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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.

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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 ...

The authors' names are listed in alphabetical order with the exception of the corresponding author. All authors' contributions are equal. SummaryThe term "quality" in relation to queens and drones refers to certain quantitative physical and / or behavioural characters. It is generally believed that a high quality queen should have the following physical characteristics: high live weight; high number of ovarioles; large size of spermatheca; high number of spermatozoa in spermatheca; and be free from diseases and pests. It is, however, also known that the performance of a honey bee colony is the result of its queen's function as well as of that of the drones that mated with her. These two approaches are often considered together and give a general picture of the queen production technique and selection. Here we describe the most common and well known anatomical, physiological, behavioural and performance characters related to the queens, as measured in different European countries: the live weight of the virgin queen (Bulgaria); the live weight of the laying queen (Bulgaria, Italy); the diameter and volume of spermatheca (Bulgaria, Greece, Slovenia); the number of ovarioles (Greece, Italy, Slovenia); the weight of ovaries (Slovenia); the number of spermatozoa in spermatheca (Italy, Poland, Slovenia); the brood pattern (Bulgaria, Greece); the egg laying ability / fecundity (Bulgaria); the brood production (Croatia, Serbia); the colony population development (Croatia, Serbia, Slovakia); the honey production (Croatia, Denmark, Serbia, Slovakia); the hygienic behaviour (Croatia, Denmark, Serbia, Slovakia); the defence behaviour (Croatia); the calmness / sitting on the comb (Croatia, Denmark); and swarming (Croatia, Denmark). The data presented fit well with the findings of the same characters in the literature, and in general they support the argument for the term "quality characters". Especially for the weight of the queen, the number of ovarioles, the volume of the spermatheca and the number of spermatozoa, data per country proved its own accuracy by repetition through the years. We also report that when instrumentally inseminated queens are kept under mass production conditions (in 338 Hatjina et al.