Bayesian Multi-Targets Strategy to Track Apis mellifera Movements at Colony Level

摘要: Simple Summary The number of honey bee, Apis mellifera L., colonies has reduced around the globe, and one potential cause is their unintended exposure to sublethal stressors such as agricultural pesticides. The quantification of such effects at colony level is a very complex task due to the innumerable collective activities done by the individual within colonies. Here, we present a Bayesian and computational approach capable of tracking the movements of bees within colonies, which allows the comparison of the collective activities of colonies that received bees previously exposed to uncontaminated diets or to diets containing sublethal concentrations of an agricultural pesticide (a commercial formulation containing the synthetic fungicides thiophanate-methyl and chlorothalonil). Our Bayesian tracking technique proved successful and superior to comparable algorithms, allowing the estimation of dynamical parameters such as entropy and kinetic energy. Our efforts demonstrated that fungicide-contaminated colonies behaved differently from uncontaminated colonies, as the former exhibited anticipated collective activities in peripheral hive areas and had reduced swarm entropy and kinetic energies. Such findings may facilitate the electronic monitoring of potential unintended effects in social pollinators, at colony level, mediated by environmental stressors (e.g., pesticides, electromagnetic fields, noise, and light intensities) alone or in combination. Abstract Interactive movements of bees facilitate the division and organization of collective tasks, notably when they need to face internal or external environmental …