Measuring factors affecting honey bee (Hymenoptera: Apidae) attraction to soybeans using bioacoustics monitoring.

Soybean (Glycine max (L.) Merr.) is an important agricultural crop around the world, and previous studies suggest that honey bees (Apis mellifera Linnaeus) can be a component for optimizing soybean production through pollination. Determining when bees are present in soybean fields is critical for assessing pollination activity and identifying periods when bees are absent so that bee-toxic pesticides may be applied. There are currently several methods for detecting pollinator activity, but these existing methods have substantial limitations, including the bias of pan trappings against large bees and the limited duration of observation possible using manual techniques. This study aimed to develop a new method for detecting honey bees in soybean fields using bioacoustics monitoring. Microphones were placed in soybean fields to record the audible wingbeats of foraging bees. Foraging activity was identified using the wingbeat frequency of honey bees (234 ±â€…14 Hz) through a combination of algorithmic and manual approaches. A total of 243 honey bees were detected over 10 days of recording in 4 soybean fields. Bee activity was significantly greater in blooming fields than in non-blooming fields. Temperature had no significant effect on bee activity, but bee activity differed significantly between soybean varieties, suggesting that soybean attractiveness to honey bees is heavily dependent on varietal characteristics. Refinement of bioacoustics methods, particularly through the incorporation of machine learning, could provide a practical tool for measuring the activity of honey bees and other flying insects in soybeans as well as other crops and ecosystems.

Review: the risks of spray adjuvants to honey bees.

Pesticide applications are often made as tank mixes containing multiple pesticide products and may include spray adjuvants to enhance pesticidal activities. The primary aim of adjuvant products is to increase the spreading and sticking of spray droplets and to increase the penetration of active ingredients through the cuticles of leaves or targeted pests, which can reduce the amount of active ingredient needed for effective pest control. Adjuvants are made up of compounds drawn from the "inert ingredient" list maintained by EPA but are identified as "principal functioning agents" when used in adjuvant products. These inert compounds do not undergo the same testing and risk assessment process that is required of pesticide active ingredients and generally have no mitigation measures that prevent application onto crops during bloom at times of day when bees are foraging. Honey bees (Apis mellifera;Hymenoptera:Apidae) are at an increased risk of exposure to adjuvant tank mixtures while providing agricultural pollination services. Colony losses attributed to pesticide applications thought to have low risk to honey bees have been reported, highlighting the need to better understand the toxicity of adjuvants included in pesticide tank mixtures. This review summarizes current literature on the risks posed to honey bees by agricultural adjuvants and tank mix combinations of adjuvants with pesticides. Based on the current state of knowledge, we make recommendations to pesticide applicators, product manufacturers, regulatory agencies, and researchers regarding adjuvant toxicity to honey bees with the goal of reducing risks that adjuvants pose to honey bees and other beneficial insects.

Effects of pesticide-adjuvant combinations used in almond orchards on olfactory responses to social signals in honey bees (Apis mellifera).

Exposure to agrochemical sprays containing pesticides and tank-mix adjuvants has been implicated in post-bloom mortality, particularly of brood, in honey bee colonies brought into California almond orchards for pollination. Although adjuvants are generally considered to be biologically inert, some adjuvants have exhibited toxicity and sublethal effects, including decreasing survival rates of next-generation queens. Honey bees have a highly developed olfactory system to detect and discriminate among social signals. To investigate the impact of pesticide-adjuvant combinations on honey bee signal perception, we performed electroantennography assays to assess alterations in their olfactory responsiveness to the brood ester pheromone (BEP), the volatile larval pheromone ß-ocimene, and the alarm pheromone 2-heptanone. These assays aimed to uncover potential mechanisms underlying changes in social behaviors and reduced brood survival after pesticide exposure. We found that combining the adjuvant Dyne-Amic with the fungicide Tilt (propiconazole) and the insecticide Altacor (chlorantraniliprole) synergistically enhanced olfactory responses to three concentrations of BEP and as well exerted dampening and compensatory effects on responses to 2-heptanone and ß-ocimene, respectively. In contrast, exposure to adjuvant alone or the combination of fungicide and insecticide had no effect on olfactory responses to BEP at most concentrations but altered responses to ß-ocimene and 2-heptanone. Exposure to Dyne-Amic, Altacor, and Tilt increased BEP signal amplitude, indicating potential changes in olfactory receptor sensitivity or sensilla permeability to odorants. Given that, in a previous study, next-generation queens raised by nurses exposed to the same treated pollen experienced reduced survival, these new findings highlight the potential disruption of social signaling in honey bees and its implications for colony reproductive success.

