In this study, we gathered sequence data from the tRNAleu-cox2 intergenic mitochondrial (mtDNA) region concurrently with single nucleotide polymorphism (SNP) data from 91 loci of nuclear DNA (ncDNA). The data was obtained from 156 colonies sampled in six apiaries from four countries. The full dataset was analysed and discussed for genetic patterns with a focus on cytonuclear diversity and admixture levels. ; This research was funded through the projects BEEHAPPY (POCI-01-0145-FEDER-029871, FCT and COMPETE/QREN/EU) and BEEHEAL. BEEHEAL was funded by the ARIMNet2 2016 Call by the following agencies: INIA (Spain), MOARD (Israel), ANR (France) and FCT (Portugal). ARIMNet2 (ERANET) received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 618127. Ana Rita Lopes is supported by a PhD scholarship (SFRH/BD/143627/2019) from the Foundation for Science and Technology (FCT), Portugal. FCT provided financial support by national funds (FCT/MCTES) to CIMO (UIDB/00690/2020). ; info:eu-repo/semantics/publishedVersion
1. Pollination by insects is a key input into many crops, with managed honeybees often being hired to support pollination services. Despite substantial research into pollination management, no European studies have yet explored how and why farmers managed pollination services and few have explored why beekeepers use certain crops. 2. Using paired surveys of beekeepers and farmers in 10 European countries, this study examines beekeeper and farmer perceptions and motivations surrounding crop pollination. 3. Almost half of the farmers surveyed believed they had pollination service deficits in one or more of their crops. 4. Less than a third of farmers hired managed pollinators; however, most undertook at least one form of agri‐environment management known to benefit pollinators, although few did so to promote pollinators. 5. Beekeepers were ambivalent towards many mass‐flowering crops, with some beekeepers using crops for their honey that other beekeepers avoid because of perceived pesticide risks. 6. The findings highlight a number of largely overlooked knowledge gaps that will affect knowledge exchange and co‐operation between the two groups. ; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Grant/Award Number: 841.11.001; Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja, Grant/Award Number: 43001; Natural Environment Research Council, Grant/Award Number: NE/K015419/1 and NE/N014472/1; Javna Agencija za Raziskovalno Dejavnost RS, Grant/Award Number: V4‐1622 and P1‐0255; Rural and Environment Science and Analytical Services Division; Bayer Crop Science; European Cooperation in Science and Technology, Grant/Award Number: oc‐2013‐1‐15320; BBSRC, Grant/ Award Number: BB/R00580X/1; The Scottish Government Rural Affairs and the Environment Strategic Research Programme ; info:eu-repo/semantics/publishedVersion
1. Pollination by insects is a key input into many crops, with managed honeybees often being hired to support pollination services. Despite substantial research into pollination management, no European studies have yet explored how and why farmers managed pollination services and few have explored why beekeepers use certain crops. 2. Using paired surveys of beekeepers and farmers in 10 European countries, this study examines beekeeper and farmer perceptions and motivations surrounding crop pollination. 3. Almost half of the farmers surveyed believed they had pollination service deficits in one or more of their crops. 4. Less than a third of farmers hired managed pollinators; however, most undertook at least one form of agri‐environment management known to benefit pollinators, although few did so to promote pollinators. 5. Beekeepers were ambivalent towards many mass‐flowering crops, with some beekeepers using crops for their honey that other beekeepers avoid because of perceived pesticide risks. 6. The findings highlight a number of largely overlooked knowledge gaps that will affect knowledge exchange and co‐operation between the two groups. ; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Grant/Award Number: 841.11.001; Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja, Grant/Award Number: 43001; Natural Environment Research Council, Grant/Award Number: NE/K015419/1 and NE/N014472/1; Javna Agencija za Raziskovalno Dejavnost RS, Grant/Award Number: V4‐1622 and P1‐0255; Rural and Environment Science and Analytical Services Division; Bayer Crop Science; European Cooperation in Science and Technology, Grant/Award Number: oc‐2013‐1‐15320; BBSRC, Grant/ Award Number: BB/R00580X/1; The Scottish Government Rural Affairs and the Environment Strategic Research Programme ; info:eu-repo/semantics/publishedVersion
INSIGNIA aims to design and test an innovative, non-invasive, scientifically proven citizen science environmental monitoring protocol for the detection of pesticides via honey bees. It is a pilot project initiated and financed by the European Commission (PP-1-1-2018; EC SANTE). The study is being carried out by a consortium of specialists in honey bees, apiculture, chemistry, molecular biology, statistics, analytics, modelling, extension, social science and citizen science from twelve countries. Honey bee colonies are excellent bio-samplers of biological material such as nectar, pollen and plant pathogens, as well as non-biological material such as pesticides or airborne contamination. Honey bee colonies forage over a circle of about 1 km radius, increasing to several km if required depending on the availability and attractiveness of food. All material collected is concentrated in the hive, and the honey bee colony can provide four main matrices for environmental monitoring: bees, honey, pollen and wax. For pesticides, pollen and wax are the focal matrices. Pollen collected in pollen traps will be sampled every two weeks to record foraging conditions. During the season, most of pollen is consumed within days, so beebread can provide recent, random sampling results. On the other hand wax acts as a passive sampler, building up an archive of pesticides that have entered the hive. Alternative in-hive passive samplers will be tested to replicate wax as a "pesticide-sponge". Samples will be analysed for the presence of pesticides and the botanical origin of the pollen using an ITS2 DNA metabarcoding approach. Data on pollen and pesticides will be then be combined to obtain information on foraging conditions and pesticide use, together with evaluation of the CORINE database for land use and pesticide legislation to model the exposure risks to honey bees and wild bees. All monitoring steps from sampling through to analysis will be studied and tested in four countries in year 1, and the best practices will then be ring-tested in nine countries in year 2. Information about the course of the project and its results and publications will be available in the INSIGNIA website www.insignia-bee.eu. ; info:eu-repo/semantics/publishedVersion
With numerous endemic subspecies representing four of its five evolutionary lineages, Europe holds a large fraction of Apis mellifera genetic diversity. This diversity and the natural distribution range have been altered by anthropogenic factors. The conservation of this natural heritage relies on the availability of accurate tools for subspecies diagnosis. Based on pool-sequence data from 2145 worker bees representing 22 populations sampled across Europe, we employed two highly discriminative approaches (PCA and FST) to select the most informative SNPs for ancestry inference. Results: Using a supervised machine learning (ML) approach and a set of 3896 genotyped individuals, we could show that the 4094 selected single nucleotide polymorphisms (SNPs) provide an accurate prediction of ancestry inference in European honey bees. The best ML model was Linear Support Vector Classifier (Linear SVC) which correctly assigned most individuals to one of the 14 subspecies or different genetic origins with a mean accuracy of 96.2% ± 0.8 SD. A total of 3.8% of test individuals were misclassified, most probably due to limited differentiation between the subspecies caused by close geographical proximity, or human interference of genetic integrity of reference subspecies, or a combination thereof. Conclusions: The diagnostic tool presented here will contribute to a sustainable conservation and support breeding activities in order to preserve the genetic heritage of European honey bees. ; The SmartBees project was funded by the European Commission under its FP7 KBBE programme (2013.1.3–02, SmartBees Grant Agreement number 613960) https://ec.europa.eu/research/fp7. MP was supported by a Basque Government grant (IT1233–19). The funders provided the financial support to the research, but had no role in the design of the study, analysis, interpretations of data and in writing the manuscript. ; info:eu-repo/semantics/publishedVersion
