Identification and CRISPR-Cas9 validation of a novel ß-adrenergic-like octopamine receptor mutation associated with amitraz resistance in Varroa destructor.

Varroa destructor is widely recognized as a significant contributor to colony collapse disorder. Chemical acaricides, such as amitraz, have been extensively used for Varroa control due to their selectivity within beehives. However, the increasing number of cases of amitraz resistance across global V. destructor populations poses a significant challenge. In this study, we conducted a comprehensive molecular screening of the ß-adrenergic-like octopamine receptor (Octß2R), the target-site of amitraz, across 66 Turkish and 63 Belgian V. destructor populations. Although previously reported amitraz resistance mutations were not detected, the screening revealed a novel Y337F mutation located within transmembrane 7 (TM7) of Octß2R in Turkish Varroa populations. Notably, this mutation was identified in the last residue of the highly conserved NPxxY motif associated with the activation of G-protein coupled receptors (GPCR). Among the 66 Varroa samples from Türkiye, twenty harbored the Y337F mutation, with eight samples exhibiting fixation of the mutation. Subsequent bioassays revealed over 8-fold resistance to amitraz in populations that contain the Y337F mutation. Genotyping of mites after exposure to 10 mg a.i./l amitraz demonstrated that all surviving mites were homozygous for the Y337F mutation, whereas dead mites carried susceptible alleles, providing genetic linkage between mutation and phenotype. Further, we used CRISPR-Cas9 editing to introduce the Y337F mutation in the orthologous Octß2R of the model organism Tetranychus urticae. Crispants exhibited over threefold resistance to amitraz. In conclusion, this study identified and validated a novel amitraz resistance mutation. Additional research is required to further evaluate the phenotypic strength of Y337F in the context of operational resistance with current treatment strategies.

Interactive effects of chlorothalonil and Varroa destructor on Apis mellifera during adult stage.

The interaction between environmental factors affecting honey bees is of growing concern due to their potential synergistic effects on bee health. Our study investigated the interactive impact of Varroa destructor and chlorothalonil on workers' survival, fat body morphology, and the expression of gene associated with detoxification, immunity, and nutrition metabolism during their adult stage. We found that both chlorothalonil and V. destructor significantly decreased workers' survival rates, with a synergistic effect observed when bees were exposed to both stressors simultaneously. Morphological analysis of fat body revealed significant alterations in trophocytes, particularly a reduction in vacuoles and granules after Day 12, coinciding with the transition of the bees from nursing to other in-hive work tasks. Gene expression analysis showed significant changes in detoxification, immunity, and nutrition metabolism over time. Detoxification genes, such as CYP9Q2, CYP9Q3, and GST-D1, were downregulated in response to stressor exposure, indicating a potential impairment in detoxification processes. Immune-related genes, including defensin-1, Dorsal-1, and Kayak, exhibited an initially upregulation followed by varied expression patterns, suggesting a complex immune response to stressors. Nutrition metabolism genes, such as hex 70a, AmIlp2, VGMC, AmFABP, and AmPTL, displayed dynamic expression changes, reflecting alterations in nutrient utilization and energy metabolism in response to stressors. Overall, these findings highlight the interactive and dynamic effects of environmental stressor on honey bees, providing insights into the mechanisms underlying honey bee decline. These results emphasize the need to consider the interactions between multiple stressors in honey bee research and to develop management strategies to mitigate their adverse effects on bee populations.

Sensorizing a Beehive: A Study on Potential Embedded Solutions for Internal Contactless Monitoring of Bees Activity.

