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Current estimates of wetland contributions to the global methane budget carry high uncertainty, particularly in accurately predicting emissions from high methane-emitting wetlands. Microorganisms mediate methane cycling, yet knowledge of their conservation across wetlands remains scarce. To address this, we integrated 1,118 16S rRNA amplicon datasets (116 new), 305 metagenomes (20 new) that yielded 4,745 medium and high-quality metagenome assembled genomes (MAGs; 617 new), 133 metatranscriptomes, and annual methane flux data across 9 wetlands to create the Multi-Omics for Understanding Climate Change (MUCC) v2.0.0 database. This new resource was leveraged to link microbiome compositional profiles to encoded functions and emissions, with specific focus on methane-cycling populations and the microbial carbon decomposition networks that fuel them. We identified eight methane-cycling genera that were conserved across wetlands, and deciphered wetland specific metabolic interactions across marshes, revealing low methanogen-methanotroph connectivity in high-emitting wetlands. Methanoregula emerged as a hub methanogen across networks and was a strong predictor of methane flux, demonstrating the potential broad relevance of methylotrophic methanogenesis in these ecosystems. Collectively, our findings illuminate trends between microbial decomposition networks and methane flux and provide an extensive publicly available database to advance future wetland research.