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

Unveiling the diet of two generalist stink bugs, Halyomorpha halys and Pentatoma rufipes (Hemiptera: Pentatomidae), through metabarcoding of the ITS2 region from gut content

BACKGROUND

The use of DNA metabarcoding has become an increasingly popular technique to infer feeding relationships in polyphagous herbivores and predators. Understanding host plant preference of native and invasive herbivore insects can be helpful in establishing effective integrated pest management (IPM) strategies. The invasive Halyomorpha halys and native Pentatoma rufipes are piercing-sucking stink bug pests that are known to cause economic damage in commercial fruit orchards.

RESULTS

In this study, we performed molecular gut content analysis (MGCA) on field-collected specimens of these two herbivorous pentatomids using next-generation amplicon sequencing (NGAS) of the internal transcribed spacer 2 (ITS2) barcode region. Additionally, a laboratory experiment was set up where H. halys was switched from a mixed diet to a monotypic diet, allowing us to determine the detectability of the initial diet in a time series of ≤3 days after the diet switch. We detected 68 unique plant species from 54 genera in the diet of two stink bug species, with fewer genera found per sample and a smaller diet breadth for P. rufipes than for H. halys. Both stink bug species generally prefer deciduous trees over gymnosperms and herbaceous plants. Landscape type significantly impacted the observed genera in the diet of both stink bug species, whereas season only had a significant effect on the diet of H. halys.

CONCLUSION

This study provides further insights into the dietary composition of two polyphagous pentatomid pests and illustrates that metabarcoding can deliver a relevant species-level resolution of host plant preference. © 2024 Society of Chemical Industry.

Using pollen DNA metabarcoding to trace the geographical and botanical origin of honey from Karangasem, Indonesia

The unique floral fingerprint embedded within honey holds valuable clues to its geographical and botanical origin, playing a crucial role in ensuring authenticity and detecting adulteration. Honey from native Apis cerana and Heterotrigona itama bees in Karangasem, Indonesia, was examined utilizing pollen DNA metabarcoding for honey source identification. In this study, we used ITS2 amplicon sequencing to identify floral DNA in honey samples. The finding reveals distinct pollen signatures for each bee species. Results analysis showed A. cerana honey generated 179,267 sequence reads, assembled into Amplicon Sequence Variants (ASVs) with a total size of 485,932 bp and an average GC content of 59 %. H. itama honey generated 177,864 sequence reads, assembled into ASVs with a total size of 350,604 bp and an average GC content of 57 %. A. cerana honey exhibited a rich tapestry of pollen from eleven diverse genera, with Schleichera genus dominating at an impressive relative read abundance of 72.8 %. In contrast, H. itama honey displayed a remarkable mono-dominance of the Syzygium genus, accounting for a staggering 99.95 % of its pollen composition or relative read abundance, highlighting their distinct foraging preferences and floral resource utilization. Notably, all identified pollen taxa were indigenous to Karangasem, solidifying the geographical link between honey and its origin. This study demonstrates pollen DNA metabarcoding may identify honey floral sources. By using pollen profiles from different bee species and their foraging patterns, we may protect consumers against honey adulteration and promote sustainable beekeeping in Karangasem district. Future research could explore expanding the database of reference pollen sequences and investigating the influence of environmental factors on pollen composition in honey. Investigating this technology's economic and social effects on beekeepers and consumers may help promote fair trade and sustainable beekeeping worldwide.

Effects of floral resources on honey bee populations in Mexico: Using dietary metabarcoding to examine landscape quality in agroecosystems

The decline of honey bee populations significantly impacts the human food supply due to poor pollination and yield decreases of essential crop species. Given the reduction of pollinators, research into critical landscape components, such as floral resource availability and land use change, might provide valuable information about the nutritional status and health of honey bee colonies. To address this issue, we examine the effects of landscape factors like agricultural area, urban area, and climatic factors, including maximum temperature, minimum temperature, relative humidity, and precipitation, on honey bee hive populations and nutritional health of 326 honey bee colonies across varying landscapes in Mexico. DNA metabarcoding facilitated the precise identification of pollen from 267 plant species, encompassing 243 genera and 80 families, revealing a primary herb-based diet. Areas characterized by high landscape diversity exhibited greater pollen diversity within the colony. Conversely, colonies situated in regions with higher proportions of agricultural and urban landscapes demonstrated lower bee density. The maximum ambient temperature outside hives positively correlated with pollen diversity, aligning with a simultaneous decrease in bee density. Conversely, higher relative humidity positively influenced both the bee density of the colony and the diversity of foraged pollen. Our national-level study investigated pollen dietary availability and colony size in different habitat types, latitudes, climatic conditions, and varied levels and types of disturbances. This effort was taken to gain a better insight into the mechanisms driving declines in honey bee populations. This study illustrates the need for more biodiverse agricultural landscapes, the preservation of diverse habitats, and the conservation of natural and semi-natural spaces. These measures can help to improve the habitat quality of other bee species, as well as restore essential ecosystem processes, such as pollination and pest control.

