Interactive comment on “ Methane dynamics in warming tundra of Northeast European Russia ”

This manuscript presents valuable data on CH4 fluxes from the understudied permafrost region of NE Europe. CH4 fluxes were measured on the plot scale by closed chambers and on the landscape scale by the eddy covariance approach. The combination of these two approaches is a particular strength of this study. Furthermore, the authors present interesting data on stable carbon signatures of pore water and emitted CH4 which allows new insights in the processes that are involved in the CH4 emission.


Introduction
The arctic tundra covers 9.2 million km 2 , i.e., 8 % of the global land area (McGuire et al., 2012).These areas are important in climate change research, because they store nearly one third of the Earth's soil carbon (Schuur et al., 2015;Tarnocai et al., 2009) and thus possess a great potential via feedback mechanisms to alter the concentrations of CO 2 (carbon dioxide) and CH 4 (methane) in the atmosphere (Post et al., 2009).Top-down modeling results based on measurements of concentrations and stable isotope composition of CH 4 have already proved the importance of high-latitude wetlands as global CH 4 sources (Riley et al., 2011).For example, the increase in the global mean atmospheric CH 4 concentration in 2007 has been attributed to anomalously high summer temperatures experienced by these ecosystems during that year (Dlugokencky et al., 2011).Despite the large areal extent, the Russian tundra region is relatively less explored with respect to its ecosystem biogeochemical functioning.According to the latest estimates (McGuire et al., 2012;Schuur et al., 2015), presently, this region is considered to be a net carbon dioxide (CO 2 ) sink and a source of atmospheric CH 4 .Although CO 2 flux represents the major component in the total C flow between tundra ecosystems and the atmosphere, CH 4 is equally important owing to its 25 times higher global warming potential (over a 100 year time horizon, IPCC, 2014).
In the arctic, CH 4 is mostly emitted from non-frozen wetlands (Heikkinen et al., 2004;Mastepanov et al., 2008) and from lakes and ponds (Walter et al., 2008).On the whole, there is a general consensus that the Arctic region is a moderate CH 4 source This is attributed to the flux variability across time and space that is poorly characterized yet.Methane exchange is unevenly distributed across the landscape (hot spots) (Walter et al., 2006) and may occur during short periods of time (Mastepanov et al., 2008).For reliable estimates of CH 4 balance, measurements made across all important constituent land cover types at a high temporal resolution are required.The ideal way to achieve this is to apply chamber and eddy covariance techniques in parallel.Such an approach has, however, rarely been adopted in Arctic investigations (Parmentier et al., 2011;Sachs et al., 2008).Eddy covariance data, with a high temporal resolution and minimal disturbance to the ecosystem being studied, provides an ensemble average ecosystem source/sink strength, while chamber techniques aid in a proper characterization of the inherent spatial variability in the methane release.The two methods employed simultaneously help improve the accuracy of the regional flux estimates, as has been shown for carbon dioxide at this site (Marushchak et al., 2013).
In addition to increasing the accuracy of flux estimates, processes underlying CH 4 dynamics need to be better understood.This is important for developing process-based biogeochemical models with an ability to simulate present and future CH 4 fluxes (Riley et al., 2011).In this respect, stable isotope analyses of CH 4 have been useful as they provide valuable information on CH 4 sources and production mechanisms (Chanton, 2005;Chanton et al., 2005;Popp et al., 1999).Knowledge on the isotopic composition of CH 4 from various ecosystem types is also important for top-down modeling where the aim is to determine the relative contribution of different emission sources to the atmospheric CH 4 content (Riley et al., 2011).Data on isotopic composition of C in peatland CH 4 emissions are sparse, especially from the Russian tundra ecosystems (Sapart et al., 2012).A more detailed characterization of CH 4 emissions is highly relevant to better constrain global CH 4 sinks and sources, particularly in view of the growing importance of northern peatlands in global C cycle.
Present day trends have revealed that the permafrost temperatures have risen by 2 • C and the southern boundary of permafrost has retreated northwards in the Russian Arctic (Romanovsky et al., 2010).Changes in permafrost extent and active layer thick-Introduction