Toxicity of spray adjuvants and tank mix combinations used in almond orchards to adult honey bees (Apis mellifera).

Commercial beekeepers transporting honey bees across the United States to provide almond pollination services have reported honey bee deaths, possibly due to pesticide applications made during crop bloom. Pesticides are often applied as "tank mixes", or mixtures of fungicides and insecticides combined into a single application. Spray adjuvants are often added to tank mixes to improve the application characteristics of a pesticide and include spreaders, stickers, or surfactants. The goal of this research was to determine toxicity of adjuvants to adult worker honey bees, both when applied alone and in adjuvant-pesticide tank mixtures. Field-relevant combinations of formulated products were applied to 3-day-old adult worker honey bees using a Potter Spray Tower, and mortality was assessed 48 h following exposure. Adjuvants tested included Activator-90, Attach, Choice Weather Master, Cohere, Dyne-Amic, Induce, Kinetic, LI 700, Liberate, Nu-Film P, PHT Latron B-1956, and Surf-90; fungicides tested include Luna Sensation (Fluopyram and Trifloxystrobin), Pristine (Pyraclostrobin and Boscalid), Tilt (Propiconazole), and Vangard (Cyprodinil), and insecticides tested include Altacor (Chlorantraniliprole), Intrepid 2F (Methoxyfenozide), and a positive control Mustang Maxx (Zeta-cypermethrin). Results demonstrated that exposure to some adjuvants causes acute honey bee mortality at near-field application rates, both when applied alone and in combination with pesticides. Some adjuvant-pesticide combinations demonstrated increased toxicity compared with the adjuvant alone, while others demonstrated decreased toxicity. A better understanding of adjuvant and adjuvant-pesticide tank mixture toxicity to honey bees will play a key role in informing "Best Management Practices" for pesticide applicators using spray adjuvants during bloom when honey bee exposure is likely.

Soybean is a Common Nectar Source for Honey Bees (Hymenoptera: Apidae) in a Midwestern Agricultural Landscape.

Large-scale soybean [Glycine max (L.) Merr.] cultivation has substantially transformed the Midwestern landscape in recent decades. Floral nectar produced by immense fields of soybeans has the potential to influence foraging ecology and resource accumulation of honey bee (Apis mellifera L.) colonies. In this study, we combined microscopic and molecular pollen analysis of honey samples with waggle dance inference of spatial foraging patterns to demonstrate that honey bees routinely forage on soybeans in Ohio. In analyzing honey samples from across the state, we found ubiquitous presence of soybean pollen in honey collected from agricultural lands during soybean bloom. The abundance of soybean pollen in honey increased with the amount of soybean fields surrounding the apiaries. Honey bee waggle dances recorded during soybean bloom revealed that honey bees preferred soybean fields for foraging over other habitat types. With these results, future research efforts aimed at enhancing mutual interactions between soybeans and honey bees may represent an unexplored pathway for increasing soybean production while supporting honey bees and other pollinators in the surrounding landscape.

Acute Toxicity of Fungicide-Insecticide-Adjuvant Combinations Applied to Almonds During Bloom on Adult Honey Bees.

