Climate is changing globally and its impacts can arise at different levels of biological organization; yet, cross-level consequences of climate change are still poorly understood. Designing effective environmental management and adaptation plans requires implementation of mechanistic models that span the biological hierarchy. Because biological systems are inherently complex and dynamic in nature, dealing with complexities efficiently necessitates simplification of systems or approximation of relevant processes, but there is little consensus on mathematical approaches to scale from genes to populations. Here we present an effort that aims to bring together groups that often do not interact, but that are essential to illuminating the complexities of life: empirical scientists and mathematical modelers, spanning levels of biological organization from genomes to organisms to populations. Through interplay between theory, models, and data, we aim to facilitate the generation of a new synthesis and a conceptual framework for biology across levels.
Bibliographical noteFunding Information:
This paper is a product of discussions during workshops and meetings made possible by the NSF grant #1656063 “Research Coordination Network (RCN): Predicting vertebrate responses to a changing climate: modeling genomes to phenomes to populations (G2P2PoP)” ( https://nau.edu/cbi-rcn-g2p2pop/ ). We thank the reviewers for their helpful comments.