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BeeDanceGap SIGNED

Honeybee communication: animal social learning at the height of social complexity

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 BeeDanceGap project word cloud

Explore the words cloud of the BeeDanceGap project. It provides you a very rough idea of what is the project "BeeDanceGap" about.

analyze    ecology    foraging    simply    integrates    dances    dance    molecular    secondly    pollinator    decline    elicit    ranges    food    brain    societies    communication    learning    vertebrate    drives    expression    ecological    honeybees    delve    complexity    models    imposing    takes    group    ultimate    location    differently    mechanisms    eusocial    individuals    centralized    contribution    pressing    flow    journey    diversity    disciplinary    networks    honeybee    world    uniquely    groups    generation    celebrated    global    deep    vast    gene    language    sciences    theme    unrecognized    kingdom    cutting    risk    edge    animal    proximate    bee    sophisticated    social    central    profiles    colony    never    profile    security    laboratory    transcriptomics    network    colonies    place    free    hard    gain    emerge    firstly    overwhelming    drivers    living    hive    track    replicate    territory    fundamental    powerful    tractable    shifts    understand    tools    natural    perspectives    diverse    unrivaled   

Project "BeeDanceGap" data sheet

The following table provides information about the project.

Coordinator
ROYAL HOLLOWAY AND BEDFORD NEW COLLEGE 

Organization address
address: EGHAM HILL UNIVERSITY OF LONDON
city: EGHAM
postcode: TW20 0EX
website: http://www.rhul.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website https://ellileadbeater.wixsite.com/beedancegap
 Total cost 1˙422˙010 €
 EC max contribution 1˙422˙010 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2014-STG
 Funding Scheme ERC-STG
 Starting year 2016
 Duration (year-month-day) from 2016-02-01   to  2021-01-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ROYAL HOLLOWAY AND BEDFORD NEW COLLEGE UK (EGHAM) coordinator 1˙320˙301.00
2    QUEEN MARY UNIVERSITY OF LONDON UK (LONDON) participant 54˙884.00
3    UNIVERSITY COLLEGE LONDON UK (LONDON) participant 24˙862.00
4    UNIVERSITY OF LEEDS UK (LEEDS) participant 21˙961.00
5    UNIVERSITY OF BRISTOL UK (BRISTOL) participant 0.00

Map

 Project objective

Learning from others is fundamental to ecological success across the animal kingdom, but a key theme to emerge from recent research is that individuals respond differently to social information. Understanding this diversity is an imposing challenge, because it is hard to replicate the overwhelming complexity of free-living groups within controlled laboratory conditions. Yet here I propose that one of the most complex social models that we know of— the sophisticated eusocial societies of honeybees— offer unrivaled and yet unrecognized potential to study social information flow through a natural group. The honeybee “dance language” is one of the most celebrated communication systems in the animal world, and central to a powerful information network that drives our most high-profile pollinator to food, but bee colonies are uniquely tractable for two reasons. Firstly, next-generation transcriptomics could allow us to delve deep into this complexity at the molecular level, on a scale that is simply not available in vertebrate social systems. I propose to track information flow through a natural group using brain gene expression profiles, to understand how dances elicit learning in the bee brain. Secondly, although bee foraging ranges are vast and diverse, social learning takes place in one centralized location (the hive). The social sciences now offer powerful new tools to analyze social networks, and I will use a cutting-edge network-based modelling approach to understand how the importance of social learning mechanisms shifts with ecology. In the face of global pollinator decline, understanding the contribution of foraging drivers to colony success has never been more pressing, but the importance of the dance language reaches far beyond food security concerns. This research integrates proximate and ultimate perspectives to produce a comprehensive, multi-disciplinary program; a high-risk, high-gain journey into new territory for understanding animal communication.

 Publications

year authors and title journal last update
List of publications.
2018 Harry Siviter, Mark J. F. Brown, Ellouise Leadbeater
Sulfoxaflor exposure reduces bumblebee reproductive success
published pages: 109-112, ISSN: 0028-0836, DOI: 10.1038/s41586-018-0430-6
Nature 06/09/2018 2019-05-29
2018 Ash E. Samuelson, Ellouise Leadbeater
A land classification protocol for pollinator ecology research: An urbanization case study
published pages: 5598-5610, ISSN: 2045-7758, DOI: 10.1002/ece3.4087
Ecology and Evolution 8/11 2019-05-29
2018 Ash E. Samuelson, Richard J. Gill, Mark J. F. Brown, Ellouise Leadbeater
Lower bumblebee colony reproductive success in agricultural compared with urban environments
published pages: 20180807, ISSN: 0962-8452, DOI: 10.1098/rspb.2018.0807
Proceedings of the Royal Society B: Biological Sciences 285/1881 2019-05-29
2018 Harry Siviter, Julia Koricheva, Mark J. F. Brown, Ellouise Leadbeater
Quantifying the impact of pesticides on learning and memory in bees
published pages: , ISSN: 0021-8901, DOI: 10.1111/1365-2664.13193
Journal of Applied Ecology 2019-05-29
2017 Ash Samuelson, Ellouise Leadbeater
Foraging by Honeybees
published pages: 1-9, ISSN: , DOI: 10.1007/978-3-319-47829-6_918-1
Encyclopaedia of Animal Cognition and Behaviour 1/1 2019-05-27
2017 Ellouise Leadbeater, Erika H. Dawson
A social insect perspective on the evolution of social learning mechanisms
published pages: 7838-7845, ISSN: 0027-8424, DOI: 10.1073/pnas.1620744114
Proceedings of the National Academy of Sciences 114/30 2019-05-27

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