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

Finding the perfect pairs: A matchmaking of plant markers and primers for multi-marker eDNA metabarcoding

As the scope of plant eDNA metabarcoding diversifies, so do the primers, markers and methods. A wealth of primers exists today, but their comparative evaluation is lacking behind. Similarly, multi-marker approaches are recommended but debates persist regarding barcode complementarity and optimal combinations. After a literature compilation of used primers, we compared in silico 102 primer pairs based on amplicon size, coverage and specificity, followed by an experimental evaluation of 15 primer pairs on a mock community sample covering 268 plant species and genera, and about 100 families. The analysis was done for the four most common plant metabarcoding markers, rbcL, trnL, ITS1 and ITS2 and their complementarity was assessed based on retrieved species. By focusing on existing primers, we identify common designs, promote alternatives and enhance prior-supported primers for immediate applications. The ITS2 was the best-performing marker for flowering vascular plants and was congruent to ITS1. However, the combined taxonomic breadth of ITS2 and rbcL surpassed any other combination, highlighting their high complementarity across Streptophyta. Overall, our study underscores the significance of comprehensive primer and barcode evaluations tailored to metabarcoding applications.

How reliable is metabarcoding for pollen identification? An evaluation of different taxonomic assignment strategies by cross-validation

Metabarcoding is a powerful tool, increasingly used in many disciplines of environmental sciences. However, to assign a taxon to a DNA sequence, bioinformaticians need to choose between different strategies or parameter values and these choices sometimes seem rather arbitrary. In this work, we present a case study on ITS2 and rbcL databases used to identify pollen collected by bees in Belgium. We blasted a random sample of sequences from the reference database against the remainder of the database using different strategies and compared the known taxonomy with the predicted one. This in silico cross-validation (CV) approach proved to be an easy yet powerful way to (1) assess the relative accuracy of taxonomic predictions, (2) define rules to discard dubious taxonomic assignments and (3) provide a more objective basis to choose the best strategy. We obtained the best results with the best blast hit (best bit score) rather than by selecting the majority taxon from the top 10 hits. The predictions were further improved by favouring the most frequent taxon among those with tied best bit scores. We obtained better results with databases containing the full sequences available on NCBI rather than restricting the sequences to the region amplified by the primers chosen in our study. Leaked CV showed that when the true sequence is present in the database, blast might still struggle to match the right taxon at the species level, particularly with rbcL. Classical 10-fold CV-where the true sequence is removed from the database-offers a different yet more realistic view of the true error rates. Taxonomic predictions with this approach worked well up to the genus level, particularly for ITS2 (5-7% of errors). Using a database containing only the local flora of Belgium did not improve the predictions up to the genus level for local species and made them worse for foreign species. At the species level, using a database containing exclusively local species improved the predictions for local species by ∼12% but the error rate remained rather high: 25% for ITS2 and 42% for rbcL. Foreign species performed worse even when using a world database (59-79% of errors). We used classification trees and GLMs to model the % of errors vs. identity and consensus scores and determine appropriate thresholds below which the taxonomic assignment should be discarded. This resulted in a significant reduction in prediction errors, but at the cost of a much higher proportion of unassigned sequences. Despite this stringent filtering, at least 1/5 sequences deemed suitable for species-level identification ultimately proved to be misidentified. An examination of the variability in prediction accuracy between plant families showed that rbcL outperformed ITS2 for only two of the 27 families examined, and that the % correct species-level assignments were much better for some families (e.g. 95% for Sapindaceae) than for others (e.g. 35% for Salicaceae).

Plants, pollinators and their interactions under global ecological change: The role of pollen DNA metabarcoding

