Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Dubois, Thibault, Pasquaretta, Cristian, Barron, Andrew B., Gautrais, Jacques, Lihoreau, Mathieu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8351995/
https://www.ncbi.nlm.nih.gov/pubmed/34319987
http://dx.doi.org/10.1371/journal.pcbi.1009260
_version_ 1783736089092030464
author Dubois, Thibault
Pasquaretta, Cristian
Barron, Andrew B.
Gautrais, Jacques
Lihoreau, Mathieu
author_facet Dubois, Thibault
Pasquaretta, Cristian
Barron, Andrew B.
Gautrais, Jacques
Lihoreau, Mathieu
author_sort Dubois, Thibault
collection PubMed
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 Online
Article
Text
id pubmed-8351995
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-83519952021-08-10 A model of resource partitioning between foraging bees based on learning Dubois, Thibault Pasquaretta, Cristian Barron, Andrew B. Gautrais, Jacques Lihoreau, Mathieu PLoS Comput Biol Research Article 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. Public Library of Science 2021-07-28 /pmc/articles/PMC8351995/ /pubmed/34319987 http://dx.doi.org/10.1371/journal.pcbi.1009260 Text en © 2021 Dubois et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Dubois, Thibault
Pasquaretta, Cristian
Barron, Andrew B.
Gautrais, Jacques
Lihoreau, Mathieu
A model of resource partitioning between foraging bees based on learning
title 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_short A model of resource partitioning between foraging bees based on learning
title_sort model of resource partitioning between foraging bees based on learning
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8351995/
https://www.ncbi.nlm.nih.gov/pubmed/34319987
http://dx.doi.org/10.1371/journal.pcbi.1009260
work_keys_str_mv AT duboisthibault amodelofresourcepartitioningbetweenforagingbeesbasedonlearning
AT pasquarettacristian amodelofresourcepartitioningbetweenforagingbeesbasedonlearning
AT barronandrewb amodelofresourcepartitioningbetweenforagingbeesbasedonlearning
AT gautraisjacques amodelofresourcepartitioningbetweenforagingbeesbasedonlearning
AT lihoreaumathieu amodelofresourcepartitioningbetweenforagingbeesbasedonlearning
AT duboisthibault modelofresourcepartitioningbetweenforagingbeesbasedonlearning
AT pasquarettacristian modelofresourcepartitioningbetweenforagingbeesbasedonlearning
AT barronandrewb modelofresourcepartitioningbetweenforagingbeesbasedonlearning
AT gautraisjacques modelofresourcepartitioningbetweenforagingbeesbasedonlearning
AT lihoreaumathieu modelofresourcepartitioningbetweenforagingbeesbasedonlearning