Here, we report the metagenomes from two Amazonian floodplain sediments in eastern Brazil. Tropical wetlands are well known for their role in the global carbon cycle. Microbial information on this diversified and dynamic landscape will provide further insights into its significance in regional and global biogeochemical cycles.

The Amazonian floodplain forests are dynamic ecosystems of great importance for the regional hydrological and biogeochemical cycles and function as a significant CH₄ source contributing to the global carbon balance. Unique geochemical factors may drive the microbial community composition and, consequently, affect CH₄ emissions across floodplain areas. Here, we report the in situ composition of CH₄ cycling microbial communities in Amazonian floodplain sediments. We considered how abiotic factors may affect the microbial community composition and, more specifically, CH₄ cycling groups. We collected sediment samples during wet and dry seasons from three different types of floodplain forests, along with upland forest soil samples, from the Eastern Amazon, Brazil. We used high-resolution sequencing of archaeal and bacterial 16S rRNA genes combined with real-time PCR to quantify Archaea and Bacteria, as well as key functional genes indicative of the presence of methanogenic (mcrA) and methanotrophic (pmoA) microorganisms. Methanogens were found to be present in high abundance in floodplain sediments, and they seem to resist the dramatic environmental changes between flooded and nonflooded conditions. Methanotrophs known to use different pathways to oxidise CH₄ were detected, including anaerobic archaeal and bacterial taxa, indicating that a wide metabolic diversity may be harboured in this highly variable environment. The floodplain environmental variability, which is affected by the river origin, drives not only the sediment chemistry but also the composition of the microbial communities. These environmental changes seem also to affect the pools of methanotrophs occupying distinct niches. Understanding these shifts in the methanotrophic communities could improve our comprehension of the CH₄ emissions in the region.

Climatic changes are altering precipitation patterns in the Amazon and may influence soil methane (CH₄) fluxes due to the differential responses of methanogenic and methanotrophic microorganisms. However, it remains unclear if these climate feedbacks can amplify land-use-related impacts on the CH₄ cycle. To better predict the responses of soil CH₄-cycling microorganisms and emissions under altered moisture levels in the Eastern Brazilian Amazon, we performed a 30-day microcosm experiment manipulating the moisture content (original moisture; 60%, 80%, and 100% of field capacity - FC) of forest and pasture soils. Gas samples were collected periodically for gas chromatography analysis, and methanogenic archaeal and methanotrophic bacterial communities were assessed using quantitative PCR and metagenomics. Positive and negative daily CH₄ fluxes were observed for forest and pasture, indicating that these soils can act as both CH₄ sources and sinks. Cumulative emissions and the abundance of methanogenesis-related genes and taxonomic groups were affected by land use, moisture, and their interaction. Pasture soils at 100% FC had the highest abundance of methanogens and CH₄ emissions, 22 times higher than forest soils under the same treatment. Higher ratios of methanogens to methanotrophs were found in pasture than in forest soils, even at field capacity conditions. Land use and moisture were significant factors influencing the composition of methanogenic and methanotrophic communities. The diversity and evenness of methanogens did not change throughout the experiment. In contrast, methanotrophs exhibited the highest diversity and evenness in pasture soils at 100% FC. Taken together, our results suggest that increased moisture exacerbates soil CH₄ emissions and microbial responses driven by land-use change in the Amazon. This is the first report on the microbial CH₄ cycle in Amazonian upland soils that combined one-month gas measurements with advanced molecular methods.