Constraints on microbial communities, decomposition and methane production in deep peat deposits

Abstract

Peatlands play outsized roles in the global carbon cycle. Despite occupying a rather small fraction of the terrestrial biosphere (~3%), these ecosystems account for roughly one third of the global soil carbon pool. This carbon is largely comprised of undecomposed deposits of plant material (peat) that may be meters thick. The fate of this deep carbon stockpile with ongoing and future climate change is thus of great interest and has large potential to induce positive feedback to climate warming. Recent in situ warming of an ombrotrophic peatland indicated that the deep peat microbial communities and decomposition rates were resistant to elevated temperatures. In this experiment, we sought to understand how nutrient and pH limitations may interact with temperature to limit microbial activity and community composition. Anaerobic microcosms of peat collected from 1.5 to 2 meters in depth were incubated at 6°C and 15°C with elevated pH, nitrogen (NH4Cl), and/or phosphorus (KH2PO4) in a full factorial design. The production of CO2 and CH4 was significantly greater in microcosms incubated at 15°C, although the structure of the microbial community did not differ between the two temperatures. Increasing the pH from ~3.5 to ~5.5 altered microbial community structure, however increases in CH4 production were non-significant. Contrary to expectations, N and P additions did not increase CO2 and CH4 production, indicating that nutrient availability was not a primary constraint in microbial decomposition of deep peat. Our findings indicate that temperature is a key factor limiting the decomposition of deep peat, however other factors such as the availability of O2 or alternative electron donors and high concentrations of phenolic compounds, may also exert constraints. Continued experimental peat warming studies will be necessary to assess if the deep peat carbon bank is susceptible to increased temperatures over the longer time scales.