Skip to main content

Quantifying microbial control of soil organic matter dynamics at macrosystem scales


Soil organic matter (SOM) stocks, decomposition and persistence are largely the product of controls that act locally. Yet the controls are shaped and interact at multiple spatiotemporal scales, from which macrosystem patterns in SOM emerge. Theory on SOM turnover recognizes the resulting spatial and temporal conditionality in the effect sizes of controls that play out across macrosystems, and couples them through evolutionary and community assembly processes. For example, climate history shapes plant functional traits, which in turn interact with contemporary climate to influence SOM dynamics. Selection and assembly also shape the functional traits of soil decomposer communities, but it is less clear how in turn these traits influence temporal macrosystem patterns in SOM turnover. Here, we review evidence that establishes the expectation that selection and assembly should generate decomposer communities across macrosystems that have distinct functional effects on SOM dynamics. Representation of this knowledge in soil biogeochemical models affects the magnitude and direction of projected SOM responses under global change. Yet there is high uncertainty and low confidence in these projections. To address these issues, we make the case that a coordinated set of empirical practices are required which necessitate (1) greater use of statistical approaches in biogeochemistry that are suited to causative inference; (2) long-term, macrosystem-scale, observational and experimental networks to reveal conditionality in effect sizes, and embedded correlation, in controls on SOM turnover; and (3) use of multiple measurement grains to capture local- and macroscale variation in controls and outcomes, to avoid obscuring causative understanding through data aggregation. When employed together, along with process-based models to synthesize knowledge and guide further empirical work, we believe these practices will rapidly advance understanding of microbial controls on SOM and improve carbon cycle projections that guide policies on climate adaptation and mitigation.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3

Data availability

No new data were collected for this manuscript, and there is no supplementary material.


Download references


We thank the Bradford lab group for comments on an earlier version of this manuscript.


MAB, AP, SAW, WRW, NF, JGR and FJ were supported by the U.S. National Science Foundation’s Macrosystem Biology and NEON-Enabled Science program grants DEB-1926482 and DEB-1926413. WRW was supported by the U.S. Department of Energy under award number BSS DE-SC0016364.

Author information

Authors and Affiliations



MAB, SAW and WRW synthesized the ideas presented to address microbial controls on SOM turnover at macrosystem scales. All authors contributed to the ideas presented and then, through the writing of the manuscript, refined their integration.

Corresponding author

Correspondence to Mark A. Bradford.

Ethics declarations

Ethical approval

The authors declare that they have no conflicting or competing interests with respect to the viewpoints presented in this manuscript.

Additional information

Responsible Editor: Samantha R. Weintraub.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Bradford, M.A., Wood, S.A., Addicott, E.T. et al. Quantifying microbial control of soil organic matter dynamics at macrosystem scales. Biogeochemistry 156, 19–40 (2021).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:


  • Forecasting
  • Functional redundancy
  • Jensen’s Inequality
  • Logical inference fallacies
  • Multilevel models
  • Soil carbon