ArticleJournal of the Royal Society, Interface2019
Bumblebees learn foraging routes through exploitation-exploration cycles.
Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A review on exploration-exploitation trade-off in psychiatric disorders.BMC psychiatry · 2025Pooled it
- Behavioral Resistance in Varroa destructor: First Evidence in Response to Acaricide?Archives of insect biochemistry and physiology · 2026Article
- Greater pollen-mediated gene flow among than within populations of a bumblebee-pollinated forest herb despite habitat fragmentation.Movement ecology · 2026Article
- The diversity of lepidopteran spatial orientation strategies - neuronal mechanisms and emerging challenges in a changing world.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2026Review
- Duration discrimination in the bumblebeeBiology letters · 2025Article
- Foraging ants as liquid brains: Movement heterogeneity shapes collective efficiency.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Foraging with your eyes: a novel task to study cognitive strategies involved in (visual) foraging behaviour.Cognitive processing · 2025Article
- Consistent long-distance foraging flights across years and seasons at colony level in a neotropical bat.Biology letters · 2024Article
- The function of episodic memory in animals.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- Multiple and subject-specific roles of uncertainty in reward-guided decision-making.bioRxiv : the preprint server for biology · 2024Article
- Using motion-detection cameras to monitor foraging behaviour of individual butterflies.Ecology and evolution · 2024Article
- Reinforcement learning as a robotics-inspired framework for insect navigation: from spatial representations to neural implementation.Frontiers in computational neuroscience · 2024Article
- The relevance of a right scale for sampling when studying high-resolution behavioral dynamics.Scientific reports · 2023Article
- Plasmodium sporozoite search strategy to locate hotspots of blood vessel invasion.Nature communications · 2023Article
- When complex movement yields simple dispersal: behavioural heterogeneity, spatial spread and parasitism in groups of micro-wasps.Movement ecology · 2023Article
- The value of spatial experience and group size for ant colonies in direct competition.Insect science · 2023Article
- The Case for Octopus Consciousness: Valence.NeuroSci · 2022Review
- Individual exploration and selective social learning: balancing exploration-exploitation trade-offs in collective foraging.Journal of the Royal Society, Interface · 2022Article
- Hummingbirds modify their routes to avoid a poor location.Learning & behavior · 2022Article
- Computational Approaches and Tools as Applied to the Study of Rhythms and Chaos in Biology.Methods in molecular biology (Clifton, N.J.) · 2022Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
How animals explore and acquire knowledge from the environment is a key question in movement ecology. For pollinators that feed on multiple small replenishing nectar resources, the challenge is to learn efficient foraging routes while dynamically acquiring spatial information about new resource locations. Here, we use the behavioural mapping t-Stochastic Neighbouring Embedding algorithm and Shannon entropy to statistically analyse previously published sampling patterns of bumblebees feeding on artificial flowers in the field. We show that bumblebees modulate foraging excursions into distinctive behavioural strategies, characterizing the trade-off dynamics between (i) visiting and exploiting flowers close to the nest, (ii) searching for new routes and resources, and (iii) exploiting learned flower visitation sequences. Experienced bees combine these behavioural strategies even after they find an optimal route minimizing travel distances between flowers. This behavioural variability may help balancing energy costs-benefits and facilitate rapid adaptation to changing environments and the integration of more profitable resources in their routes.
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