Success-biased social learning in a one-consumer, two-resource model

Talia Borofsky and Marcus W. Feldman

Theoretical Population Biology, 2022, vol. 146, issue C, 29-35

Abstract: Previous analyses have predicted that social learning should not evolve in a predator–prey system. Here we examine whether success-biased social learning, by which social learners copy successful demonstrators, allows social learning by foragers to evolve. We construct a one-predator, two-prey system in which foragers must learn how to feed on depletable prey populations in an environment where foraging information can be difficult to obtain individually. We analyze two models in which social learning is success-biased: in the first, individual learning does not depend on the resource dynamics, and in the second model it depends on the relative frequency of the resource. Unlike previous results, we find that social learning does not cause predators to over-harvest one type of prey over the other. Furthermore, increasing the probability of social learning increases the probability of learning a successful foraging behavior, especially when individually learned information tends to be inaccurate. Whereas social learning does not evolve among individual learners in the first model, the assumption of resource-dependent learning in the second model allows a mutant with an increased probability of social learning to spread through the forager population.

Keywords: Individual learning; Success-biased social learning; Predator–prey (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040580922000399
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:thpobi:v:146:y:2022:i:c:p:29-35

DOI: 10.1016/j.tpb.2022.05.004

Access Statistics for this article

Theoretical Population Biology is currently edited by Jeremy Van Cleve

More articles in Theoretical Population Biology from Elsevier
Bibliographic data for series maintained by Catherine Liu ().