Winter is the season of main concern for beekeepers since the temperature, humidity, and potential infection from mites and other diseases may lead the colony to death. As a consequence, beekeepers perform invasive checks on the colonies, exposing them to further harm. This paper proposes a novel design of an instrumented beehive involving color cameras placed inside the beehive and at the bottom of it, paving the way for new frontiers in beehive monitoring. The overall acquisition system is described focusing on design choices towards an effective solution for internal, contactless, and stress-free beehive monitoring. To validate our approach, we conducted an experimental campaign in 2023 and analyzed the collected images with YOLOv8 to understand if the proposed solution can be useful for beekeepers and what kind of information can be derived from this kind of monitoring, including the presence of Varroa destructor mites inside the beehive. We experimentally found that the observation point inside the beehive is the most challenging due to the frequent movements of the bees and the difficulties related to obtaining in-focus images. However, from these images, it is possible to find Varroa destructor mites. On the other hand, the observation point at the bottom of the beehive showed great potential for understanding the overall activity of the colony.

MSPB: a longitudinal multi-sensor dataset with phenotypic trait measurements from honey bees.

We present a one-year-long multi-sensor dataset collected from honey bee colonies (Apis mellifera) with rich phenotypic measurements. Data were collected non-stop from April 2020 to April 2021 from 53 hives located at two apiaries in Québec, Canada. The sensor data included audio features, temperature, and relative humidity. The phenotypic measurements contained beehive population, number of brood cells (eggs, larva and pupa), Varroa destructor infestation levels, defensive and hygienic behaviors, honey yield, and winter mortality. Our study is amongst the first to combine a wide variety of phenotypic trait measurements annotated by apicultural science experts with multi-sensor data, which facilitate a broader scope of analysis. We first summarize the data collection procedure, sensor data pre-processing steps, and data composition. We then provide an overview of the phenotypic data distribution as well as a visualization of the sensor data patterns. Lastly, we showcase several hive monitoring applications based on sensor data analysis and machine learning, such as winter mortality prediction, hive population estimation, and the presence of an active and laying queen.

Investigation of landscape risk factors for the recent spread of varroa mite (Varroa destructor) in European honeybee (Apis mellifera) colonies in New South Wales, Australia.

In June 2022, an exotic pest of the European honeybee (Apis mellifera), the varroa mite (Varroa destructor), was detected in surveillance hives at the Port of Newcastle, New South Wales (NSW). Previously, Australia remained the only continent free of the varroa mite. In September 2023, the National Management Group decided to shift the focus of the response from eradication to management. It is estimated that the establishment of varroa mite in Australia could lead to more than $70 million in losses each year due to greatly reduced pollination services. Currently, there are no reported studies on the epidemiology of varroa mite in NSW because it is such a recent outbreak, and there is little knowledge of the factors associated with the presence of V. destructor in the Australian context. We sourced publicly available varroa mite outbreak reports from June 22 to December 19, 2022, to determine if urbanization, land use, and distance from the incursion site are associated with the detection of varroa mite infestation in European honeybee colonies in NSW. The outcome investigated was epidemic day, relative to the first detected premises (June 22, 2022). The study population was comprised of 107 premises, which were declared varroa-infested. The median epidemic day was day 37 (July 29, 2022), and a bimodal distribution was observed from the epidemic curve, which was reflective of an intermittent source pattern of spread. We found that premises were detected to be infected with varroa mite earlier in urban areas [median epidemic day 25 (July 17, 2022)] compared to rural areas [median epidemic day 37.5 (July 29, 2022)]. Infected premises located in areas without cropping, forests, and irrigation were detected earlier in the outbreak [median epidemic days 23.5 (July 15, 2022), 30 (July 22, 2022), and 15 (July 7, 2022), respectively] compared to areas with cropping, forests, and irrigation [median epidemic days 50 (August 11, 2022), 43 (August 4, 2022), and 47 (August 8, 2022), respectively]. We also found that distance from the incursion site was not significantly correlated with epidemic day. Urbanization and land use are potential factors for the recent spread of varroa mite in European honeybee colonies in NSW. This knowledge is essential to managing the current varroa mite outbreak and preventing future mass varroa mite spread events.

Varroa destructor and deformed wing virus interaction increases incidence of winter mortality in honey bee colonies.

