Representation of dormant and active microbial dynamics for ecosystem modeling.

Area of Science:

• Microbial Ecology
• Ecosystem Modeling

Background:

• Microbial dormancy is a key survival strategy against environmental stress.
• Global ecosystem models often overlook microbial dormancy, leading to significant uncertainties.
• Existing models struggle to explain low active microbial fractions in soils.

Purpose of the Study:

• To develop a novel microbial physiology component for ecosystem models that incorporates dormancy.
• To provide a model applicable across a wide range of substrate availabilities.
• To improve the accuracy of microbially-driven processes in large-scale ecological simulations.

Main Methods:

• Developed a new microbial physiology model based on microbial physiological states.
• Identified key parameters: maximum specific growth and maintenance rates, and dormant to active maintenance rates ratio.
• Analyzed substrate-induced respiration data to validate model parameterization.

Main Results:

• The new model explains low active microbial fractions in undisturbed soils.
• Substrate-induced respiration data can robustly determine multiple key microbial parameters.
• The model differentiates parameter estimation based on respiration phases (exponential vs. non-exponential).

Conclusions:

• The proposed microbial physiology component effectively incorporates dormancy into ecosystem models.
• This advancement allows for more accurate estimations of microbial activities and microbially-driven processes.
• The model enhances the reliability of large-scale ecological predictions by accounting for microbial dormancy.