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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.

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

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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