What processes must we understand to forecast regional-scale population dynamics?

Area of Science:

• Ecology
• Evolutionary Biology
• Population Dynamics
• Environmental Change

Background:

• Accurately predicting species population dynamics amid environmental change is a critical biological challenge.
• Current phenomenological models lack the mechanistic depth needed for robust predictions.
• Integrating insights from population, evolutionary, community, and ecophysiological studies is debated as essential.

Purpose of the Study:

• To address the need for process-based predictions of population dynamics under environmental change.
• To review the importance of various biological mechanisms for accurate species distribution modeling.
• To propose a novel framework for integrating multi-scale processes influencing species' environmental responses.

Main Methods:

• Development of a conceptual framework centered on reaction norms.
• Proposal of a hierarchical Bayesian statistical framework for data integration.
• Review of mechanisms crucial for skillful prediction in ecological modeling.

Main Results:

• Identified the necessity of empirical data integration across biological sub-disciplines.
• Established reaction norms as a central concept for linking different biological processes.
• Proposed a statistical approach to synthesize data from various scales.

Conclusions:

• Answering the question of integrating multiple biological processes requires substantial, integrated empirical data.
• The proposed reaction norm and Bayesian framework facilitates the integration of diverse ecological and evolutionary data.
• Advocated research program is increasingly feasible with new collaborations and analytical tools.