Anthropogenic activities are triggering global changes in the environment, causing entire communities of plants, pollinators and their interactions to restructure, and ultimately leading to species declines. To understand the mechanisms behind community shifts and declines, as well as monitoring and managing impacts, a global effort must be made to characterize plant-pollinator communities in detail, across different habitat types, latitudes, elevations, and levels and types of disturbances. Generating data of this scale will only be feasible with rapid, high-throughput methods. Pollen DNA metabarcoding provides advantages in throughput, efficiency and taxonomic resolution over traditional methods, such as microscopic pollen identification and visual observation of plant-pollinator interactions. This makes it ideal for understanding complex ecological networks and their responses to change. Pollen DNA metabarcoding is currently being applied to assess plant-pollinator interactions, survey ecosystem change and model the spatiotemporal distribution of allergenic pollen. Where samples are available from past collections, pollen DNA metabarcoding has been used to compare contemporary and past ecosystems. New avenues of research are possible with the expansion of pollen DNA metabarcoding to intraspecific identification, analysis of DNA in ancient pollen samples, and increased use of museum and herbarium specimens. Ongoing developments in sequencing technologies can accelerate progress towards these goals. Global ecological change is happening rapidly, and we anticipate that high-throughput methods such as pollen DNA metabarcoding are critical for understanding the evolutionary and ecological processes that support biodiversity, and predicting and responding to the impacts of change.

Pollen DNA metabarcoding reveals cryptic diversity and high spatial turnover in alpine plant-pollinator networks

Alpine plant-pollinator communities play an important role in the functioning of alpine ecosystems, which are highly threatened by climate change. However, we still have a poor understanding of how environmental factors and spatiotemporal variability shape these communities. Here, we investigate what drives structure and beta diversity in a plant-pollinator metacommunity from the Australian alpine region using two approaches: pollen DNA metabarcoding (MB) and observations. Individual pollinators often carry pollen from multiple plant species, and therefore we expected MB to reveal a more diverse and complex network structure. We used two gene regions (ITS2 and trnL) to identify plant species present in the pollen loads of 154 insect pollinator specimens from three alpine habitats and construct MB networks, and compared them to networks based on observations alone. We compared species and interaction turnover across space for both types of networks, and evaluated their differences for plant phylogenetic diversity and beta diversity. We found significant structural differences between the two types of networks; notably, MB networks were much less specialized but more diverse than observation networks, with MB detecting many cryptic plant species. Both approaches revealed that alpine pollination networks are very generalized, but we estimated a high spatial turnover of plant species (0.79) and interaction rewiring (0.6) as well as high plant phylogenetic diversity (0.68) driven by habitat differences based on the larger diversity of plant species and species interactions detected with MB. Overall, our findings show that habitat and microclimatic heterogeneity drives diversity and fine-scale spatial turnover of alpine plant-pollinator networks.

Environmental metagenetics unveil novel plant-pollinator interactions

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.

A primer on pollen assignment by nanopore-based DNA sequencing

The possibility to identify plants based on the taxonomic information coming from their pollen grains offers many applications within various biological disciplines. In the past and depending on the application or research in question, pollen origin was analyzed by microscopy, usually preceded by chemical treatment methods. This procedure for identification of pollen grains is both time-consuming and requires expert knowledge of morphological features. Additionally, these microscopically recognizable features usually have a low resolution at species-level. Since a few decades, DNA has been used for the identification of pollen taxa, as sequencing technologies evolved both in their handling and affordability. We discuss advantages and challenges of pollen DNA analyses compared to traditional methods. With readers with little experience in this field in mind, we present a hands-on primer for genetic pollen analysis by nanopore sequencing. As our lab mainly works with pollen collected within agroecological research projects, we focus on pollen collected by pollinating insects. We briefly consider sample collection, storage and processing in the laboratory as well as bioinformatic aspects. Currently, pollen metabarcoding is mostly conducted with next-generation sequencing methods that generate short sequence reads (<1 kb). Increasingly, however, pollen DNA analysis is carried out using the long-read generating (several kb), low-budget and mobile MinION nanopore sequencing platform by Oxford Nanopore Technologies. Therefore, we are focusing on aspects for palynology with the MinION DNA sequencing device.

