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a b s t r a c tWorldwide, wild bumble bees (Bombus spp.) are experiencing marked declines, with potentially up to 11% of species currently under threat. Recent studies from North America suggest that disease transmission from commercially reared bumble bees to wild populations has led to marked range contractions in some species. In Europe, data on the prevalence of pathogen spillover from commercial to wild bumble bee populations is lacking, despite the widespread production and transport of hives within the EU since the early 1980s. We determined the permeability of cropping systems to commercial bumble bees, and quantified the prevalence of four pathogens in commercial Bombus terrestris hives and adjacent conspecific populations at increasing distances from greenhouses in Ireland. Commercial bumble bees collected from 31% to 97% of non-crop pollen, depending on the cropping system, and hives had markedly higher frequencies of two gut parasites, Crithidia spp. and Nosema bombi, compared to adjacent populations, but were free of tracheal mites. The highest prevalence of Crithida was observed within 2 km of greenhouses and the probability of infection declined in a host sex-and pathogen-specific manner up to 10 km. We suggest implementing measures that prevent the interaction of commercially reared and wild bumble bees by integrating the enforcement of national best management practices for users of commercial pollinators with international legislation that regulates the sanitation of commercial hives in production facilities.

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This short article presents loss rates of honey bee colonies over winter 2017/18 from 36 countries, including 33 in Europe, from data collected using the standardized COLOSS questionnaire. The 25,363 beekeepers supplying data passing consistency checks in total wintered 544,879 colonies, and reported 26,379 (4.8%, 95% CI 4.7-5.0%) colonies with unsolvable queen problems, 54,525 (10.0%, 95% CI 9.8-10.2%) dead colonies after winter and another 8,220 colonies (1.5%, 95% CI 1.4-1.6%) lost through natural disaster. This gave an overall loss rate of 16.4% (95% CI 16.1-16.6%) of honey bee colonies during winter 2017/18, but this varied greatly from 2.0 to 32.8% between countries. The included map shows relative risks of winter loss at regional level. The analysis using the total data-set confirmed findings from earlier surveys that smaller beekeeping operations with at most 50 colonies suffer significantly higher losses than larger operations (p < .001). Beekeepers migrating their colonies had significantly lower losses than those not migrating (p < .001), a different finding from previous research. Evaluation of six different forage sources as potential risk factors for colony loss indicated that intensive foraging on any of five of these plant sources (Orchards, Oilseed Rape, Maize, Heather and Autumn Forage Crops) was associated with significantly higher winter losses. This finding requires further study and explanation. A table is included giving detailed results of loss rates and the impact of the tested forage sources for each country and overall.

In this short note we present comparable loss rates of honey bee colonies during winter 2015/16 from 29 countries, obtained with the COLOSS questionnaire. Altogether, we received valid answers from 19,952 beekeepers. These beekeepers collectively wintered 421,238 colonies, and reported 18,587 colonies with unsolvable queen problems and 32,048 dead colonies after winter. This gives an overall loss rate of 12.0% (95% confidence interval 11.8%-12.2%) during winter 2015/16, with marked differences among countries. Beekeepers in the present study assessed 7.6% (95% CI 7.4%-7.8%) of their colonies as dead or empty, and 4.4% (95% CI 4.3%-4.5%) as having unsolvable queen problems after winter. The overall analysis showed that small operations suffered higher losses than larger ones. A table with detailed results and a map showing response and relative risks at regional level are presented

This article presents managed honey bee colony loss rates over winter 2018/19 resulting from using the standardised COLOSS questionnaire in 35 countries (31 in Europe). In total, 28,629 beekeepers supplying valid loss data wintered 738,233 colonies, and reported 29,912 (4.1%, 95% confidence interval (CI) 4.0-4.1%) colonies with unsolvable queen problems, 79,146 (10.7%, 95% CI 10.5-10.9%) dead colonies after winter and 13,895 colonies (1.9%, 95% CI 1.8-2.0%) lost through natural disaster. This gave an overall colony winter loss rate of 16.7% (95% CI 16.4-16.9%), varying greatly between countries, from 5.8% to 32.0%. We modelled the risk of loss as a dead/empty colony or from unresolvable queen problems, and found that, overall, larger beekeeping operations with more than 150 colonies experienced significantly lower losses (p < 0.001), consistent with earlier studies. Additionally, beekeepers included in this survey who did not migrate their colonies at least once in 2018 had significantly lower losses than those migrating (p < 0.001). The percentage of new queens from 2018 in wintered colonies was also examined as a potential risk factor. The percentage of colonies going into winter with a new queen was estimated as 55.0% over all countries. Higher percentages of young queens corresponded to lower overall losses (excluding losses from natural disaster), but also lower losses from unresolvable queen problems, and lower losses from winter mortality (p < 0.001). Detailed results for each country and overall are given in a table, and a map shows relative risks of winter loss at regional level.

