Evolution of strategic cooperation

Abstract

Group-beneficial behaviors have presented a long-standing challenge for evolutionary theory because, although their benefits are available to all group members, their costs are borne by individuals. Consequently, an individual could benefit from "cheating" their group mates by not paying the costs while still reaping the benefits. There have been many proposed evolutionary mechanisms that could favor cooperation (and disfavor cheating) in particular circumstances. However, if cooperation is still favored in some circumstances, then we might expect evolution to favor strategic cooperation, where the level of contribution toward groupbeneficial behavior is varied in response to the social context. To uncover how and why individuals should contribute toward group-beneficial behavior across social contexts, we model strategic cooperation as an evolutionary game where players can quantitatively adjust the amount they contribute toward group-beneficial behavior. We find that the evolutionarily stable strategy (ESS) predicts, unsurprisingly, that players should contribute in relation to their relatedness to the group. However, we surprisingly find that players often contribute to cooperation in such a way that their fitness is inverse to their relatedness to the group such that those that contribute to cooperation end up with the same return from group-beneficial behavior, essentially removing any potential advantage of higher relatedness. These results bring to light a paradox of group-beneficial cooperation: groups do best when they contain highly related individuals, but those with the highest relatedness to the group will often have the lowest fitness within the group. K E Y W O R D S : Cooperation, group selection, kin selection, public goods, social behavior. Impact SummaryWhat motivates organisms to contribute toward groupbeneficial behaviors? This question is challenging for evolutionary theory because such cooperative behaviors typically incur a personal cost, whereas their benefits are open to exploitation by everyone in the group-including noncontributors. To address this fundamental problem, we develop a simple game theoretical model of cooperation through "public goods." We allow the players in the game to strategically adjust their contributions to cooperation to understand how and why individuals should make costly contributions to the potential benefit of others. Our model elucidates how relatedness within groups molds cooperative strategies, revealing a paradoxical outcome that those with the highest relatedness to a group end up with the lowest fitness in the group. We also identify a surprising result, where individuals who contribute to cooperation do so in a way that leaves them with an equal fraction of the group's fitness, even if they have different levels of relatedness to the group. In addition to providing a clear framework that can be used to make testable empirical predictions, our model also provides a possible mechanism that can explain the maintenance of genetic variation in cooperative s...

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“…Systems established on cooperation instead of incentive are often more stable and prosperous. Evolution may favor those that collaborate and societies that include such individuals ( 153 ). When Lakota people pray together, saying, “ mitakuye Oyasin ,” translated “all my relations,” they embody and validate this community approach ( 154 ).…”

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“…The six equilibriums can be classified as separating (signaling), pooling, and polymorphic hybrid equilibriums, and they may possess different behavioral and payoff properties ( see Table 3 and Box S1 & S2). These equilibriums and stabilities can be significantly different, with different theoretical ramifications ( e.g ., Maynard-Smith & Harper 2003, Huttegger & Zollman 2001, Bergstrom & Lachmann 1997, 1998, Biernaskie et al 2018, Madgwick & Wolf 2020, Whitmeyer 2020). Practically, these six equilibriums can be mapped to three basic anti-pandemic policies.…”

“…S1 & S2). These equilibriums and stabilities can be significantly different, with different theoretical ramifications (e.g.,Maynard-Smith & Harper 2003, Huttegger & Zollman 2001, Bergstrom & Lachmann 1997, 1998, Biernaskie et al 2018, Madgwick & Wolf 2020, Whitmeyer 2020). Practically, these six equilibriums can be mapped to three basic anti-pandemic policies.Among the four fundamental anti-pandemic policies, the LOHC (low-risk open and high-risk closed) is essentially a middle ground of the two extreme policies: AC (always closed) and AO…”

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“…Theoretically, those ramifications have been extensively studied and well documented in the existing literatures (e.g., Maynard-Smith & Harper 2003, Huttegger & Zollman 2001, Bergstrom & Lachmann 1997, 1998, Biernaskie et al 2018, Madgwick & Wolf 2020, Whitmeyer 2020).…”

“…Furthermore, their stabilities can be dramatically different (Table 2), which may have different theoretical and practical ramifications. Theoretically, those ramifications have been extensively studied and well documented in the existing literatures ( e.g ., Maynard-Smith & Harper 2003, Huttegger & Zollman 2001, Bergstrom & Lachmann 1997, 1998, Biernaskie et al 2018, Madgwick & Wolf 2020, Whitmeyer 2020). However, their practical ramifications are much more complex, which we briefly discuss below.…”