Beekeepers report significant honey bee deaths during and after almond bloom. These losses pose a major problem for the California almond industry because of its dependence on honey bees as pollinators. The present study aimed to determine if combinations of pesticides applied during almond bloom during daylight hours were a possible explanation for these losses. In this study we aimed to mimic the spray application route of exposure to pesticides using a Potter Spray Tower to treat adult honey bees with commonly encountered pesticides and pesticide combinations at multiples of the maximum recommended field application rates. Tested insecticides included Altacor® and Intrepid®, and tested fungicides included Tilt®, Pristine®, Luna Sensation®, and Vangard®. Synergistic toxicity was observed when the fungicide Tilt (active ingredient propiconazole) was applied with the insecticide Altacor (chlorantraniliprole), though neither caused significant mortality when applied independently. The study also looked at the effect of adding a spray adjuvant, Dyne-Amic®, to pesticide mixtures. Dyne-Amic was toxic to honey bees at concentrations above the maximum recommended field application rate, and toxicity was increased when combined with the fungicide Pristine (pyraclostrobin and boscalid). Addition of Dyne-Amic also increased toxicity of the Tilt and Altacor combination. These results suggest that application of Altacor and Tilt in combination with an adjuvant at the recommended field application rates could cause mortality in adult honey bees. These findings highlight a potential explanation for honey bee losses around almond bloom, emphasize that the safety of spray adjuvants to bees should not be assumed, and provide support for recommendations to protect bees from pesticides through application at night when bees are not foraging. Environ Toxicol Chem 2022;41:1042-1053. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Pollen Treated with a Combination of Agrochemicals Commonly Applied During Almond Bloom Reduces the Emergence Rate and Longevity of Honey Bee (Hymenoptera: Apidae) Queens.

Honey bee (Apis mellifera L.) colonies that pollinate California's almond orchards are often exposed to mixtures of agrochemicals. Although agrochemicals applied during almond bloom are typically considered bee-safe when applied alone, their combined effects to honey bees are largely untested. In recent years, beekeepers providing pollination services to California's almond orchards have reported reductions in queen quality during and immediately after bloom, raising concerns that pesticide exposure may be involved. Previous research identified a synergistic effect between the insecticide active ingredient chlorantraniliprole and the fungicide active ingredient propiconazole to lab-reared worker brood, but their effects to developing queens are unknown. To test the individual and combined effects of these pesticides on the survival and emergence of developing queens, we fed worker honey bees in closed queen rearing boxes with pollen artificially contaminated with formulated pesticides containing these active ingredients as well as the spray adjuvant Dyne-Amic, which contains both organosilicone and alkyphenol ethoxylate. The translocation of pesticides from pesticide-treated pollen into the royal jelly secretions of nurse bees was also measured. Despite consistently low levels of all pesticide active ingredients in royal jelly, the survival of queens from pupation to 7 d post-emergence were reduced in queens reared by worker bees fed pollen containing a combination of formulated chlorantraniliprole (Altacor), propiconazole (Tilt), and Dyne-Amic, as well as the toxic standard, diflubenzuron (Dimilin 2L), applied in isolation. These results support recommendations to protect honey bee health by avoiding application of pesticide tank-mixes containing insecticides and adjuvants during almond bloom.

Application of plant metabarcoding to identify diverse honeybee pollen forage along an urban-agricultural gradient.

Understanding animal foraging ecology requires large sample sizes spanning broad environmental and temporal gradients. For pollinators, this has been hampered by the laborious nature of morphologically identifying pollen. Identifying pollen from urban environments is particularly difficult due to the presence of diverse ornamental species associated with consumer horticulture. Metagenetic pollen analysis represents a potential solution to this issue. Building upon prior laboratory and bioinformatic methods, we applied quantitative multilocus metabarcoding to characterize the foraging ecology of honeybee colonies situated in urban, suburban, mixed suburban-agricultural and rural agricultural sites in central Ohio, USA. In cross-validating a subset of our metabarcoding results using microscopic palynology, we find strong concordance between the molecular and microscopic methods. Our results suggest that forage from the agricultural site exhibited decreased taxonomic diversity and temporal turnover relative to the urban and suburban sites, though the generalization of this observation will require replication across additional sites and cities. Our work demonstrates the power of honeybees as environmental samplers of floral community composition at large spatial scales, aiding in the distinction of taxa characteristically associated with urban or agricultural land use from those distributed ubiquitously across the sampled landscapes. Observed patterns of high forage diversity and compositional turnover in our more urban sites are likely reflective of the fine-grain heterogeneity and high beta diversity of urban floral landscapes at the scale of honeybee foraging. This provides guidance for future studies investigating how relationships between urbanization and measures of pollinator health are mediated by variation in floral resource dynamics across landscapes.