Winter mortality of honey bee colonies represents a major source of economic loss for the beekeeping industry. The objectives of this prospective study were to estimate the incidence risk of winter colony mortality in southwestern Quebec, Canada and to evaluate and quantify the impact of the associated risk factors. A total of 242 colonies from 31 apiaries was selected for sampling in August 2017. The presence of Varroa destructor, Vairimorpha (Nosema) spp., Melissococcus plutonius, deformed wing virus (DWV), and viruses of the acute-Kashmir-Israeli complex (AKI complex) was investigated in each colony. Management practices of the various colonies were obtained from a questionnaire. The incidence risk of colony mortality during the winter of 2017-2018 was estimated to be 26.5% [95% confidence interval (CI): 15.4 to 40.3]. In logistic regression modeling of winter mortality in colonies, an interaction was discovered between V. destructor and DWV; the detection of ≥ 1 V. destructor mites per 100 bees was associated with higher odds of mortality (3.46, 95% CI: 1.35 to 8.90) compared to colonies with < 1 mite per 100 bees, but only in DWV-positive colonies. There were more colony losses in apiaries from beekeepers owning 1 to 5 colonies than in apiaries from beekeepers owning over 100 colonies, which suggests that beekeeper experience and/or type of management are important contributors to winter colony mortality. Assuming a causal relationship, the results of this study suggest that up to 9% of all colony mortalities in the population could have been prevented by reducing the level of V. destructor to < 1 mite per 100 bees in all colonies.

La mortalité hivernale des colonies d'abeilles est une cause importante de pertes économiques en apiculture. Cette étude prospective visait à estimer le risque d'incidence de mortalité hivernale des colonies d'abeilles et les facteurs de risque associés dans le sud-ouest du Québec (Canada). Au total, 242 colonies provenant de 31 ruches ont été sélectionnées en août 2017. La présence de Varroa destructor, de Vairimorpha (Nosema) spp., de Melissococcus plutonius, du virus des ailes déformées (DWV) et des virus du complexe AKI ont été évalués. Les pratiques de régie ont été obtenues selon un questionnaire. Le risque de mortalité des colonies à l'hiver 2017­2018 a été estimé à 26,5 % (95 % CI : 15,4 à 40,3). Dans un modèle de régression logistique, la détection de ≥ 1 mite de V. destructor par 100 abeilles était associée à des cotes plus élevées de mortalité (3,46, 95 % CI : 1,35 à 8,90) comparativement aux colonies avec < 1 mite par 100 abeilles, mais seulement pour les colonies positives au DWV. Les ruchers d'apiculteurs possédant entre 1 et 5 colonies présentaient une mortalité plus élevée comparativement à ceux d'apiculteurs possédant plus de 100 colonies, suggérant une influence de l'expérience ou du type de régie. En assumant une relation causale, les résultats de cette étude suggèrent que jusqu'à 9 % de toutes les mortalités hivernales observées dans la population auraient pu être prévenues en réduisant le niveau d'infestation par V. destructor à moins d'une mite per 100 abeilles dans toutes les colonies.(Traduit par les auteurs).

Varroa destructor shapes the unique viral landscapes of the honey bee populations of the Azores archipelago.

