Burgess Andrew E F, Lorenzi Tommaso, Schofield Pietà G, Hubbard Stephen F, Chaplain Mark A J
Division of Mathematics, University of Dundee, Dundee DD1 4HN, Scotland, United Kingdom.
School of Mathematics and Statistics, University of St Andrews, St Andrews KY16 9SS, United Kingdom.
J Theor Biol. 2017 Apr 21;419:323-332. doi: 10.1016/j.jtbi.2017.02.028. Epub 2017 Feb 27.
The emergence of cooperation is a major conundrum of evolutionary biology. To unravel this evolutionary riddle, several models have been developed within the theoretical framework of spatial game theory, focussing on the interactions between two general classes of player, "cooperators" and "defectors". Generally, explicit movement in the spatial domain is not considered in these models, with strategies moving via imitation or through colonisation of neighbouring sites. We present here a spatially explicit stochastic individual-based model in which pure cooperators and defectors undergo random motion via diffusion and also chemotaxis guided by the gradient of a semiochemical. Individual movement rules are derived from an underlying system of reaction-diffusion-taxis partial differential equations which describes the dynamics of the local number of individuals and the concentration of the semiochemical. Local interactions are governed by the payoff matrix of the classical prisoner's dilemma, and accumulated payoffs are translated into offspring. We investigate the cases of both synchronous and non-synchronous generations. Focussing on an ecological scenario where defectors are parasitic on cooperators, we find that random motion and semiochemical sensing bring about self-generated patterns in which resident cooperators and parasitic defectors can coexist in proportions that fluctuate about non-zero values. Remarkably, coexistence emerges as a genuine consequence of the natural tendency of cooperators to aggregate into clusters, without the need for them to find physical shelter or outrun the parasitic defectors. This provides further evidence that spatial clustering enhances the benefits of mutual cooperation and plays a crucial role in preserving cooperative behaviours.
合作的出现是进化生物学中的一个主要难题。为了解开这个进化之谜,在空间博弈论的理论框架内已经开发了几种模型,重点关注两类一般参与者“合作者”和“背叛者”之间的相互作用。一般来说,这些模型不考虑空间域中的明确移动,策略通过模仿或邻近位点的殖民化来移动。我们在此提出一个空间明确的基于个体的随机模型,其中纯合作者和背叛者通过扩散以及由信息素梯度引导的趋化作用进行随机运动。个体运动规则源自一个反应 - 扩散 - 趋化偏微分方程的基础系统,该系统描述了个体局部数量和信息素浓度的动态变化。局部相互作用由经典囚徒困境的收益矩阵控制,累积收益转化为后代。我们研究了同步和非同步世代的情况。聚焦于背叛者寄生在合作者身上的生态情景,我们发现随机运动和信息素感知会产生自我生成的模式,其中常驻合作者和寄生背叛者能够以围绕非零值波动的比例共存。值得注意的是,共存是合作者自然倾向于聚集形成簇的真正结果,而无需它们寻找物理庇护所或躲避寄生背叛者。这进一步证明了空间聚集增强了相互合作的益处,并在维持合作行为中发挥了关键作用。