Flower-bee versus pollen-bee metanetworks in fragmented landscapes

Understanding the organization of mutualistic networks at multiple spatial scales is key to ensure biological conservation and functionality in human-modified ecosystems. Yet, how changing habitat and landscape features affect pollen-bee interaction networks is still poorly understood. Here, we analysed how bee-flower visitation and bee-pollen-transport interactions respond to habitat fragmentation at the local network and regional metanetwork scales, combining data from 29 fragments of calcareous grasslands, an endangered biodiversity hotspot in central Europe. We found that only 37% of the total unique pairwise species interactions occurred in both pollen-transport and flower visitation networks, whereas 28% and 35% were exclusive to pollen-transport and flower visitation networks, respectively. At local level, network specialization was higher in pollen-transport networks, and was negatively related to the diversity of land cover types in both network types. At metanetwork level, pollen transport data revealed that the proportion of single-fragment interactions increased with landscape diversity. Our results show that the specialization of calcareous grasslands' plant-pollinator networks decreases with landscape diversity, but network specialization is underestimated when only based on flower visitation information. Pollen transport data, more than flower visitation, and multi-scale analyses of metanetworks are fundamental for understanding plant-pollinator interactions in human-dominated landscapes.

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).

Stepping towards pollen DNA metabarcoding: A breakthrough in forensic sciences

This review is engaged in determining the capability of plant pollen as a significant source of evidence for the linkage between suspects and crime location in forensic sciences. Research and review articles were collected from Google Scholar, the Web of Science, and PubMed. Articles were searched using specific keywords such as "Forensic Palynology," "Pollen metabarcoding," "Plant forensics," and "Pollen" AND "criminal investigation." Boolean logic was also utilized to narrow the articles to be included in this review article. Through the literature and exploratory research, it has been observed in the current study that with advancements in technology, forensic palynology has found its application in creating an association between the crime scene and suspected individuals to have a link to it, as pollen DNA is a long-lasting investigative tool that can effectively help forensic investigations. Moreover, the literature shows that the DNA of pollen and spores has helped forensic scientists link suspects to crime scenes, and the introduction of pollen DNA metabarcoding tools has eased the efforts of palynologists to analyze pollen DNA. The introduction of DNA metabarcoding techniques to analyze pollen from plants has helped identify the geological locations of the plants and ultimately identify the culprit.

Temporal change in floral availability leads to periods of resource limitation and affects diet specificity in a generalist pollinator

Generalist species are core components of ecological networks and crucial for the maintenance of biodiversity. Generalist species and networks are expected to be more resilient, and therefore understanding the dynamics of specialization and generalization in ecological networks is a key focus in a time of rapid global change. Whilst diet generalization is frequently studied, our understanding of how it changes over time is limited. Here we explore temporal variation in diet specificity in the honeybee (Apis mellifera), using pollen DNA metabarcoding of honey samples, through the foraging season, over two years. We find that, overall, honeybees are generalists that visit a wide range of plants, but there is temporal variation in the degree of specialization. Temporal specialization of honeybee colonies corresponds to periods of resource limitation, identified as a lack of honey stores. Honeybees experience a lack of preferred resources in June when switching from flowering trees in spring to shrubs and herbs in summer. Investigating temporal patterns in specialization can identify periods of resource limitation that may lead to species and network vulnerability. Diet specificity must therefore be explored at different temporal scales in order to fully understand species and network stability in the face of ecological 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.

