DOE OSTI · 3386572
Multi‐Decadal Dynamics of Wetland Methane Emissions Revealed by Knowledge‐Guided Machine Learning
Abstract
Measurement of methane fluxes (FCH 4 ) from natural systems, such as wetlands, has lagged far behind carbon dioxide fluxes. Short and fragmented wetland FCH 4 data limit our ability to assess its long-term dynamics and potential climate feedbacks. Extrapolating short-term FCH 4 records to recent decades remains challenging for both process-based models and data-driven machine learning (ML) approaches. Here, we develop a knowledge-guided ML framework that integrates eddy covariance (EC) FCH 4 observations, field warming experiments, and biogeochemical knowledge to reconstruct the long-term FCH 4 budgets and trends. Focusing on the 11 longest EC monitoring sites in the AmeriFlux network, we found considerable variability in multi-decadal trends of wetland FCH 4 , with increases up to 14% per decade from 2000 to 2024. We also found that the strength of these increasing trends declines from high to low latitudes, highlighting the vulnerability of northern wetlands. This work presents novel and robust reconstructions of long-term wetland FCH 4 , offering critical benchmark datasets for bottom-up ecosystem models and advancing fundamental understanding of wetland biogeochemistry.
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Zhu, Qing [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:000000032441944X), Arndt, Kyle A. [Woodwell Climate Research Center, Falmouth, MA (United States)], Yuan, Kunxiaojia [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Univ. of Houston, TX (United States)], Li, Fa [Stanford Univ., CA (United States); Univ. of Texas, Austin, TX (United States)], Ying, Qing [Univ. of Maryland, College Park, MD (United States); NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)], Liu, Licheng [Univ. of Minnesota, Minneapolis, WI (United States); Univ. of Wisconsin, Madison, WI (United States)] (ORCID:0000000296491056), Ward, Eric [Univ. of Maryland, College Park, MD (United States); NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)], Malhotra, Avni [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000278506402), Zheng, Jianqiu [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000216099004), Yuan, Fenghui [Univ. of Minnesota, Minneapolis, MN (United States)] (ORCID:000000031004873X), Malone, Sparkle L. [Yale Univ., New Haven, CT (United States)] (ORCID:0000000190341076), McNicol, Gavin [Univ. of Illinois, Chicago, IL (United States)], Knox, Sara H. [McGill Univ., Montreal, QC (Canada)], Riley, William J. [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Torn, Margaret S. [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000281740099), Chen, Shuo [Purdue Univ., West Lafayette, IN (United States)], Riddell‐Young, Ben [Univ. of Colorado, Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences (CIRES); National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Global Monitoring Laboratory (GML)], Oh, Youmi [Univ. of Colorado, Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences (CIRES); National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Global Monitoring Laboratory (GML)], Bruhwiler, Lori [National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Global Monitoring Laboratory (GML)]. 2026-05-14. Multi‐Decadal Dynamics of Wetland Methane Emissions Revealed by Knowledge‐Guided Machine Learning. https://doi.org/10.1111/gcb.70899
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