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Vegetation Type Dominates the Spatial Variability in CH4 Emissions Across Multiple Arctic Tundra Landscapes

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Vegetation Type Dominates the Spatial Variability in CH4 Emissions Across Multiple Arctic Tundra Landscapes Ecosystems (2016) 19: 1116–1132 DOI: 10.1007/s10021-016-9991-0 Ó 2016 The Author(s). This article is published with open access at Springerlink.com Vegetation Type Dominates the Spatial Variability in CH4 Emissions Across Multiple Arctic Tundra Landscapes Scott J. Davidson,1,2* Victoria L. Sloan,2 Gareth K. Phoenix,1 Robert Wagner,2 James P. Fisher,1 Walter C. Oechel,2,3 and Donatella Zona1,2 1Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield, South Yorkshire S10 2TN, UK; 2Global Change Research Group and Department of Biology, San Diego State University, San Diego, California 92182, USA; 3Department of Environment, Earth and Ecosystems, The Open University, Walton Hall, Milton Keynes MK7 6AA, UK ABSTRACT Methane (CH4) emissions from Arctic tundra are to identify drivers of CH4 flux, and to examine an important feedback to global climate. Cur- relationships between gross primary productivity rently, modelling and predicting CH4 fluxes at (GPP), dissolved organic carbon (DOC) and CH4 broader scales are limited by the challenge of fluxes. We found that a highly simplified vegeta- upscaling plot-scale measurements in spatially tion classification consisting of just three vegeta- heterogeneous landscapes, and by uncertainties tion types (wet sedge, tussock sedge and other) regarding key controls of CH4 emissions. In this explained 54% of the variation in CH4 fluxes study, CH4 and CO2 fluxes were measured to- across the entire transect, performing almost as gether with a range of environmental variables well as a more complex model including water and detailed vegetation analysis at four sites table, sedge height and soil moisture (explaining spanning 300 km latitude from Barrow to Ivotuk 58% of the variation in CH4 fluxes). Substantial (Alaska). We used multiple regression modelling CH4 emissions were recorded from tussock sedges in locations even when the water table was lower than 40 cm below the surface, demonstrating the importance of plant-mediated transport. We also found no relationship between instantaneous GPP and CH4 fluxes, suggesting that models should be cautious in assuming a direct relationship between primary production and CH4 emissions. Our findings demonstrate the importance of vegetation as an integrator of processes controlling CH4 Received 9 January 2016; accepted 24 March 2016; emissions in Arctic ecosystems, and provide a published online 31 May 2016 simplified framework for upscaling plot scale CH Electronic supplementary material: The online version of this article 4 (doi:10.1007/s10021-016-9991-0) contains supplementary material, flux measurements from Arctic ecosystems. which is available to authorized users. Author contribution DZ, WCO, and GKP secured the funding, DZ, Key words: climate change; methane emissions; WCO, GKP, SJD, and VLS designed the study, SJD and VLS performed the research, SJD and VLS analysed the data with input from DZ and GKP, arctic vegetation; plant mediated CH4 transport; RW collected and analysed the DOC data, JPF helped with statistical gross primary productivity; spatial chambers; sed- analyses, SJD, VLS, GKP, WCO and DZ wrote the paper. ges; arctic tundra. *Corresponding author; e-mail: sjdavidson1@sheffield.ac.uk 1116 Ecological Controls on Arctic Tundra CH4 Fluxes 1117 INTRODUCTION tion of CH4 fluxes from assessment of vegetation cover instead of measuring multiple environmental The Arctic is warming at nearly double the global rate variables. However, many studies to date which have (IPCC 2013). A temperature increase of approxi- examined the vegetation and environmental controls mately 6°C is predicted by the end of the twenty-first on CH4 fluxes in northern ecosystems are focused on century in northern high latitudes (IPCC 2013), single sites or vegetation types (Christensen and leading to major changes in hydrological and thermal others 2003, 2004;Zonaandothers2009;Olivasand regimes, which in turn will heavily influence the others 2010). Thus, further assessment of the con- direction and magnitude of the Arctic carbon (C) sistency of relationships between vegetation, envi- balance (Oechel and others 2000; Chapin and others ronmental controls and CH4 fluxes across multiple 2005). One of the greatest concerns is the potential for tundra ecosystem types is still lacking (Fox and others increases in methane (CH4) emissions from tundra 2008; Sachs and others 2010). ecosystems to the atmosphere. Arctic tundra ecosys- In particular, improved understanding of rela- tems currently account for approximately 8–30 Tg -1 tionships between gross primary productivity CH4 y released to the atmosphere (Christensen (GPP), above-ground