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

自然死亡率和环境资源与生理、体型、繁殖力和寿命密切相关，所有这些都在种群动态中起着重要作用。然而，众所周知，野生种群的死亡率和资源限制很难衡量，这阻碍了我们优先考虑处于过度开发风险最大的海洋物种的能力。关键是，我们缺乏将生理、生活史和种群动态联系起来的机械理论。我们的中心假设是，进化理论可以取代关于人口比率或种群趋势的缺失信息，并可以用来结合来自类似物种的数据来预测种群动态。我们建议开发一个科学研究项目来验证这一想法，并增加我们对海洋种群动态调节过程的知识。我们将使用进化理论和数据的分层贝叶斯状态空间模型来推断和预测具有不同生活史的三个海洋鱼类支系的生活史和种群动态：鲨鱼和鱼类、金枪鱼和群体。具体地说，我们将1)使用状态依赖的生活史理论来建立人口速率的进化先验，包括死亡率和资源限制。2)使用状态空间模型来推算相关物种的种群轨迹，鉴于我们的进化先例，这将为鲨鱼、银鱼、石斑鱼和金枪鱼的进化产生和完善新的理论，最终可以进行比较测试。最后，我们将参与物种评估、培训和推广，以促进我们工作的更广泛影响。我们的研究将产生预测与一系列生活史特征相关的人口比率的理论，然后通过拟合一个结构化的人口模型来产生对这些人口比率更精确的后验估计。这种综合的方法将使我们能够用已经评估的物种来改进和验证我们的结果，然后评估数据有限和潜在濒危的鲨鱼、射线、石斑鱼和金枪鱼等物种的脆弱性。一路走来，我们的工作将产生关于海洋物种的生活史特征、资源和死亡等环境驱动因素以及对人为或环境扰动的弹性之间关系的新见解。智力优势：我们采取了一种新的方法将进化理论与生态数据联系起来。虽然以前的工作在渔业种群评估中使用了进化派生的先验(他等人)。2006年；曼格尔等人。2010年)，这项研究将提供一个机制框架，评估特定阶段的死亡率和资源限制如何决定生活史进化和种群动态。这种方法的新奇之处在于，我们没有将我们关于生活史-性状协变的假设硬性地嵌入到模型中。我们将通过用野生鱼类的真实数据来对抗我们的种群动态模型，来测试我们对资源和自然死亡率如何在生活史上选择的预测。

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.