Objective
Long distance migration in birds is among the most dramatic and exciting phenomena in nature. However despite many years of study, there are still huge gaps in our understanding of how this behaviour shapes individual ecology and influences population processes. For example, we have very little understanding of how migratory animals manage trade offs within and among seasons and how these in turn drive variation in productivity, survival or breeding phenology. Increased understanding in this area has important implications for ecology, evolution conservation and management
Our lack of progress in this area is almost inevitable given the complex nature of migration. Migration is sequential in nature, meaning that an animal’s state in one season is heavily influenced by previous conditions. Therefore the costs/benefits of behaviours can be carried over into subsequent seasons and thus the processes regulating fitness may not occur at the time it is being expressed. This also means that regulating processes and response can also be separated spatially making it even harder to identify cause. These effects are likely to be emphasized in migrants because fuelling flights and breeding also places huge physiological demands on migratory birds. Yet few studies have linked the stress incurred during migration with subsequent fitness. Integrating mechanism and function would provide very important insights into the ecology and evolution of migration. In order to progress we need to able to follow large numbers of individuals throughout their annual cycles, tracking the different conditions they experience and how this influences their state at each point in time. I would use state of the art technologies and statistical tools to follow migratory geese throughout the year and integrate, for the first time, how interactions among physiological, social, ecological and climatic environments underpin state and in turn fitness across the annual cycle.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencesbiological scienceszoologyornithology
- natural sciencesbiological sciencesecology
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- medical and health sciencesbasic medicinephysiology
- social sciencessociologydemographyhuman migrations
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Call for proposal
ERC-2012-StG_20111109
See other projects for this call
Funding Scheme
ERC-SG - ERC Starting GrantHost institution
EX4 4QJ Exeter
United Kingdom