Honey Bees and Neonicotinoid-Treated Corn Seed: Contamination, Exposure, and Effects.

Most corn (Zea mays) seeds planted in the United States in recent years are coated with a seed treatment containing neonicotinoid insecticides. Abrasion of the seed coating generates insecticide-laden planter dust that disperses through the landscape during corn planting and has resulted in many "bee-kill" incidents in North America and Europe. We investigated the linkage between corn planting and honey bee colony success in a region dominated by corn agriculture. Over 3 yr we consistently observed an increased presence of corn seed treatment insecticides in bee-collected pollen and elevated worker bee mortality during corn planting. Residues of seed treatment neonicotinoids, clothianidin and thiamethoxam, detected in pollen positively correlated with cornfield area surrounding the apiaries. Elevated worker mortality was also observed in experimental colonies fed field-collected pollen containing known concentrations of corn seed treatment insecticides. We monitored colony growth throughout the subsequent year in 2015 and found that colonies exposed to higher insecticide concentrations exhibited slower population growth during the month of corn planting but demonstrated more rapid growth in the month following, though this difference may be related to forage availability. Exposure to seed treatment neonicotinoids during corn planting has clear short-term detrimental effects on honey bee colonies and may affect the viability of beekeeping operations that are dependent on maximizing colony size in the springtime. Environ Toxicol Chem 2021;40:1212-1221. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Combined Toxicity of Insecticides and Fungicides Applied to California Almond Orchards to Honey Bee Larvae and Adults.

Beekeepers providing pollination services for California almond orchards have reported observing dead or malformed brood during and immediately after almond bloom-effects that they attribute to pesticide exposure. The objective of this study was to test commonly used insecticides and fungicides during almond bloom on honey bee larval development in a laboratory bioassay. In vitro rearing of worker honey bee larvae was performed to test the effect of three insecticides (chlorantraniliprole, diflubenzuron, and methoxyfenozide) and three fungicides (propiconazole, iprodione, and a mixture of boscalid-pyraclostrobin), applied alone or in insecticide-fungicide combinations, on larval development. Young worker larvae were fed diets contaminated with active ingredients at concentration ratios simulating a tank-mix at the maximum label rate. Overall, larvae receiving insecticide and insecticide-fungicide combinations were less likely to survive to adulthood when compared to the control or fungicide-only treatments. The insecticide chlorantraniliprole increased larval mortality when combined with the fungicides propiconazole or iprodione, but not alone; the chlorantraniliprole-propiconazole combination was also found to be highly toxic to adult workers treated topically. Diflubenzuron generally increased larval mortality, but no synergistic effect was observed when combined with fungicides. Neither methoxyfenozide nor any methoxyfenozide-fungicide combination increased mortality. Exposure to insecticides applied during almond bloom has the potential to harm honey bees and this effect may, in certain instances, be more damaging when insecticides are applied in combination with fungicides.

Quantitative multi-locus metabarcoding and waggle dance interpretation reveal honey bee spring foraging patterns in Midwest agroecosystems.

