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Recent research has highlighted the potential of honeybees and bee products as biological samplers for monitoring xenobiotic pollutants. However, the effectiveness of these biological samplers in tracking microplastics (MPs) has not yet been explored. This study evaluates several methods of sampling MPs, using honeybees, pollen, and a novel in-hive passive sampler named the APITrap. The collected samples were characterized using a stereomicroscopy to count and categorise MPs by morphology, colour, and type. To chemical identification, a micro-Fourier transform-infrared (FTIR) spectroscopy was employed to determine the polymer types. The study was conducted across four consecutive surveillance programmes, in five different apiaries in Denmark. Our findings indicated that APITrap demonstrated better reproducibility, with a lower variation in results of 39%, compared to 111% for honeybee samples and 97% for pollen samples. Furthermore, the use of APITrap has no negative impact on bees and can be easily applied in successive samplings. The average number of MPs detected in the four monitoring studies ranged from 39 to 67 in the APITrap, 6 to 9 in honeybee samples, and 6 to 11 in pollen samples. Fibres were the most frequently found, accounting for an average of 91% of the total MPs detected in the APITrap, and similar values for fragments (5%) and films (4%). The MPs were predominantly coloured black, blue, green and red. Spectroscopy analysis confirmed the presence of up to five different synthetic polymers. Polyethylene terephthalate (PET) was the most common in case of fibres and similarly to polypropylene (PP), polyethylene (PE), polyacrylonitrile (PAN) and polyamide (PA) in non fibrous MPs. This study, based on citizen science and supported by beekeepers, highlights the potential of MPs to accumulate in beehives. It also shows that the APITrap provides a highly reliable and comprehensive approach for sampling in large-scale monitoring studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

One of the most critical steps for accurate taxonomic identification in DNA (meta)-barcoding is to have an accurate DNA reference sequence dataset for the marker of choice. Therefore, developing such a dataset has been a long-term ambition, especially in the Viridiplantae kingdom. Typically, reference datasets are constructed with sequences downloaded from general public databases, which can carry taxonomic and other relevant errors. Herein, we constructed a curated (i) global dataset, (ii) European crop dataset, and (iii) 27 datasets for the EU countries for the ITS2 barcoding marker of vascular plants. To that end, we first developed a pipeline script that entails (i) an automated curation stage comprising five filters, (ii) manual taxonomic correction for misclassified taxa, and (iii) manual addition of newly sequenced species. The pipeline allows easy updating of the curated datasets. With this approach, 13% of the sequences, corresponding to 7% of species originally imported from GenBank, were discarded. Further, 259 sequences were manually added to the curated global dataset, which now comprises 307,977 sequences of 111,382 plant species., (© 2024. The Author(s).)

The steady conditions of temperature, humidity and air flux within beehives make them a valuable location for conducting environmental monitoring of pollutants such as PAHs. In this context, the selection of an appropriate apicultural matrix plays a key role in these monitoring studies, as it maximizes the information that will be obtained in the analyses while minimizing the inaccurate results. In the present study, three apicultural matrices (honey bees, pollen and propolis) and two passive samplers (APIStrips and silicone wristbands) are compared in terms of the number and total load of PAHs detected in them. Samplings took place in a total of 11 apiaries scattered in Austria, Denmark, and Greece, with analyses performed by GC-MS/MS. Up to 14 different PAHs were identified in silicone wristbands and pollen, whereas the remaining matrices contained a maximum of five contaminants. Naphthalene, 1-methylnaphthalene, 2-methylnaphthalene, and pyrene were found to be the most prevalent substances in the environment. Recovery studies were also performed; these suggested that the chemical structure of APIStrips is likely to produce very strong interactions with PAHs, thus hindering the adequate desorption of these substances from their surface. Overall, silicone wristbands placed inside the beehives proved the most suitable matrix for PAH monitoring through honey bee colonies., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

The use of apicultural matrices for the environmental monitoring of pesticides is a widely employed approach that facilitates to a great extent the sampling procedures. Honey bees are one of the most commonly employed matrices in these studies due to their abundance in the colonies and their direct contact with the beehive and the environment. However, the analysis of this matrix is associated to a lack of representativity of the contaminants accumulated within the beehive, due mainly to the limited number of honey bees that are sampled and analyzed compared to the population in a hive. This small proportion of organisms which are sampled from the colony may lead to underestimations or overestimations of the total pesticide load, depending on the specific individuals that are included in the analysis. In the present work, the passive, non-invasive APIStrip-based sampling approach is compared to active bee sampling with a total of 240 samples taken from 15 apiaries from Austria, Denmark and Greece over a two-month period in 2022. The APIStrips have been found to provide a more comprehensive image of the pesticide residues accumulated in the beehive in terms of number of identified residues and robustness of the results. A total of 74 different pesticide residues were detected: the use of APIStrips allowed to detect 66 pesticides in the three countries, compared to 38 residues in honey bees. The use of APIStrips also resulted in a higher percentage of positive samples (containing at least one pesticide residue). The results provided by the passive sampling approach were also more consistent among the replicates and over time, which reveals an increased sampling robustness., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jozef J.M. Van der Steen reports financial support was provided by European Commission., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Due to their extensive use in both agricultural and non-agricultural applications, pesticides are a major source of environmental contamination. Honey bee colonies are proven sentinels of these and other contaminants, as they come into contact with them during their foraging activities. However, active sampling strategies involve a negative impact on these organisms and, in most cases, the need of analyzing multiple heterogeneous matrices. Conversely, the APIStrip-based passive sampling is innocuous for the bees and allows for long-term monitorings using the same colony. The versatility of the sorbent Tenax, included in the APIStrip composition, ensures that comprehensive information regarding the contaminants inside the beehive will be obtained in one single matrix. In the present study, 180 APIStrips were placed in nine apiaries distributed in Denmark throughout a six-month sampling period (10 subsequent samplings, April to September 2020). Seventy-five pesticide residues were detected (out of a 428-pesticide scope), boscalid and azoxystrobin being the most frequently detected compounds. There were significant variations in the findings of the sampling sites in terms of number of detections, pesticide diversity and average concentration. A relative indicator of the potential risk of pesticide exposure for the honey bees was calculated for each sampling site. The evolution of pesticide detections over the sampling periods, as well as the individual tendencies of selected pesticides, is herein described. The findings of this large-scale monitoring were compared to the ones obtained in a previous Danish, APIStrip-based pilot monitoring program in 2019. Samples of honey and wax were also analyzed and compared to the APIStrip findings., (Copyright © 2021. Published by Elsevier Ltd.)

