4.7 Article

Trade-off between travel distance and prioritization of high-reward sites in traplining bumblebees

Journal

FUNCTIONAL ECOLOGY
Volume 25, Issue 6, Pages 1284-1292

Publisher

WILEY-BLACKWELL
DOI: 10.1111/j.1365-2435.2011.01881.x

Keywords

Bombus terrestris; distance reward trade-off; optimal foraging theory; spatial cognition; trapline foraging; Travelling Salesman Problem

Categories

Funding

  1. Wellcome Trust
  2. Biotechnology and Biological Sciences Research Council
  3. Engineering and Physical Sciences Research Council [BB/F52765X/1]
  4. BBSRC [BB/F52765X/1] Funding Source: UKRI
  5. Biotechnology and Biological Sciences Research Council [BB/F52765X/1] Funding Source: researchfish

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1. Animals exploiting renewable resource patches are faced with complex multi-location routing problems. In many species, individuals visit foraging patches in predictable sequences called traplines. However, whether and how they optimize their routes remains poorly understood. 2. In this study, we demonstrate that traplining bumblebees (Bombus terrestris) make a trade-off between minimizing travel distance and prioritizing the most rewarding feeding locations. 3. Individual bees trained to forage on five artificial flowers of equal reward value selected the shortest possible route as a trapline. After introducing a single highly rewarding flower to the array, they re-adjusted their routes visiting the most rewarding flower first provided the departure distance from the shortest possible route remained small (18%). When routes optimizing the initial rate of reward intake were much longer (42%), bees prioritized short travel distances. 4. Under natural conditions, in which individual flowers vary in nectar productivity and replenish continuously, it might pay bees to prioritize highly rewarding locations, both to minimize the overall number of flowers to visit and to beat competitors. 5. We discuss how combined memories of location and quality of resource patches could allow bees and other traplining animals to optimize their routing decisions in heterogeneous environments.

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