The worldwide dispersal of the ectoparasitic mite Varroa destructor from its Asian origins has fundamentally transformed the relationship of the honey bee (Apis mellifera) with several of its viruses, via changes in transmission and/or host immunosuppression. The extent to which honey bee-virus relationships change after Varroa invasion is poorly understood for most viruses, in part because there are few places in the world with several geographically close but completely isolated honey bee populations that either have, or have not, been exposed long-term to Varroa, allowing for separate ecological, epidemiological, and adaptive relationships to develop between honey bees and their viruses, in relation to the mite's presence or absence. The Azores is one such place, as it contains islands with and without the mite. Here, we combined qPCR with meta-amplicon deep sequencing to uncover the relationship between Varroa presence, and the prevalence, load, diversity, and phylogeographic structure of eight honey bee viruses screened across the archipelago. Four viruses were not detected on any island (ABPV-Acute bee paralysis virus, KBV-Kashmir bee virus, IAPV-Israeli acute bee paralysis virus, BeeMLV-Bee macula-like virus); one (SBV-Sacbrood virus) was detected only on mite-infested islands; one (CBPV-Chronic bee paralysis virus) occurred on some islands, and two (BQCV-Black queen cell virus, LSV-Lake Sinai virus,) were present on every single island. This multi-virus screening builds upon a parallel survey of Deformed wing virus (DWV) strains that uncovered a remarkably heterogeneous viral landscape featuring Varroa-infested islands dominated by DWV-A and -B, Varroa-free islands naïve to DWV, and a refuge of the rare DWV-C dominating the easternmost Varroa-free islands. While all four detected viruses investigated here were affected by Varroa for one or two parameters (usually prevalence and/or the Richness component of ASV diversity), the strongest effect was observed for the multi-strain LSV. Varroa unambiguously led to elevated prevalence, load, and diversity (Richness and Shannon Index) of LSV, with these results largely shaped by LSV-2, a major LSV strain. Unprecedented insights into the mite-virus relationship were further gained from implementing a phylogeographic approach. In addition to enabling the identification of a novel LSV strain that dominated the unique viral landscape of the easternmost islands, this approach, in combination with the recovered diversity patterns, strongly suggests that Varroa is driving the evolutionary change of LSV in the Azores. This study greatly advances the current understanding of the effect of Varroa on the epidemiology and adaptive evolution of these less-studied viruses, whose relationship with Varroa has thus far been poorly defined.

Varroa Mite Counting Based on Hyperspectral Imaging.

Varroa mite infestation poses a severe threat to honeybee colonies globally. This study investigates the feasibility of utilizing the HS-Cam and machine learning techniques for Varroa mite counting. The methodology involves image acquisition, dimensionality reduction through Principal Component Analysis (PCA), and machine learning-based segmentation and classification algorithms. Specifically, a k-Nearest Neighbors (kNNs) model distinguishes Varroa mites from other objects in the images, while a Support Vector Machine (SVM) classifier enhances shape detection. The final phase integrates a dedicated counting algorithm, leveraging outputs from the SVM classifier to quantify Varroa mite populations in hyperspectral images. The preliminary results demonstrate segmentation accuracy exceeding 99% and an average precision of 0.9983 and recall of 0.9947 across all the classes. The results obtained from our machine learning-based approach for Varroa mite counting were compared against ground-truth labels obtained through manual counting, demonstrating a high degree of agreement between the automated counting and manual ground truth. Despite working with a limited dataset, the HS-Cam showcases its potential for Varroa counting, delivering superior performance compared to traditional RGB images. Future research directions include validating the proposed hyperspectral imaging methodology with a more extensive and diverse dataset. Additionally, the effectiveness of using a near-infrared (NIR) excitation source for Varroa detection will be explored, along with assessing smartphone integration feasibility.

Do Varroa destructor (Acari: Varroidae) mite flows between Apis mellifera (Hymenoptera: Apidae) colonies bias colony infestation evaluation for resistance selection?

Since the global invasion of the ectoparasitic mite Varroa destructor (Anderson and Trueman), selection of mite-resistant honey bee (Apis mellifera L.) colonies appears challenging and has to date not broadly reduced colony mortality. The low published estimated heritability values for mite infestation levels could explain the limited genetic progresses obtained so far. We hypothesize that intercolonial horizontal mite transmission could differentially affect the single colonies located in a given apiary and therefore invisibly bias colony infestation phenotypes. This bias may be lower in regions with lower colony density, providing suitable conditions to set up evaluation apiaries. To verify these hypotheses, we monitored mite infestation and reinvasion in experimental colonies, as well as infestation in neighboring colonies belonging to beekeepers in three areas with variable colony densities in the canton of Bern, Switzerland during three consecutive beekeeping seasons. Mite immigration fluctuated between apiaries and years and significantly contributed to colony infestation level. Depending on apiary and year, 17-48% of the mites present in the experimental colonies at the time of the summer oxalic acid final treatment potentially derived from mite immigration that had occurred since mid-spring. Mite immigration was not linked to local colony density or the infestation levels of beekeepers' colonies located within 2 km. Our results do not prove that apiaries for colony evaluation should necessarily be established in areas with low colony density. However, they highlight the high impact of beekeeping management practices on mite colony infestation levels.

