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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. 

Abstract Carbosulfenylation of olefins represents an important class of reactions for the synthesis of structurally diverse organosulfur compounds. Previous studies typically yield 1,2‐regioselectivity. In the context of diversity‐oriented synthesis, accessing the regioreversed products is desirable, significantly broadening the scope of these reactions. In this study, we report a nickel‐catalyzed 2,1‐carbosulfenylation of trifluoromethyl‐ andgem‐difluoroalkenes, using free thiols and benzyl bromides as sulfur and carbon sources, respectively. The unusual regioselectivity observed is enabled by a “radical sorting” mechanism. The Ni catalyst activates benzyl bromide to generate a benzylic radical that undergoes hydrogen atom transfer (HAT) with the thiol to form a sulfur‐centered radical. The sulfur radical subsequently adds to the fluoroalkenes, resulting in an α‐fluoroalkyl C‐radical. This radical undergoes S_H2 with a Ni–CH₂Ar to form a C(sp³)─C(sp³) bond and quaternary center, ultimately producing valuable fluoroalkyl thioethers. Isotopic labeling experiments corroborate a hydrogen atom transfer (HAT) event within the working mechanism.