Meyer, K.M. and Morris, A.H. and Webster, K. and Klein, A.M. and Kroeger, M.E. and Meredith, L.K. and Brændholt, A. and Nakamura, F. and Venturini, A. and Fonseca de Souza, L. and Shek, K.L. and Danielson, R. and van Haren, J. and Barbosa de Camargo, P. and Tsai, S.M. and Dini-Andreote, F. and de Mauro, J.M.S. and Barlow, J. and Berenguer, E. and Nüsslein, K. and Saleska, S. and Rodrigues, J.L.M. and Bohannan, B.J.M. (2020) Belowground changes to community structure alter methane-cycling dynamics in Amazonia. Environmental International, 145: 106131.
Full text not available from this repository.Abstract
Amazonian rainforest is undergoing increasing rates of deforestation, driven primarily by cattle pasture expansion. Forest-to-pasture conversion has been associated with increases in soil methane (CH4) emission. To better understand the drivers of this change, we measured soil CH4 flux, environmental conditions, and belowground microbial community structure across primary forests, cattle pastures, and secondary forests in two Amazonian regions. We show that pasture soils emit high levels of CH4 (mean: 3454.6 ± 9482.3 μg CH4 m−2 d−1), consistent with previous reports, while forest soils on average emit CH4 at modest rates (mean: 9.8 ± 120.5 μg CH4 m−2 d−1), but often act as CH4 sinks. We report that secondary forest soils tend to consume CH4 (mean: −10.2 ± 35.7 μg CH4 m−2 d−1), demonstrating that pasture CH4 emissions can be reversed. We apply a novel computational approach to identify microbial community attributes associated with flux independent of soil chemistry. While this revealed taxa known to produce or consume CH4 directly (i.e. methanogens and methanotrophs, respectively), the vast majority of identified taxa are not known to cycle CH4. Each land use type had a unique subset of taxa associated with CH4 flux, suggesting that land use change alters CH4 cycling through shifts in microbial community composition. Taken together, we show that microbial composition is crucial for understanding the observed CH4 dynamics and that microorganisms provide explanatory power that cannot be captured by environmental variables.