Molecular phylogeny reveals Varroa mites are not a separate family but a subfamily of Laelapidae.

Varroa mites, notorious for parasitizing honeybees, are generally classified as Varroidae. Their extremely modified morphologies and behaviors have led to debates regarding their phylogenetic position and classification as an independent family. In this study, two different datasets were employed to reconstruct the phylogenies of Varroa mites and related Laelapidae species: (1) 9257 bp from the whole 13 mitochondrial protein-coding genes of 24 taxa, (2) 3158 bp from 113 taxa using Sanger sequencing of four nuclear loci. Both mitochondrial and nuclear analyses consistently place Varroa mites within the Laelapidae. Here we propose to place Varroa mites in the subfamily Varroinae stat. nov., which represents a highly morphologically adapted group within the Laelapidae. Ancestral state reconstructions reveal that bee-associated lifestyles evolved independently at least three times within Laelapidae, with most phoretic traits originating from free-living ancestors. Our revised classification and evolutionary analyses will provide new insight into understanding the Varroa mites.

First detection and prevalence of Apis mellifera filamentous virus in Apis mellifera and Varroa destructor in the Republic of Korea.

Apis mellifera filamentous virus (AmFV) is a double-stranded DNA virus that infects Apis mellifera bees. To our knowledge, this is the first comprehensive study aiming to detect and analyse the genetic diversity and prevalence of AmFV in Korean honeybee colonies. Phylogenetic analysis based on baculovirus repeat open reading frame-N gene (Bro-N) sequences revealed that AmFV isolates from the Republic of Korea (ROK) fell into two distinct lineages, with genetic origins in Switzerland and China, with nucleotide similarities of 98.3% and 98.2%, respectively. Our prevalence analysis demonstrated a noteworthy infection rate of AmFV in 545 honeybee colonies, reaching 33.09% in 2022 and increasing to 44.90% by 2023. Intriguingly, we also detected AmFV in Varroa destructor mites, highlighting their potential role as vectors and carriers of AmFV. The presence of AmFV was correlated with an increased infection rate of sacbrood virus, deformed wing virus, Lake Sinai virus 2, black queen cell virus, and Nosema ceranae in honeybee colonies. These findings provide valuable insight into the prevalence and potential transmission mechanisms of AmFV in honeybee colonies in the ROK. The results of this study may be instrumental in the effective management of viral infections in honeybee apiaries.

Characterization of a Molecular Clone of Deformed Wing Virus B.

Honey bees (Apis mellifera) play a crucial role in agriculture through their pollination activities. However, they have faced significant health challenges over the past decades that can limit colony performance and even lead to collapse. A primary culprit is the parasitic mite Varroa destructor, known for transmitting harmful bee viruses. Among these viruses is deformed wing virus (DWV), which impacts bee pupae during their development, resulting in either pupal demise or in the emergence of crippled adult bees. In this study, we focused on DWV master variant B. DWV-B prevalence has risen sharply in recent decades and appears to be outcompeting variant A of DWV. We generated a molecular clone of a typical DWV-B strain to compare it with our established DWV-A clone, examining RNA replication, protein expression, and virulence. Initially, we analyzed the genome using RACE-PCR and RT-PCR techniques. Subsequently, we conducted full-genome RT-PCR and inserted the complete viral cDNA into a bacterial plasmid backbone. Phylogenetic comparisons with available full-length sequences were performed, followed by functional analyses using a live bee pupae model. Upon the transfection of in vitro-transcribed RNA, bee pupae exhibited symptoms of DWV infection, with detectable viral protein expression and stable RNA replication observed in subsequent virus passages. The DWV-B clone displayed a lower virulence compared to the DWV-A clone after the transfection of synthetic RNA, as evidenced by a reduced pupal mortality rate of only 20% compared to 80% in the case of DWV-A and a lack of malformations in 50% of the emerging bees. Comparable results were observed in experiments with low infection doses of the passaged virus clones. In these tests, 90% of bees infected with DWV-B showed no clinical symptoms, while 100% of pupae infected with DWV-A died. However, at high infection doses, both DWV-A and DWV-B caused mortality rates exceeding 90%. Taken together, we have generated an authentic virus clone of DWV-B and characterized it in animal experiments.

