Distinct Microbiomes Underlie Divergent Responses of Methane Emissions from Diverse Wetland soils to Oxygen Shifts
Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
The effects of hydrological shifts on wetlands, a globally important source of methane (CH 4 ), are critical to constraining global CH 4 emissions. Wetland CH 4 emissions are uncertain due to a limited understanding of how hydrologically driven oxygen (O 2 ) variability affects microbial CH 4 cycling. Transient O 2 exposure has been shown to significantly stimulate anoxic CH 4 production in Sphagnum peat from a temperate bog by enriching for polyphenol oxidizers and polysaccharide degraders, enhancing substrate flow toward methanogenesis under subsequent anoxic conditions. To assess whether key structural shifts in soil microbiome operate similarly across wetland types, here we examined the sensitivity of different wetland soils to transient oxygenation. In slurry incubations of Sphagnum peat from a minerotrophic fen, and sediments from a freshwater marsh and saltmarsh, we examined temporal shifts in microbiomes using 16S rRNA gene profiling, metagenomics, and metatranscriptomics, coupled with geochemical characterization of the slurries and incubation headspaces (GC-TCD, FTIR, etc.). Oxygenation did not affect anoxic CH 4 emissions from fen-origin peat and freshwater marsh sediments, nor the microbiome structure. Key taxa linked to O 2 -stimulated CH 4 emissions in the bog-origin peat were notably rare in the fen-origin peat, supporting microbiome structure as a primary determinant of wetland response to O 2 shifts. In contrast to the freshwater wetlands, saltmarsh geochemistry— particularly pH—and microbiome structure were persistently and significantly altered post-oxygenation, albeit with no significant impact on greenhouse gas emissions. With climate change driving greater O 2 variability in wetlands, our results inform mechanisms of wetland resiliency and highlight microbiome structure as a potential resiliency biomarker.