NSFDEB-NERC: Informing population models with evolutionary theory to infer species' conservation status

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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. Yetmortality 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 informationon demographic rates or population trends, and can be used to combine data from similar speciesto predict population dynamics. We propose to develop a scientific research program to testthis 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 modelsof data to infer and predict the life history and population dynamics of three marine fishclades with diverse life histories: sharks and rays, tunas, and groupers.Specifically, we will 1) use state-dependent life history theory to develop evolutionary priorsfor demographic rates, including mortality and resource limitation and 2) use state-spacemodels 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 researchwill produce theory predicting the demographic rates that are correlated with suites of lifehistory traits, and then generate more precise posterior estimates of these demographic ratesby fitting a structured population model. This integrative approach will allow us to refineand validate our results with species that have been assessed, and then to assess the vulnerabilityof 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-historytraits of marine species, environmental drivers such as resources and mortality, and resilienceto anthropogenic or environmental perturbations.Intellectual Merit :We take a new approach to linking evolutionary theory with ecological data. While previouswork 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-specificmortality 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 historytrait co-variation into the model. We will test our predictions for how resources and naturalmortality select on life histories by confronting our population dynamics model with real-worlddata from wild fishes.