Adaptive behavioural strategies promote species persistence in niche-constrained ecological communities

Abstract Species persistence in ecosystems results from the interplay between ecological interactions and behavioural strategies. Classical niche theory explains how resource overlap determines the strength of interactions, while evolutionary game theory (EGT) describes how cooperation and defection strategies arise from payoff-dependent decisions. Most eco-evolutionary models assume that strategies remain fixed over generations, overlooking the potential for behavioural adjustments on ecological time scales. Here, we develop a mathematical framework that integrates Lotka–Volterra niche competition (LVNC) dynamics with an adaptive strategy model, allowing species to update their strategies based on the payoff-sensitive Fermi rule. We examine community outcomes on four symmetric games: prisoner's dilemma (PD), snowdrift, stag hunt (SH) and trivial (TR) (also known as harmony), implemented on networks with varying topologies and connectivity. We find that adaptive strategy updates significantly reduce the likelihood of species extinction in comparison to static strategies, enabling coexistence in payoff regions that would otherwise lead to collapse. The structure of the network plays an important role in determining persistence, particularly in snowdrift and PD games. Furthermore, regular ecological networks may experience abrupt extinction with changes in connectivity, whereas scale-free networks support persistence through cooperative hubs. Overall, our results demonstrate that behavioural adaptation is pivotal in promoting species persistence, more so than network architecture alone.

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Publication Details

Journal
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
Published
2026-08-19
DOI
https://doi.org/10.1098/rspa.2026.0009
Primary Topic
Evolutionary Game Theory and Cooperation
Type
article
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article

Adaptive behavioural strategies promote species persistence in niche-constrained ecological communities

Subhendu Bhandary, Partha Sharathi Dutta
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
Evolutionary Game Theory and Cooperation
article

Adaptive behavioural strategies promote species persistence in niche-constrained ecological communities

Subhendu Bhandary, Partha Sharathi Dutta
article en

Abstract

Abstract Species persistence in ecosystems results from the interplay between ecological interactions and behavioural strategies. Classical niche theory explains how resource overlap determines the strength of interactions, while evolutionary game theory (EGT) describes how cooperation and defection strategies arise from payoff-dependent decisions. Most eco-evolutionary models assume that strategies remain fixed over generations, overlooking the potential for behavioural adjustments on ecological time scales. Here, we develop a mathematical framework that integrates Lotka–Volterra niche competition (LVNC) dynamics with an adaptive strategy model, allowing species to update their strategies based on the payoff-sensitive Fermi rule. We examine community outcomes on four symmetric games: prisoner's dilemma (PD), snowdrift, stag hunt (SH) and trivial (TR) (also known as harmony), implemented on networks with varying topologies and connectivity. We find that adaptive strategy updates significantly reduce the likelihood of species extinction in comparison to static strategies, enabling coexistence in payoff regions that would otherwise lead to collapse. The structure of the network plays an important role in determining persistence, particularly in snowdrift and PD games. Furthermore, regular ecological networks may experience abrupt extinction with changes in connectivity, whereas scale-free networks support persistence through cooperative hubs. Overall, our results demonstrate that behavioural adaptation is pivotal in promoting species persistence, more so than network architecture alone.

Proceedings of the Royal Society A Mathematical Physical and Engineering SciencesVol. 482(2344)
Indian Institute of Technology Ropar (IN), Technische Universität Dresden (DE)
Openalex Percentile: Top 4%
Evolutionary Game Theory and Cooperation
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