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Microbial carbon use efficiency promotes global soil carbon storage.

Feng TaoYuanyuan HuangBruce A HungateStefano ManzoniSerita D FreyMichael W I SchmidtMarkus ReichsteinNuno CarvalhaisPhilippe CiaisLifen JiangJohannes LehmannYing-Ping WangBenjamin Z HoultonBernhard AhrensUmakant MishraGustaf HugeliusToby D HockingXingjie LuZheng ShiKostiantyn ViatkinRonald VargasYusuf YiginiChristian OmutoAshish A MalikGuillermo PeraltaRosa Cuevas-CoronaLuciano E Di PaoloIsabel LuottoCuijuan LiaoYi-Shuang LiangVinisa S SaynesXiaomeng HuangYiqi Luo
Published in: Nature (2023)
Soils store more carbon than other terrestrial ecosystems 1,2 . How soil organic carbon (SOC) forms and persists remains uncertain 1,3 , which makes it challenging to understand how it will respond to climatic change 3,4 . It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss 5-7 . Although microorganisms affect the accumulation and loss of soil organic matter through many pathways 4,6,8-11 , microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes 12,13 . Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved 7,14,15 . Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.
Keyphrases
  • microbial community
  • climate change
  • deep learning
  • organic matter
  • human health
  • plant growth
  • risk assessment
  • single cell
  • rna seq
  • data analysis