Back to the Future: Reintegrating Biology to Understand How Past Eco-evolutionary Change Can Predict Future Outcomes

Area of Science:

• Ecology and Evolutionary Biology
• Systems Biology
• Computational Biology

Background:

• Significant progress in understanding life's processes, yet gaps remain in eco-evolutionary dynamics across scales.
• Rapid environmental changes necessitate understanding eco-evolutionary implications.
• Existing models require improvement and interdisciplinary convergence.

Purpose of the Study:

• Propose a data-driven approach to enhance eco-evolutionary models.
• Expand conceptual frameworks using knowledge of biological system functioning.
• Develop models for accurate prediction of future eco-evolutionary outcomes.

Main Methods:

• Harnessing knowledge of biological system functioning.
• Iterative progression through three stages: informing models, improving predictions, and applying models.
• Investigating timescales, parameter space, and dynamic interactions of eco-evolutionary processes.

Main Results:

• A roadmap for advancing eco-evolutionary modeling is proposed.
• Integration of biological system knowledge into model development.
• Identification of key objectives for short, medium, and long-term progress.

Conclusions:

• Accurate modeling, monitoring, and anticipation of eco-evolutionary changes are transformational.
• Predictive models offer novel tools for human health, conservation, and biosphere management.
• This vision enhances humanity's interaction with the global environment and increases biosphere resilience.