Spatio-Seasonal Eco-Evolutionary Dynamics

My overarching ambition in EcoEvoMove is to provide new theoretical and empirical understanding of how ecological and evolutionary dynamics can interact to ‘rescue’ wild populations from impending extinctions caused by changing and increasingly extreme seasonal climatic conditions.Seasonal climates are rapidly changing, but capabilities to predict real-world population responses are still severely limited.

Major problems are that 1) existing eco-evolutionary theory relies on core assumptions that are fundamentally violated by intrinsic properties of key traits that shape seasonal population dynamics, and 2) key micro-evolutionary processes that drive interacting seasonal and spatial dynamics have not yet been quantified in any wild population.

We therefore have no capacity to predict how fast climate-impacted animal populations could adapt through changing seasonal movements, profoundly reshaping seasonal locations and wider ecological interactions.I will provide:1) new theory that identifies general principles of eco-evolutionary dynamics arising in seasonally- and spatially-varying environments;2) the first empirical estimates of complex quantitative genetic effects and feedbacks that drive micro-evolution and plasticity in seasonal movements, and resulting spatio-seasonal dynamics, in nature.By coupling these theoretical and empirical advances I will test the overarching hypothesis that rapid micro-evolution of the degree or form of seasonal movement could facilitate rapid ‘evolutionary rescue’ of wild meta-populations facing changing seasonal climates, preventing system collapse.I will achieve these advances through new general theoretical models of complex non-linear eco-evolutionary dynamics; new widely-applicable statistical methods for quantitative genetic analyses of spatio-seasonal field data; and ground-breaking application to an unprecedented large-scale multi-generation dataset on a wild bird system exhibiting flexible seasonal migration.