Unraveling the potential of environmental DNA for deciphering recent advances in plant-animal interactions: a systematic review

MAIN CONCLUSION

Environmental DNA-based monitoring provides critical insights for enhancing our understanding of plant-animal interactions in the context of worldwide biodiversity decrease for developing a global framework for effective plant biodiversity conservation. To understand the ecology and evolutionary patterns of plant-animal interactions (PAI) and their pivotal roles in ecosystem functioning advances in molecular ecology tools such as Environmental DNA (eDNA) provide unprecedented research avenues. These methods being non-destructive in comparison to traditional biodiversity monitoring methods, enhance the discernment of ecosystem health, integrity, and complex interactions. This review intends to offer a systematic and critical appraisal of the prospective of eDNA for investigating PAI. The review thoroughly discusses and analyzes the recent reports (2015-2022) employing preferred reporting items for systematic reviews and meta-analyses (PRISMA) to outline the recent progression in eDNA approaches for elucidating PAI. The current review envisages that eDNA has a significant potential to monitor both plants and associated cohort of prospective pollinators (avian species and flowering plants, bees and plants, arthropods and plants, bats and plants, etc.). Furthermore, a brief description of the factors that influence the utility and interpretation of PAI eDNA is also presented. The review establishes that factors such as biotic and abiotic, primer selection and taxonomic resolution, and indeterminate spatio-temporal scales impact the availability and longevity of eDNA. The study also identified the limitations that influence PAI detection and suggested possible solutions for better execution of these molecular approaches. Overcoming these research caveats will augment the assortment of PAI analysis through eDNA that could be vital for ecosystem health and integrity. This review forms a critical guide and offers prominent insights for ecologists, environmental managers and researchers to assess and evaluate plant-animal interaction through environmental DNA.

Validating a multi-locus metabarcoding approach for characterizing mixed-pollen samples

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.

Microscale pollen release and dispersal patterns in flowering grass populations

Characterizing pollen release and dispersion processes is fundamental for knowledge advancement in ecological, agricultural and public health disciplines. Understanding pollen dispersion from grass communities is especially relevant due to their high species-specific allergenicity and heterogeneously distributed source areas. Here, we aimed to address questions concerning fine level heterogeneity in grass pollen release and dispersion processes, with a focus on characterizing the taxonomic composition of airborne grass pollen over the grass flowering season using eDNA and molecular ecology methods. High resolution grass pollen concentrations were compared between three microscale sites (<300 m apart) in a rural area in Worcestershire, UK. The grass pollen was modelled with local meteorology in a MANOVA (Multivariate ANOVA) approach to investigate factors relevant to pollen release and dispersion. Simultaneously, airborne pollen was sequenced using Illumina MySeq for metabarcoding, analysed against a reference database with all UK grasses using the R packages DADA2 and phyloseq to calculate Shannon's Diversity Index (α-diversity). The flowering phenology of a local Festuca rubra population was observed. We found that grass pollen concentrations varied on a microscale level, likely attributed to local topography and the dispersion distance of pollen from flowering grasses in local source areas. Six genera (Agrostis, Alopecurus, Arrhenatherum, Holcus, Lolium and Poa) dominated the pollen season, comprising on average 77 % of the relative abundance of grass species reads. Temperature, solar radiation, relative humidity, turbulence and wind speeds were found to be relevant for grass pollen release and dispersion processes. An isolated flowering Festuca rubra population contributed almost 40 % of the relative pollen abundance adjacent to the nearby sampler, but only contributed 1 % to samplers situated 300 m away. This suggests that most emitted grass pollen has limited dispersion distance and our results show substantial variation in airborne grass species composition over short geographical scales.

Metabarcoding of eDNA for tracking the floral and geographical origins of bee honey

Authentic honey products have a high commercial value and are often falsified via adulteration. Metabarcoding of environmental DNA (eDNA) from bacterial, floral, and entomological sources has recently been proposed as a useful tool for identifying and authenticating floral and geographical origins of bee honey. In this study, eDNA metabarcoding was applied to reveal the bacterial, plant, and honey bee DNA signatures of 48 commercial honey products from six different geographical origins. Bacterial DNA composition in commercial honey showed different relative abundance of Paenibacillus and Bacillus in geographically different samples, and high abundance of Methylobacterium in chestnut honey implying potential use of bacterial DNA composition for honey authentication. Using the chloroplast trnL (UAA) as a DNA marker, floral origins of commercial honey were investigated. Based on floral DNA signatures, 12 monofloral honey samples were identified among the 45 samples tested. Targeted amplicon sequencing of cytochrome oxidase I (COI) gene from entomological DNA identified three different Apis mellifera sequence variants, specific to geographic origin of honey, suggesting that COI can be implemented as a DNA marker to trace the origin of honey. Therefore, the current study demonstrated the potential of eDNA based metabarcoding as a robust tool for evaluating commercial bee honey by exploring their floral and geographical origins.

