Literature DB >> 20973670

Travel optimization by foraging bumblebees through readjustments of traplines after discovery of new feeding locations.

Mathieu Lihoreau1, Lars Chittka, Nigel E Raine.   

Abstract

Animals collecting resources that replenish over time often visit patches in predictable sequences called traplines. Despite the widespread nature of this strategy, we still know little about how spatial memory develops and guides individuals toward suitable routes. Here, we investigate whether flower visitation sequences by bumblebees Bombus terrestris simply reflect the order in which flowers were discovered or whether they result from more complex navigational strategies enabling bees to optimize their foraging routes. We analyzed bee flight movements in an array of four artificial flowers maximizing interfloral distances. Starting from a single patch, we sequentially added three new patches so that if bees visited them in the order in which they originally encountered flowers, they would follow a long (suboptimal) route. Bees' tendency to visit patches in their discovery order decreased with experience. Instead, they optimized their flight distances by rearranging flower visitation sequences. This resulted in the development of a primary route (trapline) and two or three less frequently used secondary routes. Bees consistently used these routes after overnight breaks while occasionally exploring novel possibilities. We discuss how maintaining some level of route flexibility could allow traplining animals to cope with dynamic routing problems, analogous to the well-known traveling salesman problem.

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Mesh:

Year:  2010        PMID: 20973670     DOI: 10.1086/657042

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  33 in total

1.  FLOBOTS: ROBOTIC FLOWERS FOR BEE BEHAVIOUR EXPERIMENTS.

Authors:  Carla J Essenberg
Journal:  J Pollinat Ecol       Date:  2015

2.  Olfactory searches with limited space perception.

Authors:  Jean-Baptiste Masson
Journal:  Proc Natl Acad Sci U S A       Date:  2013-06-26       Impact factor: 11.205

3.  Adding landscape genetics and individual traits to the ecosystem function paradigm reveals the importance of species functional breadth.

Authors:  Antonio R Castilla; Nathaniel S Pope; Megan O'Connell; María F Rodriguez; Laurel Treviño; Alonso Santos; Shalene Jha
Journal:  Proc Natl Acad Sci U S A       Date:  2017-11-10       Impact factor: 11.205

Review 4.  Treating hummingbirds as feathered bees: a case of ethological cross-pollination.

Authors:  D J Pritchard; M C Tello Ramos; F Muth; S D Healy
Journal:  Biol Lett       Date:  2017-12-06       Impact factor: 3.703

Review 5.  Using natural travel paths to infer and compare primate cognition in the wild.

Authors:  Karline R L Janmaat; Miguel de Guinea; Julien Collet; Richard W Byrne; Benjamin Robira; Emiel van Loon; Haneul Jang; Dora Biro; Gabriel Ramos-Fernández; Cody Ross; Andrea Presotto; Matthias Allritz; Shauhin Alavi; Sarie Van Belle
Journal:  iScience       Date:  2021-04-15

6.  Onset of morning activity in bumblebee foragers under natural low light conditions.

Authors:  Katie Hall; Théo Robert; Kevin J Gaston; Natalie Hempel de Ibarra
Journal:  Ecol Evol       Date:  2021-05-01       Impact factor: 2.912

7.  Numerical cognition in bees and other insects.

Authors:  Mario Pahl; Aung Si; Shaowu Zhang
Journal:  Front Psychol       Date:  2013-04-18

8.  Unravelling the mechanisms of trapline foraging in bees.

Authors:  Mathieu Lihoreau; Nigel E Raine; Andrew M Reynolds; Ralph J Stelzer; Ka S Lim; Alan D Smith; Juliet L Osborne; Lars Chittka
Journal:  Commun Integr Biol       Date:  2013-01-01

9.  Radar tracking and motion-sensitive cameras on flowers reveal the development of pollinator multi-destination routes over large spatial scales.

Authors:  Mathieu Lihoreau; Nigel E Raine; Andrew M Reynolds; Ralph J Stelzer; Ka S Lim; Alan D Smith; Juliet L Osborne; Lars Chittka
Journal:  PLoS Biol       Date:  2012-09-20       Impact factor: 8.029

10.  A simple iterative model accurately captures complex trapline formation by bumblebees across spatial scales and flower arrangements.

Authors:  Andrew M Reynolds; Mathieu Lihoreau; Lars Chittka
Journal:  PLoS Comput Biol       Date:  2013-03-07       Impact factor: 4.475

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