Effects of Brood Pheromone Modulated Brood Rearing Behaviors on Honey Bee (Apis mellifera L.) Colony Growth

A hallmark of eusociality is cooperative brood care. In most social insect systems brood rearing labor is divided between individuals working in the nest tending the queen and larvae, and foragers collecting food outside the nest. To place brood rearing division of labor within an evolutionary context, it is necessary to understand relationships between individuals in the nest engaged in brood care and colony growth in the honey bee. Here we examined responses of the queen, queen-worker interactions, and nursing behaviors to an increase in the brood rearing stimulus environment using brood pheromone. Colony pairs were derived from a single source and were headed by open-mated sister queens, for a total of four colony pairs. One colony of a pair was treated with 336 µg of brood pheromone, and the other a blank control. Queens in the brood pheromone treated colonies laid significantly more eggs, were fed longer, and were less idle compared to controls. Workers spent significantly more time cleaning cells in pheromone treatments. Increasing the brood rearing stimulus environment with the addition of brood pheromone significantly increased the tempo of brood rearing behaviors by bees working in the nest resulting in a significantly greater amount of brood reared

Using national movement databases to help inform responses to swine disease outbreaks in Scotland:the impact of uncertainty around incursion time

Modelling is an important component of contingency planning and control of disease outbreaks. Dynamic network models are considered more useful than static models because they capture important dynamic patterns of farm behaviour as evidenced through animal movements. This study evaluates the usefulness of a dynamic network model of swine fever to predict pre-detection spread via movements of pigs, when there may be considerable uncertainty surrounding the time of incursion of infection. It explores the utility and limitations of animal movement data to inform such models and as such, provides some insight into the impact of improving traceability through real-time animal movement reporting and the use of electronic animal movement databases. The study concludes that the type of premises and uncertainty of the time of disease incursion will affect model accuracy and highlights the need for improvements in these areas

Modulation of social interactions by immune stimulation in honey bee, Apis mellifera, workers

International audienceBACKGROUND:Immune response pathways have been relatively well-conserved across animal species, with similar systems in both mammals and invertebrates. Interestingly, honey bees have substantially reduced numbers of genes associated with immune function compared with solitary insect species. However, social species such as honey bees provide an excellent environment for pathogen or parasite transmission with controlled environmental conditions in the hive, high population densities, and frequent interactions. This suggests that honey bees may have developed complementary mechanisms, such as behavioral modifications, to deal with disease.RESULTS:Here, we demonstrate that activation of the immune system in honey bees (using bacterial lipopolysaccharides as a non-replicative pathogen) alters the social responses of healthy nestmates toward the treated individuals. Furthermore, treated individuals expressed significant differences in overall cuticular hydrocarbon profiles compared with controls. Finally, coating healthy individuals with extracts containing cuticular hydrocarbons of immunostimulated individuals significantly increased the agonistic responses of nestmates.CONCLUSION:Since cuticular hydrocarbons play a critical role in nestmate recognition and other social interactions in a wide variety of insect species, modulation of such chemical profiles by the activation of the immune system could play a crucial role in the social regulation of pathogen dissemination within the colony

Balancing timeliness of reporting with increasing testing probability for epidemic data.

Reporting of epidemiological data requires coordinated action by numerous agencies, across a multitude of logistical steps. Using collated and reported information to inform direct interventions can be challenging due to associated delays. Mitigation can, however, occur indirectly through the public generation of concern, which facilitates adherence to protective behaviors. We utilized a coupled-dynamic multiplex network model with a communication- and disease-layer to examine how variation in reporting delay and testing probability are likely to impact adherence to protective behaviors, such as reducing physical contact. Individual concern mediated adherence and was informed by new- or active-case reporting, at the population- or community-level. Individuals received information from the communication layer: direct connections that were sick or adherent to protective behaviors increased their concern, but absence of illness eroded concern. Models revealed that the relative benefit of timely reporting and a high probability of testing was contingent on how much information was already obtained. With low rates of testing, increasing testing probability was of greater mitigating value. With high rates of testing, maximizing timeliness was of greater value. Population-level reporting provided advanced warning of disease risk from nearby communities; but we explore the relative costs and benefits of delays due to scale against the assumption that people may prioritize community-level information. Our findings emphasize the interaction of testing accuracy and reporting timeliness for the indirect mitigation of disease in a complex social system