Analysis of honeybee drone activity during the mating season in northwestern argentina

Males in Hymenopteran societies are understudied in many aspects and it is assumed that they only have a reproductive function. We studied the time budget of male honey bees, drones, using multiple methods. Changes in the activities of animals provide important information on biological clocks and their health. Yet, in nature, these changes are subtle and often unobservable without the development and use of modern technology. During the spring and summer mating season, drones emerge from the hive, perform orientation flights, and search for drone congregation areas for mating. This search may lead drones to return to their colony, drift to other colonies (vectoring diseases and parasites), or simply get lost to predation. In a low percentage of cases, the search is successful, and drones mate and die. Our objective was to describe the activity of Apis mellifera drones during the mating season in Northwestern Argentina using three methods: direct observation, video recording, and radio frequency identification (RFID). The use of RFID tagging allows the tracking of a bee for 24 h but does not reveal the detailed activity of drones. We quantified the average number of drones’ departure and arrival flights and the time outside the hive. All three methods confirmed that drones were mostly active in the afternoon. We found no differences in results between those obtained by direct observation and by video recording. RFID technology enabled us to discover previously unknown drone behavior such as activity at dawn and during the morning. We also discovered that drones may stay inside the hive for many days, even after initiation of search flights (up to four days). Likewise, we observed drones to leave the hive for several days to return later (up to three days). The three methods were complementary and should be considered for the study of bee drone activity, which may be associated with the diverse factors influencing hive health.Fil: Ayup, María Marta. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigaciones Agropecuarias. Instituto de Investigación Animal del Chaco Semiárido; ArgentinaFil: Gärtner, Philipp. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Agosto Rivera, José L.. Universidad de Puerto Rico; Puerto RicoFil: Marendy, Peter. University of Tansmania. School Of Technology, Environments And Design ; AustraliaFil: de Souza, Paulo. University of Tansmania. School Of Technology, Environments And Design ; AustraliaFil: Galindo Cardona, Alberto. Fundación Miguel Lillo; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigaciones Agropecuarias. Instituto de Investigación Animal del Chaco Semiárido; Argentin

Towards Automatic Honey Bee Flower-Patch Assays with Paint Marking Re-Identification

In this paper, we show that paint markings are a feasible approach to automatize the analysis of behavioral assays involving honey bees in the field where marking has to be as lightweight as possible. We contribute a novel dataset for bees re-identification with paint-markings with 4392 images and 27 identities. Contrastive learning with a ResNet backbone and triplet loss led to identity representation features with almost perfect recognition in closed setting where identities are known in advance. Diverse experiments evaluate the capability to generalize to separate IDs, and show the impact of using different body parts for identification, such as using the unmarked abdomen only. In addition, we show the potential to fully automate the visit detection and provide preliminary results of compute time for future real-time deployment in the field on an edge device.Comment: Paper 17, workshop "CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling", in conjunction with Computer Vision and Pattern Recognition (CVPR 2023), June 18, 2023, Vancouver, Canad

Neonicotinoids Disrupt Circadian Rhythms and Sleep in Honey Bees

Honey bees are critical pollinators in ecosystems and agriculture, but their numbers have significantly declined. Declines in pollinator populations are thought to be due to multiple factors including habitat loss, climate change, increased vulnerability to disease and parasites, and pesticide use. Neonicotinoid pesticides are agonists of insect nicotinic cholinergic receptors, and sub-lethal exposures are linked to reduced honey bee hive survival. Honey bees are highly dependent on circadian clocks to regulate critical behaviors, such as foraging orientation and navigation, time-memory for food sources, sleep, and learning/memory processes. Because circadian clock neurons in insects receive light input through cholinergic signaling we tested for effects of neonicotinoids on honey bee circadian rhythms and sleep. Neonicotinoid ingestion by feeding over several days results in neonicotinoid accumulation in the bee brain, disrupts circadian rhythmicity in many individual bees, shifts the timing of behavioral circadian rhythms in bees that remain rhythmic, and impairs sleep. Neonicotinoids and light input act synergistically to disrupt bee circadian behavior, and neonicotinoids directly stimulate wake-promoting clock neurons in the fruit fly brain. Neonicotinoids disrupt honey bee circadian rhythms and sleep, likely by aberrant stimulation of clock neurons, to potentially impair honey bee navigation, time-memory, and social communication