Precision Monitoring of Honey Bee (Hymenoptera: Apidae) Activity and Pollen Diversity during Pollination to Evaluate Colony Health

Certain crops depend upon pollination services for fruit set, and, of these, almonds are of high value for Australia. Stressors, such as diseases, parasites, pesticides, and nutrition, can contribute to honey bee Apis mellifera L. colony decline, thereby reducing bee activity and pollination efficiency. In Australia, field studies are required to monitor honey bee health and to ascertain whether factors associated with colony decline are impacting hives. We monitored honey bee colonies during and after pollination services of almond. Video surveillance technology was used to quantify bee activity, and bee-collected pollen was periodically tested for pesticide residues. Plant species diversity was also assessed using DNA metabarcoding of the pollen. Results showed that bee activity increased in almond but not in bushland. Residues detected included four fungicides, although the quantities were of low risk of oral toxicity to bees. Floral diversity was lower in the pollen collected by bees from almonds compared to bushland. However, diversity was higher at the onset and conclusion of the almond bloom, suggesting that bees foraged more widely when availability was low. Our findings suggest that commercial almond orchards may sustain healthier bee colonies compared to bushland in early spring, although the magnitude of the benefit is likely landscape-dependent.

Secretion of IL-6 by fibroblasts exposed to Australian honeys involves lipopolysaccharide and is independent of floral source

Honey stimulates cellular secretion of cytokines, which has been attributed to activation of lipopolysaccharide (LPS)-dependent and LPS-independent pathways. The objective of this study was to identify whether LPS is present in Australian honey samples at levels that can stimulate interleukin-6 (IL-6) secretion by fibroblasts and whether it can transduce cell signalling by activating toll-like receptor 4 (TLR4). IL-6 was measured in culture media of fibroblasts exposed to honey for 24 h. LPS was detected in a 0.125 mg/mL solution of grey ironbark honey (0.61 ± 0.05 ng/g honey). TLR4 signalling was observed in RAW264.7 macrophages that were exposed to honey and this was prevented by preincubating the honey with the LPS-neutralising agent, polymyxin B. Australian Eucalyptus, Leptospermum and Cyathode honeys stimulated IL-6 secretion in cultured human dermal fibroblasts. To examine whether the response was dependent on floral source, fibroblasts were exposed to four different samples of grey ironbark honey obtained from Queensland and New South Wales, Australia. The magnitude of the cytokine response to these honeys was highly varied. We conclude that Australian honeys contain endotoxin at levels that can stimulate IL-6 secretion by fibroblasts and that signalling in macrophages involves TLR4 activation. The IL-6 secretory response was independent of floral source.

DNA metabarcoding for identification of species used in fish burgers

The absence of morphological identification characters, together with the complexity of the fish supply chain make processed seafood vulnerable to cases of species substitution. Therefore, the authentication and the traceability of such products play a strategic role in ensuring quality and safety. The aim of the present study was to detect species used in the production of multi-species fish burgers and to evaluate mislabelling rates, using a DNA metabarcoding approach by sequencing a fragment of the 16S rRNA mitochondrial gene. The study highlighted the presence of 16 marine and 2 mammalian taxa with an overall mislabelling rate of 80%, including cases of species substitution, the undeclared presence of molluscs and of taxa whose use is not permitted by current Italian legislation. The presence of swine DNA as well as the inclusion of undeclared taxa potentially causing allergies raise concerns regarding consumer safety and protection regarding ethical or religious issues. Overall, the study shows that the application of DNA metabarcoding is a promising approach for successfully enforcing traceability systems targeting multi-species processed food and for supporting control activities, as a guarantee of an innovative food safety management system.

