Eco-evolutionary dynamics of seasonally mobile systems

Many wild populations are now experiencing dramatic changes in environmental conditions, including changing seasonalities and increasing frequencies and severities of extreme climatic events. Urgent ambitions spanning population and evolutionary biology are to understand how ecological and evolutionary responses to such perturbations can interact to shape population dynamics and persistence and, further, to understand how impacted populations can retain capacity to respond to future environmental changes.

Such advances are required to identify fundamental principles of eco-evolutionary dynamics that can emerge in complex wild systems experiencing turbulent environments and, ultimately, to inform effective and future-proof population management strategies. Yet, useful prediction is currently severely impeded because key components of eco-evolutionary dynamics that could arise in wild populations have never been quantified, or even explicitly conceptualised.

Hence, our overarching objective is to provide ground-breaking conceptual, analytical and empirical advances that generate new understanding of eco-evolutionary dynamics involving variable seasonal migration, thereby revealing how seasonally mobile populations could adapt and persist in the face of changing and increasingly extreme seasonal environments.

Seasonal migration, defined as reversible seasonal movements between discrete breeding and non-breeding locations, is a taxonomically widespread trait that allows spatial escape from deteriorating environments and directly shapes spatio-seasonal population dynamics. Migration therefore acts as a 'hotline' that directly links phenotypic evolution and population dynamics. Yet, despite such fundamental links, key components of eco-evolutionary dynamics involving seasonal migration have never been quantified in wild populations. Consequently, we cannot yet understand or predict what forms of rapid changes in seasonal movements could arise, or how such changes will translate into spatio-seasonal population dynamic outcomes.

Accordingly, our project will achieve major advances by providing:

1) First estimates of complex landscapes of natural selection acting on forms of seasonal migration (or year-round residence) in spatially-structured seasonally-varying environments, setting the potential for rapid phenotypic change.

2) First estimates of quantitative genetic 'evolvabilities' of seasonal migration, setting the potential for rapid micro-evolution of spatio-seasonal population dynamics.

3) First inferences on how such landscapes of selection and quantitative genetic variation can combine to generate eco-evolutionary spatio-seasonal dynamics, and also maintain genetic and phenotypic variation in seasonal movement over short and longer timeframes.

Further, we will quantify to what degree such selection landscapes, quantitative genetic architectures and eco-evolutionary outcomes can be dramatically reshaped by extreme climatic events, acting as harbingers of projected climate change.

We will achieve these objectives by devising advanced statistical models, including multi-state quantitative genetic 'animal models', that facilitate unbiased estimation of key micro-evolutionary parameters from field data. We will apply these models to an unprecedented large-scale multi-year full-annual-cycle dataset on individual movements, survival and reproduction from a climate-threatened partially-migratory meta-population of European shags. This bird field system and dataset is currently uniquely able to support the proposed cutting-edge analyses.

We will thereby provide major conceptual, analytical and empirical advances that integrate the currently separate fields of migration ecology and evolutionary quantitative genetics, injecting wide new impetus in evolutionary ecology, and providing fundamental new insights into the potential for rapid spatio-seasonal population change.