Shifts in functional traits and interactions patterns of soil methane‐cycling communities following forest‐to‐pasture conversion in the Amazon Basin

Abstract

Deforestation threatens the integrity of the Amazon biome and the ecosystem services it provides, including greenhouse gas mitigation. Forest-to-pasture conversion has been shown to alter the flux of methane gas (CH4) in Amazonian soils, driving a switch from acting as a sink to a source of atmospheric CH4. This study aimed to better understand this phenomenon by investigating soil microbial metagenomes, focusing on the taxonomic and functional structure of methane-cycling communities. Metagenomic data from forest and pasture soils were combined with in situ CH4 fluxes and soil edaphic factors measurements and analysed using multivariate statistical approaches. We found a significantly higher abundance and diversity of methanogens in pasture soils. As inferred by co-occurrence networks, these microorganisms seem to be less interconnected within the soil microbiota in pasture soils.Metabolic traits were also different between land uses, with increased hydrogenotrophic and methylotrophic pathways of methanogenesis in pasture soils. Land-use change also induced shifts in taxonomic and functional traits of methanotrophs, with bacteria harboring genes encoding the soluble form of methane monooxygenase enzyme (sMMO) depleted in pasture soils. Redundancy analysis and multimodel inference revealed that the shift in methanecycling communities was associated with high pH, organic matter, soil porosity, and micronutrients in pasture soils. These results comprehensively characterize the effect of forest-to-pasture conversion on the microbial communities driving the methane-cycling microorganisms in the Amazon rainforest, which will contribute to the efforts to preserve this important biome.

Differential structure and function of phosphorus‐mineralizing microbial communities in organic and upper mineral soil horizons across a temperate rainforest chronosequence

“…The network properties (i.e., eigenvector centrality, number of modules, clustering coefficient, degree, and edges) were evaluated to detect differences in the topology and strength of the networks. In particular, eigenvector centrality was used in combination with the centre log ratio as described in Obregon Alvarez et al (2023) to select hub taxa or keystone taxa in both the organic and mineral soils. Network metrics and visualization were performed in Gephi (version 0.9.2) (Bastian et al, 2009).…”

Methane-cycling microbial communities from Amazon floodplains and upland forests respond differently to simulated climate change scenarios

“…However, the nature and extent of these influences may be driven by an intricate interplay of environmental factors [ 30 , 69 , 72 ]. Several studies have investigated the role of CH 4 -related microbial communities in Amazonian floodplains and upland soils [ 2 , 5 , 25 , 57 , 82 ]. For instance, Venturini et al [ 82 ] found that an increase in soil moisture led to changes in the CH 4 -related microbial communities and increased CH 4 emissions in Amazonian soils.…”

Methanogen–methanotroph community has a more consistent and integrated structure in rice rhizosphere than in bulk soil and rhizoplane

“…Previous studies have primarily investigated the cooccurrence patterns of either methanogens (Zhang, Jiao, et al, 2018) or methanotrophs (Ho et al, 2016), respectively, rarely as a combined network. Li, Hambright, et al (2021) had studied the interactions between methanogens and methanotrophs in the lake system, and Alvarez et al (2023) focused on the land use change effects on methane-cycling microbes in forest-to-pasture ecosystems. Although there have been discussions on the co-occurrence links between these two groups among environmental gradients (Obregon et al, 2023) and seasonal changes (Wang et al, 2022) in agriculture systems and also in rice fields (Wang et al, 2023), there has not been a concerted effort to explore the spatial disparities of linkage among soil compartments between the methanogen and methanotroph communities in paddy fields and how this linkage varies along environmental gradients.…”