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Full ness affect composition (Christensen, 2004) and CH 4 flux (Johansson et al., 2006) from northern wetlands.In a study on permafrost dynamics of the Russian tundra (Anisimov, 2007), permafrost temperatures have been projected to increase by 2-3 • C by 2050 with a 15-25 % increase in the active layer thickness leading to a 25 % increase in the CH 4 emissions from the northern Russian wetlands.Such projections can be improved with a robust estimate of the magnitude of CH 4 fluxes, their spatial and temporal variability and underlying mechanisms.
Our aim here was to provide an estimate of CH 4 fluxes as measured by two independent measurement techniques in a subarctic Russian tundra region and to deepen our understanding of the factors regulating methane exchange in this environment, vulnerable to climate change.To investigate methane fluxes and underlying mechanisms in the Russian Arctic at various scales (from processes to landscape) we used a set of methodological tools including stable isotope investigations, EC and chamber based flux measurement techniques and regional upscaling by fine scale QuickBird satellite image based land cover classification scheme.We report here a full year of CH 4 measurements by static chambers and gas gradient methods.These methods were complemented by fluxes measured using the EC technique from early spring to autumn in 2008.Chamber measurements on dominant terrestrial surfaces and lake flux studies were used to evaluate the potential effect of changes in ecosystem composition on CH 4 exchange from the tundra.Based on the observed relationship between methane fluxes and controlling variables, we have projected the regional methane release by taking into account specific climate scenarios generated for this region by a regional climate model.Overall, to the best of our knowledge, this is one of the rare multi-level approaches on CH 4 dynamics over various temporal and spatial scales in an arctic environment.Introduction

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Full 2 Materials and methods

Site description
This study was conducted in the subarctic tundra of the Komi Republic, Northeast European Russia.The measurement site is located near the village Seida (67  Marushchak et al. (2013) and Biasi et al. (2013).
A high resolution QuickBird satellite image (Fig. 1) was used to map the distribution of the various land cover types (LCTs) of the study area of 98.6 km 2 (Hugelius et al., 2011;Marushchak et al., 2013).In terms of areal coverage, the tundra heath (58 %) and tundra bog vegetation (24 %) found especially on permanently frozen peat plateaus, are the dominant ecosystem types in the region followed by willow stands (9 %), and various fen ecosystems (6 %).The peat plateaus are spotted by unvegetated, patterned ground features (referred to hereafter as bare peat circles which have been studied by Repo et al., 2009, as  the water together with vascular plant roots.Small lakes, mostly of thermokarst origin, cover a minor part of the landscape (1 %).

Plot-scale CH 4 flux measurements at terrestrial land cover types
Ten land cover types, each with three replicate measuring plots, were established for the determination of CH 4 fluxes from the soil surface, three of them on water-logged wetlands, three on peat plateau and four on upland tundra.Fluxes of CH 4 were determined using the methodology described in detail for nitrous oxide fluxes by Marushchak et al. (2011).Fluxes were measured by the static chamber technique 11-16 times during the snow-free season from early July to mid October 2007 and 16-21 times during the snow-free season from late May-early July until the beginning of October 2008.
In addition, CH 4 fluxes were measured 2-5 times per plot during the snow cover period in January-June with a snow-gradient method (Merbold et al., 2013).The CH 4 concentrations in the collected gas samples were analyzed within three months from sampling using a gas chromatograph equipped with a flame ionization detector (Agilent 6890N, Agilent Technologies Deutschland, Böblingen, Germany).A leakage test with a high CH 4 concentration (15 ppm) showed that the reduction in gas concentration in the sample vials over two months was less than 1 % (data not shown).Flux calculation and criteria to accept or reject fluxes for further analysis are described in Marushchak et al. (2011).Water table level (WT), active layer depth (AL), soil temperature at 2 and 25 cm depths and vascular leaf area index (LAI; only in 2008) were monitored at different land cover types by manual and continuous measurements as described by Marushchak et al. (2011Marushchak et al. ( , 2013)).The adjustment of moss surface to water table fluctuations on willow and fen microsites was monitored in 2008 by a measuring pole pushed through the peat profile down to the mineral soil.Introduction

