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Graduate Research School Available Projects Population dynamical responses to climate change on a continental scale

Population dynamical responses to climate change on a continental scale

Title of Project

Population dynamical responses to climate change on a continental scale


Dr Martijn van de Pol

College or Research Centre

College of Science & Engineering

Summary of Project

Species respond very different to climate change, with some species benefitting and others suffering. A major challenge is to understand what causes this diversity in responses, as this will help us to predict the winners and losers from global warming and prioritize conservation strategies. However, it has proven challenging to make progress on this, as species’ responses are typically highly idiosyncratic. At the same time, even within species, different population also exhibit widely different responses. Understanding intra-specific variation in climate responses may be more feasible and a logical first step, as populations mainly differ in their environment, while the species life-history typically varies little within species ranges. However, intra-specific comparisons are extremely rare, as it requires long-term data from many different sites of the same species. Here we propose to apply population dynamical models on one of the best studied species in the wild, for which data is available for over 30 populations across the continents of its species range. Hierarchical population models can be combined with path analysis to study the importance of different pathways by which climate affects traits (e.g. body size, or timing of reproduction), which in turn affect demographic rates (reproduction and survival) and ultimately population growth. Next a comparison can be made how the environment of the different populations affects the impact and pathways by which global warming affects population change in this species.

Key Words

climate change; population ecology; comparative study; statistics

Would suit an applicant who

has an interest in climate change and population ecology. Some affinity with mathematical modelling and experience with Bayesian statistics is desirable.

Updated: 15 Nov 2021