SummaryThis chapter addresses survey methodology and questionnaire design for the collection of data pertaining to estimation of honey bee colony loss rates and identification of risk factors for colony loss. Sources of error in surveys are described. Advantages and disadvantages of different random and non-random sampling strategies and different modes of data collection are presented to enable the researcher to make an informed choice. We discuss survey and questionnaire methodology in some detail, for the purpose of raising awareness of issues to be considered during the survey design stage in order to minimise error and bias in the results. Aspects of survey design are illustrated using surveys in Scotland. Part of a standardized questionnaire is given as a further example, developed by the COLOSS working group for Monitoring and Diagnosis. Approaches to data analysis are described, focussing on estimation of loss rates. Dutch monitoring data from 2012 were used for an example of a statistical analysis with the public domain R software. We demonstrate the estimation of the overall proportion of losses and corresponding confidence interval using a quasi-binomial model to account for extra-binomial variation. We also illustrate generalized linear model fitting when incorporating a single risk factor, and derivation of relevant confidence intervals. Métodos estándar de encuestas para la estimación de la pérdida de colonias y los factores de riesgo que los explican en Apis mellifera ResumenEste capítulo trata sobre la metodología de encuestas y el diseño del cuestionario para la recogida de datos relativos a la estimación de las tasas de pérdida de colonias de abejas de la miel y la identificación de los factores de riesgo de la pérdida de colonias. Se describen las fuentes de error en las encuestas. Se presentan las ventajas y desventajas de las diferentes estrategias de muestreo aleatorio y no aleatorio y diferentes modos de recogida de datos que permitan al investigador tomar una decisión informada. Discutimos sobre la metodología de las encuestas y los cuestionarios con cierto detalle, con el propósito de dar a conocer las cuestiones a tener en cuenta durante la fase de diseño de la encuesta con el fin de minimizar el error y el sesgo en los resultados. Se ilustran aspectos de la encuesta que a través de encuestas realizadas en Escocia. Se da como ejemplo parte de un cuestionario estandarizado, desarrollado por el grupo de trabajo COLOSS de Monitoreo y Diagnóstico. Se describen enfoques para el análisis de datos, centrándose en la estimación de las tasas de pérdida. Se utilizaron datos de un monitoreo holandés de 2012 como ejemplo de análisis estadístico con el software de dominio público R. Demostramos la estimación de la proporción total de las pérdidas y el intervalo de confianza correspondiente usando un modelo cuasi-binomial para dar cuenta de la variación extra-binomial. También ilustramos ajustes del modelo lineal generalizado al incorporar un solo factor de riesgo, y la derivación de los intervalos ...

Submit your article to this journal Received 23 December 2013, accepted subject to revision 14 January 2014, accepted for publication 28 January 2014. * Corresponding author: E-mail: romee.van.der.zee@beemonitoring.org †performed the analysis and provided the manuscript SummaryThis article presents results of an analysis of winter losses of honey bee colonies from 19 mainly European countries, most of which implemented the standardised 2013 COLOSS questionnaire. Generalised linear mixed effects models (GLMMs) were used to investigate the effects of several factors on the risk of colony loss, including different treatments for Varroa destructor, allowing for random effects of beekeeper and region.Both winter and summer treatments were considered, and the most common combinations of treatment and timing were used to define treatment factor levels. Overall and within country colony loss rates are presented. Significant factors in the model were found to be:percentage of young queens in the colonies before winter, extent of queen problems in summer, treatment of the varroa mite, and access by foraging honey bees to oilseed rape and maize. Spatial variation at the beekeeper level is shown across geographical regions using random effects from the fitted models, both before and after allowing for the effect of the significant terms in the model. This spatial variation is considerable.