Analysis of Varroa Mite Colony Infestation Level Using New Open Software Based on Deep Learning Techniques.

Varroa mites, scientifically identified as Varroa destructor, pose a significant threat to beekeeping and cause one of the most destructive diseases affecting honey bee populations. These parasites attach to bees, feeding on their fat tissue, weakening their immune systems, reducing their lifespans, and even causing colony collapse. They also feed during the pre-imaginal stages of the honey bee in brood cells. Given the critical role of honey bees in pollination and the global food supply, controlling Varroa mites is imperative. One of the most common methods used to evaluate the level of Varroa mite infestation in a bee colony is to count all the mites that fall onto sticky boards placed at the bottom of a colony. However, this is usually a manual process that takes a considerable amount of time. This work proposes a deep learning approach for locating and counting Varroa mites using images of the sticky boards taken by smartphone cameras. To this end, a new realistic dataset has been built: it includes images containing numerous artifacts and blurred parts, which makes the task challenging. After testing various architectures (mainly based on two-stage detectors with feature pyramid networks), combination of hyperparameters and some image enhancement techniques, we have obtained a system that achieves a mean average precision (mAP) metric of 0.9073 on the validation set.

Comparison of Brain Gene Expression Profiles Associated with Auto-Grooming Behavior between Apis cerana and Apis mellifera Infested by Varroa destructor.

The grooming behavior of honeybees serves as a crucial auto-protective mechanism against Varroa mite infestations. Compared to Apis mellifera, Apis cerana demonstrates more effective grooming behavior in removing Varroa mites from the bodies of infested bees. However, the underlying mechanisms regulating grooming behavior remain elusive. In this study, we evaluated the efficacy of the auto-grooming behavior between A. cerana and A. mellifera and employed RNA-sequencing technology to identify differentially expressed genes (DEGs) in bee brains with varying degrees of grooming behavior intensity. We observed that A. cerana exhibited a higher frequency of mite removal between day 5 and day 15 compared to A. mellifera, with day-9 bees showing the highest frequency of mite removal in A. cerana. RNA-sequencing results revealed the differential expression of the HTR2A and SLC17A8 genes in A. cerana and the CCKAR and TpnC47D genes in A. mellifera. Subsequent homology analysis identified the HTR2A gene and SLC17A8 gene of A. cerana as homologous to the HTR2A gene and SLC17A7 gene of A. mellifera. These DEGs are annotated in the neuroactive ligand-receptor interaction pathway, the glutamatergic synaptic pathway, and the calcium signaling pathway. Moreover, CCKAR, TpnC47D, HTR2A, and SLC17A7 may be closely related to the auto-grooming behavior of A. mellifera, conferring resistance against Varroa infestation. Our results further explain the relationship between honeybee grooming behavior and brain function at the molecular level and provide a reference basis for further studies of the mechanism of honeybee grooming behavior.

Caught in the act: the invasion of a viral vector changes viral prevalence and titre in native honeybees and bumblebees.