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Lake methane emission measurements
Release of CH 4 by diffusion and ebullition pathways was studied in three thermokarst lakes from July to August 2007 (11 samplings between days 191-239) and from June to October 2008 (19 samplings between days 182-276).The area of the studied lakes was 0.03-3 ha with the maximum depth ranging from 2.0 to 2.6 m and surface water pH from 4.6 to 5.5.Diffusive CH 4 flux was calculated from CH 4 concentration in the surface water and local wind speed using the thin boundary layer (TBL) model (Liss and Slater, 1974).Surface water samples were collected during daytime (8 a.m.-19 p.m.).The determination of CH 4 concentration with a head space method and flux calculation were carried out as described in (Repo et al., 2007).Linear interpolation was used to obtain daily CH 4 concentrations.The hourly averaged wind speed measured at 2 m, normalized to 10 m using a logarithmic wind profile, was used to calculate hourly flux rates.Ebullitive CH 4 flux was monitored with permanently installed, submerged funnel gas collectors (Repo et al., 2007).Each lake had 6-7 replicate gas collectors (Ø 0.35 m), which were sampled concurrently with surface water sampling.Gas samples were stored and analyzed as described above.

Temporal extrapolation of plot-scale CH 4 fluxes
The temperature dependence of CH 4 flux was used to produce daily CH 4 exchange rates during the snow-free period for the land cover types with large CH 4 fluxes: willow stands, Carex fen and Eriophorum fen.Regression functions based on air temperature and peat temperatures at 2 and 25 cm were tested, and the best fit was obtained with temperature at 25 cm.Addition of a water table term improved the model fit in 2007 (helped explain 20 % additional variation in the flux data) and resulted in a more realistic seasonal pattern, so the following function was used: (1) Introduction

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Full where T is the soil temperature at 25 cm ( • C) and WT is the water table level (cm).Model parameters were estimated for each measurement plot individually using the SPSS 14.0 statistical software.The regression functions explained 85 % of the overall variability in fluxes across the different vegetation types (Table 1; Fig. 2).
For the remaining terrestrial plots with low emissions and for lakes, CH 4 fluxes were integrated over time using linear interpolation for the days between the measurements as described by Marushchak et al. (2011).Linear interpolation was also used for willows and fens for the snow period when the water table levels were not monitored.The annual fluxes were calculated for the period from 6 October 2007 until the termination of measurements on 5 October 2008.

Isotope analysis of emitted and porewater CH 4
The δ 13 C values of the emitted and porewater CH 4 were determined during summer 2007 and 2008 from the three surface types with high water table and, thus, with a potential for high CH 4 release: willow stands, Carex and Eriophorum fens.Gas samples were collected biweekly starting from mid-July until late August (total 5 times) in 2007 and twice in 2008, in late June and in early August.Five gas samples were collected for the isotopic analysis during the time of the chamber closure and injected into 35 mL glass vials (Wheaton) topped with rubber septa and prefilled with N 2 gas.In addition, pore water at 5 and 30 cm depths was sampled from gas collectors made out of perforated plastic tubes following Maljanen et al. (2003).A water sample of 30 mL was taken in a 60 mL syringe, a similar volume of air was added and the syringe was then shaken for 2 min, after which the gas phase was transferred to a glass vial (Labco Exetainer) prefilled with pure N 2 .The 5 cm gas collector was occasionally above water table level, in which case pore gas was sampled and transferred directly into a vial.Also ambient gas samples were collected for isotopic analysis.
Isotope analyses of CH 4 were done at the laboratories of University of Eastern Finland by gas chromatography isotope ratio mass spectrometry (GC-IRMS; Thermo Finnigan Delta XP, Germany) equipped with a preconcentration unit (Precon, Thermo 13939 Introduction

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Full Scientific, Germany) (Dorodnikov et al., 2013).If needed, samples were diluted.Values are expressed as δ 13 C relative to VPDB (Vienna Pee Dee Belemnite Standard) using a standard gas with known 13 C values.Standard error of five repeated measurements of isotope standard was less than 0.5 ‰ for CH 4 .Methane concentrations of all samples were separately analyzed by gas chromatography (Hewlett Packard 5890A) equipped with flame ionization detector (FID) for CH 4 (Mörsky et al., 2008).The Keeling plot method (Pataki et al., 2003) was used to determine the δ 13 C value of emitted CH 4 .According to this method, the δ 13 C value of the emitted CH 4 is obtained by plotting the measured δ 13 C values against the inverse of CH 4 concentrations, where the intercept of the linear equation with the y axis is the δ 13 C value of the emitted CH 4 .

