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Emerging multiscale insights on microbial carbon use efficiency in the land carbon cycle.

Xianjin HeElsa AbsSteven D AllisonFeng TaoYuanyuan HuangStefano ManzoniRose Z AbramoffElisa BruniSimon P K BowringArjun ChakrawalPhilippe CiaisLars ElsgaardPierre FriedlingsteinKaterina GeorgiouGustaf HugeliusLasse Busk HolmWei LiYiqi LuoGaëlle MarmasseNaoise NunanChunjing QiuStephen SitchYing-Ping WangDaniel S Goll
Published in: Nature communications (2024)
Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial ecosystems, but its global importance remains uncertain. Accurately modeling and predicting CUE on a global scale is challenging due to inconsistencies in measurement techniques and the complex interactions of climatic, edaphic, and biological factors across scales. The link between microbial CUE and soil organic carbon relies on the stabilization of microbial necromass within soil aggregates or its association with minerals, necessitating an integration of microbial and stabilization processes in modeling approaches. In this perspective, we propose a comprehensive framework that integrates diverse data sources, ranging from genomic information to traditional soil carbon assessments, to refine carbon cycle models by incorporating variations in CUE, thereby enhancing our understanding of the microbial contribution to carbon cycling.
Keyphrases
  • microbial community
  • climate change
  • gene expression
  • machine learning
  • drinking water
  • health information
  • deep learning
  • high intensity
  • genome wide