In most soil microbial communities, the controls on growth and metabolism are poorly understood and are simply too complex to be included in computer models of climate, soil fertility for agriculture, or waste management.

To determine the principles by which soil microbial communities function under varying environmental constraints, development of a scalable biogeochemical modeling approach is critical.

In a new collaborative project funded by the National Science Foundation (NSF), MBL Senior Scientists Joe Vallino and Zoe Cardon will develop a flexible framework for analyzing microbial biogeochemistry from the perspective of maximum entropy production (MEP) (a concept that proposes complex systems will likely organize to maximize dissipation of useful energy).

Example of a simplified soil metabolic network model representing the conversion of soil organic matter (SOM) to methane (CH4) or carbon dioxide (CO2) overlaying an image of methanogens stained with SYBR green. Credit: Joe Vallino and Zoe Cardon
Example of a simplified soil metabolic network model representing the conversion of soil organic matter (SOM) to methane (CH4) or carbon dioxide (CO2) overlaying an image of methanogens stained with SYBR green. Credit: Joe Vallino and Zoe Cardon

The work takes advantage of the high diversity of microbial communities to enable thermodynamically based predictions about system-level biogeochemical responses to global change.

Ultimately, the goal is to integrate sensor-derived information of soil properties with the MEP model to predict shifting activities of microbial communities in soils using far fewer model parameters than would be required with conventional modeling. The project will also support undergraduate research activities as part of the MBL’s Semester in Environmental Science program.

This grant is through the NSF’s “Signals in the Soil” program.