EC measurements
The landscape scale CH 4 fluxes were measured by the EC technique during the period from mid-May to early October 2008.The CO 2 fluxes, measured simultaneously with the CH 4 fluxes data presented in this paper, have already been reported in Marushchak et al. (2013) and Kiepe et al. (2013).Fluctuations in the vertical wind speed were measured at a height of 2.75 m above the ground using a three-dimensional sonic anemometer (R3, Gill Instruments Ltd, UK).A quantum cascade laser (QCL) spectrometer was used for CH 4 concentrations (Aerodyne Inc., USA).The CH 4 fluxes were calculated and corrected for theoretical separation between instruments and attenuation of the CH 4 signal in the intake tube using the software package, AltEddy version 3.5 (Alterra, University of Wageningen, the Netherlands).Methane fluxes were further corrected for simultaneous flux of H 2 O (Webb et al., 1980).Further data processing and quality control followed the standard methodology of Aubinet et al. (1999) and Foken et al. (2005).Calculation of the source area for the flux measurements followed the principles described in Soegaard et al. (2000) and Marushchak et al. (2013), where LCTs were based on a QuickBird satellite image classification.Introduction

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Regional CH 4 emission
For area integration of the CH 4 fluxes to the landscape and regional level we used a land cover classification (Fig. 1; Hugelius et al., 2011;Marushchak et al., 2013) that was made based on a QuickBird satellite image acquired on 6 July 2007 (QuickBird ©2007, Digital Globe; Distributed by Eurimage/Pöyry).Classification procedure is explained in more detail in (Virtanen and Ek, 2014).High resolution of the satellite image (2.4 m pixel size, 4 channels) allowed accurate representation of the heterogeneous landscape, including fens that are distributed across the landscape as narrow stripes or patches (Virtanen and Ek, 2014).The hourly chamber fluxes of different land-cover types were weighted by their relative area contributions to estimate flux values for the EC footprint and for the whole QuickBird area.For rivers, we used a CH 4 emission value of 1 g C m −2 during summer, estimated for a river in the same region by Heikkinen et al. (2004).A zero CH 4 balance was assumed for forest stands, sand and impacted tundra.

Climatic conditions during the study period
Plot scale measurements of CH 4 fluxes on terrestrial sites and lakes covered the growing seasons 2007 and 2008 and, less frequently during the cold season in between (Fig. 3a and b).A detailed discussion of weather conditions during the study period can be found in Marushchak et al. (2011).In brief, mid-summer temperatures were higher than the long-term averages during both years, and July was hotter in 2007 (17.9 • C) than in 2008 (15.8 • C).The amount of precipitation received during the two growing seasons was comparable to the long-term regional precipitation.In 2008, a period from mid-May through early October was covered by simultaneous plot scale and eddy covariance measurements (Fig. 3c).In the beginning of this measurement cam-Introduction

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Full paign, there was still a 90 % snow cover, temperatures were below freezing point and there was no active layer above permafrost.By early October, the diurnal average air temperatures had again dropped close to zero and the maximum active layer thickness varied from 41 cm to greater than 120 cm depending on the land cover type.