Appetitive reversal learning differences of two honey bee subspecies with different foraging behaviors

We aimed to examine mechanistically the observed foraging differences across two honey bee, Apis mellifera, subspecies using the proboscis extension response assay. Specifically, we compared differences in appetitive reversal learning ability between honey bee subspecies: Apis mellifera caucasica (Pollman), and Apis mellifera syriaca (Skorikov) in a “common garden” apiary. It was hypothesized that specific learning differences could explain previously observed foraging behavior differences of these subspecies: A.m. caucasica switches between different flower color morphs in response to reward variability, and A.m. syriaca does not switch. We suggest that flower constancy allows reduced exposure by minimizing search and handling time, whereas plasticity is important when maximizing harvest in preparation for long winter is at a premium. In the initial or Acquisition phase of the test we examined specifically discrimination learning, where bees were trained to respond to a paired conditioned stimulus with an unconditioned stimulus and not to respond to a second conditioned stimulus that is not followed by an unconditioned stimulus. We found no significant differences among the subspecies in the Acquisition phase in appetitive learning. During the second, Reversal phase of the experiment, where flexibility in association was tested, the paired and unpaired conditioned stimuli were reversed. During the Reversal phase A.m. syriaca showed a reduced ability to learn the reverse association in the appetitive learning task. This observation is consistent with the hypothesis that A.m. syriaca foragers cannot change the foraging choice because of lack of flexibility in appetitive associations under changing contingencies. Interestingly, both subspecies continued responding to the previously rewarded conditioned stimulus in the reversal phase. We discuss potential ecological correlates and molecular underpinnings of these differences in learning across the two subspecies. In addition, in a supplemental experiment we demonstrated that these differences in appetitive reversal learning do not occur in other learning contexts.National Science Foundation (NSF)Publisher's Versio

The Impact of Natural Disasters on Maternal Health: Hurricanes Irma and María in Puerto Rico

The PROTECT research Center funded by the NIH’s National Institute of Environmental Health Sciences (NIEHS) Superfund Research Program was launched in 2010 to explore the impact of exposure to pollutants on the high rate of premature births in Puerto Rico. In September 2017, Hurricanes Irma and María devastated the archipelago, which caused: collapse of the electrical system, collapse of the communication system, limited access to clean water, food, gas, and health services, destruction of public (e.g., hospitals) and private property (e.g., houses) and more than 4500 deaths. Pregnant and postpartum individuals are especially vulnerable to natural disasters. They face difficulty obtaining adequate pre- and post-natal care, are exposed to increased risk of miscarriage, premature delivery, and giving birth to low birth weight babies during and after disasters and are also more likely to suffer physical and mental health problems compared to the general population during and after disasters. A face-to-face questionnaire was administered to PROTECT participants who were pregnant during hurricanes Irma or Maria or who became pregnant shortly after in order to identify hurricane-related sources of stress and other adverse effects. This paper is based on the answers to the open-ended question at the end of the questionnaire where participants were asked to share their experiences during and after the hurricanes. Among the 375 participants who completed the survey, 76 answers to the open-ended question were considered due to data saturation. The answers to the open-ended question were transcribed into a document in order to facilitate the coding process. The transcribed text was analyzed first to identify emerging categories and then coded to identify common themes as well as divergence among participants. The following themes were identified: pregnancy and birth challenges, lack of access to basic services, housing conditions, stressful working conditions, concerns about health, concerns about their children, and positive or protective aspects. The results indicate how the disruption in access to basic services has a unique impact on the physical and mental health of pregnant and post-partum women in an emergency situation. These findings point to the potential benefit of developing specific protocols designed for emergency preparedness aimed at this population, which can inform healthcare providers and community organizations in case of future events