b). We cor- in which a total of 10 heated gas measurements were made, rected for this drift by measuring the standard used 18 the linear dependence of D18 on d was consistent through- for the correction multiple times over the course of these 184 P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188

A B

18 Fig. A2. Plots of d vs. D18 for heated methane standards, indicating the relationship between these values for (A) the measurement period 18 from April to August 2015 when the dependence of D18 on d was most clearly documented; and (B) for earlier measurement periods. In (A) results for methane heated to both 500 and 200 °C are shown. D18 values equivalent to methane equilibration at 500 and 200 °C are shown on the right side of the plots. The average difference recovered for the 500 °C and 200 °C heated gases (1.59‰) is within 1 r of the predicted difference based on the calibration given in Stolper et al. (2014a) (1.78‰).

18 18 18 sessions and assumed the values required for sample correc- Rm ¼ f t Rt þð1 f tÞ Rb ðA5Þ tion changed linearly with time between observations of the R R R standard. The quality of the correction was checked where f, t, and m represent the isotope ratios of a given m t through multiple measurements of a secondary standard fractional mixture ( ), or of the thermogenic ( ) or biogenic b in all sessions and re-analysis of at least some samples in (i.e. microbial; ) end-members, respectively, while super- script numbers denote the applicable isotopes. ft is the frac- other sessions. For both sessions, average D18 values of the secondary standard were within 2 standard errors tion of thermogenic gas in a given mixture. While these terms imply a high-temperature thermogenic end-member, (2 SE) of its long-term average (D18 = 1.6): 1.54 ± 0.48 (n = 4) and 1.46 ± 0.18 (n = 11). we note that a high-temperature microbial end-member is Ten of the samples analyzed for this study were analyzed also possible. D as replicates, in some cases in multiple measurement peri- The 18 mixing model assumes linear, conservative mix- ing of d13C, and dD values between only two end-members ods. The 2 SE standard error in D18 for these replicate anal- yses (n = 2 for all replicates) ranged between 0.03‰ and (Fig. 7A). The assumption of only two end-members d d13 0.80‰. The pooled standard deviation for replicate analy- requires that end-member D and C values fall along a d d13 ses (defined as the 1r standard deviation of the residual mixing line defined by the sample D and C values d13 of individual measurements from the sample mean) is (Fig. 7A). This means that, for a given end-member C d 0.21‰. value, the end-member D value is directly constrained by the dD–d13C mixing line. The thermogenic end-member d d13 D14 d13 APPENDIX 3: DETAILS OF ISOTOPIC MIXING D and C values predicted by the C– C(Fig. 7C) D14 d d MODEL and C– D (not shown) mixing lines plots on the D– d13C mixing line for Lake Eyak samples (Fig. 7A), which validates our approach. Note that there are different dD– The mixing model presented in this study calculates the 13 13 d C mixing lines depending on the inclusion of the PWS trends in plots of d C vs. D18 and dD vs. D18 created by fractional mixing of specified end member isotopic compo- sample (Fig. 7A). sitions. We performed these mixing model calculations Using a Monte-Carlo approach, we randomly sampled d13 D using isotope ratios as the primary measure of composition 100,000 sets of C and 18 values, with a uniform distri- (i.e., as opposed to d or D values, which are less suitable as bution, for the thermogenic and microbial end-members, proxies for concentration in such models). Test calculations from a wide range of possible values (Fig. 7B). As discussed d based on fractional isotopic abundance (a more accurate above, end-member D values were directly constrained by d13 but laborious approach) were within error of the calcula- end-member C values and were not specified. For the D tions performed with isotope ratios. The governing equa- microbial end-member, 18 values were allowed to range ‰ ‰ tions in our mixing model include, in addition to Eqs. from 8.4 (defined by sample Eyak-3) to 0.5 (the low- (3)–(5) above: est value observed in a natural methane sample in this study; Table 2). Microbial end-member d13C values were 13 13 13 Rm ¼ f t Rt þð1 f tÞ Rb ðA3Þ allowed to range from 74‰ (defined by sample Eyak-3) 2 2 2 to 120‰ (based on the empirical range of microbial Rm ¼ f Rt þð1 f Þ Rb ðA4Þ t t methane d13C; Whiticar et al., 1986). Thermogenic P.M.J. Douglas et al. / Geochimica et Cosmochimica Acta 188 (2016) 163–188 185 end-member D18 values were allowed to range from 6.2‰ Thawing Sub-arctic permafrost: effects on vegetation and (defined by sample Eyak-1) to 1.5‰ (an upper temperature methane emissions. Geophys. Res. Lett. 31. limit of 300 °C; Quigley and Mackenzie, 1988; Clayton, Clayton C. (1991) Carbon isotope fractionation during natural gas 1991). Thermogenic end-member d13C values were allowed generation from . Mar. Pet. Geol. 8, 232–240. to range from 20‰ (an empirical upper limit for thermo- Comiso J. C. and Hall D. K. (2014) Climate trends in the Arctic as observed from space. Wiley Interdiscip. Rev. Clim. Change 5, genic methane; Whiticar et al., 1986) and 47‰ (defined by 389–409. sample Eyak-1). We then calculated the resulting mixing Conrad R. (2005) Quantification of methanogenic pathways using d13 D d D lines in C– 18 and D– 18 space for each set of end- stable carbon isotopic signatures: a review and a proposal. Org. member compositions. A set of end-member values was Geochem. 36, 739–752. determined to be acceptable if its mixing line passed within Conrad R., Klose M. and Claus P. (2002) Pathway of CH4 13 the 2 SE error of the d C–D18 and dD–D18 compositions of formation in anoxic rice field and rice roots determined by each of the sample measurements (Table 2). The acceptable 13C-stable isotope fractionation. Chemosphere 47, 797–806. 13 Coplen T. B. (2011) Guidelines and recommended terms for sets of end-member values define d C–D18 (Fig. 8B) and expression of stable-isotope-ratio and gas-ratio measurement dD–D18 (not shown) mixing lines. results. Rapid Commun. 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