Spatial variability in CH 4 fluxes
Based on the plot scale measurements, only the wetland sites (willow stands and fens) emitted high amounts of CH 4 to the atmosphere throughout the snow-free season (Fig. 3a).The CH 4 fluxes increased in the order: Eriophorum fen < Carex fen < willow stands, with LAI of vascular plants explaining 88 % of the differences in fluxes among the sites (Fig. 4).The annual CH 4 emissions from these wetland types were 11 ± 4.5, 37 ± 17 and 53 ± 8 g CH 4 m −2 , respectively.At willow and Carex fen sites, the floating Sphagnum mat followed the fluctuations in the ground water level.This dampened the amplitude of the water table level variation relative to the moss surface.While the absolute amplitude of the water table level at the fen sites in 2008 was 23 cm, this was reduced to about 10 cm relative to the moss surface as a result of the surface adjustment.
Consequently, the fen sites remained submerged 5-10 cm below the water level even during the driest part of the growing season in July 2008.The willow LCT did not have a floating moss layer but the mean water table was still maintained close to the moss surface.The CH 4 fluxes from these sites showed a strong exponential dependence on temperature at the individual plot level.Moreover, a strong exponential relationship between CH 4 flux and soil temperature was also corroborated by EC measurements made on the landscape level (Fig. 5).The drier peatland habitats, the tundra bog and bare peat circles were smaller CH 4 sources (0.2 ± 0.2 and 0.7 ± 1.1 g CH 4 m −2 yr −1 , respectively).The upland tundra types were at times small sinks for atmospheric methane during the season.When accumulated over the entire season, they were close to being neutral with the CH 4 emissions ranging from −0.03 to 0.13 g CH 4 m −2 .

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Full The annual CH 4 emissions from the thermokarst lakes varied from 2.1 to 5.3 g CH 4 m −2 (mean 4.2 g CH 4 m −2 ) and thus, they were lower compared to wetland sites (Fig. 3b).The magnitude of total CH 4 emissions as well as the importance of diffusion vs. ebullition pathways varied strongly among the lakes.The contribution of the ebullitive flux ranged from 5 to 94 % and was the highest in the biggest of the lakes with the most intensive thermokarst processes occurring.The highest diffusive flux was observed in the smallest lake with the least open water area.The seasonal mean CH 4 concentration in the surface water was 0.3-3.7 µmol L −1 in 2007 and 0.4-8.0µmol L −1 in 2008.

Isotopic signature of C-CH 4 in emission and porewater
The δ 13 C in CH 4 flux did not show much variability among the wetland types, years or sampling dates (Table 2, Fig. 6).In 2008, the Eriophorum fen was still partly frozen during the first sampling date.This presumably led to an anomalously high δ 13 C value, likely decreasing the average δ 13 C-CH 4 value for this site in 2008.The bulk average ±SD of δ 13 C in CH 4 emitted from different peatland types and years was −68.2 ± 2.0 ‰.Methane emitted from wetlands was lighter (δ 13 C more negative) than the porewater CH 4 at all wetland types and lighter CH 4 was found at 30 cm than at 5 cm (Fig. 6).A negative linear correlation was found between δ 13 C in CH 4 emission and vascular LAI across the wetland plots (Fig. 4, the higher the LAI, the lighter the CH 4 ; P < 0.0001).

Landscape scale and regional CH 4 balance
The fluxes of various land cover types were spatially extrapolated over the EC footprint area and further over the whole study region of 98.6 km 2 using the data on the land cover classification.When the plot scale measurements were scaled up to the EC footprint area, the CH 4 flux estimate (3.7 g CH 4 m −2 ) obtained was larger than the estimate by the EC technique (2.4 g CH 4 m −2 for the whole EC measuring campaign, Fig. 3c).Introduction

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Full An LAI map produced for the area based on the QuickBird image showed that the fen plots selected for the chamber measurements had on average higher LAI (1.2) than the fens in the region (0.7).If the linear relationship between CH 4 flux and LAI presented in Fig. 4 is used to correct the CH 4 fluxes from fens to account for the lower LAI in the landscape, the CH 4 estimate was reduced to 2.8 g CH 4 m −2 .This is close to the estimate based on EC measurements (Table 2).
The regional CH 4 emission, without LAI correction for fen fluxes, was 5.6 g CH 4 m −2 for the EC measurement period from May through September and 6.7 g CH 4 m −2 for the whole year.Contribution of the non-growing season to this annual CH 4 flux was 30 %.The higher emission compared to the EC footprint area can be explained by higher coverage of wetlands in the whole study region (willow coverage 8.7 vs. 1.6 %).In the EC footprint area there were more tundra bog (39 %), fen (10 %) and lakes (9 %) and less tundra heath (41 %) and willows (2 %) than in the whole QuickBird area.