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., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

A diverse supply of pollen is an important factor for honey bee health, but information about the pollen diversity available to colonies at the landscape scale is largely missing. In this COLOSS study, beekeeper citizen scientists sampled and analyzed the diversity of pollen collected by honey bee colonies. As a simple measure of diversity, beekeepers determined the number of colors found in pollen samples that were collected in a coordinated and standardized way. Altogether, 750 beekeepers from 28 different regions from 24 countries participated in the two-year study and collected and analyzed almost 18,000 pollen samples. Pollen samples contained approximately six different colors in total throughout the sampling period, of which four colors were abundant. We ran generalized linear mixed models to test for possible effects of diverse factors such as collection, i.e., whether a minimum amount of pollen was collected or not, and habitat type on the number of colors found in pollen samples. To identify habitat effects on pollen diversity, beekeepers' descriptions of the surrounding landscape and CORINE land cover classes were investigated in two different models, which both showed that both the total number and the rare number of colors in pollen samples were positively affected by 'urban' habitats or 'artificial surfaces', respectively. This citizen science study underlines the importance of the habitat for pollen diversity for bees and suggests higher diversity in urban areas.

Microplastics are ubiquitous and their sampling is a difficult task. Honeybees interact with the environment inside their foraging range and take pollutants with them. In this work, we demonstrated for the first time that worker bees can act as active samplers of microplastics. We collected honeybees from apiaries located in the centre of Copenhagen and from nearby semiurban and rural areas. We showed the presence of microplastics in all sampled locations mostly in the form of fragments (52%) and fibres (38%) with average equivalent diameter of 64 ± 39 μm for fibres and 234 ± 156 μm for fragments. The highest load corresponded to urban apiaries, but comparable number of microplastics was found in hives from suburban and rural areas, which can be explained by the presence of urban settlements inside the foraging range of worker bees and to the easy dispersion of small microplastics by wind. Micro-FTIR analysis confirmed the presence of thirteen synthetic polymers, the most frequently of which was polyester followed by polyethylene and polyvinyl chloride. Our results demonstrated the presence of microplastics attached to the body of the honeybees and opens a new research pathway to their use as active biosamplers for anthropogenic pollution., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Honeybee colonies are proven bio-samplers in their foraging area, as organic contaminants such as pesticides are continuously deposited in their hives. However, the use of honeybee colonies for the biomonitoring of contaminants requires the sampling of biological matrices such as bees, pollen, honey or beeswax. This active sampling alters the colonies, especially in the case of frequent sampling intervals. In this study, a non-biological passive sampler based on Tenax TA is described: the APIStrip (Adsorb Pesticide In-hive Strip). A concentrated solution of Tenax in dichloromethane has been applied to a polystyrene strip, resulting in a bee-proof, in-hive passive sampler. The pesticides and related contaminants adsorbed onto its surface can be extracted in acetonitrile and analyzed by LC-MS/MS and GC-MS/MS. The APIStrip preparation has been optimized, the optimal exposure period has been stablished as 14 days and the stability of the pesticides on the APIStrip surface has been evaluated. Preliminary tests demonstrated the efficacy, sensitivity, representativeness and reproducibility of the APIStrip-based sampling when compared to the analysis of beeswax comb, which facilitates the detection of contaminants even in beehives exposed to low polluting pressure. Field studies in Denmark, performed in the INSIGNIA monitoring study over a six-month period, demonstrated their value and applicability by detecting 40 different pesticide residues., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Over the last few decades, a gradual departure away from traditional agricultural practices has resulted in alterations to the composition of the countryside and landscapes across Europe. In the face of such changes, monitoring the development and productivity of honey bee colonies from different sites can give valuable insight on the influence of landscape on their productivity and might point towards future directions for modernized beekeeping practices. Using data on honeybee colony weights provided by electronic scales spread across Denmark, we investigated the effect of the immediate landscape on colony productivity. In order to extract meaningful information, data manipulation was necessary prior to analysis as a result of different management regimes or scales malfunction. Once this was carried out, we were able to show that colonies situated in landscapes composed of more than 50% urban areas were significantly more productive than colonies situated in those with more than 50% agricultural areas or those in mixed areas. As well as exploring some of the potential reasons for the observed differences, we discuss the value of weight monitoring of colonies on a large scale.