Laboratory protocol is important to improve the correlation between target copies and metabarcoding read numbers of seed DNA in ground beetle regurgitates

DNA metabarcoding is increasingly important for studying feeding interactions, yet it remains unresolved whether reporting read counts or occurrences is to be preferred. To address this issue for gut content samples, basic experimental data on the relationship between read numbers and initial prey DNA amounts and how both change over digestion time is needed. Using regurgitates of the carabid Pseudoophonus rufipes the digestion of Taraxacum officinale seeds was documented for 128 h post-feeding to determine how the number of (1) seed DNA copies and (2) metabarcoding reads change over digestion time, and (3) how they correlate to each other. Additionally, we tested (4) whether PCR cycle-numbers during library preparation affect this correlation. The number of copies and reads both decreased with digestion time, but variation between samples was high. Read and copy numbers correlated when using a library preparation protocol with 35 cycles (R² = 42.0%), yet a reduction to 30 cycles might significantly improve this correlation, as indicated by additional PCR testing. Our findings show that protocol optimization is important to reduce technical distortions of read numbers in metabarcoding analysis. However, high inter-sample variation, likely due to variable digestive efficiency of individual consumers, can blur the relationship between the amount of food consumed and metabarcoding read numbers.

Wild Bee Nutritional Ecology: Integrative Strategies to Assess Foraging Preferences and Nutritional Requirements

Bees depend on flowering plants for their nutrition, and reduced availability of floral resources is a major driver of declines in both managed and wild bee populations. Understanding the nutritional needs of different bee species, and how these needs are met by the varying nutritional resources provided by different flowering plant taxa, can greatly inform land management recommendations to support bee populations and their associated ecosystem services. However, most bee nutrition research has focused on the three most commonly managed and commercially reared bee taxa—honey bees, bumble bees, and mason bees—with fewer studies focused on wild bees and other managed species, such as leafcutting bees, stingless bees, and alkali bees. Thus, we have limited information about the nutritional requirements and foraging preferences of the vast majority of bee species. Here, we discuss the approaches traditionally used to understand bee nutritional ecology: identification of floral visitors of selected focal plant species, evaluation of the foraging preferences of adults in selected focal bee species, evaluation of the nutritional requirements of focal bee species (larvae or adults) in controlled settings, and examine how these methods may be adapted to study a wider range of bee species. We also highlight emerging technologies that have the potential to greatly facilitate studies of the nutritional ecology of wild bee species, as well as evaluate bee nutritional ecology at significantly larger spatio-temporal scales than were previously feasible. While the focus of this review is on bee species, many of these techniques can be applied to other pollinator taxa as well.

Using Metabarcoding to Investigate the Strength of Plant-Pollinator Interactions From Surveys of Visits to DNA Sequences

The ongoing decline in pollinators and increasing concerns about pollination services require a better understanding of complex pollination networks, particularly their response to global climate change. While metabarcoding is increasingly used for the identification of taxa in DNA mixtures, its reliability in providing quantitative information on plant-pollinator interactions is still the subject of debate. Combining metabarcoding and microscopy, we investigated the relationships between the number and composition of sequences and the abundance and composition of pollen in insect pollen loads (IPL) and how the two are linked to insect visits. Our findings confirm that metabarcoding is more effective than microscopy in identifying plant species in IPL. For a given species, we found a strong positive relationship between the amount of pollen in IPL and the number of sequences. The relationship was stable across species even if the abundance of co-occurring species in IPL (hereafter “co-occurring pollen”) tended to reduce the sequence yield (number of sequences obtained from one pollen grain) of a given species. We also found a positive relationship between the sequence count and the frequency of visits, and between the frequency and the amounts of pollen in IPL. Our results demonstrate the reliability of metabarcoding in assessing the strength of plant-pollinator interactions and in providing a broader perspective for the analyses of plant-pollinator interactions and pollination networks.

Using DNA Metabarcoding to Identify Floral Visitation by Pollinators

The identification of floral visitation by pollinators provides an opportunity to improve our understanding of the fine-scale ecological interactions between plants and pollinators, contributing to biodiversity conservation and promoting ecosystem health. In this review, we outline the various methods which can be used to identify floral visitation, including plant-focused and insect-focused methods. We reviewed the literature covering the ways in which DNA metabarcoding has been used to answer ecological questions relating to plant use by pollinators and discuss the findings of this research. We present detailed methodological considerations for each step of the metabarcoding workflow, from sampling through to amplification, and finally bioinformatic analysis. Detailed guidance is provided to researchers for utilisation of these techniques, emphasising the importance of standardisation of methods and improving the reliability of results. Future opportunities and directions of using molecular methods to analyse plant–pollinator interactions are then discussed.

