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。众所周知，在野生种群中，死亡率和资源限制很难衡量，这阻碍了我们优先考虑那些最有可能被过度开发的海洋物种的能力。至关重要的是，我们缺乏将生理学、生活史和种群动态联系起来的机械理论。我们的核心假设是，进化理论可以取代缺失的关于人口统计率或种群趋势的信息，并可用于联合收割机数据从类似物种预测人口动态。我们建议开发一个科学研究计划来验证这一想法，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分层贝叶斯数据状态空间模型的组合来推断和预测具有不同生活史的三种海洋鱼类的生活史和种群动态：鲨鱼和鳐，金枪鱼和石斑鱼。具体来说，我们将1）使用状态依赖生活史理论来开发人口统计率的进化优先级，包括死亡率和资源限制，2）使用状态空间模型来估算相关物种的人口轨迹，这将产生并完善有关鲨鱼、鳐、石斑鱼和金枪鱼进化的新理论，最终可以进行比较检验。最后，我们将参与物种评估、培训和推广活动，以扩大我们工作的影响。我们的研究将产生预测与生活史特征套件相关的人口统计学比率的理论，然后通过拟合结构化人口模型来生成这些人口统计学比率的更精确的后验估计。这种综合方法将使我们能够用已经评估过的物种来完善和验证我们的结果，然后评估数据有限和潜在濒危物种鲨鱼和鳐、石斑鱼和金枪鱼的可行性。沿着这条路，我们的工作将产生关于海洋物种的生活史特征、资源和死亡率等环境驱动因素之间关系的新见解，智力上的优点：我们采用了一种新的方法将进化理论与生态学数据联系起来。虽然以前的工作已经在渔业资源评估中使用了进化推导的先验知识（He et al. 2006;Mangel et al. 2010），但这项研究将提供一个机制框架，评估阶段特异性死亡率和资源限制如何决定生活史进化和种群动态。这种方法的新奇在于，我们没有将我们对生活史性状协变的假设硬连接到模型中。我们将通过将我们的种群动力学模型与野生鱼类的真实数据进行对比，来测试我们对资源和自然死亡率如何选择生活史的预测。

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.