4.7 Article

The stoichiometry of soil microbial biomass determines metabolic quotient of nitrogen mineralization

期刊

ENVIRONMENTAL RESEARCH LETTERS
卷 15, 期 3, 页码 -

出版社

IOP PUBLISHING LTD
DOI: 10.1088/1748-9326/ab6a26

关键词

dominant driver; global warming; metabolic quotient; natural ecosystems; nitrogen cycling; stoichiometry of microbial biomass

资金

  1. National Natural Science Foundation of China [31988102, 31625006]
  2. CAS international collaboration program [131A11KYSB20180010]
  3. Postdoctoral Science Foundation of China [2018M641459]

向作者/读者索取更多资源

Soil nitrogen (N) mineralization is crucial for the sustainability of available soil N and hence ecosystem productivity and functioning. Metabolic quotient of N mineralization (Q(min)), which is defined as net soil N mineralization per unit of soil microbial biomass N, reflects the efficiency of soil N mineralization. However, it is far from clear how soil Q(min) changes and what are the controlling factors at the global scale. We compiled 871 observations of soil Q(min) from 79 published articles across terrestrial ecosystems (croplands, forests, grasslands, and wetlands) to elucidate the global variation of soil Q(min) and its predictors. Soil Q(min) decreased from the equator to two poles, which was significant in the North Hemisphere. Soil Q(min) correlated negatively with soil pH, total soil N, the ratio of soil carbon (C) to N, and soil microbial biomass C, and positively with mean annual temperature and C:N ratio of soil microbial biomass at a global scale. Soil microbial biomass, climate, and soil physical and chemical properties in combination accounted for 41% of the total variations of global soil Q(min). Among those predictors, C:N ratio of soil microbial biomass was the most important factor contributing to the variations of soil Q(min) (the standardized coefficient = 0.39) within or across ecosystem types. This study emphasizes the critical role of microbial stoichiometry in soil N cycling, and suggests the necessity of incorporating soil Q(min) into Earth system models to better predict N cycling under environmental change.

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