A Comparison of Springtime Pollen and Nectar Foraging in Honey Bees Kept in Urban and Agricultural Environments

Spring is an essential time for honey bee foraging in temperate climates. This is a period of increased brood rearing supporting colony growth and demands access to high-quality pollen and nectar resources. With the expansion of urban and agricultural landscapes, the availability of pollen and nectar producing flowers is declining in many areas. We aim to determine how patterns of spring pollen and nectar foraging differ between colonies surrounded by varying degrees of urban and agricultural intensity, as well as to assess the potential for nectar sampling to serve as a proxy for pollen collection. Thirteen apiaries in Central Ohio, along a gradient of urban and agricultural intensity, were monitored in spring of 2019 through the periodic collection of pollen and nectar samples and continuous colony weight monitoring. We found that spring honey bees in urban and agricultural areas gain comparable amounts of weight and use similar spring resources. Foraging was heavily focused on flowering trees and shrubs including Malus (apple), Salix (willow), and Prunus (cherry), until the beginning of clover bloom (Trifolium spp.). We also identified differences in pollen and nectar foraging within colonies, with nectar containing fewer species collected more evenly than matched pollen samples. These results demonstrate that honey bees in both agricultural and urban environments exhibit similar foraging patterns during the spring, and that plant species important for nectar collection are substantially different from plants important for pollen foraging, though limitations in nectar collection hinder our ability to draw definitive comparisons of pollen and nectar foraging in this region.

DNA metabarcoding using nrITS2 provides highly qualitative and quantitative results for airborne pollen monitoring

Airborne pollen monitoring is of global socio-economic importance as it provides information on presence and prevalence of allergenic pollen in ambient air. Traditionally, this task has been performed by microscopic investigation, but novel techniques are being developed to automate this process. Among these, DNA metabarcoding has the highest potential of increasing the taxonomic resolution, but uncertainty exists about whether the results can be used to quantify pollen abundance. In this study, it is shown that DNA metabarcoding using trnL and nrITS2 provides highly improved taxonomic resolution for pollen from aerobiological samples from the Netherlands. A total of 168 species from 143 genera and 56 plant families were detected, while using a microscope only 23 genera and 22 plant families were identified. NrITS2 produced almost double the number of OTUs and a much higher percentage of identifications to species level (80.1%) than trnL (27.6%). Furthermore, regressing relative read abundances against the relative abundances of microscopically obtained pollen concentrations showed a better correlation for nrITS2 (R2 = 0.821) than for trnL (R2 = 0.620). Using three target taxa commonly encountered in early spring and fall in the Netherlands (Alnus sp., Cupressaceae/Taxaceae and Urticaceae) the nrITS2 results showed that all three taxa were dominated by one or two species (Alnus glutinosa/incana, Taxus baccata and Urtica dioica). Highly allergenic as well as artificial hybrid species were found using nrITS2 that could not be identified using trnL or microscopic investigation (Alnus × spaethii, Cupressus arizonica, Parietaria spp.). Furthermore, perMANOVA analysis indicated spatiotemporal patterns in airborne pollen trends that could be more clearly distinguished for all taxa using nrITS2 rather than trnL. All results indicate that nrITS2 should be the preferred marker of choice for molecular airborne pollen monitoring.

Plant biodiversity assessment through pollen DNA metabarcoding in Natura 2000 habitats (Italian Alps)

Monitoring biodiversity is of increasing importance in natural ecosystems. Metabarcoding can be used as a powerful molecular tool to complement traditional biodiversity monitoring, as total environmental DNA can be analyzed from complex samples containing DNA of different origin. The aim of this research was to demonstrate the potential of pollen DNA metabarcoding using the chloroplast trnL partial gene sequencing to characterize plant biodiversity. Collecting airborne biological particles with gravimetric Tauber traps in four Natura 2000 habitats within the Natural Park of Paneveggio Pale di San Martino (Italian Alps), at three-time intervals in 1 year, metabarcoding identified 68 taxa belonging to 32 local plant families. Metabarcoding could identify with finer taxonomic resolution almost all non-rare families found by conventional light microscopy concurrently applied. However, compared to microscopy quantitative results, Poaceae, Betulaceae, and Oleaceae were found to contribute to a lesser extent to the plant biodiversity and Pinaceae were more represented. Temporal changes detected by metabarcoding matched the features of each pollen season, as defined by aerobiological studies running in parallel, and spatial heterogeneity was revealed between sites. Our results showcase that pollen metabarcoding is a promising approach in detecting plant species composition which could provide support to continuous monitoring required in Natura 2000 habitats for biodiversity conservation.

Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering Approaches

Although DNA metabarcoding of pollen mixtures has been increasingly used in the field of pollination biology, methodological and interpretation issues arise due to its high sensitivity. Filtering or maintaining false positives, contaminants, and rare taxa or molecular features could lead to different ecological results. Here, we reviewed how this choice has been addressed in 43 studies featuring pollen DNA metabarcoding, which highlighted a very high heterogeneity of filtering methods. We assessed how these strategies shaped pollen assemblage composition, species richness, and interaction networks. To do so, we compared four processing methods: unfiltering, filtering with a proportional 1% of sample reads, a fixed threshold of 100 reads, and the ROC approach (Receiver Operator Characteristic). The results indicated that filtering impacted species composition and reduced species richness, with ROC emerging as a conservative approach. Moreover, in contrast to unfiltered networks, filtering decreased network Connectance and Entropy, and it increased Modularity and Connectivity, indicating that using cut-off thresholds better describes interactions. Overall, unfiltering might compromise reliable ecological interpretations, unless a study targets rare species. We discuss the suitability of each filtering type, plead for justifying filtering strategies on biological or methodological bases and for developing shared approaches to make future studies more comparable.

Capabilities and limitations of using DNA metabarcoding to study plant-pollinator interactions

Many pollinator populations are experiencing declines, emphasizing the need for a better understanding of the complex relationship between bees and flowering plants. Using DNA metabarcoding to describe plant-pollinator interactions eliminates many challenges associated with traditional methods and has the potential to reveal a more comprehensive understanding of foraging behavior and pollinator life history. Here we use DNA metabarcoding of ITS2 and rbcL gene regions to identify plant species present in pollen loads of 404 bees from three habitats in eastern Oregon. Our specific objectives were to 1) determine whether plant species identified using DNA metabarcoding are consistent with plant species identified using observations, 2) compare characterizations of diet breadth derived from foraging observations to those based on plant species assignments obtained using DNA metabarcoding, and 3) compare plant species assignments produced by DNA metabarcoding using a "regional" reference database to those produced using a "local" database. At the three locations, 31-86% of foraging observations were consistent with DNA metabarcoding data, 8-50% of diet breadth characterizations based on observations differed from those based on DNA metabarcoding data, and 22-25% of plant species detected using the regional database were not known to occur in the study area in question. Plant-pollinator networks produced from DNA metabarcoding data had higher sampling completeness and significantly lower specialization than networks based on observations. Here, we examine some strengths and limitations of using DNA metabarcoding to identify plant species present in bee pollen loads, make ecological inferences about foraging behavior, and provide guidance for future research.

Pollen DNA metabarcoding identifies regional provenance and high plant diversity in Australian honey

Accurate identification of the botanical components of honey can be used to establish its geographical provenance, while also providing insights into honeybee (Apis mellifera L.) diet and foraging preferences. DNA metabarcoding has been demonstrated as a robust method to identify plant species from pollen and pollen-based products, including honey. We investigated the use of pollen metabarcoding to identify the floral sources and local foraging preferences of honeybees using 15 honey samples from six bioregions from eastern and western Australia. We used two plant metabarcoding markers, ITS2 and the trnL P6 loop. Both markers combined identified a total of 55 plant families, 67 genera, and 43 species. The trnL P6 loop marker provided significantly higher detection of taxa, detecting an average of 15.6 taxa per sample, compared to 4.6 with ITS2. Most honeys were dominated by Eucalyptus and other Myrtaceae species, with a few honeys dominated by Macadamia (Proteaceae) and Fabaceae. Metabarcoding detected the nominal primary source provided by beekeepers among the top five most abundant taxa for 85% of samples. We found that eastern and western honeys could be clearly differentiated by their floral composition, and clustered into bioregions with the trnL marker. Comparison with previous results obtained from melissopalynology shows that metabarcoding can detect similar numbers of plant families and genera, but provides significantly higher resolution at species level. Our results show that pollen DNA metabarcoding is a powerful and robust method for detecting honey provenance and examining the diet of honeybees. This is particularly relevant for hives foraging on the unique and diverse flora of the Australian continent, with the potential to be used as a novel monitoring tool for honeybee floral resources.

