The Spatial Dynamics of Predators and the Benefits and Costs of Sharing Information

Matthieu Barbier and James R Watson

PLOS Computational Biology, 2016, vol. 12, issue 10, 1-22

Abstract: Predators of all kinds, be they lions hunting in the Serengeti or fishermen searching for their catch, display various collective strategies. A common strategy is to share information about the location of prey. However, depending on the spatial characteristics and mobility of predators and prey, information sharing can either improve or hinder individual success. Here, our goal is to investigate the interacting effects of space and information sharing on predation efficiency, represented by the expected rate at which prey are found and consumed. We derive a feeding functional response that accounts for both spatio-temporal heterogeneity and communication, and validate this mathematical analysis with a computational agent-based model. This agent-based model has an explicit yet minimal representation of space, as well as information sharing about the location of prey. The analytical model simplifies predator behavior into a few discrete states and one essential trade-off, between the individual benefit of acquiring information and the cost of creating spatial and temporal correlation between predators. Despite the absence of an explicit spatial dimension in these equations, they quantitatively predict the predator consumption rates measured in the agent-based simulations across the explored parameter space. Together, the mathematical analysis and agent-based simulations identify the conditions for when there is a benefit to sharing information, and also when there is a cost.Author Summary: When should we work together and when should we work alone? This question is central to our efforts to understand social and ecological systems alike, from lions hunting in the Serengeti to fishermen searching for their catch. Here, we develop a mathematical modeling framework to identify the essential spatial factors controlling the benefits and costs of sharing information. Our approach marries computation with mathematical analysis, and our results highlight that it is only under certain spatial conditions that information sharing is a useful cooperative strategy. Notably, we find conditions for which fully collective and fully individual search are both attractive.

Date: 2016
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1005147

DOI: 10.1371/journal.pcbi.1005147

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