May Samuel A, Hard Jeffrey J, Ford Michael J, Naish Kerry A, Ward Eric J
School of Aquatic and Fishery Sciences University of Washington Seattle Washington USA.
NOAA Fisheries Northwest Fisheries Science Center Seattle Washington USA.
Evol Appl. 2023 Jan 20;16(3):657-672. doi: 10.1111/eva.13524. eCollection 2023 Mar.
Quantitative models that simulate the inheritance and evolution of fitness-linked traits offer a method for predicting how environmental or anthropogenic perturbations can affect the dynamics of wild populations. Random mating between individuals within populations is a key assumption of many such models used in conservation and management to predict the impacts of proposed management or conservation actions. However, recent evidence suggests that non-random mating may be underestimated in wild populations and play an important role in diversity-stability relationships. Here we introduce a novel individual-based quantitative genetic model that incorporates assortative mating for reproductive timing, a defining attribute of many aggregate breeding species. We demonstrate the utility of this framework by simulating a generalized salmonid lifecycle, varying input parameters, and comparing model outputs to theoretical expectations for several eco-evolutionary, population dynamic scenarios. Simulations with assortative mating systems resulted in more resilient and productive populations than those that were randomly mating. In accordance with established ecological and evolutionary theory, we also found that decreasing the magnitude of trait correlations, environmental variability, and strength of selection each had a positive effect on population growth. Our model is constructed in a modular framework so that future components can be easily added to address pressing issues such as the effects of supportive breeding, variable age structure, differential selection by sex or age, and fishery interactions on population growth and resilience. With code published in a public Github repository, model outputs may easily be tailored to specific study systems by parameterizing with empirically generated values from long-term ecological monitoring programs.
模拟与适应度相关性状的遗传和进化的定量模型提供了一种方法，用于预测环境或人为干扰如何影响野生种群的动态。种群内个体间的随机交配是许多用于保护和管理的此类模型的关键假设，这些模型用于预测拟议的管理或保护行动的影响。然而，最近的证据表明，野生种群中的非随机交配可能被低估，并且在多样性 - 稳定性关系中发挥重要作用。在这里，我们引入了一种新颖的基于个体的定量遗传模型，该模型纳入了繁殖时间的选型交配，这是许多聚集繁殖物种的一个决定性属性。我们通过模拟一个广义的鲑鱼生命周期、改变输入参数，并将模型输出与几种生态进化、种群动态情景的理论预期进行比较，来证明这个框架的实用性。与随机交配的种群相比，选型交配系统的模拟产生了更具恢复力和生产力的种群。根据已确立的生态和进化理论，我们还发现降低性状相关性的幅度、环境变异性和选择强度对种群增长都有积极影响。我们的模型是在一个模块化框架中构建的，以便未来可以轻松添加组件来解决紧迫问题，如辅助繁殖的影响、可变年龄结构、性别或年龄的差异选择以及渔业相互作用对种群增长和恢复力的影响。由于代码发布在公共的Github存储库中，通过使用来自长期生态监测计划的经验生成值进行参数化，模型输出可以很容易地针对特定研究系统进行定制。
