Editor: Martin Sykes
Global drivers and patterns of microbial abundance in soil
Article first published online: 7 JUN 2013
© 2013 John Wiley & Sons Ltd
Global Ecology and Biogeography
Volume 22, Issue 10, pages 1162–1172, October 2013
How to Cite
Serna-Chavez, H. M., Fierer, N. and van Bodegom, P. M. (2013), Global drivers and patterns of microbial abundance in soil. Global Ecology and Biogeography, 22: 1162–1172. doi: 10.1111/geb.12070
- Issue published online: 4 SEP 2013
- Article first published online: 7 JUN 2013
- European Commission's Education
- Audiovisual and Culture Executive Agency (EACEA)
- Biogeochemical cycles;
- global carbon cycling;
- moisture limitation;
- nitrogen limitation;
- soil microbial abundance;
- soil microbial biomass;
- soil microbial carbon
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.
We used a comprehensive global dataset of georeferenced soil microbial biomass estimates and high-resolution climatic and soil data.
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.
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.