Global drivers and patterns of microbial abundance in soil. Issue 10 (7th June 2013)

• Record Type: Journal Article
• Authors: Serna‐Chavez, Hector M.; Fierer, Noah; van Bodegom, Peter M.
• Is Part Of: Global ecology & biogeography. Volume 22:Issue 10(2013:Oct.)
• Page Start: 1162
• Page End: 1172
• Publication Date: 2013-06-07
• Subjects: Biogeochemical cycles -- global carbon cycling -- moisture limitation -- nitrogen limitation -- soil microbial abundance -- soil microbial biomass -- soil microbial carbon; Ecology -- Periodicals; Biogeography -- Periodicals; Biodiversity -- Periodicals; Macroevolution -- Periodicals; 577
• DOI: 10.1111/geb.12070
• Languages: English
• ISSNs: 1466-822X

Abstract

Abstract: Aim: While soil microorganisms play key roles in Earth's biogeochemical cycles, methodological constraints and sparse data have hampered our ability to describe and understand the global distribution of soil microbial biomass. Here, we present a comprehensive quantification of the environmental drivers of soil microbial biomass. Location: Global. Methods: We used a comprehensive global dataset of georeferenced soil microbial biomass estimates and high‐resolution climatic and soil data. Results: We show that microbial biomass carbon (CMic ) is primarily driven by moisture availability, with this single variable accounting for 34% of the global variance. For the microbial carbon‐to‐soil organic carbon ratio (CMic /COrg ), soil nitrogen content was an equally important driver as moisture. In contrast, temperature was not a significant predictor of microbial biomass patterns at a global scale, while temperature likely has an indirect effect on microbial biomass by influencing rates of evapotranspiration and decomposition. As our models explain an unprecedented 50% of the global variance of CMic and CMic /COrg, we were able to leverage gridded environmental information to build the first spatially explicit global estimates of microbial biomass and quantified the global soil microbial carbon pool to equal 14.6 Pg C. Main Conclusions: Our unbiased models allowed us to build the first global spatially explicit predictions of microbial biomass. These patterns show that soil microbial biomass is not primarily driven by temperature, but instead, biomass is more heterogeneous through the effects of moisture availability and soil nutrients. Our global estimates provide important data for integration into large‐scale carbon and nutrient models that may imply a major step forward in our ability to predict the global carbon balance, now and in a future climate.