Parvinen Kalle, Heino Mikko, Dieckmann Ulf
Department of Mathematics and Statistics, University of Turku, 20014, Turku, Finland.
J Math Biol. 2013 Sep;67(3):509-33. doi: 10.1007/s00285-012-0549-2. Epub 2012 Jul 5.
In this article we further develop the theory of adaptive dynamics of function-valued traits. Previous work has concentrated on models for which invasion fitness can be written as an integral in which the integrand for each argument value is a function of the strategy value at that argument value only. For this type of models of direct effect, singular strategies can be found using the calculus of variations, with singular strategies needing to satisfy Euler's equation with environmental feedback. In a broader, more mechanistically oriented class of models, the function-valued strategy affects a process described by differential equations, and fitness can be expressed as an integral in which the integrand for each argument value depends both on the strategy and on process variables at that argument value. In general, the calculus of variations cannot help analyzing this much broader class of models. Here we explain how to find singular strategies in this class of process-mediated models using optimal control theory. In particular, we show that singular strategies need to satisfy Pontryagin's maximum principle with environmental feedback. We demonstrate the utility of this approach by studying the evolution of strategies determining seasonal flowering schedules.
在本文中,我们进一步发展了函数值性状的自适应动力学理论。先前的工作主要集中在入侵适应度可写成积分形式的模型上,其中每个自变量值的被积函数仅为该自变量值处策略值的函数。对于这种直接效应类型的模型,可使用变分法找到奇异策略,奇异策略需要满足带有环境反馈的欧拉方程。在更广泛、更具机制导向性的一类模型中,函数值策略会影响由微分方程描述的过程,适应度可表示为一个积分,其中每个自变量值的被积函数既取决于策略,也取决于该自变量值处的过程变量。一般来说,变分法无助于分析这类更广泛的模型。在此我们解释如何使用最优控制理论在这类过程介导模型中找到奇异策略。特别地,我们表明奇异策略需要满足带有环境反馈的庞特里亚金极大值原理。我们通过研究决定季节性开花时间表的策略演变来证明这种方法的实用性。