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PLoS One ; 7(3): e32677, 2012.
Artigo em Inglês | MEDLINE | ID: mdl-22427864

RESUMO

Physiological state profoundly influences the expression of the behaviour of individuals and can affect social interactions between animals. How physiological state influences food sharing and social behaviour in social insects is poorly understood. Here, we examined the social interactions and food sharing behaviour of honeybees with the aim of developing the honeybee as a model for understanding how an individual's state influences its social interactions. The state of individual honeybees was manipulated by either starving donor bees or feeding them sucrose or low doses of ethanol to examine how a change in hunger or inebriation state affected the social behaviours exhibited by two closely-related nestmates. Using a lab-based assay for measuring individual motor behaviour and social behaviour, we found that behaviours such as antennation, willingness to engage in trophallaxis, and mandible opening were affected by both hunger and ethanol intoxication. Inebriated bees were more likely to exhibit mandible opening, which may represent a form of aggression, than bees fed sucrose alone. However, intoxicated bees were as willing to engage in trophallaxis as the sucrose-fed bees. The effects of ethanol on social behaviors were dose-dependent, with higher doses of ethanol producing larger effects on behaviour. Hungry donor bees, on the other hand, were more likely to engage in begging for food and less likely to antennate and to display mandible opening. We also found that when nestmates received food from donors previously fed ethanol, they began to display evidence of inebriation, indicating that ethanol can be retained in the crop for several hours and that it can be transferred between honeybee nestmates during trophallaxis.


Assuntos
Abelhas/fisiologia , Comportamento Alimentar/fisiologia , Comportamento Social , Intoxicação Alcoólica , Animais , Relação Dose-Resposta a Droga , Etanol/toxicidade , Comportamento Alimentar/efeitos dos fármacos , Modelos Lineares , Observação
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