Shifts in functional traits and interactions patterns of soil methane-cycling communities following forest-to-pasture conversion in the Amazon Basin.
Dasiel Obregón AlvarezLeandro Fonseca de SouzaLucas William MendesMoacir Tuzzin de MoraesMicaela TosiAndressa Monteiro VenturiniKyle M MeyerPlinio Barbosa de CamargoBrendan J M BohannanJorge Luiz Mazza RodriguesKari E DunfieldSiu Mui TsaiPublished in: Molecular ecology (2023)
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 (CH 4 ) in Amazonian soils, driving a switch from acting as a sink to a source of atmospheric CH 4 . 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 measurements of in situ CH 4 fluxes and soil edaphic factors 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 harbouring genes encoding the soluble form of methane monooxygenase enzyme (sMMO) depleted in pasture soils. Redundancy analysis and multimodel inference revealed that the shift in methane-cycling 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.
Keyphrases
- climate change
- heavy metals
- organic matter
- human health
- dairy cows
- anaerobic digestion
- carbon dioxide
- risk assessment
- genome wide
- high intensity
- antibiotic resistance genes
- room temperature
- healthcare
- machine learning
- microbial community
- endothelial cells
- big data
- single cell
- dna methylation
- high glucose
- diabetic rats
- stress induced
- data analysis
- bioinformatics analysis