Quantitative assessments of honeybee colony's response to an artificial vibrational pulse resulting in non-invasive measurements of colony's overall mobility and restfulness.

In this work we aim to provide a quantitative method allowing the probing of the physiological status of honeybee colonies by providing them with a gentle, short, external artificial vibrational shockwave, and recording their response. The knock is provided by an external electromagnetic shaker attached to the outer wall of a hive, driven by a computer with a 0.1 s long, monochromatic vibration at 340Hz set to an amplitude that occasionally yields a mild response from the bees, recorded by an accelerometer placed in the middle of the central frame of the colony. To avoid habituation, the stimulus is supplied at randomised times, approximately every hour. The method is pioneered with a pilot study on a single colony hosted indoors, then extended onto eight outdoors colonies. The results show that we can quantitatively sense the colony's overall mobility, independently from another physiological aspect, which is phenomenologically explored. Using this, a colony that is queenless is easily discriminated from the others.

Allele Frequencies of Genetic Variants Associated with Varroa Drone Brood Resistance (DBR) in Apis mellifera Subspecies across the European Continent.

Implementation of marker-assisted selection (MAS) in modern beekeeping would improve sustainability, especially in breeding programs aiming for resilience against the parasitic mite Varroa destructor. Selecting honey bee colonies for natural resistance traits, such as brood-intrinsic suppression of varroa mite reproduction, reduces the use of chemical acaricides while respecting local adaptation. In 2019, eight genomic variants associated with varroa non-reproduction in drone brood were discovered in a single colony from the Amsterdam Water Dune population in the Netherlands. Recently, a new study tested the applicability of these eight genetic variants for the same phenotype on a population-wide scale in Flanders, Belgium. As the properties of some variants varied between the two studies, one hypothesized that the difference in genetic ancestry of the sampled colonies may underly these contribution shifts. In order to frame this, we determined the allele frequencies of the eight genetic variants in more than 360 Apis mellifera colonies across the European continent and found that variant type allele frequencies of these variants are primarily related to the A. mellifera subspecies or phylogenetic honey bee lineage. Our results confirm that population-specific genetic markers should always be evaluated in a new population prior to using them in MAS programs.

Bridging the Gap between Field Experiments and Machine Learning: The EC H2020 B-GOOD Project as a Case Study towards Automated Predictive Health Monitoring of Honey Bee Colonies.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping.

Sub-lethal doses of sulfoxaflor impair honey bee homing ability.

Agricultural intensification has increased the number of stressors that pollinators are exposed to. Besides increasing landscape fragmentation that limit the supply of flower resources, intensive agricultural practices relying on the use of pesticides to control agricultural pests also affect non-target organisms like honey bees. The use of most pesticides containing neonicotinoids has been severely restricted in the European Union, leaving pesticides containing acetamiprid as the only ones that are still authorized. In the meantime, new substances like sulfoxaflor, that have a similar mode of action acting on the insect's nicotinic acetylcholine receptors (nAChR), have been approved for agricultural use. In Europe and USA, the use of pesticides containing this active ingredient is limited due to toxic effects already reported on bees, but no restrictions regarding this matter were applied in other countries (e.g., Brazil). In this study, homing ability tests with acetamiprid and sulfoxaflor were performed, in which honey bees were fed with three sub-lethal doses from each substance. After exposure, each honey bee was equipped with an RFID chip and released 1 km away from the colony to evaluate their homing ability. No significant effects were detected in honey bees fed with 32, 48 and 61 ng of acetamiprid while a poor performance on their homing ability, with only 28% of them reaching the colony instead of 75%, was detected at a 26 ng/a.s./bee dose of sulfoxaflor. Although, both pesticides act on the nAChR, the higher sulfoxaflor toxicity might be related with the honey bees detoxifying mechanisms, which are more effective on cyano-based neonicotinoids (i.e., acetamiprid) than sulfoximines. With this study we encourage the use of homing ability tests to be a suitable candidate to integrate the future risk assessment scheme, providing valuable data to models predicting effects on colony health that emerge from the individual actions of each bee.

Exposure and risk assessment of acetamiprid in honey bee colonies under a real exposure scenario in Eucalyptus sp. landscapes.

Honey bee colonies have shown abnormal mortality rates over the last decades. Colonies are exposed to biotic and abiotic stressors including landscape changes caused by human pressure. Modern agriculture and even forestry, rely on pesticide inputs and these chemicals have been indicated as one of the major causes for colony losses. Neonicotinoids are a common class of pesticides used worldwide that are specific to kill insect pests, with acetamiprid being the only neonicotinoid allowed to be applied outdoors in the EU. To evaluate honeybees' exposure to acetamiprid under field conditions as well as to test the use of in-situ tools to monitor pesticide residues, two honeybee colonies were installed in five Eucalyptus sp. plantations having different area where Epik® (active substance: acetamiprid) was applied as in a common spraying event to control the eucalyptus weevil pest. Flowers, fresh nectar, honey bees and colony products samples were collected and analyzed for the presence of acetamiprid residues. Our main findings were that (1) acetamiprid residues were found in samples collected outside the spraying area, (2) the amount of residues transported into the colonies increased with the size of the sprayed area, (3) according to the calculated Exposure to Toxicity Ratio (ETR) values, spraying up to 22 % of honeybees foraging area does not harm the colonies, (4) colony products can be used as a valid tool to monitor colony accumulation of acetamiprid and (5) the use of Lateral Flow Devices (LFDs) can be a cheap, fast and easy tool to apply in the field, to evaluate the presence of acetamiprid residues in the landscape and colony products.

Monitoring the effects of field exposure of acetamiprid to honey bee colonies in Eucalyptus monoculture plantations.

Eucalyptus plantations occupy 26 % of Portuguese forested areas. Its flowers constitute important sources for bees and beekeepers take advantage of this and keep their honey bee colonies within or near the plantations for honey production. Nonetheless, these plantations are susceptible to pests, such as the eucalyptus weevil Gonipterus platensis. To control this weevil, some plantations must be treated with pesticides, which might harm non-target organisms. This study aimed to perform a multifactorial assessment of the health status and development of Apis mellifera iberiensis colonies in two similar landscape windows dominated by Eucalyptus globulus plantations - one used as control and the other with insecticide treatment. In each of the two selected areas, an apiary with five hives was installed and monitored before and after a single application of the insecticide acetamiprid (40 g a.i./ha). Colony health and development, resources use, and pesticide residues accumulation were measured. The results showed that the application of acetamiprid in this area did not alter the health status and development of the colonies. This can be explained by the low levels of residues of acetamiprid detected only in pollen and bee bread samples, ~52 fold lower than the sublethal effect threshold. This could be attributed to the low offer of resources during and after the application event and within the application area, with the consequent foraging outside the sprayed area during that period. Since exposure to pesticides in such complex landscapes seems to be dependent on the spatial and temporal distribution of resources, we highlight some key monitoring parameters and tools that are able to provide reliable information on colony development and use of resources. These tools can be easily applied and can provide a better decision-taking of pesticide application in intensive production systems to decrease the risk of exposure for honey bees.