The potential of metabarcoding plant components of Malaise trap samples to enhance knowledge of plant-insect interactions

The worldwide rapid declines in insect and plant abundance and diversity that have occurred in the past decades have gained public attention and demand for political actions to counteract these declines are growing. Rapid large-scale biomonitoring can aid in observing these changes and provide information for decisions for land management and species protection. Malaise traps have long been used for insect sampling and when insects are captured in these traps, they carry traces of plants they have visited on the body surface or as digested food material in the gut contents. Metabarcoding offers a promising method for identifying these plant traces, providing insight into the plants with which insects are directly interacting at a given time. To test the efficacy of DNA metabarcoding with these sample types, 79 samples from 21 sites across Germany were analysed with the ITS2 barcode. This study, to our knowledge, is the first examination of metabarcoding plant DNA traces from Malaise trap samples. Here, we report on the feasibility of sequencing these sample types, analysis of the resulting taxa, the usage of cultivated plants by insects near nature conservancy areas and the detection of rare and neophyte species. Due to the frequency of contamination and false positive reads, isolation and PCR negative controls should be used in every reaction. Metabarcoding has advantages in efficiency and resolution over microscopic identification of pollen and is the only possible identification method for the other plant traces from Malaise traps and could provide a broad utility for future studies of plant-insect interactions.

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.

The Honey Bee Apis mellifera: An Insect at the Interface between Human and Ecosystem Health

Simple Summary

Apis mellifera Linnaeus (1758), a honey bee, is a eusocial insect widely known for its role in pollination, an essential ecosystem service for plant biodiversity, and quality of vegetables and fruit products. In addition, honey bees and bee products are valuable bioindicators of pollutants, such as airborne particulate matter, heavy metals, and pesticides. In this review, we explore the provisioning, regulating, and cultural services provided by the honey bee, an insect at the interface between human and ecosystem health.

Abstract

The concept of ecosystem services is widely understood as the services and benefits thatecosystems provide to humans, and they have been categorised into provisioning, regulating, supporting, and cultural services. This article aims to provide an updated overview of the benefits that the honey bee Apis mellifera provides to humans as well as ecosystems. We revised the role of honey bees as pollinators in natural ecosystems to preserve and restore the local biodiversity of wild plants; in agro-ecosystems, this species is widely used to enhance crop yield and quality, meeting the increasing food demand. Beekeeping activity provides humans not only with high-quality food but also with substances used as raw materials and in pharmaceuticals, and in polluted areas, bees convey valuable information on the environmental presence of pollutants and their impact on human and ecosystem health. Finally, the role of the honey bee in symbolic tradition, mysticism, and the cultural values of the bee habitats are also presented. Overall, we suggest that the symbolic value of the honey bee is the most important role played by this insect species, as it may help revitalise and strengthen the intimate and reciprocal relationship between humans and the natural world, avoiding the inaccuracy of considering the ecosystems as mere providers of services to humans.

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.

Preservation methods of honey bee-collected pollen are not a source of bias in ITS2 metabarcoding

Pollen metabarcoding is emerging as a powerful tool for ecological research and offers unprecedented scale in citizen science projects for environmental monitoring via honey bees. Biases in metabarcoding can be introduced at any stage of sample processing and preservation is at the forefront of the pipeline. While in metabarcoding studies pollen has been preserved at - 20 °C (FRZ), this is not the best method for citizen scientists. Herein, we compared this method with ethanol (EtOH), silica gel (SG) and room temperature (RT) for preservation of pollen collected from hives in Austria and Denmark. After ~ 4 months of storage, DNAs were extracted with a food kit, and their quality and concentration measured. Most DNA extracts exhibited 260/280 absorbance ratios close to the optimal 1.8, with RT samples from Austria performing slightly worse than FRZ and SG samples (P < 0.027). Statistical differences were also detected for DNA concentration, with EtOH samples producing lower yields than RT and FRZ samples in both countries and SG in Austria (P < 0.042). Yet, qualitative and quantitative assessments of floral composition obtained using high-throughput sequencing with the ITS2 barcode gave non-significant effects of preservation methods on richness, relative abundance and Shannon diversity, in both countries. While freezing and ethanol are commonly employed for archiving tissue for molecular applications, desiccation is cheaper and easier to use regarding both storage and transportation. Since SG is less dependent on ambient humidity and less prone to contamination than RT, we recommend SG for preserving pollen for metabarcoding. SG is straightforward for laymen to use and hence robust for widespread application in citizen science studies.