Tarnita, C. | Search bioRxiv

bioRxiv2026

Evolution of informed dispersal strategies in trophic meta-communities

Living organisms move and their movement is both a response to local conditions and, often, the cause of change in those conditions. This feedback loop is often overlooked in theoretical studies on the evolution of dispersal, which assume that either the decision to leave is uninformed or that the local conditions are exogenously driven. Here, we embrace the feedback loop and study what dispersal strategies evolve in a trophic meta-population where the dynamics are entirely endogenous. We show that there are five possible classes of strategies that can evolve depending on the ecological conditions: leaving once local conditions fall low enough (Unsaturated), having an extended stay even under adverse conditions (Saturated), leaving from a high quality location (Anxious), leaving independently of the location state (Ignorant), and completely abstaining from dispersal (No-dispersal). The Unsaturated class captures the classical prediction of the marginal value theorem, while the other four extend the range of possible evolutionarily optimal strategies. Which class of strategies evolves depends on the kind of information being sensed (resource availability versus conspecifics density), the size of the local consumer population at equilibrium, and the stability of this equilibrium. Our results provide a theoretical underpinning for the diversity of movement strategies observed in nature that deviate from classic predictions and suggest a comparative framework that can inform experimental design.

evolutionary biology↗

bioRxiv2024

Reconciling ecology and evolutionary game theory or When not to think cooperation

Evolutionary game theory (EGT)--overwhelmingly employed today for the study of cooperation in a variety of systems, from microbes to cancer and from insect to human societies--started with the seminal 1973 paper by John Maynard Smith and George Price [1], in which they probed the logic of limited war in animal conflict. If fighting was essential to get access to mates and territory, then why did fights rarely lead to serious injury? Maynard Smith and Price developed game theory to show that limited war can be selected at the individual level. Owing to the explanatory potential of this first paper, and enabled by the elegant and powerful machinery of the soon-to-be-developed replicator dynamics [2, 3], EGT took off at an accelerated pace and began to shape expectations across systems and scales. But, even as it expanded its reach from animals to microbes [4-8] and from microbes to cancer [9-11], the field did not revisit a fundamental assumption of that first paper, which subsequently got weaved into the very fabric of the framework--that individual differences in reproduction are determined only by payoff from the game (i.e. in isolation, all individuals, regardless of strategy, were assumed to have identical intrinsic growth rates). Here, we argue that this original assumption substantially limits the scope of EGT. But, because it is not explicitly presented as a caveat, predictions of EGT have been empirically tested broadly across real systems, where the intrinsic growth rates are generally not equal. That has, unsurprisingly, led to puzzling findings and contentious debates [7, 12-15]. Flagging the high potential for confusion to arise from applications of EGT to empirical systems that it is not designed to study and suggesting a way forward constitute our main motivation for this work. In the process, we reestablish a dialog with ecology that can be fruitful both ways, e.g., by providing a so-far-elusive explanation for how diverse ecological communities can assemble evolutionarily.

evolutionary biology↗