Novel transmission routes change pathogen landscapes and may facilitate disease emergence. The varroa mite is a virus vector that switched to western honeybees at the beginning of the last century, leading to hive mortality, particularly in combination with RNA viruses. A recent invasion of varroa on the French island of Ushant introduced vector-mediated transmission to one of the last varroa-naive native honeybee populations and caused rapid changes in the honeybee viral community. These changes were characterized by a drastic increase in deformed wing virus type B prevalence and titre in honeybees, as well as knock-on effects in bumblebees, particularly in the year following the invasion. Slow bee paralysis virus also appeared in honeybees and bumblebees, with a 1 year delay, while black queen cell virus declined in honeybees. This study highlights the rapid and far-reaching effects of vector-borne transmission that can extend beyond the directly affected host species, and that the direction of the effect depends on the pathogen's virulence.

Brood indicators are an early warning signal of honey bee colony loss-a simulation-based study.

Honey bees (Apis mellifera) are exposed to multiple stressors such as pesticides, lack of forage, and diseases. It is therefore a long-standing aim to develop robust and meaningful indicators of bee vitality to assist beekeepers While established indicators often focus on expected colony winter mortality based on adult bee abundance and honey reserves at the beginning of the winter, it would be useful to have indicators that allow detection of stress effects earlier in the year to allow for adaptive management. We used the established honey bee simulation model BEEHAVE to explore the potential of different indicators such as population size, number of capped brood cells, flight activity, abundance of Varroa mites, honey stores and a brood-bee ratio. We implemented two types of stressors in our simulations: 1) parasite pressure, i.e. sub-optimal Varroa treatment by the beekeeper (hereafter referred as Biotic stress) and 2) temporal forage gaps in spring and autumn (hereafter referred as Environmental stress). Neither stressor type could be detected by bee abundance or honey reserves at the end of the first year. However, all response variables used in this study did reveal early warning signals during the course of the year. The most reliable and useful measures seem to be related to brood and the abundance of Varroa mites at the end of the year. However, while in the model we have full access to time series of variables from stressed and unstressed colonies, knowledge of these variables in the field is challenging. We discuss how our findings can nevertheless be used to develop practical early warning indicators. As a next step in the interactive development of such indicators we suggest empirical studies on the importance of the number of capped brood cells at certain times of the year on bee population vitality.

Evaluating the seasonal efficacy of commonly used chemical treatments on Varroa destructor (Mesostigmata: Varroidae) population resurgence in honey bee colonies.

The purpose of this research was to determine how common chemical treatments influence Varroa destructor (Anderson and Trueman) population resurgence rates (defined as time posttreatment for mite populations to reach 3 mites/100 adult bees) in managed honey bee (Apis mellifera L.) colonies seasonally. We conducted 2 experiments that followed the same basic protocol to address this purpose. We established 6 treatment groups in Experiment 1 in the fall of 2014: untreated control, Apivar, Apistan, CheckMite+, ApiLifeVar, and Mite Away II applied to 10 colonies per treatment. In Experiment 2, we applied 8 chemical treatments to each of 4 seasonal (spring, summer, fall, and winter) cohorts of honey bee colonies to determine how mite populations are influenced by the treatments. The treatments/formulations tested were Apivar, Apistan, Apiguard, MAQS, CheckMite+, oxalic acid (dribble), oxalic acid (shop towels), and amitraz (shop towels soaked in Bovitraz). In Experiment 1, Apivar and Mite Away II were able to delay V. destructor resurgence for 2 and 6 months, respectively. In Experiment 2, Apiguard, MAQS, oxalic acid (dribble), and Bovitraz treatments were effective at delaying V. destructor resurgence for at least 2 months during winter and spring. Only the Bovitraz and MAQS treatments were effective at controlling V. destructor in the summer and fall. Of the 2 amitraz-based treatments, the off-label Bovitraz treatment was the only treatment to reduce V. destructor populations in every season. The data gathered through this study allow for the refinement of treatment recommendations for V. destructor, especially regarding the seasonal efficacy of each miticide and the temporal efficacy posttreatment.

Combined treatment with amitraz and thymol to manage Varroa destructor mites (Acari: Varroidae) in Apis mellifera honey bee colonies (Hymenoptera: Apidae).

