A model of resource partitioning between foraging bees based on learning

PLoS Comput Biol. 2021 Jul 28;17(7):e1009260. doi: 10.1371/journal.pcbi.1009260. eCollection 2021 Jul.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Bees / physiology*
  • Behavior, Animal / physiology
  • Computational Biology
  • Computer Simulation
  • Feeding Behavior / physiology
  • Flight, Animal / physiology
  • Flowers
  • Learning / physiology
  • Models, Biological*
  • Pollination
  • Reinforcement, Psychology
  • Systems Analysis

Grants and funding

TD was funded by a co-tutelle PhD grant from the University Paul Sabatier (Toulouse) and Macquarie University (Sydney). ABB was supported by the Templeton World Charity Foundation project grant TWCF0266. CP and ML were supported by research grants of the Agence Nationale de la Recherche (ANR-16-CE02-0002-01, ANR-19-CE37-0024, ANR-20-ERC8-0004-01) to ML. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.