Untangling the complexity of priority effects in multispecies communities

Area of Science:

• Ecology
• Theoretical Ecology
• Community Ecology

Background:

• Species immigration history influences local community interactions, leading to historical contingency in community assembly.
• Uncertainty in immigration history, termed priority effects, complicates predictions of community assembly.
• Predicting community assembly dynamics is crucial for understanding ecological stability and biodiversity.

Purpose of the Study:

• To develop a theoretical framework for understanding community assembly predictability under priority effects.
• To classify the diverse consequences of priority effects on multispecies communities.
• To assess the predictability of history-dependent community assembly.

Main Methods:

• Developed a graph-based, non-parametric theoretical framework.
• Classified priority effect consequences into four basic types.
• Utilized a neural network to analyze community predictability with repeated species immigration.
• Applied the framework to empirical community assembly graphs (algal and ciliate).

Main Results:

• The diversity of priority effects increases super-exponentially with species number.
• Four basic types of priority effect consequences were identified: alternative stable states, alternative transient paths, compositional cycles, and lack of escapes from cycles.
• The classification accurately explains community predictability, especially with repeated immigration.
• Empirical data from algal and ciliate communities validated the framework's utility.

Conclusions:

• A theoretical framework was established to understand and predict community assembly influenced by priority effects.
• The classification of priority effects provides a structured approach to analyzing historical contingency.
• This framework can guide future experimental research on history-dependent ecological dynamics.