The parasitic mite Varroa destructor (Anderson and Trueman) is one of the greatest stressors of Apis mellifera (L.) honey bee colonies. When Varroa infestations reach damaging levels during fall, rapid control is necessary to minimize damage to colonies. We performed a field trial in the US Southeast to determine if a combination of registered treatments (Apivar, amitraz-based; and Apiguard, thymol-based) could provide rapid and effective control of Varroa. We compared colonies that received this combination treatment against colonies that received amitraz-based positive control treatments: (i) Apivar alone; or (ii) amitraz emulsifiable concentrate ("amitraz EC"). While not registered, amitraz EC is used by beekeepers in the United States in part because it is thought to control Varroa more rapidly and effectively than registered products. Based on measurements of Varroa infestation rates of colonies after 21 days of treatment, we found that the combination treatment controlled Varroa nearly as rapidly as the amitraz EC treatment: this or other combinations could be useful for Varroa management. At the end of the 42-day trial, colonies in the amitraz EC group had higher bee populations than those in the Apivar group, which suggests that rapid control helps reduce Varroa damage. Colonies in the combination group had lower bee populations than those in the amitraz EC group, which indicates that the combination treatment needs to be optimized to avoid damage to colonies.

Heightened sensitivity in high-grooming honey bees (Hymenoptera: Apidae).

Honey bees use grooming to defend against the devastating parasite Varroa destructor Anderson and Trueman. We observed the grooming responses of individual bees from colonies previously chosen for high- and low-grooming behavior using a combination of mite mortality and mite damage. Our aim was to gain insight into specific aspects of grooming behavior to compare if high-grooming bees could discriminate between a standardized stimulus (chalk dust) and a stimulus of live Varroa mites and if bees from high-grooming colonies had greater sensitivity across different body regions than bees from low-grooming colonies. We hypothesized that individuals from high-grooming colonies would be more sensitive to both stimuli than bees from low-grooming colonies across different body regions and that bees would have a greater response to Varroa than a standardized irritant (chalk dust). Individuals from high-grooming colonies responded with longer bouts of intense grooming when either stimulus was applied to the head or thorax, compared to sham-stimulated controls, while bees from low-grooming colonies showed no differences between stimulated and sham-stimulated bees. Further, high-grooming bees from colonies with high mite damage exhibited greater grooming to Varroa than high-grooming colonies with only moderate mite damage rates. This study provides new insights into Varroa-specific aspects of grooming, showing that although a standardized stimulus (chalk dust) may be used to assess general grooming ability in individual bee grooming assays, it does not capture the same range of responses as a stimulus of Varroa. Thus, continuing to use Varroa mites in grooming assays should help select colonies with more precise sensitivity to Varroa.

Neonicotinoid exposure increases Varroa destructor (Mesostigmata: Varroidae) mite parasitism severity in honey bee colonies and is not mitigated by increased colony genetic diversity.

Agrochemical exposure is a major contributor to ecological declines worldwide, including the loss of crucial pollinator species. In addition to direct toxicity, field-relevant doses of pesticides can increase species' vulnerabilities to other stressors, including parasites. Experimental field demonstrations of potential interactive effects of pesticides and additional stressors are rare, as are tests of mechanisms via which pollinators tolerate pesticides. Here, we controlled honey bee colony exposure to field-relevant concentrations of 2 neonicotinoid insecticides (clothianidin and thiamethoxam) in pollen and simultaneously manipulated intracolony genetic heterogeneity. We showed that exposure increased rates of Varroa destructor (Anderson and Trueman) parasitism and that while increased genetic heterogeneity overall improved survivability, it did not reduce the negative effect size of neonicotinoid exposure. This study is, to our knowledge, the first experimental field demonstration of how neonicotinoid exposure can increase V. destructor populations in honey bees and also demonstrates that colony genetic diversity cannot mitigate the effects of neonicotinoid pesticides.