Time scales and wave formation in non-linear spatial public goods games

IF 3.6 2区 生物学 PLoS Computational Biology Pub Date : 2019-09-01 DOI:10.1371/journal.pcbi.1007361
Gregory J. Kimmel, P. Gerlee, P. Altrock
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引用次数: 9

Abstract

The co-evolutionary dynamics of competing populations can be strongly affected by frequency-dependent selection and spatial population structure. As co-evolving populations grow into a spatial domain, their initial spatial arrangement and their growth rate differences are important factors that determine the long-term outcome. We here model producer and free-rider co-evolution in the context of a diffusive public good (PG) that is produced by the producers at a cost but evokes local concentration-dependent growth benefits to all. The benefit of the PG can be non-linearly dependent on public good concentration. We consider the spatial growth dynamics of producers and free-riders in one, two and three dimensions by modeling producer cell, free-rider cell and public good densities in space, driven by the processes of birth, death and diffusion (cell movement and public good distribution). Typically, one population goes extinct, but the time-scale of this process varies with initial conditions and the growth rate functions. We establish that spatial variation is transient regardless of dimensionality, and that structured initial conditions lead to increasing times to get close to an extinction state, called ε-extinction time. Further, we find that uncorrelated initial spatial structures do not influence this ε-extinction time in comparison to a corresponding well-mixed (non-spatial) system. In order to estimate the ε-extinction time of either free-riders or producers we derive a slow manifold solution. For invading populations, i.e. for populations that are initially highly segregated, we observe a traveling wave, whose speed can be calculated. Our results provide quantitative predictions for the transient spatial dynamics of cooperative traits under pressure of extinction.
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非线性空间公共产品博弈中的时间尺度与波浪形成
频率依赖性选择和种群空间结构会强烈影响竞争种群的协同进化动态。当共同进化的种群成长为一个空间域时,它们的初始空间排列和生长速率差异是决定长期结果的重要因素。我们在这里模拟生产者和搭便车者在扩散公共产品(PG)的背景下的共同进化,这种公共产品是由生产者以成本生产的,但唤起了当地集中度依赖的增长利益。PG的利益可以非线性地依赖于公共产品的集中。在生、死和扩散(细胞运动和公共产品分布)的驱动下,我们通过对生产者细胞、搭便车细胞和公共产品密度的空间建模,在一、二和三维空间中考虑生产者和搭便车者的空间增长动态。通常,一个种群灭绝,但这一过程的时间尺度随初始条件和增长率函数而变化。我们确定了空间变化是短暂的,而与维度无关,并且结构化的初始条件导致增加时间以接近消光状态,称为ε-消光时间。此外,我们发现与相应的良好混合(非空间)系统相比,不相关的初始空间结构不影响ε-消光时间。为了估计搭便车者或生产者的ε-消光时间,我们导出了一个慢流形解。对于入侵的种群,即最初高度隔离的种群,我们观察到一种行波,其速度可以计算出来。我们的研究结果为合作性状在灭绝压力下的瞬时空间动态提供了定量预测。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology 生物-生化研究方法
CiteScore
7.10
自引率
4.70%
发文量
820
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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