Detecting the ecological footprint of selection

Area of Science:

• Ecology
• Evolutionary Biology
• Biodiversity Science

Background:

• Community structure is shaped by ecological and evolutionary processes, but distinguishing these from neutral processes is challenging.
• Classic biodiversity patterns often obscure the underlying mechanisms driving community assembly.

Purpose of the Study:

• To differentiate ecological selection (competition, environmental filtering) from neutral processes in community assembly.
• To develop and implement a more realistic pairwise competition model for detecting selective forces.

Main Methods:

• Utilized Massive Eco-evolutionary Synthesis Simulations (MESS) incorporating species abundances, genetic diversity, and trait variation.
• Introduced a novel pairwise individual-trait comparison for competition, distinct from community-mean-based approaches.
• Applied advanced mechanistic models and inference techniques to empirical data.

Main Results:

• The new pairwise competition model is more readily identifiable in empirical data than previous methods, especially with trait data.
• Findings suggest that some biodiversity patterns attributed to neutrality may result from pairwise selective forces.
• Qualitatively different results compared to models using community-mean trait distances.

Conclusions:

• Advanced mechanistic models and diverse data types are crucial for understanding community assembly.
• Re-evaluation of empirical data may be needed, as signatures previously attributed to neutrality could be due to pairwise selection.
• The relative importance of neutral versus selective processes in community assembly requires further investigation.