Using RNA-seq to characterize pollen-stigma interactions for pollination studies

Insects are essential for the reproduction of pollinator-dependent crops and contribute to the pollination of 87% of wild plants and 75% of the world’s food crops. Understanding pollen flow dynamics between plants and pollinators is thus essential to manage and conserve wild plants and ensure yields are maximized in food crops. However, the determination of pollen transfer in the field is complex and laborious. We developed a field experiment in a pollinator-dependent crop and used high throughput RNA sequencing (RNA-seq) to quantify pollen flow by measuring changes in gene expression between pollination treatments across different apple (Malus domestica Borkh.) cultivars. We tested three potential molecular indicators of successful pollination and validated these results with field data by observing single and multiple visits by honey bees (Apis mellifera) to apple flowers and measured fruit set in a commercial apple orchard. The first indicator of successful outcrossing was revealed via differential gene expression in the cross-pollination treatments after 6 h. The second indicator of successful outcrossing was revealed by the expression of specific genes related to pollen tube formation and defense response at three different time intervals in the stigma and the style following cross-pollination (i.e. after 6, 24, and 48 h). Finally, genotyping variants specific to donor pollen could be detected in cross-pollination treatments, providing a third indicator of successful outcrossing. Field data indicated that one or five flower visits by honey bees were insufficient and at least 10 honey bee flower visits were required to achieve a 25% probability of fruit set under orchard conditions. By combining the genotyping data, the differential expression analysis, and the traditional fruit set field experiments, it was possible to evaluate the pollination effectiveness of honey bee visits under orchards conditions. This is the first time that pollen-stigma-style mRNA expression analysis has been conducted after a pollinator visit (honey bee) to a plant (in vivo apple flowers). This study provides evidence that mRNA sequencing can be used to address complex questions related to stigma–pollen interactions over time in pollination ecology.

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.

Diverse Diets with Consistent Core Microbiome in Wild Bee Pollen Provisions

Bees collect pollen from flowers for their offspring, and by doing so contribute critical pollination services for our crops and ecosystems. Unlike many managed bee species, wild bees are thought to obtain much of their microbiome from the environment. However, we know surprisingly little about what plant species bees visit and the microbes associated with the collected pollen. Here, we addressed the hypothesis that the pollen and microbial components of bee diets would change across the range of the bee, by amplicon sequencing pollen provisions of a widespread small carpenter bee, Ceratina calcarata, across three populations. Ceratina calcarata was found to use a diversity of floral resources across its range, but the bacterial genera associated with pollen provisions were very consistent. Acinetobacter, Erwinia, Lactobacillus, Sodalis, Sphingomonas and Wolbachia were among the top ten bacterial genera across all sites. Ceratina calcarata uses both raspberry (Rubus) and sumac (Rhus) stems as nesting substrates, however nests within these plants showed no preference for host plant pollen. Significant correlations in plant and bacterial co-occurrence differed between sites, indicating that many of the most common bacterial genera have either regional or transitory floral associations. This range-wide study suggests microbes present in brood provisions are conserved within a bee species, rather than mediated by climate or pollen composition. Moving forward, this has important implications for how these core bacteria affect larval health and whether these functions vary across space and diet. These data increase our understanding of how pollinators interact with and adjust to their changing environment.

