| Bumblebees learn to forage like Bayesians. | |
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MedLine Citation:
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PMID: 19630548 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Bayesian foraging in patchy environments requires that foragers have information about the distribution of resources among patches (prior information), either set by natural selection or learned from past experience. We test the hypothesis that bumblebee foragers can rapidly learn prior information from past experience in two very different experimental environments. In the high-variance environment (patches of low and high quality), stochastic optimality models predicted that finding rewards should sometimes sharply increase an optimal forager's tendency to stay in a patch (an incremental response), whereas in the uniform environment, finding rewards should always decrease the tendency to stay (a decremental response). We use Cox regression models to show that, in a matter of hours, bees learned to match both predicted responses, resulting in a reward intake rate that averaged 80% of the predicted maximum. Following training in either environment, bees' adaptive behavior carried over to a common test environment, thus confirming the influence of memorized prior information. Although Bayesian foraging by learning is often presumed, this study is the first to clearly isolate the adaptive use of a learned prior expectation. More generally, it highlights the remarkable adaptive plasticity of an important generalist pollinator and agent of selection. |
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Authors:
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Jay M Biernaskie; Steven C Walker; Robert J Gegear |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: The American naturalist Volume: 174 ISSN: 1537-5323 ISO Abbreviation: Am. Nat. Publication Date: 2009 Sep |
Date Detail:
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Created Date: 2009-08-05 Completed Date: 2009-10-01 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 2984688R Medline TA: Am Nat Country: United States |
Other Details:
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Languages: eng Pagination: 413-23 Citation Subset: IM |
Affiliation:
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Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario M5S 3B2, Canada. jay.biernaskie@utoronto.ca |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Adaptation, Biological Animals Bees / physiology* Behavior, Animal Learning Male |
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