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Highbush blueberry pollination depends on managed honey bees (Apis mellifera) L. for adequate fruit sets; however, beekeepers have raised concerns about the poor health of colonies after pollinating this crop. Postulated causes include agrochemical exposure, nutritional deficits, and interactions with parasites and pathogens, particularly Melisococcus plutonius [(ex. White) Bailey and Collins, Lactobacillales: Enterococcaceae], the causal agent of European foulbrood disease, but other pathogens could be involved. To broadly investigate common honey bee pathogens in relation to blueberry pollination, we sampled adult honey bees from colonies at time points corresponding to before (t1), during (t2), at the end (t3), and after (t4) highbush blueberry pollination in British Columbia, Canada, across 2 years (2020 and 2021). Nine viruses, as well as M. plutonius, Vairimorpha ceranae, and V. apis [Tokarev et al., Microsporidia: Nosematidae; formerly Nosema ceranae (Fries et al.) and N. apis (Zander)], were detected by PCR and compared among colonies located near and far from blueberry fields. We found a significant interactive effect of time and blueberry proximity on the multivariate pathogen community, mainly due to differences at t4 (corresponding to ∼6 wk after the beginning of the pollination period). Post hoc comparisons of pathogens in near and far groups at t4 showed that detections of sacbrood virus (SBV), which was significantly higher in the near group, not M. plutonius, was the primary driver. Further research is needed to determine if the association of SBV with highbush blueberry pollination is contributing to the health decline that beekeepers observe after pollinating this crop.

Honey bee viruses are serious pathogens that can cause poor colony health and productivity. We analyzed a multi-year longitudinal dataset of abundances of nine honey bee viruses (deformed wing virus A, deformed wing virus B, black queen cell virus, sacbrood virus, Lake Sinai virus, Kashmir bee virus, acute bee paralysis virus, chronic bee paralysis virus, and Israeli acute paralysis virus) in colonies located across Canada to describe broad trends in virus intensity and occurrence among regions and years. We also tested climatic variables (temperature, wind speed, and precipitation) as predictors in an effort to understand possible drivers underlying seasonal patterns in viral prevalence. Temperature was a significant positive predictor of the total number of viruses per sample, which was highest in British Columbia (mean = 5.0). Lake Sinai virus (LSV) was the most prevalent overall (at 89%) and had the highest infection intensity, at an average of 3.9 × 10 8 copies per bee. Acute bee paralysis virus was the least prevalent virus (at 4.7%) and had the lowest infection intensity (1.9 × 10 5 copies per bee). Surprisingly, including Varroa abundance as a covariate did not significantly improve model fit for any virus. All viruses, except Kashmir bee virus, varied by region, and one or more climatic variables were significant predictors for six of the nine viruses. Although climatic effects were often inconsistent among individual viruses, we show that climatic variables can be better predictors of virus intensity and occurrence than Varroa mite abundance, at least when infestation rates are low.

The Western honey bee ( Apis mellifera ) plays an essential role in agriculture around the world. In Canada, honey bees contribute up to $7 billion in economic value annually by pollinating crops and producing honey. However, since 2006–2007 North American beekeepers have lost more than a quarter of their colonies each winter. In recent years, the losses have been up to 50% in some regions. The causes of losses are complex, including the interacting effects of nutrition, pathogens, and pesticides. Although the bee gut microbiome plays a crucial role in colony health and disease, studies on the effects of agricultural pesticides on the bee microbial community are sparse. We report the use of shotgun metagenomic sequencing to investigate bee gut microbiota changes, or dysbiosis, in response to two neonicotinoid insecticides, clothianidin and thiamethoxam. Common dysbiosis signatures included an increase in Bifidobacterium spp. after chronic sublethal exposure and an increase in Apibacter adventoris after short-term acute exposure. Other dysbiosis signatures were unique to each compound, such as an increase in Snodgrassella alvi for clothianidin and a decrease in Lactobacillus spp. for thiamethoxam. These findings enhance our understanding of how the honey bee gut microbiome responds to stressors and highlight identifiable microbial profile signatures which underscores the potential utility of gut microbiome profiling as a bee health diagnostic tool. Access to timely and accurate bee health diagnosis will inform regulatory actions to decrease and mitigate exposure to stressors and will facilitate managing and improving bee health.