Introduced bees (Osmia cornifrons) collect pollen from both coevolved and novel host-plant species within their family-level phylogenetic preferences

Studying the pollen preferences of introduced bees allows us to investigate how species use host-plants when establishing in new environments. Osmia cornifrons is a solitary bee introduced into North America from East Asia for pollination of Rosaceae crops such as apples and cherries. We investigated whether O. cornifrons (i) more frequently collected pollen from host-plant species they coevolved with from their geographic origin, or (ii) prefer host-plant species of specific plant taxa independent of origin. To address this question, using pollen metabarcoding, we examined the identity and relative abundance of pollen in larval provisions from nests located in different landscapes with varying abundance of East-Asian and non-Asian plant species. Our results show that O. cornifrons collected more pollen from plant species from their native range. Plants in the family Rosaceae were their most preferred pollen hosts, but they differentially collected species native to East Asia, Europe, or North America depending on the landscape. Our results suggest that while O. cornifrons frequently collect pollen of East-Asian origin, the collection of pollen from novel species within their phylogenetic familial affinities is common and can facilitate pollinator establishment. This phylogenetic preference highlights the effectiveness of O. cornifrons as crop pollinators of a variety of Rosaceae crops from different geographic origins. Our results imply that globalization of non-native plant species may ease the naturalization of their coevolved pollinators outside of their native range.

Flowers in Conservation Reserve Program (CRP) Pollinator Plantings and the Upper Midwest Agricultural Landscape Supporting Honey Bees

A present goal of the Conservation Reserve Program (CRP) is to manage land in agricultural landscapes to increase pollinator abundance and diversity. CP42, or the pollinator seed mix, is planted and managed to support foraging pollinators with blooming flowers present at all points in the foraging season. This high-quality habitat provides an excellent opportunity to study honey bee nutrition and determine whether honey bees located near CRP sites use known resources included in planting seed mixes. This study aims to highlight the primary sources of honey bee forage in the northern Midwest as well as to assess honey bee utilization of the floral resources provided by the pollinator seed mix used for CRP plantings. We received pollen samples collected using pollen traps by beekeepers in Ohio, South Dakota, Indiana, Illinois, and Michigan. Metabarcoding methods were used to identify and quantify pollen collected at different points in the season. The results indicate that honey bees frequently used major mass flowering resources such as Glycine, Trifolium, and Symphiotrichum throughout the season. In addition, flowers included in the CRP pollinator seed mix were used modestly. These results have implications for pollinator seed mix design.

Experimental quantification of pollen with DNA metabarcoding using ITS1 and trnL

Although the use of metabarcoding to identify taxa in DNA mixtures is widely approved, its reliability in quantifying taxon abundance is still the subject of debate. In this study we investigated the relationships between the amount of pollen grains in mock solutions and the abundance of high-throughput sequence reads and how the relationship was affected by the pollen counting methodology, the number of PCR cycles, the type of markers and plant species whose pollen grains have different characteristics. We found a significant positive relationship between the number of DNA sequences and the number of pollen grains in the mock solutions. However, better relationships were obtained with light microscopy as a pollen grain counting method compared with flow cytometry, with the chloroplastic trnL marker compared with ribosomal ITS1 and with 30 when compared with 25 or 35 PCR cycles. We provide a list of recommendations to improve pollen quantification.

A screening-level assessment of the pollinator-attractiveness of ornamental nursery stock using a honey bee foraging assay

In urban and suburban landscapes characterized by extensive designed greenspaces, the support of pollinator communities hinges significantly on floral resources provided by ornamental plants. The attractiveness of ornamental plants to pollinators, however, cannot be presumed, and some studies suggest that a majority of ornamental plant varieties receive little or no pollinator visitation. Here, we harness the sampling power of the western honey bee, a generalist pollinator whose diet breadth overlaps substantially with that of other pollinators, to survey the utilization of ornamental plants grown at three commercial nurseries in Connecticut, USA. Using a combination of DNA metabarcoding and microscopy, we identify, to genus-level, pollen samples from honey bee colonies placed within each nursery, and we compare our results with nursery plant inventories to identify the subset of cultivated genera that were visited during pollen foraging. Samples were collected weekly from May to September, encompassing the majority of the growing season. Our findings show that some plant genera known to be cultivated as ornamentals in our system, particularly ornamental trees and shrubs (e.g. Hydrangea, Rosa, Spiraea, Syringa, Viburnum), functioned as major pollen sources, but the majority of plants inventoried at our nurseries provided little or no pollen to honey bees. These results are in agreement with a growing body of literature highlighting the special importance of woody plants as resources for flower-visiting insects. We encourage further exploration of the genera highlighted in our data as potential components of pollinator-friendly ornamental greenspace.

