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Gillespie eco‐evolutionary models (GEMs) reveal the role of heritable trait variation in eco‐evolutionary dynamics

机译:吉莱斯皮生态进化模型(GEMs)揭示了遗传性状变异在生态进化动力学中的作用

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摘要

Heritable trait variation is a central and necessary ingredient of evolution. Trait variation also directly affects ecological processes, generating a clear link between evolutionary and ecological dynamics. Despite the changes in variation that occur through selection, drift, mutation, and recombination, current eco‐evolutionary models usually fail to track how variation changes through time. Moreover, eco‐evolutionary models assume fitness functions for each trait and each ecological context, which often do not have empirical validation. We introduce a new type of model, Gillespie eco‐evolutionary models (GEMs), that resolves these concerns by tracking distributions of traits through time as eco‐evolutionary dynamics progress. This is done by allowing change to be driven by the direct fitness consequences of model parameters within the context of the underlying ecological model, without having to assume a particular fitness function. GEMs work by adding a trait distribution component to the standard Gillespie algorithm – an approach that models stochastic systems in nature that are typically approximated through ordinary differential equations. We illustrate GEMs with the Rosenzweig–MacArthur consumer–resource model. We show not only how heritable trait variation fuels trait evolution and influences eco‐evolutionary dynamics, but also how the erosion of variation through time may hinder eco‐evolutionary dynamics in the long run. GEMs can be developed for any parameter in any ordinary differential equation model and, furthermore, can enable modeling of multiple interacting traits at the same time. We expect GEMs will open the door to a new direction in eco‐evolutionary and evolutionary modeling by removing long‐standing modeling barriers, simplifying the link between traits, fitness, and dynamics, and expanding eco‐evolutionary treatment of a greater diversity of ecological interactions. These factors make GEMs much more than a modeling advance, but an important conceptual advance that bridges ecology and evolution through the central concept of heritable trait variation.
机译:遗传性状变异是进化的核心和必要成分。性状的变化也直接影响生态过程,在进化和生态动力学之间建立了清晰的联系。尽管通过选择,漂移,突变和重组发生了变化,但当前的生态进化模型通常无法跟踪变化随时间的变化。此外,生态进化模型假设每个特征和每个生态环境的适应度函数,而这些函数通常没有经验验证。我们引入了一种新型模型,即吉莱斯皮生态进化模型(GEMs),该模型通过随着生态进化动力学的进展随时间跟踪特征分布来解决这些问题。这是通过在基础生态模型的上下文中允许模型参数的直接适应性结果驱动更改来完成的,而不必承担特定的适应性功能。 GEM通过向标准的Gillespie算法中添加特征分布组件来工作,该方法是对自然界中的随机系统进行建模的方法,通常通过常微分方程来近似。我们用Rosenzweig-MacArthur消费者-资源模型来说明GEM。我们不仅展示了可遗传的性状变异如何促进性状进化并影响生态进化动力学,而且还显示了随着时间的推移,变异的侵蚀如何从长远来看会阻碍生态进化动力学。可以针对任何常微分方程模型中的任何参数开发GEM,并且可以同时对多个相互作用的特征进行建模。我们预计,GEM将通过消除长期存在的建模障碍,简化性状,适应性和动力学之间的联系,并扩大生态进化对更大范围的生态相互作用的处理方式,为生态进化和进化建模的新方向打开大门。这些因素使GEM的发展远不止是建模方面的进步,而是重要的概念发展,通过遗传性状变异的中心概念在生态学和进化之间架起了桥梁。

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