Details of Award
NERC Reference : NE/P004180/1
NSFDEB-NERC: Informing population models with evolutionary theory to infer species' conservation status
Grant Award
- Principal Investigator:
- Professor J Matthiopoulos, University of Glasgow, College of Medical, Veterinary, Life Sci
- Grant held at:
- University of Glasgow, College of Medical, Veterinary, Life Sci
- Science Area:
- Atmospheric
- Earth
- Freshwater
- Marine
- Terrestrial
- Overall Classification:
- Panel D
- ENRIs:
- Biodiversity
- Environmental Risks and Hazards
- Global Change
- Natural Resource Management
- Pollution and Waste
- Science Topics:
- Population Ecology
- Statistical Ecology
- Bayesian Methods
- Statistics & Appl. Probability
- Abstract:
- Natural mortality and environmental resources are intimately related to physiology, body size, fecundity, and lifespan, all of which play an instrumental role in population dynamics. Yet mortality and resource limitation are notoriously difficult to measure in wild populations, hindering our ability to prioritize marine species that are at greatest risk of overexploitation. Crucially, we lack mechanistic theory linking physiology, life histories and population dynamics. Our central hypothesis is that evolutionary theory can take the place of missing information on demographic rates or population trends, and can be used to combine data from similar species to predict population dynamics. We propose to develop a scientific research program to test this idea and add to our knowledge of the processes regulating the dynamics of marine populations. We will use a combination of evolutionary theory and hierarchical Bayesian state-space models of data to infer and predict the life history and population dynamics of three marine fish clades with diverse life histories: sharks and rays, tunas, and groupers. Specifically, we will 1) use state-dependent life history theory to develop evolutionary priors for demographic rates, including mortality and resource limitation and 2) use state-space models to impute the population trajectories of related species, given our evolutionary priors. This will 3) generate and refine new theory for the evolution of sharks and rays, groupers, and tunas that can ultimately be tested comparatively. Finally, we will 4) engage in species' assessments, training, and outreach to boost the broader impacts of our work. Our research will produce theory predicting the demographic rates that are correlated with suites of life history traits, and then generate more precise posterior estimates of these demographic rates by fitting a structured population model. This integrative approach will allow us to refine and validate our results with species that have been assessed, and then to assess the vulnerability of data-limited and potentially endangered species of sharks and rays, groupers, and tunas. Along the way, our work will generate new insights about the relationship between life-history traits of marine species, environmental drivers such as resources and mortality, and resilience to anthropogenic or environmental perturbations. Intellectual Merit : We take a new approach to linking evolutionary theory with ecological data. While previous work has used evolutionarily derived priors in fishery stock assessments (He et al. 2006; Mangel et al. 2010), this research will provide a mechanistic framework assessing how stage-specific mortality and resource limitation determine life history evolution and population dynamics. The novelty of this approach is that we are not hardwiring our assumptions about life history trait co-variation into the model. We will test our predictions for how resources and natural mortality select on life histories by confronting our population dynamics model with real-world data from wild fishes.
- NERC Reference:
- NE/P004180/1
- Grant Stage:
- Completed
- Scheme:
- Standard Grant FEC
- Grant Status:
- Closed
- Programme:
- Lead Agency Grant
This grant award has a total value of £243,445
FDAB - Financial Details (Award breakdown by headings)
| Indirect - Indirect Costs | DA - Investigators | DA - Estate Costs | DI - Staff | DA - Other Directly Allocated |
|---|---|---|---|---|
| £96,520 | £16,872 | £33,044 | £92,450 | £4,560 |
If you need further help, please read the user guide.