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周期性波动环境下结构种群的生态进化动态:G 函数方法。

Eco-evolutionary dynamics of structured populations in periodically fluctuating environments: a G function approach.

机构信息

Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

出版信息

Theory Biosci. 2024 Nov;143(4):293-299. doi: 10.1007/s12064-024-00424-5. Epub 2024 Aug 21.

Abstract

Understanding the ecological and evolutionary dynamics of populations is critical for both basic and applied purposes in a variety of biological contexts. Although several modeling frameworks have been developed to simulate eco-evolutionary dynamics, many fewer address how to model structured populations. In a prior paper, we put forth the first modeling approach to simulate eco-evolutionary dynamics in structured populations under the G function modeling framework. However, this approach does not allow for accurate simulation under fluctuating environmental conditions. To address this limitation, we draw on the study of periodic differential equations to propose a modified approach that uses a different definition of fitness more suitable for fluctuating environments. We illustrate this method with a simple toy model of life history trade-offs. The generality of this approach allows it to be used in a variety of biological contexts.

摘要

理解种群的生态和进化动态对于各种生物学背景下的基础研究和应用研究都至关重要。虽然已经开发了几种模型框架来模拟生态进化动态,但很少有模型能够解决如何对结构种群进行建模的问题。在之前的一篇论文中,我们提出了第一个在 G 函数建模框架下模拟结构种群生态进化动态的建模方法。然而,这种方法在波动的环境条件下无法进行准确的模拟。为了解决这个限制,我们借鉴周期微分方程的研究,提出了一种使用更适合波动环境的适应性定义的改进方法。我们使用一个简单的生活史权衡的玩具模型来说明这种方法。这种方法的通用性使其可以在各种生物学背景下使用。

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