Background The mutualistic interaction between entomophilous plants and pollinators is fundamental to the structure of most terrestrial ecosystems. The sensitive nature of this relationship has been disrupted by anthropogenic modifications to natural landscapes, warranting development of new methods for exploring this trophic interaction. Characterizing the composition of pollen collected by pollinators, e.g. Apis mellifera , is a common means of exploring this relationship, but traditional methods of microscopic pollen assessment are laborious and limited in their scope. The development of pollen metabarcoding as a method of rapidly characterizing the abundance and diversity of pollen within mixed samples presents a new frontier for this type of work, but metabarcoding may have limitations, and validation is warranted before any suite of primers can be confidently used in a research program. We set out to evaluate the utility of an integrative approach, using a set of established primers (ITS2 and rbcL) versus melissopalynological analysis for characterizing 27 mixed-pollen samples from agricultural sites across Canada. Results Both individual markers performed well relative to melissopalynology at the family level with decreases in the strength of correlation and linear model fits at the genus level. Integrating data from both markers together via a multi-locus approach provided the best rank-based correlation between metagenetic and melissopalynological data at both the genus (ρ = 0.659; p < 0.001) and family level (ρ = 0.830; p < 0.001). Species accumulation curves indicated that, after controlling for sampling effort, melissopalynological characterization provides similar or higher species richness estimates than either marker. The higher number of plant species discovered via the metabarcoding approach simply reflects the vastly greater sampling effort in comparison to melissopalynology. Conclusions Pollen metabarcoding performed well at characterizing the composition of mixed pollen samples relative to a traditional melissopalynological approach. Limitations to the quantitative application of this method can be addressed by adopting a multi-locus approach that integrates information from multiple markers.

Here, we analyze 248 DNA barcode sequences of 35 fly species of forensic importance in Brazil. DNA barcoding can be effectively used for specimen identification of these species, allowing the unambiguous identification of 31 species, an overall success rate of 88%. Our results show a high rate of success for molecular identification using DNA barcoding sequences and open new perspectives for immature species identification, a subject on which limited forensic investigations exist inTropical regions. We also address the implications of building a robust forensic DNA barcode database. A geographic bias is recognized for the COI dataset available for forensically important fly species in Brazil, with concentration of sequences from specimens collected mainly in sites located in the Cerrado, Mata Atlântica, and Pampa biomes.

We present a DNA barcoding study of Neotropical odonates from the Upper Plata basin, Brazil. A total of 38 species were collected in a transition region of \"Cerrado\" and Atlantic Forest, both regarded as biological hotspots, and 130 cytochrome c oxidase subunit I (COI) barcodes were generated for the collected specimens. The distinct gap between intraspecific (0-2%) and interspecific variation (15% and above) in COI, and resulting separation of Barcode Index Numbers (BIN), allowed for successful identification of specimens in 94% of cases. The 6% fail rate was due to a shared BIN between two separate nominal species. DNA barcoding, based on COI, thus seems to be a reliable and efficient tool for identifying Neotropical odonate specimens down to the species level. These results underscore the utility of DNA barcoding to aid specimen identification in diverse biological hotspots, areas that require urgent action regarding taxonomic surveys and biodiversity conservation.

Honey bees are efficient pollinators of flowering plants, aiding in the plant reproductive cycle and acting as vehicles for evolutionary processes. Their role as agents of selection and drivers of gene flow is instrumental to the structure of plant populations, but historically, our understanding of their influence has been limited to predominantly insect‐dispersed flowering species. Recent metagenetic work has provided evidence that honey bees also forage on pollen from anemophilous species, suggesting that their role as vectors for transmission of plant genetic material is not confined to groups designated as entomophilous, and leading us to ask: could honey bees act as dispersal agents for non‐flowering plant taxa? Using an extensive pollen metabarcoding dataset from Canada, we discovered that honey bees may serve as dispersal agents for an array of sporophytes (Anchistea, Claytosmunda, Dryopteris, Osmunda, Osmundastrum, Equisetum) and bryophytes (Funaria, Orthotrichum, Sphagnum, Ulota). Our findings also suggest that honey bees may occasionally act as vectors for the dispersal of aquatic phototrophs, specifically Coccomyxa and Protosiphon, species of green algae. Our work has shed light on the broad resource‐access patterns that guide plant‐pollinator interactions and suggests that bees could act as vectors of gene flow, and potentially even agents of selection, across Plantae. We used pollen metabarcoding to investigate if honey bees interact with and disperse cells from non‐flowering plants. We discovered that honey bees may serve as dispersal agents for an array of sporophytes (Anchistea, Claytosmunda, Dryopteris, Osmunda, Osmundastrum, Equisetum) and bryophytes (Funaria, Orthotrichum, Sphagnum, Ulota). Our findings also suggest that honey bees may occasionally act as vectors for dispersal of aquatic phototrophs, specifically Coccomyxa and Protosiphon, species of green algae. These findings, though preliminary, open up a new field of research.

