Summary
The impact of global environmental change on natural populations is both an urgent concern, and an invaluable opportunity to understand how environmental variation shapes evolutionary and ecological processes. This project will combine state-of-the-art genomic and statistical technology with globally distributed studies to build a ground-breaking new understanding of the evolutionary and ecological dynamics of wild populations. At the same time, it will deliver much-needed application of both long-standing and new evolutionary theory. My track record of building the field of wild quantitative genetics together with the new multi-species consortium I have created, means I am uniquely positioned to exert powerful leverage over core questions. My project has three major objectives: (1) to understand variation in fitness and current rates of evolutionary adaptation in the wild, including contributions from social evolution; (2) to determine the effects of environmental variation on natural selection and adaptive evolutionary responses; and (3) to provide comprehensive assessment of the contribution of evolutionary genetic adaptation vs ecological responses to the dynamics of phenotypic traits and population numbers. It will do so using seven exceptional long-term studies of wild mammal populations from across the world: red deer, bighorn sheep, Soay sheep, spotted hyaenas, meerkats, eastern grey kangaroos and Tasmanian devils, all experiencing environmental change such as the effects of climate or disease. The multi-species consortium will enable valuable insight into the generality of the results, which can inform the management of wild populations. The project will also develop new analytical approaches, bringing together the latest quantitative genetic and genomic developments with hierarchical population modelling, which will have application across a broad range of systems.
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| Web resources: | https://cordis.europa.eu/project/id/101020503 |
| Start date: | 01-12-2021 |
| End date: | 30-11-2026 |
| Total budget - Public funding: | 1 818 417,00 Euro - 1 818 417,00 Euro |
Cordis data
Original description
The impact of global environmental change on natural populations is both an urgent concern, and an invaluable opportunity to understand how environmental variation shapes evolutionary and ecological processes. This project will combine state-of-the-art genomic and statistical technology with globally distributed studies to build a ground-breaking new understanding of the evolutionary and ecological dynamics of wild populations. At the same time, it will deliver much-needed application of both long-standing and new evolutionary theory. My track record of building the field of wild quantitative genetics together with the new multi-species consortium I have created, means I am uniquely positioned to exert powerful leverage over core questions. My project has three major objectives: (1) to understand variation in fitness and current rates of evolutionary adaptation in the wild, including contributions from social evolution; (2) to determine the effects of environmental variation on natural selection and adaptive evolutionary responses; and (3) to provide comprehensive assessment of the contribution of evolutionary genetic adaptation vs ecological responses to the dynamics of phenotypic traits and population numbers. It will do so using seven exceptional long-term studies of wild mammal populations from across the world: red deer, bighorn sheep, Soay sheep, spotted hyaenas, meerkats, eastern grey kangaroos and Tasmanian devils, all experiencing environmental change such as the effects of climate or disease. The multi-species consortium will enable valuable insight into the generality of the results, which can inform the management of wild populations. The project will also develop new analytical approaches, bringing together the latest quantitative genetic and genomic developments with hierarchical population modelling, which will have application across a broad range of systems.Status
SIGNEDCall topic
ERC-2020-ADGUpdate Date
27-04-2024
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