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DOI	10.1038/s41467-021-22452-1
	Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions
	Chang K.-Y.; Riley W.J.; Knox S.H.; Jackson R.B.; McNicol G.; Poulter B.; Aurela M.; Baldocchi D.; Bansal S.; Bohrer G.; Campbell D.I.; Cescatti A.; Chu H.; Delwiche K.B.; Desai A.R.; Euskirchen E.; Friborg T.; Goeckede M.; Helbig M.; Hemes K.S.; Hirano T.; Iwata H.; Kang M.; Keenan T.; Krauss K.W.; Lohila A.; Mammarella I.; Mitra B.; Miyata A.; Nilsson M.B.; Noormets A.; Oechel W.C.; Papale D.; Peichl M.; Reba M.L.; Rinne J.; Runkle B.R.K.; Ryu Y.; Sachs T.; Schäfer K.V.R.; Schmid H.P.; Shurpali N.; Sonnentag O.; Tang A.C.I.; Torn M.S.; Trotta C.; Tuittila E.-S.; Ueyama M.; Vargas R.; Vesala T.; Windham-Myers L.; Zhang Z.; Zona D.
发表日期	2021
ISSN	2041-1723
卷号	12 期号:1
英文摘要	Wetland methane (CH4) emissions (FCH4) are important in global carbon budgets and climate change assessments. Currently, FCH4 projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent FCH4 temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that FCH4 are often controlled by factors beyond temperature. Here, we evaluate the relationship between FCH4 and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between FCH4 and temperature, suggesting larger FCH4 sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments. © 2021, The Author(s).
语种	英语
scopus关键词	carbon budget; climate change; database; global change; hysteresis; machine learning; meta-analysis; methane; parameterization; sensitivity analysis; temperature effect; wetland; article; budget; human; hysteresis; machine learning; meta analysis; season; temperature dependence; temperature sensitivity; wetland
来源期刊	Nature Communications
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/251471
作者单位	Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States; Department of Geography, The University of British Columbia, Vancouver, BC, Canada; Department of Earth System Science, Stanford University, Stanford, CA, United States; Woods Institute for the Environment and Precourt Institute for Energy, Stanford, CA, United States; NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD, United States; Finnish Meteorological Institute, Helsinki, Finland; Department of Environmental Science, Policy & Management, UC Berkeley, Berkeley, CA, United States; U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND, United States; Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH, United States; School of Science, University of Waikato, Hamilton, New Zealand; European Commission, Joint Research Centre (JRC), Ispra, Italy; Department of Atmospheric and Oceanic Sciences, U...
推荐引用方式 GB/T 7714	Chang K.-Y.,Riley W.J.,Knox S.H.,et al. Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions[J],2021,12(1).
APA	Chang K.-Y..,Riley W.J..,Knox S.H..,Jackson R.B..,McNicol G..,...&Zona D..(2021).Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions.Nature Communications,12(1).
MLA	Chang K.-Y.,et al."Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions".Nature Communications 12.1(2021).