Water table depth and vegetation are key controls of methane (CH4) emissions from peatlands. Microtopography integrates these factors into features called microforms. Microforms often differ in CH4emissions, but microform‐dependent patterns of belowground CH4cycling remain less clearly resolved. To investigate the impact of microtopography on belowground CH4cycling, we characterized depth profiles of the community composition and activity of CH4‐cycling microbes using 16S rRNA amplicon sequencing, incubations, and measurements of porewater CH4concentration and isotopic composition from hummocks and lawns at Sallie's Fen in NH, USA. Geochemical proxies of methanogenesis and methanotrophy indicated that microforms differ in dominant microbial CH4cycling processes. Hummocks, where water table depth is lower, had higher porewater redox potential (Eh) and higher porewater δ13C‐CH4values in the upper 30 cm than lawns, where water table depth is closer to the peat surface. Porewater δ13C‐CH4and δD‐CH3D values were highest at the surface of hummocks where the ratio of methanotrophs to methanogens was also greatest. These results suggest that belowground CH4cycling in hummocks is more strongly regulated by methanotrophy, while in lawns methanogenesis is more dominant. We also investigated controls of porewater CH4chemistry. The ratio of the relative abundance of methanotrophs to methanogens was the strongest predictor of porewater CH4concentration and δ13C‐CH4, while vegetation composition had minimal influence. As microbial community composition was strongly influenced by redox conditions but not vegetation, we conclude that water table depth is a stronger control of belowground CH4cycling across microforms than vegetation.
Belowground ecosystem processes can be highly variable and difficult to predict using microbial community data. Here, we argue that this stems from at least three issues: (a) complex covariance structure of samples (with environmental conditions or spatial proximity) can make distinguishing biotic drivers a challenge; (b) communities can control ecosystem processes through multiple mechanisms, making the identification of these controls a challenge; and (c) ecosystem function assessments can be broad in physiological scale, encapsulating multiple processes with unique microbially mediated controls. We test these assertions using methane (CH4)‐cycling processes in soil samples collected along a wetland‐to‐upland habitat gradient in the Congo Basin. We perform our measurements of function under controlled laboratory conditions and statistically control for environmental covariates to aid in identifying biotic drivers. We divide measurements of microbial communities into four attributes (abundance, activity, composition, and diversity) that represent different forms of community control. Lastly, our process measurements differ in physiological scale, including broader processes (gross methanogenesis and methanotrophy) that involve more mediating groups, to finer processes (hydrogenotrophic methanogenesis and high‐affinity CH4oxidation) with fewer mediating groups. We observed that finer scale processes can be more readily predicted from microbial community structure than broader scale processes. In addition, the nature of those relationships differed, with broad processes limited by abundance while fine‐scale processes were associated with diversity and composition. These findings demonstrate the importance of carefully defining the physiological scale of ecosystem function and performing community measurements that represent the range of possible controls on ecosystem processes.
more » « less- NSF-PAR ID:
- 10457612
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Molecular Ecology
- Volume:
- 29
- Issue:
- 10
- ISSN:
- 0962-1083
- Page Range / eLocation ID:
- p. 1806-1819
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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