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Title: Genome‐Enabled Parameterization Enhances Model Simulation of CH 4 Cycling in Four Natural Wetlands
Abstract Microbial processes are crucial in producing and oxidizing biological methane (CH4) in natural wetlands. Therefore, modeling methanogenesis and methanotrophy is advantageous for accurately projecting CH4cycling. Utilizing the CLM‐Microbe model, which explicitly represents the growth and death of methanogens and methanotrophs, we demonstrate that genome‐enabled model parameterization improves model performance in four natural wetlands. Compared to the default model parameterization against CH4flux, genomic‐enabled model parameterization added another contain on microbial biomass, notably enhancing the precision of simulated CH4flux. Specifically, the coefficient of determination (R2) increased from 0.45 to 0.74 for Sanjiang Plain, from 0.78 to 0.89 for Changbai Mountain, and from 0.35 to 0.54 for Sallie's Fen, respectively. A drop inR2was observed for the Dajiuhu nature wetland, primarily caused by scatter data points. Theil's coefficient (U) and model efficiency (ME) confirmed the model performance from default parameterization to genome‐enabled model parameterization. Compared with the model solely calibrated to surface CH4flux, additional constraints of functional gene data led to better CH4seasonality; meanwhile, genome‐enabled model parameterization established more robust associations between simulated CH4production rates and environmental factors. Sensitivity analysis underscored the pivotal role of microbial physiology in governing CH4flux. This genome‐enabled model parameterization offers a valuable promise to integrate fast‐cumulating genomic data with CH4models to better understand microbial roles in CH4in the era of climate change.  more » « less
Award ID(s):
2208656 2145130
PAR ID:
10552600
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ; ; ;
Publisher / Repository:
American Geophysical Union
Date Published:
Journal Name:
Journal of Advances in Modeling Earth Systems
Volume:
16
Issue:
10
ISSN:
1942-2466
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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