The effectiveness of artificial microbial community selection: a conceptual framework and a meta-analysis

Area of Science:

• Applied Microbiology
• Ecosystem Science
• Evolutionary Biology

Background:

• Artificial selection at the community level is a promising approach to improve ecosystem functions.
• Understanding the conditions that enable successful artificial community selection is crucial.

Purpose of the Study:

• To propose hypotheses on factors influencing artificial microbial community selection effectiveness.
• To conduct a meta-analysis of published artificial microbial community selection experiments.

Main Methods:

• Formulated six hypotheses based on existing literature and multilevel selection theory.
• Performed a meta-analysis on published artificial microbial community selection experiments.

Main Results:

• Responses to community selection varied significantly across experiments, with no overall significant effect size.
• Effectiveness increased with no migration between communities and a larger number of replicated communities.
• Success appears contingent on multiple necessary conditions.

Conclusions:

• Artificial community selection holds promise for improving ecosystem functions.
• Strategies such as increasing among-community variance and optimizing selection parameters are recommended.
• Further research is needed to refine artificial community selection protocols.