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Van Der Zee R.,Netherlands Center for Bee Research | Brodschneider R.,University of Graz | Brusbardis V.,Latvian Beekeepers Association | Charriere J.-D.,Swiss Bee Research Center | And 17 more authors.
Journal of Apicultural Research | Year: 2014

This 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. © IBRA 2014.

Van Der Zee R.,Netherlands Center for Bee Research | Pisa L.,Netherlands Center for Bee Research | Andonov S.,Faculty for Agricultural Science and Food | Brodschneider R.,University of Graz | And 33 more authors.
Journal of Apicultural Research | Year: 2012

In 2008 the COLOSS network was formed by honey bee experts from Europe and the USA. The primary objectives set by this scientific network were to explain and to prevent large scale losses of honey bee (Apis mellifera) colonies. In June 2008 COLOSS obtained four years support from the European Union from COST and was designated as COST Action FA0803 - COLOSS (Prevention of honey bee COlony LOSSes). To enable the comparison of loss data between participating countries, a standardized COLOSS questionnaire was developed. Using this questionnaire information on honey bee losses has been collected over two years. Survey data presented in this study were gathered in 2009 from 12 countries and in 2010 from 24 countries. Mean honey bee losses in Europe varied widely, between 7-22% over the 2008-9 winter and between 7-30% over the 2009-10 winter. An important finding is that for all countries which participated in 2008-9, winter losses in 2009-10 were found to be substantially higher. In 2009-10, winter losses in South East Europe were at such a low level that the factors causing the losses in other parts of Europe were absent, or at a level which did not affect colony survival. The five provinces of China, which were included in 2009-10, showed very low mean (4%) A. mellifera winter losses. In six Canadian provinces, mean winter losses in 2010 varied between 16-25%, losses in Nova Scotia (40%) being exceptionally high. In most countries and in both monitoring years, hobbyist beekeepers (1-50 colonies) experienced higher losses than practitioners with intermediate beekeeping operations (51-500 colonies). This relationship between scale of beekeeping and extent of losses effect was also observed in 2009-10, but was less pronounced. In Belgium, Italy, the Netherlands and Poland, 2008-9 mean winter losses for beekeepers who reported 'disappeared' colonies were significantly higher compared to mean winter losses of beekeepers who did not report 'disappeared' colonies. Mean 2008-9 winter losses for those beekeepers in the Netherlands who reported symptoms similar to "Colony Collapse Disorder" (CCD), namely: 1. no dead bees in or surrounding the hive while; 2. capped brood was present, were significantly higher than mean winter losses for those beekeepers who reported 'disappeared' colonies without the presence of capped brood in the empty hives. In the winter of 2009-10 in the majority of participating countries, beekeepers who reported 'disappeared' colonies experienced higher winter losses compared with beekeepers, who experienced winter losses but did not report 'disappeared' colonies. © IBRA 2012.

Hatjina F.,Hellenic Institute of Apiculture | Bienkowska M.,Research Institute of Horticulture | Charistos L.,Hellenic Institute of Apiculture | Chlebo R.,Slovak University of Agriculture | And 17 more authors.
Journal of Apicultural Research | Year: 2014

The 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 small cages in queen banks and with low number of attendants) they can transfer the semen to their spermatheca and clear their oviducts more efficiently when they have been inseminated with small amounts of semen in two or three sequences (but not four), compared to those inseminated with the same amount of semen at once (Poland). Furthermore, we had an inside view of the sanitary conditions of the colony: A. through the health status of the queen (nosema plus virus analysis) (Slovenia); and b. evaluating the nosema load of worker bees (Denmark) and of the queens (Greece). This is the first step to summarize this type of diverse data for such an important issue. The knowledge acquired can be used to fill in the existing gaps in the breeding or queen evaluation systems of each country in order to facilitate standardization of methodology for comparable results. © IBRA 2014.

Lecocq A.,Copenhagen University | Kryger P.,University of Aarhus | Vejsnaes F.,Danish Beekeepers Association | Jensen A.B.,Copenhagen University
PLoS ONE | Year: 2015

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. Copyright: © 2015 Lecocq et al.

Van Der Zee R.,Netherlands Center for Bee Research | Gray A.,University of Strathclyde | Holzmann C.,Institute Technique Et Scientifique Of L Apiculture Et Of La Pollinisation | Pisa L.,Netherlands Center for Bee Research | And 13 more authors.
Journal of Apicultural Research | Year: 2013

This 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. © IBRA 2013.

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