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Diversity begets diversity during community assembly until ecological limits impose a diversity ceiling
Magdalena San Roman1,2, Andreas Wagner1,2,3,4
1Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.
Molecular Ecology
|September 3, 2021
Summary
Microbial communities initially grow diverse through species interactions creating new niches. However, environmental limitations eventually dominate, stabilizing microbial diversity.
Area of Science:
- Microbial Ecology
- Community Assembly
- Metabolic Modeling
Background:
- Microbial diversity is vast, but the drivers of its assembly and limits remain unclear.
- Two main hypotheses explain diversity limits: ecological limits (resources) and diversity-begets-diversity (biotic interactions creating niches).
Purpose of the Study:
- To determine which hypothesis better explains microbial community assembly.
- To investigate the roles of species invasions and extinctions in microbial diversity dynamics.
Main Methods:
- Utilized metabolic modeling to represent microbial species' biochemical reactions and resource utilization.
- Simulated thousands of species invasions in a chemostat-like environment to model community assembly.
- Analyzed how metabolic by-products influence nutrient availability and niche creation.
Main Results:
- Early community assembly is characterized by 'diversity begets diversity,' where by-product excretion creates numerous new niches.
- This interaction-driven niche creation significantly expands the environment's capacity to support diverse species.
- Later stages show a slowdown in niche creation, niche saturation, and a plateau in species diversity due to ecological limitations.
Conclusions:
- Both the ecological limits and diversity-begets-diversity hypotheses explain different stages of microbial community assembly.
- Species interactions can dramatically increase diversity ceilings, but this effect is ultimately constrained by environmental factors.
- Understanding these dynamics is crucial for predicting microbial community structure and function.
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