plant community cover and 1993; McGuire and others 2012; Olefeldt and others CH4 fluxes is important for modelling future CH4 2013). For context, global emission rate from both emissions. Plants provide the substrate for natural and anthropogenic sources is approximately -1 methanogenesis through transfer of labile C to the 500–600 Tg CH4 y (Dlugokencky and others 2011). rhizosphere, and thus many climate models assume As CH4 has 28.5 times the global warming potential of an increase in plant productivity in arctic tundra carbon dioxide (CO2) over 100 years (IPCC 2013), wetlands will result in higher CH4 emissions increased emissions are an important positive feed- (Melton and others 2013). However, GPP and CH4 back from the arctic region to global climate (Forster fluxes are very rarely measured at the same time and others 2007;IPCC2013), further warming the across a variety of tundra ecosystems, meaning the climate system, leading to permafrost degradation validity of this assumption has yet to be tested and therefore increased emissions. across multiple tundra sites. In addition to provid- To reduce uncertainties in predicting future cli- ing substrate, plants such as sedges enable the mate, an improvement in modelling of CH4 emis- transport of CH4 from anoxic zones of production sions is urgently required (Matthews and Fung 1987; (methanogenesis) to the atmosphere, bypassing Petrescu and others 2010; Bohn and others 2015). oxic zones where CH4 consumption (methanotro- Currently, many carbon cycle models disagree on phy) may occur (Torn and Chapin 1993; Bubier the response of CH4 fluxes to climate change (Mel- 1995; Bubier and others 1995; King and others ton and others 2013; Bohn and others 2015). Despite 1998; Stro¨ m and others 2003; McEwing and others many empirical studies in the Arctic, the controls on 2015). This capacity to facilitate transport can differ CH4 fluxes remain uncertain, most notably for large widely between plant species or growth forms and heterogeneous tundra ecosystems. Substantial (Koelbener and others 2010; Dorodnikov and variation in CH4 flux has been observed even over others 2011), and the relative importance of sub- distances of just a few meters (Kutzbach and others strate limitation and plant transport are not well 2004; Olivas and others 2010; Kade and others established (Schimel 1995; Joabsson and Chris- 2012), making predictions of CH4 fluxes from these tensen 2001; King and others 2002). A strong landscapes particularly challenging. Previous studies relationship between CH4 fluxes and DOC may have identified important environmental controls indicate supply limitation rather than transport- on the spatial heterogeneity of CH4 fluxes as water limitation of ecosystem CH4 fluxes (Neff and Hoo- table height, active layer thaw depth, soil moisture per 2002), and thus inform the conceptual ap- and soil temperature (Zona and others 2009; proach to modelling these ecosystems. Sturtevant and others 2012; Zona and others 2016). To address these issues, we measured CH4 fluxes Vegetation also plays an important role, as it pro- in contrasting micro-topographic positions in mul- vides substrate for methanogenesis and increases tiple Arctic vegetation types in four sites spanning a CH4 transport and atmospheric emissions (Whiting 300 km latitudinal gradient in northern Alaska, and Chanton 1993; King and others 2002; Bridgham and investigated the vegetation and environmental and others 2013). controls of these fluxes. Because vegetation type is a product of many This study provides critical advances on the work environmental variables that also control CH4 emis- undertaken by McEwing and others (2015) using sions, vegetation type itself may be a good integrator the same field sites. Our investigations present a of conditions controlling CH4 flux, allowing predic- 1118 S. J. Davidson and others more extensive analysis of the vegetation com- surface, with a soil organic matter (SOM) depth of munities present, a wider range of environmental between 0 and more than 30 cm. and vegetation variables, and a much larger sample Atqasuk is located approximately 100 km south size than the McEwing and others 2015 study. of Barrow with well-developed, low-centred, ice- We hypothesised that (i) the dominant overall wedge polygons with well-drained rims (Ko- control on CH4 fluxes is water table depth across markova and Webber 1980; Oechel and others different vegetation types, (ii) when the water 2014). The vegetation consists mainly of wet sedge- table is below the surface, the most important moss communities and, unlike Barrow, has moist controls are the presence of sedges, and (iii) vege- shrub and tussock sedge communities on higher tation type will be a good predictor of CH4 fluxes microsites (Raynolds and others 2005). Soils are across arctic tundra, despite variation in environ- approximately 95% sand and 5% clay and silt to a
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