Discussion
In wet parts of the tundra ecosystem in the Seida area emit CH 4 at a rate equivalent or higher than what has been reported for similar tundra habitats in Russia (e.g., Heikkinen et al., 2004).
The area integrated chamber measurements in this study show somewhat higher fluxes than what is estimated by the EC technique (Table 3).This could be attributed to the disparity in the distribution of different land cover types within and outside the footprint of the EC tower and to the variability associated with the fluxes among various surface types as measured by the chambers.Variability among the surface types is relatively high and can, at least partly, explain the difference compared to the EC measurements.For example, the fen plots measured with chambers had higher LAI than the fens in the region in general.Based on the relationship between CH 4 flux and LAI, when we corrected the chamber CH 4 flux estimate for such a LAI variation, the CH 4 estimates based on the two independent methods were found to agree with each other.Without this correction, the seasonal CH 4 flux estimated based on the chamber method was higher for the region than based on the eddy covariance (2.4 g CH 4 m −2 ), but still lower as compared to other studies (referred to above) conducted at sites where wetlands are relatively more abundant.
To characterize the CH 4 source from the studied fens and willow stand, we employed stable isotope analysis and measured the δ 13 C values of CH 4 in porewater and surface emissions.The overall mean δ 13 C value of CH 4 released to the atmosphere was −68.2 ‰ and falls within the range of values reported for wetlands from the Arctic including Siberia (McCalley et al., 2014;Sriskantharajah et al., 2012).The δ 13 C value of CH 4 from wetlands worldwide is −59 ± 6 ‰ (McCalley et al., 2014).Generally, the isotope signal of CH 4 from wetlands appears to be rather constant and sufficiently distinct from other large sources, e.g.biomass burning (Monteil et al., 2011), supporting the use of isotopes to better constrain sources and sinks of atmospheric CH 4 by inverse modelling.We have shown here that the δ 13 C emitted from the surface is lighter than the δ 13 C dissolved in pore-water.This indicates that a large part of the emitted CH 4 is transported from peat to the atmosphere from deeper peat layers, likely via plant Introduction

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Full aerenchyma.Such a process leads to enhanced fractionation, thus depleting the δ 13 C of methane (Chanton et al., 2005).Similar observations of depleted CH 4 in surface emissions compared to pore-water were made by others (e.g., Popp et al., 1999).It has been generally argued that plant-mediated transport accounts for a large share of CH 4 emissions in wetlands inhabited by vascular plants (Kutzbach et al., 2004;Riley et al., 2011;Van Der Nat et al., 1998).The assumption that plants significantly impact on the net CH 4 emissions from this site is further supported by the linear correlation between δ 13 C of CH 4 and LAI, although this correlation may also indicate the influence of plant-derived C supply for methanogens (Riley et al., 2011).The observation that plants mediate CH 4 release is important in the context of climate change.This implies that a significant part of the CH 4 produced in the soil profile bypasses the oxic soil zones thus confounding the effect of water table variations.
Temperature records from the nearby Vorkuta station (75 km North of the field site) show that the average air temperature in the region rose by 0.9 • C from 1980-1999 to 2000-08 (P.Kuhry, personal communication, 2010).A climate scenario for the northern part of the Komi Republic was developed as part of the CARBO-North project using the IPCC-SRES emission scenario A1B (Stendel et al., 2011).As per these projections, a 3.5 • C regional warming relative to the present day climate is expected to occur by the end of the 21st century.For the northern part of the Komi Republic, the region within which the study site is situated, a temperature increase of nearly 7.0 • C relative to the average over the period 1980-1999 is predicted by 2100.
Employing the temperature CH 4 flux relationship observed in this study (Table 1), a temperature increase of 7.0 • C alone by 2100 relative to 1980-99 would lead to an increase of approximately 69 % in the annual CH 4 emission.The floating peatland surface in fens typical of this area, adjusts to fluctuations in the water table.This implies that the fen types might remain water-logged, even if other tundra habitats would get drier.If the water table level remains within a range favorable for CH 4 production and its release to the atmosphere, the higher temperatures would enhance CH 4 emissions.Additionally, the isotope data suggest that CH 4 is released largely from deeper layers