We explored the pollen foraging behaviour of honey bee colonies situated in the corn and soybean dominated agroecosystems of central Ohio over a month-long period using both pollen metabarcoding and waggle dance inference of spatial foraging patterns. For molecular pollen analysis, we developed simple and cost-effective laboratory and bioinformatics methods. Targeting four plant barcode loci (ITS2, rbcL, trnL and trnH), we implemented metabarcoding library preparation and dual-indexing protocols designed to minimize amplification biases and index mistagging events. We constructed comprehensive, curated reference databases for hierarchical taxonomic classification of metabarcoding data and used these databases to train the metaxa2 DNA sequence classifier. Comparisons between morphological and molecular palynology provide strong support for the quantitative potential of multi-locus metabarcoding. Results revealed consistent foraging habits between locations and show clear trends in the phenological progression of honey bee spring foraging in these agricultural areas. Our data suggest that three key taxa, woody Rosaceae such as pome fruits and hawthorns, Salix, and Trifolium provided the majority of pollen nutrition during the study. Spatially, these foraging patterns were associated with a significant preference for forests and tree lines relative to herbaceous land cover and nonflowering crop fields.

A reference cytochrome c oxidase subunit I database curated for hierarchical classification of arthropod metabarcoding data.

Metabarcoding is a popular application which warrants continued methods optimization. To maximize barcoding inferences, hierarchy-based sequence classification methods are increasingly common. We present methods for the construction and curation of a database designed for hierarchical classification of a 157 bp barcoding region of the arthropod cytochrome c oxidase subunit I (COI) locus. We produced a comprehensive arthropod COI amplicon dataset including annotated arthropod COI sequences and COI sequences extracted from arthropod whole mitochondrion genomes, the latter of which provided the only source of representation for Zoraptera, Callipodida and Holothyrida. The database contains extracted sequences of the target amplicon from all major arthropod clades, including all insect orders, all arthropod classes and Onychophora, Tardigrada and Mollusca outgroups. During curation, we extracted the COI region of interest from approximately 81 percent of the input sequences, corresponding to 73 percent of the genus-level diversity found in the input data. Further, our analysis revealed a high degree of sequence redundancy within the NCBI nucleotide database, with a mean of approximately 11 sequence entries per species in the input data. The curated, low-redundancy database is included in the Metaxa2 sequence classification software (http://microbiology.se/software/metaxa2/). Using this database with the Metaxa2 classifier, we performed a cross-validation analysis to characterize the relationship between the Metaxa2 reliability score, an estimate of classification confidence, and classification error probability. We used this analysis to select a reliability score threshold which minimized error. We then estimated classification sensitivity, false discovery rate and overclassification, the propensity to classify sequences from taxa not represented in the reference database. Our work will help researchers design and evaluate classification databases and conduct metabarcoding on arthropods and alternate taxa.

Metaxa2 Database Builder: enabling taxonomic identification from metagenomic or metabarcoding data using any genetic marker.

Motivation: Correct taxonomic identification of DNA sequences is central to studies of biodiversity using both shotgun metagenomic and metabarcoding approaches. However, no genetic marker gives sufficient performance across all the biological kingdoms, hampering studies of taxonomic diversity in many groups of organisms. This has led to the adoption of a range of genetic markers for DNA metabarcoding. While many taxonomic classification software tools can be re-trained on these genetic markers, they are often designed with assumptions that impair their utility on genes other than the SSU and LSU rRNA. Here, we present an update to Metaxa2 that enables the use of any genetic marker for taxonomic classification of metagenome and amplicon sequence data. Results: We evaluated the Metaxa2 Database Builder on 11 commonly used barcoding regions and found that while there are wide differences in performance between different genetic markers, our software performs satisfactorily provided that the input taxonomy and sequence data are of high quality. Availability and implementation: Freely available on the web as part of the Metaxa2 package at http://microbiology.se/software/metaxa2/. Supplementary information: Supplementary data are available at Bioinformatics online.

Cytochrome P450 diversification and hostplant utilization patterns in specialist and generalist moths: Birth, death and adaptation.

