A meta-analysis of temperature sensitivity as a microbial trait

Area of Science:

• Microbial Ecology
• Environmental Microbiology
• Biogeochemistry

Background:

• Traits-based approaches offer a framework for understanding microbial ecology and community function.
• Macromolecular Rate Theory (MMRT) identifies temperature sensitivity as a key microbial trait.
• Understanding microbial temperature sensitivity is crucial for predicting responses to climate change.

Purpose of the Study:

• To analyze the distribution of microbial temperature sensitivity traits (heat capacity, Topt, TSmax).
• To identify commonalities and variations in temperature responses across diverse microbial communities and biological systems.
• To assess the implications of temperature sensitivity for ecological understanding and climate change modeling.

Main Methods:

• Meta-analysis of over 350 microbial temperature response curves.
• Analysis of temperature sensitivity traits (heat capacity, Topt, TSmax) from bacteria, fungi, and mixed communities.
• Comparison of trait distributions across various biological systems (soils, oceans, foods, wastewater).

Main Results:

• A wide distribution of temperature sensitivity traits was observed, with Topt and TSmax within biologically relevant ranges.
• Temperature sensitivity varied significantly by organism type (fungi > bacteria), microbial diversity (lower diversity = higher sensitivity), and environment.
• Carbon dioxide production showed lower temperature sensitivity compared to denitrification, indicating a greater impact of temperature changes on nitrogen cycling.

Conclusions:

• Microbial temperature sensitivity is a complex trait influenced by organism type, diversity, and environment.
• These findings enhance our fundamental understanding of biological reaction temperature sensitivity.
• Improved modeling of temperature sensitivity is essential for ecological predictions under climate change.