Interaction intensity in strategic fitness: A quantifying yardstick of selection optimization for evolutionary game

IF 1.9 4区 数学 Q2 BIOLOGY Mathematical Biosciences Pub Date : 2024-06-25 DOI:10.1016/j.mbs.2024.109241
Ritesh Kumar Bera , Sourav Rana , Sabyasachi Bhattacharya
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Abstract

The notion of the fitness of a strategy has been assimilated as the reproductive success in the evolutionary game. Initially, this fitness was tied to the game’s pay-off and the strategy’s relative frequency. However, density dependence becomes exigent in order to make ecologically reliable fitness. However, the contributions of each different type of interaction to the species’s overall growth process were surprisingly under-explored. This oversight has occasionally led to either more or less prediction of strategy selection compared to the actual possibility. Moreover, density regulation of the population has always been analysed in a general way compared to strategy selection. In this context, our study introduces the concept of mean relative death payoff, which helps in assessing interaction intensity coefficients and integrates them into strategic fitness. Based on this fitness function, we develop the frequency-density replicator dynamics, which eventually provides distinguishing criteria for directional and balancing selection. Our optimized, evolutionarily stable strategy emerges as a superior alternative to the conventional trade-off between selection forces and ecological processes. More significantly, mean relative death pay-off has both conditional and quantitative roles in getting a stable population size. As a case study, we have extensively analysed the evolution of aggression using the Hawk-Dove game. We have shown that pure Dove selection is always beneficial for species growth rather than pure Hawk selection, and the condition of selection is dependent on external mortality pressure. However, the condition of coexistence is independent of external mortality pressure, representing a strong evolutionary selection that optimizes population density governed by interaction intensity.

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战略适应性中的交互强度:进化博弈选择优化的量化标准
一种策略的适应性概念已被同化为进化游戏中的繁殖成功。最初,这种适应性与博弈的收益和策略的相对频率相关。然而,为了获得生态学上可靠的适应性,密度依赖性变得非常重要。然而,每种不同类型的相互作用对物种整体生长过程的贡献却出人意料地没有得到充分探讨。这种疏忽有时会导致对策略选择的预测多于或少于实际可能性。此外,与策略选择相比,对种群密度调节的分析总是比较笼统。在这种情况下,我们的研究引入了平均相对死亡报酬的概念,这有助于评估交互强度系数,并将其纳入策略适应度。在此适应度函数的基础上,我们开发了频率密度复制器动力学,最终为青色定向选择和平衡选择提供了区分标准。我们的优化、进化稳定的战略是传统的选择力与生态过程之间权衡的一个优越替代方案。更重要的是,平均相对死亡报酬对获得稳定的种群数量具有条件性和定量性作用。作为一个案例研究,我们利用鹰-鸽博弈广泛分析了攻击性的进化。结果表明,纯粹的鸽子选择比纯粹的鹰选择更有利于物种的增长,而选择的条件取决于外部的死亡压力。然而,共存的条件与外部死亡压力无关,这代表了一种强烈的进化选择,即通过互动强度优化种群密度。
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来源期刊
Mathematical Biosciences
Mathematical Biosciences 生物-生物学
CiteScore
7.50
自引率
2.30%
发文量
67
审稿时长
18 days
期刊介绍: Mathematical Biosciences publishes work providing new concepts or new understanding of biological systems using mathematical models, or methodological articles likely to find application to multiple biological systems. Papers are expected to present a major research finding of broad significance for the biological sciences, or mathematical biology. Mathematical Biosciences welcomes original research articles, letters, reviews and perspectives.
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