Across insect genomes, the size of the cytochrome P450 monooxygenase (CYP) gene superfamily varies widely. CYPome size variation has been attributed to reciprocal adaptive radiations in insect detoxification genes in response to plant biosynthetic gene radiations driven by co-evolution between herbivores and their chemically defended hostplants. Alternatively, variation in CYPome size may be due to random "birth-and-death" processes, whereby exponential increase via gene duplications is limited by random decay via gene death or transition via divergence. We examined CYPome diversification in the genomes of seven Lepidoptera species varying in host breadth from monophagous (Bombyx mori) to highly polyphagous (Amyelois transitella). CYPome size largely reflects the size of Clan 3, the clan associated with xenobiotic detoxification, and to some extent phylogenetic age. Consistently across genomes, families CYP6, CYP9 and CYP321 are most diverse and CYP6AB, CYP6AE, CYP6B, CYP9A and CYP9G are most diverse among subfamilies. Higher gene number in subfamilies is due to duplications occurring primarily after speciation and specialization ("P450 blooms"), and the genes are arranged in clusters, indicative of active duplicating loci. In the parsnip webworm, Depressaria pastinacella, gene expression levels in large subfamilies are high relative to smaller subfamilies. Functional and phylogenetic data suggest a correlation between highly dynamic loci (reflective of extensive gene duplication, functionalization and in some cases loss) and the ability of enzymes encoded by these genes to metabolize hostplant defences, consistent with an adaptive, nonrandom process driven by ecological interactions.

Evaluating and optimizing the performance of software commonly used for the taxonomic classification of DNA metabarcoding sequence data.

The taxonomic classification of DNA sequences has become a critical component of numerous ecological research applications; however, few studies have evaluated the strengths and weaknesses of commonly used sequence classification approaches. Further, the methods and software available for sequence classification are diverse, creating an environment in which it may be difficult to determine the best course of action and the trade-offs made using different classification approaches. Here, we provide an in silico evaluation of three DNA sequence classifiers, the rdp Naïve Bayesian Classifier, rtax and utax. Further, we discuss the results, merits and limitations of both the classifiers and our method of classifier evaluation. Our methods of comparison are simple, yet robust, and will provide researchers a methodological and conceptual foundation for making such evaluations in a variety of research situations. Generally, we found a considerable trade-off between accuracy and sensitivity for the classifiers tested, indicating a need for further improvement of sequence classification tools.

Mechanistic modeling of pesticide exposure: The missing keystone of honey bee toxicology.

The role of pesticides in recent honey bee losses is controversial, partly because field studies often fail to detect effects predicted by laboratory studies. This dissonance highlights a critical gap in the field of honey bee toxicology: there exists little mechanistic understanding of the patterns and processes of exposure that link honey bees to pesticides in their environment. The authors submit that 2 key processes underlie honey bee pesticide exposure: 1) the acquisition of pesticide by foraging bees, and 2) the in-hive distribution of pesticide returned by foragers. The acquisition of pesticide by foraging bees must be understood as the spatiotemporal intersection between environmental contamination and honey bee foraging activity. This implies that exposure is distributional, not discrete, and that a subset of foragers may acquire harmful doses of pesticide while the mean colony exposure would appear safe. The in-hive distribution of pesticide is a complex process driven principally by food transfer interactions between colony members, and this process differs importantly between pollen and nectar. High priority should be placed on applying the extensive literature on honey bee biology to the development of more rigorously mechanistic models of honey bee pesticide exposure. In combination with mechanistic effects modeling, mechanistic exposure modeling has the potential to integrate the field of honey bee toxicology, advancing both risk assessment and basic research. Environ Toxicol Chem 2017;36:871-881. © 2016 SETAC.

An insecticide resistance-breaking mosquitocide targeting inward rectifier potassium channels in vectors of Zika virus and malaria.

