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BeeDanceGap

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Honeybee communication animal social learning at the height of social complexit...

Honeybee communication animal social learning at the height of social complexity 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... ver más

31/01/2021

RHUL

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

ROYAL HOLLOWAY AND BEDFORD NEW COLLEGE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 6 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-01-31

ERC-StG-2014: ERC Starting Grant Scope:Objectives

I+D

Cerrada hace 11 años

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

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6 Participantes

RHUL

1.32M€ | Lider

DATAPIXEL

268.99K€ | Participante

QMUL

54.88K€ | Participante

UNIVERSITY COLLEGE LONDON

24.86K€ | Participante

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Duración del proyecto: 69 meses Fecha Inicio: 2015-04-22
Fecha Fin: 2021-01-31

Líder del proyecto

ROYAL HOLLOWAY AND BEDFORD NEW COLLEGE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto 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.

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