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Full of peat via plant roots thereby escaping its oxidation, implying relatively minor effects of water-table fluctuations.Moreover, the growth of willow stands in the study area has been reported to be higher owing to warmer temperatures (Forbes et al., 2010).Enhanced willow stand productivity may further lead to increased CH 4 emissions, also evidenced by the fact that plants control the net CH 4 and 13 C-CH 4 release.Based on the positive correlation between LAI and CH 4 flux, we estimate that a 50 % increase in the LAI would favor enhanced release of CH 4 to the extent of nearly 35 % from tundra wetlands in the study region.
While less uncertainty is associated with the direct effects of temperature increase on the methanogenic processes, a high degree of uncertainty exists with respect to consequences of temperature increases on the geomorphological changes of the studied tundra landscape and their possible impact on vegetation.In addition to the direct enhancement of CH 4 fluxes by higher temperatures, warming of 6.1 • C by 2100 will evidently cause thawing of permafrost and result in landscape changes in the study region.Our measurements of active layer thickness over the season reveal that the seasonal active layer is deepest in the wettest (low laying) parts of the tundra, which are characterized by lakes, fens and willow wetlands.A possible consequence of the predicted warming could be that these wetland cover types become more prevalent in the future.Based on our results, fen sites are the strongest emitters of CH 4 .Any landscape change leading to the formation and expansion of such wetland types owing to permafrost thaw would further increase CH 4 escape, thus providing a strong positive feedback to climate change in the region.
In view of the above, we have performed a scenario analysis to understand the potential impact of the warming temperature and consequent permafrost thaw leading to landscape change favoring wetland formation on the one hand and their expansion, on the other.Figure 7 (top panel) shows the annual CH 4 flux of the different methane emitting land cover types in the studied area.We assume here that the thawing of permafrost will primarily affect lowland ecosystem types, leading to relatively dry organic rich tundra bogs and palsas being converted into wet organic rich willows, fens and

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Full lakes, or the drainage of lakes leading to bog/fen type peatland formations.As stated above, we do not expect that the existing wetlands will dry out due to the high water buffer capacity of these sites.As we have performed plot scale measurements from all land cover types relevant from CH 4 exchange point of view, we have the unique opportunity to evaluate the effect of such potential landscape changes on future CH 4 emissions.As indicated in Fig. 7 (bottom panel), a 10 % change from the main drier land cover types to a combination of willows, fens and lakes would result in a 51 % increase in the annual CH 4 flux, in addition to the direct effect of temperature.Similar observations have been reported for northern Scandinavia (Johansson et al., 2006), where widespread permafrost thawing leading to wider distribution of wet peatlands with high CH 4 emissions has been observed (Åkerman and Johansson, 2008;Christiansen et al., 2010) over the last 20 years.Likewise, a decrease in the wet ecosystem types owing to drainage would result in a dramatic decrease in CH 4 emissions from this part of the Russian tundra.This may be an unlikely scenario for our site, as argued above, but not for sites where non-floating wetland types dominate, and where water table draw down is expected be more pronounced as a result of temperature increase.
Changes in permafrost distribution are likely to change water table level, as discussed above, but a further and more detailed modeling of the effects will be needed to add credibility to the CH 4 scenarios for the tundra.

Concluding remarks
Arctic tundra ecosystems are among the world's fastest warming biomes.These ecosystems, underlain by permafrost, are extremely vulnerable to the impacts of anthropogenic climate change.They have been a huge store for organic C since last glaciation in the area.The current warming arctic trend poses a threat to these ecosystems as their soil temperature is likely to rise above 0 • C leading subsequently to the thawing of the underlying permafrost.While the fact that these ecosystems are fast undergoing changes has been established with a fair degree of certainty based on field Introduction

