Toward a function-first framework to make soil microbial ecology predictive

Area of Science:

• Microbiology
• Ecology
• Environmental Science

Background:

• Soil microbial communities are crucial for ecosystem functions like organic matter decomposition and nutrient cycling.
• Linking microbial community composition to specific ecosystem functions remains a challenge due to limited understanding of structure-function relationships.

Purpose of the Study:

• To propose a novel "function-first" framework for predicting ecosystem functions based on microbial community composition.
• To establish a method for identifying microbial "biomarker" taxa that indicate ecosystem function regulation.

Main Methods:

• Viewing microbial communities as functional units and defining their aggregate "functional response curves" based on environmental factors (temperature, pH, salinity).
• Combining functional response curves with environmental conditions to predict community-level ecosystem functions.
• Linking functional response curves with taxonomic data to identify indicator taxa.

Main Results:

• The proposed framework successfully interlinks soil bacterial community structure and function.
• Demonstrated the ability to predict ecosystem functions directly from microbial community composition using three illustrative examples.
• Identified potential "biomarker" taxa that signal microbial regulation of ecosystem functions.

Conclusions:

• The function-first framework provides a powerful tool for predicting ecosystem functions from microbial community composition.
• This approach can serve as a diagnostic tool for understanding and managing soil ecosystems.
• Future applications can leverage this framework for ecological forecasting and microbial resource management.