Standard methods for Apis mellifera anatomy and dissection

An understanding of the anatomy and functions of internal and external structures is fundamental to many studies on the honey bee Apis mellifera. Similarly, proficiency in dissection techniques is vital for many more complex procedures. In this paper, which is a prelude to the other papers of the COLOSS BEEBOOK, we outline basic honey bee anatomy and basic dissection techniques

Honey bee genotypes and the environment

Although knowledge about honey bee geographic and genetic diversity has increased tremendously in recent decades (Meixner et al., 2013), the adaptation of honey bees to their local environment has not been well studied. The current demand for high economic performance of bee colonies with desirable behavioural characteristics contributes to changing the natural diversity via mass importations and an increasing practice of queen trade and colony movement. At the same time, there is also a growing movement in opposition to this trend, aimed at conserving the natural heritage of local populations, with on-going projects in several countries (Strange et al., 2008; Dall’Olio et al., 2008, De la Rúa et al., 2009)

Mapping priority areas for apiculture development with the use of geographical information systems

Supporting local and central authorities in decision-making processes pertaining to environmental planning requires the adoption of scientific methods and the submission of proposals that could be implemented in practice. Taking into consideration the dual role that honeybees play as honey producers and crop pollinators, the aim of the present study is to identify and utilize a number of indicators and subsequently develop priority thematic maps. Previous research has focused on the determination of, and, on certain occasions, on mapping, priority areas for apiculture development, based mainly on the needs of honeybees, without taking into consideration the pollination needs of crops that are cultivated in these areas. In addition, research so far has been carried out in specific spatial entities, in contrast to the current study, in which the areas to be comparatively assessed are pre-chosen based on their geographical boundaries. The information derived from this process is expected to help decision-makers in local and regional authorities to adopt measures for optimal land use and sound pollination practices in order to enhance apiculture development at a local scale. To achieve this target, the study incorporates literature about the attractiveness of crops and plants to pollinating honeybees as well as the pollination services provided by honeybees, in combination with detailed vegetative land cover data. The local communities of each municipality were comparatively evaluated, by introducing three indicators through numerical and spatial data analysis: Relative Attractiveness Index (RAI), Relative Dependence Index (RDI), and Relative Priority Index (RPI). Based on these indicators, attractiveness, dependence, and priority maps were created and explained in detail. We suggest that a number of improvement measures that will boost pollination or honey production or both should be taken by decision-makers, based on the correlations between the aforementioned indicators and the exanimated areas. In addition, dependence maps can constitute a powerful tool for raising awareness among both the public and the farmers about the value of honeybees in pollination, thus reinforcing bee protection efforts undertaken globally. Attractiveness maps that provide a thorough picture of the areas that are sources of pollen and nectar can serve as a general guide for the establishment of hives in areas with high potential for beekeeping

Honey vs. Mite—a trade-off strategy by applying summer brood interruption for Varroa destructor control in the Mediterranean region

Ectoparasitic mite Varroa destructor with its associated viruses is a common global threat to the health of honey bee colonies. If colonies are not treated, the vast majority die in a 3-year period. Existing acaricides used for treatment are becoming less effective, and new approaches to honey bee protection are required. A reliable method is to create a broodless condition in a colony by preventing the queen from laying eggs, and after 25 days all mites will be exposed to the treatment with organic acids or essential oils. The focus of our study, performed on 178 colonies in six Mediterranean countries, was to compare different periods of queen caging on honey production, colony development, and the effect of treatment. Queen caging had no negative effect on colony strength before the wintering period, while it affected honey production; colonies in which queens were caged two weeks before the main summer nectar flow produced significantly less honey. However, tested colonies ten weeks after the treatment had significantly lower infestation with V. destructor mites. This study shows that caging the queen with subsequent oxalic acid treatment 25 days after caging is an efficient method to control V. destructor infestation, while the starting point of queen caging in relation to the main summer nectar flow affects honey production

Evaluation of Suppressed Mite Reproduction (SMR) Reveals Potential for Varroa Resistance in European Honey Bees (Apis melliferaL.)

