Testing the limits and potential of evolution in r.. (CLIMADAPT)
Testing the limits and potential of evolution in response to climate change
Start date: Apr 1, 2013,
End date: Mar 31, 2015
BACKGROUND: Predicting the consequences of rapid environmental change for biodiversity is a critical global issue. However, we lack data on how quickly populations will evolve to escape extinction. Such evolution is especially important to specialist organisms that depend on other species as hosts or prey. Understanding limits to adaptation depends on knowing how genetic variation affects the fitness of organisms in natural habitats rather than the lab. Recent advances in genomic technology finally make this possible.OBJECTIVE: I will exploit these novel technologies and integrate them with fitness assays in ecological experiments to explore recent evolution in the Brown Argus butterfly. By linking genome-wide variation with individual fitness and population ecology, I will investigate the nature of genetic variation underpinning ecologically important traits such as host plant preference and fecundity, and the role this variation plays in shaping adaptive population divergence across the northward expanding range in the UK.STRATEGY: My research and training will be guided by world-leading researchers with expertise in: evolution at species’ margins; the generation and analysis of large-scale genomic data; and using such data to infer the ecological context in which evolution occurred. This fellowship will take the Brown Argus system forward as a model to study adaptation to climate change. The impact of my research on policy will be maximised by exposure to Bristol’s world-class environment for engagement with industry and the publicLONG-TERM RELEVANCE: Developing expertise in genomics is critical to take my science forward; researchers with such skills are also in high demand. Expert mentoring at Bristol will boost my development as an independent PI, placing me in an ideal position for fellowship applications. By testing key predictions from theory using real populations, the project will also make an important contribution to EU scientific excellence.
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