Insecticide resistance is a growing threat to mosquito control programs around the world, thus creating the need to discover novel target sites and target-specific compounds for insecticide development. Emerging evidence suggests that mosquito inward rectifier potassium (Kir) channels represent viable molecular targets for developing insecticides with new mechanisms of action. Here we describe the discovery and characterization of VU041, a submicromolar-affinity inhibitor of Anopheles (An.) gambiae and Aedes (Ae.) aegypti Kir1 channels that incapacitates adult female mosquitoes from representative insecticide-susceptible and -resistant strains of An. gambiae (G3 and Akron, respectively) and Ae. aegypti (Liverpool and Puerto Rico, respectively) following topical application. VU041 is selective for mosquito Kir channels over several mammalian orthologs, with the exception of Kir2.1, and is not lethal to honey bees. Medicinal chemistry was used to develop an analog, termed VU730, which retains activity toward mosquito Kir1 but is not active against Kir2.1 or other mammalian Kir channels. Thus, VU041 and VU730 are promising chemical scaffolds for developing new classes of insecticides to combat insecticide-resistant mosquitoes and the transmission of mosquito-borne diseases, such as Zika virus, without harmful effects on humans and beneficial insects.

Rank-based characterization of pollen assemblages collected by honey bees using a multi-locus metabarcoding approach.

PREMISE OF THE STUDY: Difficulties inherent in microscopic pollen identification have resulted in limited implementation for large-scale studies. Metabarcoding, a relatively novel approach, could make pollen analysis less onerous; however, improved understanding of the quantitative capacity of various plant metabarcode regions and primer sets is needed to ensure that such applications are accurate and precise. METHODS AND RESULTS: We applied metabarcoding, targeting the ITS2, matK, and rbcL loci, to characterize six samples of pollen collected by honey bees, Apis mellifera. Additionally, samples were analyzed by light microscopy. We found significant rank-based associations between the relative abundance of pollen types within our samples as inferred by the two methods. CONCLUSIONS: Our findings suggest metabarcoding data from plastid loci, as opposed to the ribosomal locus, are more reliable for quantitative characterization of pollen assemblages. Furthermore, multilocus metabarcoding of pollen may be more reliable than single-locus analyses, underscoring the need for discovering novel barcodes and barcode combinations optimized for molecular palynology.

Social evolution. Genomic signatures of evolutionary transitions from solitary to group living.

The evolution of eusociality is one of the major transitions in evolution, but the underlying genomic changes are unknown. We compared the genomes of 10 bee species that vary in social complexity, representing multiple independent transitions in social evolution, and report three major findings. First, many important genes show evidence of neutral evolution as a consequence of relaxed selection with increasing social complexity. Second, there is no single road map to eusociality; independent evolutionary transitions in sociality have independent genetic underpinnings. Third, though clearly independent in detail, these transitions do have similar general features, including an increase in constrained protein evolution accompanied by increases in the potential for gene regulation and decreases in diversity and abundance of transposable elements. Eusociality may arise through different mechanisms each time, but would likely always involve an increase in the complexity of gene networks.

Application of ITS2 metabarcoding to determine the provenance of pollen collected by honey bees in an agroecosystem.

PREMISE OF THE STUDY: Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees. Information provided by melissopalynology could guide floral enrichment efforts aimed at supporting pollinators, but it has rarely been used because traditional methods of pollen identification are laborious and require expert knowledge. We approach melissopalynology in a novel way, employing a molecular method to study the pollen foraging of honey bees (Apis mellifera) in a landscape dominated by field crops, and compare these results to those obtained by microscopic melissopalynology. • METHODS: Pollen was collected from honey bee colonies in Madison County, Ohio, USA, during a two-week period in midspring and identified using microscopic methods and ITS2 metabarcoding. • RESULTS: Metabarcoding identified 19 plant families and exhibited sensitivity for identifying the taxa present in large and diverse pollen samples relative to microscopy, which identified eight families. The bulk of pollen collected by honey bees was from trees (Sapindaceae, Oleaceae, and Rosaceae), although dandelion (Taraxacum officinale) and mustard (Brassicaceae) pollen were also abundant. • DISCUSSION: For quantitative analysis of pollen, using both metabarcoding and microscopic identification is superior to either individual method. For qualitative analysis, ITS2 metabarcoding is superior, providing heightened sensitivity and genus-level resolution.