Simple Summary The miteVarroa destructorrepresents a great threat to honey bees and the beekeeping industry. The opportunity to select and breed honey bees that are naturally able to fight the mite stands a sustainable solution. This can be achieved by evaluation of the failure of mite reproduction (SMR, suppressed mite reproduction). We conducted a large European experiment to assess the SMR trait in different populations of honey bees spread over 13 different countries, and representing different honey bee populations. The first goal was to standardize and validate the SMR evaluation method, and then to compare the SMR trait between the different populations. Our results indicate that it is necessary to examine at least 35 brood cells infested by a single mite to reliably estimate the SMR score of any given colony. Several colonies from our dataset display high SMR scores, indicating that this trait is present within the European honey bee populations. No major differences could be identified between countries for a given population, or between populations in different countries. This study shows the potential to increase selection efforts to breedV. destructorhoney bee resistant populations. In the fight against theVarroa destructormite, selective breeding of honey bee (Apis melliferaL.) populations that are resistant to the parasitic mite stands as a sustainable solution. Selection initiatives indicate that using the suppressed mite reproduction (SMR) trait as a selection criterion is a suitable tool to breed such resistant bee populations. We conducted a large European experiment to evaluate the SMR trait in different populations of honey bees spread over 13 different countries, and representing different honey bee genotypes with their local mite parasites. The first goal was to standardize and validate the SMR evaluation method, and then to compare the SMR trait between the different populations. Simulation results indicate that it is necessary to examine at least 35 single-infested cells to reliably estimate the SMR score of any given colony. Several colonies from our dataset display high SMR scores indicating that this trait is present within the European honey bee populations. The trait is highly variable between colonies and some countries, but no major differences could be identified between countries for a given genotype, or between genotypes in different countries. This study shows the potential to increase selective breeding efforts ofV. destructorresistant populations

Emerging threats and opportunities to managed bee species in European agricultural systems: a horizon scan

Managed bee species provide essential pollination services that contribute to food security worldwide. However, managed bees face a diverse array of threats and anticipating these, and potential opportunities to reduce risks, is essential for the sustainable management of pollination services. We conducted a horizon scanning exercise with 20 experts from across Europe to identify emerging threats and opportunities for managed bees in European agricultural systems. An initial 63 issues were identified, and this was shortlisted to 21 issues through the Horizon Scanning process. These ranged from local landscape-level management to geopolitical issues on a continental and global scale across seven broad themes - Pesticides & pollutants, Technology, Management practices, Predators & parasites, Environmental stressors, Crop modification, and Political & trade influences. While we conducted this Horizon Scan within a European context, the opportunities and threats identified will likely be relevant to other regions. A renewed research and policy focus, especially on the highest-ranking issues, is required to maximise the value of these opportunities and mitigate threats to maintain sustainable and healthy managed bee pollinators within agricultural systems

Queen rearing and selection practices and their impact on the genetic diversity and fitness of honey bee colonies

The Apimondia working group on honey bee diversity and fitness (AWG 7) was created on October 25, 2010 as a Scientific Working Group of Apimondia. The aim of this AWG is to collect information on honey bee queen rearing practices, and examine their impact on the genetic variability and general health of honey bee colonies. The AWG consists of 23 members from 16 different countries. The world wide survey being conducted by this AWG is focused on gathering information on how selection methods, instrumental insemination, disease management procedures, introduction of exotic bee lines, queen replacement strategies, and loss of local colony populations due to introduced parasites and pathogens, affect the ability of our bees to survive and reproduce. The information collected will contribute on an international level to our understanding of how apiculture practices affect honey bee genetics, health and productivity

Authoritative subspecies diagnosis tool for European honey bees based on ancestryinformative SNPs

Background 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 F-ST) 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

CSI pollen: diversity of honey bee collected pollen studied by citizen scientists

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

Multi-dimensional modelling tools supporting decision-making for the beekeeping sector

Honey bee colonies are fundamental for the provision of goods and ecosystem services. Honey bees are highly influenced by environmental conditions and quality, beekeepers’ management practices, socio-economic conditions and policies adopted for cropping and land use. We propose a modelling framework aiming at assessing the bee health status and forecast colony outputs. Two modelling tools are here presented: (i) a Health Status Index (HSI) exploring the consequences of abiotic, biotic drivers and beekeeping actions on bee health; and (ii) predictive models for the estimation of honey production and the provision of pollination service considering abiotic, biotic drivers and HSI. The models proposed represent useful tools for science-based decision support for beekeepers, risk managers and policy-makers