Global climate change is producing novel biospheric conditions, presenting a threat to the stability of ecological systems and the health of the organisms that reside within them. Variation in climatic conditions is expected to facilitate phenological reshuffling within plant communities, impacting the plant‐pollinator interface and the release of allergenic pollen into the atmosphere. Impacts on plant, invertebrate, and human health remain unclear largely due to the variable nature of phenological reshuffling and insufficient monitoring of these trends. Large‐scale temporal surveillance of plant community flowering has been difficult in the past due to logistical constraints. To address this, we set out to test if metabarcoding (ITS2 and rbcL1) of pollen collected by honey bees could be used to infer the phenology of plant communities via comparison to in situ field monitoring at our urban apiary in Toronto, Canada. We found that pooled pollen samples from the five honey bee colonies used in our pilot project could accurately indicate the onset of anthesis, but not its duration, in the wide variety of plant genera they forage on. Increasing the number of colonies used to monitor and employing a multi‐locus approach for metabarcoding of pollen substantially increased the genus detection power of our approach. Here, we demonstrate that metabarcoding of bee‐collected pollen could streamline the establishment of long‐term phenological monitoring programs to document the consequences of global climate change and its impact on the temporal aspects of plant‐pollinator relationships. Multi‐locus metabarcoding of pollen collected by honey bees can reliably indicate the onset of flowering in a large number of plant species. Applications of this method can be used to infer the phenological structure of plant communities, and document phenological reshuffling as a consequence of climate change.

Environmental DNA (eDNA) refers to genetic material collected from the environment and not directly from an organism. eDNA is best known as a tool in aquatic ecology but has been found associated with almost every substrate examined including soils, surfaces, and riding around on other animals. The collection of eDNA from air is one of the most recent advances and has been used to monitor a variety of organisms, including plants, animals, and microorganisms. Current evidence suggests a high turnover rate providing a recent signal for the presence of DNA associated with an organism. Here, we test whether material carried in air can be collected from honey bee hives to evaluate recent foraging behavior and colony health. We sampled air using purpose built “bee safe” air filters operating for 5–6 h at each colony. We successfully recovered plant, fungal and microbial DNA from the air within hives over a 3‐week pilot period. From these data we identified the core honey bee microbiome and plant interaction data representing foraging behavior. We calculated beta diversity to estimate the effects of apiary sites and sampling date on data recovery. We observed that variance in ITS data was influenced by sampling date. Given that honey bees are generalist pollinators our ability to detect temporal signals in associated plant sequence data suggest this method opens new avenues into the ecological analysis of short term foraging behavior at the colony level. In comparison variance in microbial 16S sequencing data was more influenced by sampling location. As the assessment of colony health needs to be localized, spatial variance in these data indicate this may be an important tool in detecting infection. This pilot study demonstrates that colony air filtration has strong potential for the rapid screening of honey bee health and for the study of bee behavior. Using a novel modification of our simple hand airborne eDNA samplers this pilot study demonstrates that eDNA filtered from the air of a honey been colony has the strong potential for rapid screening of honey bee health and for the study of bee foraging behavior.

Abstract Recent declines in the health of honey bee colonies used for crop pollination pose a considerable threat to global food security. Foraging by honey bee workers represents the primary route of exposure to a plethora of toxins and pathogens known to affect bee health, but it remains unclear how foraging preferences impact colony-level patterns of stressor exposure. Resolving this knowledge gap is crucial for enhancing the health of honey bees and the agricultural systems that rely on them for pollination. To address this, we carried out a national-scale experiment encompassing 456 Canadian honey bee colonies to first characterize pollen foraging preferences in relation to major crops and then explore how foraging behavior influences patterns of stressor exposure. We used a metagenetic approach to quantify honey bee dietary breadth and found that bees display distinct foraging preferences that vary substantially relative to crop type and proximity, and the breadth of foraging interactions can be used to predict the abundance and diversity of stressors a colony is exposed to. Foraging on diverse plant communities was associated with increased exposure to pathogens, while the opposite was associated with increased exposure to xenobiotics. Our work provides the first large-scale empirical evidence that pollen foraging behavior plays an influential role in determining exposure to dichotomous stressor syndromes in honey bees.