Argasinski K, Broom M
Institute of Mathematics of Polish Academy of Sciences, ul. Śniadeckich 8, 00-956, Warszawa 10, Poland.
Department of Mathematics, City, University of London, Northampton Square, London, EC1V 0HB, UK.
Theory Biosci. 2018 Apr;137(1):33-50. doi: 10.1007/s12064-017-0257-y. Epub 2017 Nov 20.
In this paper we are concerned with how aggregated outcomes of individual behaviours, during interactions with other individuals (games) or with environmental factors, determine the vital rates constituting the growth rate of the population. This approach needs additional elements, namely the rates of event occurrence (interaction rates). Interaction rates describe the distribution of the interaction events in time, which seriously affects the population dynamics, as is shown in this paper. This leads to the model of a population of individuals playing different games, where focal game affected by the considered trait can be extracted from the general model, and the impact on the dynamics of other events (which is not neutral) can be described by an average background fertility and mortality. This leads to a distinction between two types of background fitness, strategically neutral elements of the focal games (correlated with the focal game events) and the aggregated outcomes of other interactions (independent of the focal game). The new approach is useful for clarification of the biological meaning of concepts such as weak selection. Results are illustrated by a Hawk-Dove example.
在本文中,我们关注的是个体行为在与其他个体互动(博弈)或与环境因素互动期间的聚合结果如何决定构成种群增长率的生命率。这种方法需要额外的要素,即事件发生率(互动率)。互动率描述了互动事件在时间上的分布,正如本文所示,这严重影响种群动态。这就引出了一个个体群体参与不同博弈的模型,其中受所考虑特征影响的焦点博弈可以从一般模型中提取出来,而对其他事件动态的影响(并非中性)可以用平均背景生育率和死亡率来描述。这导致了两种类型的背景适应性之间的区别,焦点博弈的策略中性要素(与焦点博弈事件相关)以及其他互动的聚合结果(与焦点博弈无关)。这种新方法有助于阐明诸如弱选择等概念的生物学意义。结果通过鹰鸽博弈的例子进行说明。