Towards evolutionary predictions: Current promises and challenges.

Area of Science:

• Evolutionary biology
• Predictive modeling
• Interdisciplinary applications

Background:

• Evolutionary science traditionally focused on historical description, deeming future prediction impossible.
• Recent advancements enable evolutionary predictions across medicine, agriculture, biotechnology, and conservation.

Purpose of the Study:

• To raise awareness of diverse evolutionary prediction methods and data across research fields.
• To establish a common framework for understanding evolutionary predictions based on scope, timescale, and precision.

Main Methods:

• Review of diverse applications of evolutionary predictions.
• Analysis of common structural elements (scope, timescale, precision) in predictive models.
• Case studies including viral evolution (SARS-CoV-2, influenza), gene drives, and biotechnology.

Main Results:

• Evolutionary predictions are utilized for preparation, intervention, and assessing understanding of evolutionary processes.
• Predictability is influenced by various factors, and predictions can guide evolutionary control.
• A shared structure underlies diverse evolutionary predictions, facilitating interdisciplinary communication.

Conclusions:

• Evolutionary prediction is a vital and increasingly applicable tool across scientific disciplines.
• Establishing a common language and framework for evolutionary predictions can foster collaboration.
• Harnessing evolutionary predictions allows for proactive management and control of evolutionary trajectories.