Unraveling the depth-dependent causal dynamics of methanogenesis and methanotrophy in a high-latitude fen peatland

The dynamics of methane (CH₄) cycling in high-latitude peatlands through different pathways of methanogenesis and methanotrophy are still poorly understood due to the spatiotemporal complexity of microbial activities and biogeochemical processes. Additionally, long-term in situ measurements within soil columns are limited and associated with large uncertainties in microbial substrates (e.g. dissolved organic carbon, acetate, hydrogen). To better understand CH₄ cycling dynamics, we first applied an advanced biogeochemical model, ecosys, to explicitly simulate methanogenesis, methanotrophy, and CH₄ transport in a high-latitude fen (within the Stordalen Mire, northern Sweden). Next, to explore the vertical heterogeneity in CH₄ cycling, we applied the PCMCI/PCMCI+ causal detection framework with a bootstrap aggregation method to the modeling results, characterizing causal relationships among regulating factors (e.g. temperature, microbial biomass, soil substrate concentrations) through acetoclastic methanogenesis, hydrogenotrophic methanogenesis, and methanotrophy, across three depth intervals (0-10 cm, 10-20 cm, 20-30 cm). Our results indicate that temperature, microbial biomass, and methanogenesis and methanotrophy substrates exhibit significant vertical variations within the soil column. Soil temperature demonstrates strong causal relationships with both biomass and substrate concentrations at the shallower depth (0-10 cm), while these causal relationships decrease significantly at the deeper depth within the two methanogenesis pathways. In contrast, soil substrate concentrations show significantly greater causal relationships with depth, suggesting the substantial influence of substrates on CH₄ cycling. CH₄ production is found to peak in August, while CH₄ oxidation peaks predominantly in October, showing a lag response between production and oxidation. Overall, this research provides important insights into the causal mechanisms modulating CH₄ cycling across different depths, which will improve carbon cycling predictions, and guide the future field measurement strategies.