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Full data, how these ecosystems will respond to the future climate is still uncertain.Therefore, with a view to understanding the future ecosystem responses better, regional studies aiming at a proper characterization of the atmosphere-biosphere greenhouse gas (GHG) exchange in the Arctic have been launched.To that end, the work presented in this paper serves to provide the much needed seasonal and annual methane flux estimates from the northwest Russian Siberia, a region not yet well represented in the Arctic studies.Flux data on other GHGs (CO 2 and N 2 O) from this study site have already been reported in earlier publications (Repo et al., 2009;Marushchak et al., 2011Marushchak et al., , 2013)).
Owing to the spatially heterogeneous nature of the studied ecosystem (Virtanen and Ek, 2014), this study segregated the site into several major land cover types employing a fine scale land cover classification scheme.Chamber techniques were used to measure CH 4 fluxes during 2007 and 2008 growing seasons from replicate plots on ten different LCTs.These data were useful in charactering the inherent variability in methane CH 4 flux at the studied site.To complement these plot scale measurements, the eddy covariance technique was also used to characterize this ecosystem's CH 4 source strength.Employing empirical modelling and vascular leaf area data, the upscaled plot scale data agreed well with the seasonal CH 4 flux estimates obtained using EC technique.Soil temperature, water table level and leaf area were found to be the major factors controlling CH 4 release to the atmosphere.Growing season δ 13 C-CH 4 isotopic analyses confirmed the active role of plants in transferring methane to the atmosphere.The seasonal/annual estimates reported here were employed to gain an insight into how the regional CH 4 flux would vary in the future with increasing air temperatures, associated permafrost thaw and plausible geomorphological changes in the landscape.Using the HIRHAM-4 RCM climate output, a scenario projecting the  Full

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19 Tg yr −1 ) (McGuire et al., 2012).However, this estimate of the methane source strength is fraught with uncertainty ranging from 8 and 29 Tg yr −1 (McGuire et al., 2012).Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | they were found to emit large amounts of N 2 O to the atmosphere).The willow stands are typically 0.5-1.5 m in height and grow on lowlying areas with water logged soils.The fens are found on littoral areas of thermokarst lakes and on the edges of the frozen peat plateau peatlands.They are mesotrophic and can be divided according to dominant vascular plant into Eriophorum and Carex fens.Sphagnum species dominate the ground layer and form a dense mat floating on Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | comparison with other studies of the Russian arctic tundra, the integrative landscape scale CH 4 emissions found in the present study are relatively low.A seasonal (May-September) emission of 2.4-2.8g CH 4 m −2 as revealed by eddy covariance measurements is less than what has been reported, e.g., for northeastern Siberia by Van Der Molen et al. (2007), who estimated an annual emission of about 4.0 g CH 4 m −2 and by Corradi et al. (2005), who reported an even higher annual emission rate (16 g CH 4 m −2 ).The emissions reported in this study are also lower compared to the work of Jackowicz-Korczyński et al. (2010) in sub-arctic Scandinavia (25 g CH 4 m −2 ).Emission rates similar to the ones reported here were measured during the summer season by Friborg (2003) at a high arctic fen site in NE Greenland.The overall emission of CH 4 from this site seems to be relatively low, owing to a low coverage of high emitting wetlands (less than 20 %).Nevertheless, it is evident from our chamber measurements that the Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | regional CH 4 flux to the end of the 21st century, informs us that a 10 % increase in the area of major methane emitting surfaces would lead to a 51 % increase in the regional CH 4 flux by the end of this century.The "what-if" analysis presented here is based solely on methane flux-temperature relationship observed at this study site.Discussion Paper | Discussion Paper | Discussion Paper | IPCC: Climate Change 2014: Mitigation of Climate Change, Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge, UK and New York, NY, USA, 2014.Jackowicz-Korczyński, M., Christensen, T. R., Bäckstrand, K., Crill, P., Friborg, T., Mastepanov, M., and Ström, L.: Annual cycle of methane emission from a subarctic peatland, Discussion Paper | Discussion Paper | Discussion Paper |

Figure 1 .Figure 2 .Figure 3 .
Figure 1.Land cover classification of the field site employing QuickBird satellite imagery.Eddy tower is indicated by a star, concentric lines drawn around the tower at 100 m intervals represent the EC footprint area.Areal coverage of fen and willow land cover types in different sectors from eddy tower is shown in a table to the right of the figure, zero refers to North.

Figure 4 .Figure 5 .
Figure 4. Correlation between cumulative seasonal CH 4 fluxes with (a) mean vascular LAI, (b) δ 13 C of CH 4 flux recorded in different wetland LCTs during the 2008 growing season.

Table 1 .
Summary of the empirical models used to generate the seasonal CH 4 flux estimates for the different wetland land cover types at the Seida study site.These seasonal estimates are based on chamber fluxes measured during the snowfree period.Models were fitted separately for each measurement plot.