A model of resource partitioning between foraging bees based on learning.

Central place foraging pollinators tend to develop multi-destination routes (traplines) to exploit patchily distributed plant resources. While the formation of traplines by individual pollinators has been studied in detail, how populations of foragers use resources in a common area is an open questi...

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Autores principales:	Thibault Dubois, Cristian Pasquaretta, Andrew B Barron, Jacques Gautrais, Mathieu Lihoreau
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/da6025b95210419e986a46e833057fc6
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id	oai:doaj.org-article:da6025b95210419e986a46e833057fc6
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spelling	oai:doaj.org-article:da6025b95210419e986a46e833057fc62021-12-02T19:57:21ZA model of resource partitioning between foraging bees based on learning.1553-734X1553-735810.1371/journal.pcbi.1009260https://doaj.org/article/da6025b95210419e986a46e833057fc62021-07-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009260https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Central place foraging pollinators tend to develop multi-destination routes (traplines) to exploit patchily distributed plant resources. While the formation of traplines by individual pollinators has been studied in detail, how populations of foragers use resources in a common area is an open question, difficult to address experimentally. We explored conditions for the emergence of resource partitioning among traplining bees using agent-based models built from experimental data of bumblebees foraging on artificial flowers. In the models, bees learn to develop routes as a consequence of feedback loops that change their probabilities of moving between flowers. While a positive reinforcement of movements leading to rewarding flowers is sufficient for the emergence of resource partitioning when flowers are evenly distributed, the addition of a negative reinforcement of movements leading to unrewarding flowers is necessary when flowers are patchily distributed. In environments with more complex spatial structures, the negative experiences of individual bees on flowers favour spatial segregation and efficient collective foraging. Our study fills a major gap in modelling pollinator behaviour and constitutes a unique tool to guide future experimental programs.Thibault DuboisCristian PasquarettaAndrew B BarronJacques GautraisMathieu LihoreauPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 7, p e1009260 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Thibault Dubois Cristian Pasquaretta Andrew B Barron Jacques Gautrais Mathieu Lihoreau A model of resource partitioning between foraging bees based on learning.
description	Central place foraging pollinators tend to develop multi-destination routes (traplines) to exploit patchily distributed plant resources. While the formation of traplines by individual pollinators has been studied in detail, how populations of foragers use resources in a common area is an open question, difficult to address experimentally. We explored conditions for the emergence of resource partitioning among traplining bees using agent-based models built from experimental data of bumblebees foraging on artificial flowers. In the models, bees learn to develop routes as a consequence of feedback loops that change their probabilities of moving between flowers. While a positive reinforcement of movements leading to rewarding flowers is sufficient for the emergence of resource partitioning when flowers are evenly distributed, the addition of a negative reinforcement of movements leading to unrewarding flowers is necessary when flowers are patchily distributed. In environments with more complex spatial structures, the negative experiences of individual bees on flowers favour spatial segregation and efficient collective foraging. Our study fills a major gap in modelling pollinator behaviour and constitutes a unique tool to guide future experimental programs.
format	article
author	Thibault Dubois Cristian Pasquaretta Andrew B Barron Jacques Gautrais Mathieu Lihoreau
author_facet	Thibault Dubois Cristian Pasquaretta Andrew B Barron Jacques Gautrais Mathieu Lihoreau
author_sort	Thibault Dubois
title	A model of resource partitioning between foraging bees based on learning.
title_short	A model of resource partitioning between foraging bees based on learning.
title_full	A model of resource partitioning between foraging bees based on learning.
title_fullStr	A model of resource partitioning between foraging bees based on learning.
title_full_unstemmed	A model of resource partitioning between foraging bees based on learning.
title_sort	model of resource partitioning between foraging bees based on learning.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/da6025b95210419e986a46e833057fc6
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_version_	1718375871722553344

A model of resource partitioning between foraging bees based on learning.

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