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

• Published in: Integrative and comparative biology Vol. 61; no. 6; pp. 2218 - 2232
• Main Authors: Thompson, Cynthia L, Alberti, Marina, Barve, Sahas, Battistuzzi, Fabia U, Drake, Jeana L, Goncalves, Guilherme Casas, Govaert, Lynn, Partridge, Charlyn, Yang, Ya
• Format: Journal Article
• Language: English
• Published: England 05.02.2022
• ISSN: 1540-7063; 1557-7023
• DOI: 10.1093/icb/icab068

During the last few decades, biologists have made remarkable progress in understanding the fundamental processes that shape life. But despite the unprecedented level of knowledge now available, large gaps still remain in our understanding of the complex interplay of eco-evolutionary mechanisms across scales of life. Rapidly changing environments on Earth provide a pressing need to understand the potential implications of eco-evolutionary dynamics, which can be achieved by improving existing eco-evolutionary models and fostering convergence among the sub-fields of biology. We propose a new, data-driven approach that harnesses our knowledge of the functioning of biological systems to expand current conceptual frameworks and develop corresponding models that can more accurately represent and predict future eco-evolutionary outcomes. We suggest a roadmap toward achieving this goal. This long-term vision will move biology in a direction that can wield these predictive models for scientific applications that benefit humanity and increase the resilience of natural biological systems. We identify short, medium, and long-term key objectives to connect our current state of knowledge to this long-term vision, iteratively progressing across three stages: (1) utilizing knowledge of biological systems to better inform eco-evolutionary models, (2) generating models with more accurate predictions, and (3) applying predictive models to benefit the biosphere. Within each stage, we outline avenues of investigation and scientific applications related to the timescales over which evolution occurs, the parameter space of eco-evolutionary processes, and the dynamic interactions between these mechanisms. The ability to accurately model, monitor, and anticipate eco-evolutionary changes would be transformational to humanity's interaction with the global environment, providing novel tools to benefit human health, protect the natural world, and manage our planet's biosphere.