Pollinator specialization increases with a decrease in a mass-flowering plant in networks inferred from DNA metabarcoding

How native mass-flowering plants affect the specialization of insects at individual and species levels and the consequences for pollination networks have received much less attention than for mass-flowering crops or alien species and basically remain unexplored.Using existing DNA metabarcoding data on the pollen loads of 402 flower-visiting insects, we assessed the effects of a native mass-flowering plant of high reward quality, the shrub Rhododendron ferrugineum, on pollination networks by investigating: (a) the food niches of individual pollinators and pollinator species and (b) the structure of individual and species networks in subalpine heathland patches with extremely contrasted densities of R. ferrugineum.Relative to its high abundance in high-density patches, the shrub was greatly underrepresented and did not dominate individual's or species' generalized networks, rather individual and species specialization increased with a decrease in R. ferrugineum density. Furthermore, individuals of the more generalist dipteran Empididae species tended to extend exclusive interactions with rare plant species in low-density networks. The same trend was observed in the more specialist Apidea but toward rare species in high-density networks. Our results reveal a quite paradoxical view of pollination and a functional complementarity within networks. Niche and network indices mostly based on the occurrence of links showed that individual pollinators and pollinator species and networks were highly generalized, whereas indices of link strength revealed that species and above all individuals behave as quite strict specialists. Synthesis. Our study provides insights into the status of a native mass-flowering plant in individual's and insect species' food niches and pollination networks. It revealed that a generalist pollinator species can be highly specialized at the individual level and how rare plant species coexisting with mass-flowering plants may nevertheless be visited.

A citizen science supported study on seasonal diversity and monoflorality of pollen collected by honey bees in Austria

Austrian beekeepers participated in the “C.S.I. Pollen” study as citizen scientists and collected pollen from honey bee colonies in hive mounted traps every three weeks from April to September in 2014 and 2015 to uncover the seasonal availability of pollen sources for bees. 1622 pollen samples were collected and analysed using palynological light microscopy to the lowest taxonomic level possible. For 2014 and 2015 combined, 239 pollen types from more than 85 families were detected. ‘Various unknown’ species, Taraxacum-form and Plantago spp. were the pollen types collected by the majority of colonies (occurrence), whereas the most pollen grains collected were from Trifolium repens-form, Plantago spp. and Salix spp. (abundance). In spring, trees were found to be the most abundant pollen source, whereas in summer herbs dominated. On average, a colony collected pollen from 16.8 ± 4.7 (2014) and 15.0 ± 4.4 (2015) pollen types per sampling. Those numbers, however, vary between sampling dates and indicate a seasonal pattern. This is also supported by Simpson’s diversity index, which was on median 0.668. In both years, 50.0% of analysed pollen samples were partially (>50%) and 4.2% were highly monofloral (i.e. containing >90% of one pollen type). Prevalence of monofloral pollen samples peaked at the beginning and the end of the season, when pollen diversity was the lowest.

Linking pollen foraging of megachilid bees to their nest bacterial microbiota

Solitary bees build their nests by modifying the interior of natural cavities, and they provision them with food by importing collected pollen. As a result, the microbiota of the solitary bee nests may be highly dependent on introduced materials. In order to investigate how the collected pollen is associated with the nest microbiota, we used metabarcoding of the ITS2 rDNA and the 16S rDNA to simultaneously characterize the pollen composition and the bacterial communities of 100 solitary bee nest chambers belonging to seven megachilid species. We found a weak correlation between bacterial and pollen alpha diversity and significant associations between the composition of pollen and that of the nest microbiota, contributing to the understanding of the link between foraging and bacteria acquisition for solitary bees. Since solitary bees cannot establish bacterial transmission routes through eusociality, this link could be essential for obtaining bacterial symbionts for this group of valuable pollinators.

OPEN RESEARCH BADGES

This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at https://www.ebi.ac.uk/ena/data/view/PRJEB27223, https://www.ebi.ac.uk/ena/data/view/PRJEB31610, and https://doi.org/10.5061/dryad.qk36k8q.