气候变化领域集成服务门户(CCPortal): Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling

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DOI	10.1088/1748-9326/ab4d32
	Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling
	Reuss-Schmidt K.; Levy P.; Oechel W.; Tweedie C.; Wilson C.; Zona D.
发表日期	2019
ISSN	17489318
卷号	14 期号:12
英文摘要	The Arctic is warming at twice the rate of the global mean. This warming could further stimulate methane (CH4) emissions from northern wetlands and enhance the greenhouse impact of this region. Arctic wetlands are extremely heterogeneous in terms of geochemistry, vegetation, microtopography, and hydrology, and therefore CH4 fluxes can differ dramatically within the metre scale. Eddy covariance (EC) is one of the most useful methods for estimating CH4 fluxes in remote areas over long periods of time. However, when the areas sampled by these EC towers (i.e. tower footprints) are by definition very heterogeneous, due to encompassing a variety of environmental conditions and vegetation types, modelling environmental controls of CH4 emissions becomes even more challenging, confounding efforts to reduce uncertainty in baseline CH4 emissions from these landscapes. In this study, we evaluated the effect of footprint variability on CH4 fluxes from two EC towers located in wetlands on the North Slope of Alaska. The local domain of each of these sites contains well developed polygonal tundra as well as a drained thermokarst lake basin. We found that the spatiotemporal variability of the footprint, has a significant influence on the observed CH4 fluxes, contributing between 3% and 33% of the variance, depending on site, time period, and modelling method. Multiple indices were used to define spatial heterogeneity, and their explanatory power varied depending on site and season. Overall, the normalised difference water index had the most consistent explanatory power on CH4 fluxes, though generally only when used in concert with at least one other spatial index. The spatial bias (defined here as the difference between the mean for the 0.36 km2 domain around the tower and the footprint-weighted mean) was between \|51\|% and \|18\|% depending on the index. This study highlights the need for footprint modelling to infer the representativeness of the carbon fluxes measured by EC towers in these highly heterogeneous tundra ecosystems, and the need to evaluate spatial variability when upscaling EC site-level data to a larger domain. © 2019 The Author(s). Published by IOP Publishing Ltd.
语种	英语
scopus关键词	Methane; Towers; Vegetation; Wetlands; Environmental conditions; Environmental control; Explanatory power; Greenhouse impact; North Slope of Alaska; Spatial heterogeneity; Spatial variability; Spatiotemporal variability; Uncertainty analysis; ecosystem service; footprint; methane; spatial variation; thermokarst; tundra; upscaling; vegetation type; wetland; Alaska; Arctic; North Slope; United States
来源期刊	Environmental Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/154260
作者单位	Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield, S10 2TN, United Kingdom; Global Change Research Group, Dept. Biology, San Diego State University, San Diego, CA 92182, United States; Centre for Ecology and Hydrology Bush Estate, Edinburgh, EH10, United Kingdom; Department of Biological Sciences, University of Texas, El Paso, TX 79968, United States; Los Alamos National Lab, Po Box 1663, Los Alamos, NM 87545, United States; Department of Geography, University of Exeter, Exeter, EX4 4RJ, United Kingdom
推荐引用方式 GB/T 7714	Reuss-Schmidt K.,Levy P.,Oechel W.,et al. Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling[J],2019,14(12).
APA	Reuss-Schmidt K.,Levy P.,Oechel W.,Tweedie C.,Wilson C.,&Zona D..(2019).Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling.Environmental Research Letters,14(12).
MLA	Reuss-Schmidt K.,et al."Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling".Environmental Research Letters 14.12(2019).