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    Complex evolutionary interactions in multiple populations

    Kaipeng Hu1, Pengyue Wang1, Junzhou He1, Matjaž Perc2,3,4,5,6, and Lei Shi1,7,*

    • 1School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming 650221, China
    • 2Faculty of Natural Sciences and Mathematics, University of Maribor, 2000 Maribor, Slovenia
    • 3Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 404332, Taiwan
    • 4Alma Mater Europaea, 2000 Maribor, Slovenia
    • 5Complexity Science Hub Vienna, 1080 Vienna, Austria
    • 6Department of Physics, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, Republic of Korea
    • 7Interdisciplinary Research Institute of Data Science, Shanghai Lixin University of Accounting and Finance, Shanghai 201209, China

    • *lshi@ynufe.edu.cn

    Phys. Rev. E 107, 044301 – Published 12 April, 2023

    DOI: https://doi.org/10.1103/PhysRevE.107.044301

    Abstract

    In competitive settings that entail several populations, individuals often engage in intra- and interpopulation interactions that determine their fitness and evolutionary success. With this simple motivation, we here study a multipopulation model where individuals engage in group interactions within their own population and in pairwise interactions with individuals from different populations. We use the evolutionary public goods game and the prisoner's dilemma game to describe these group and pairwise interactions, respectively. We also take into account asymmetry in the extent to which group and pairwise interactions determine the fitness of individuals. We find that interactions across multiple populations reveal new mechanisms through which the evolution of cooperation can be promoted, but this depends on the level of interaction asymmetry. If inter- and intrapopulation interactions are symmetric, the sole presence of multiple populations promotes the evolution of cooperation. Asymmetry in the interactions can further promote cooperation at the expense of the coexistence of the competing strategies. An in-depth analysis of the spatiotemporal dynamics reveals loop-dominated structures and pattern formation that can explain the various evolutionary outcomes. Thus, complex evolutionary interactions in multiple populations reveal an intricate interplay between cooperation and coexistence, and they also open up the path toward further explorations of multipopulation games and biodiversity.

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