Managed honey bee colony losses in Canada, China, Europe, Israel and Turkey, for the winters of 2008-9 and 1009-10

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

Standard survey methods for estimating colony losses and explanatory risk factors in Apis mellifera

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

An update of the Worldwide Integrated Assessment (WIA) on systemic insecticides. Part 2: impacts on organisms and ecosystems

New information on the lethal and sublethal effects of neonicotinoids and fipronil on organisms is presented in this review, complementing the previous WIA in 2015. The high toxicity of these systemic insecticides to invertebrates has been confirmed and expanded to include more species and compounds. Most of the recent research has focused on bees and the sublethal and ecological impacts these insecticides have on pollinators. Toxic effects on other invertebrate taxa also covered predatory and parasitoid natural enemies and aquatic arthropods. Little, while not much new information has been gathered on soil organisms. The impact on marine coastal ecosystems is still largely uncharted. The chronic lethality of neonicotinoids to insects and crustaceans, and the strengthened evidence that these chemicals also impair the immune system and reproduction, highlights the dangers of this particular insecticidal classneonicotinoids and fipronil. , withContinued large scale – mostly prophylactic – use of these persistent organochlorine pesticides has the potential to greatly decreasecompletely eliminate populations of arthropods in both terrestrial and aquatic environments. Sublethal effects on fish, reptiles, frogs, birds and mammals are also reported, showing a better understanding of the mechanisms of toxicity of these insecticides in vertebrates, and their deleterious impacts on growth, reproduction and neurobehaviour of most of the species tested. This review concludes with a summary of impacts on the ecosystem services and functioning, particularly on pollination, soil biota and aquatic invertebrate communities, thus reinforcing the previous WIA conclusions (van der Sluijs et al. 2015)

Divinity and maximal greatness

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Percentage of colonies lost, with 95% confidence intervals, for colonies with/without plant species present in bee bread.

<p>Percentage of colonies lost, with 95% confidence intervals, for colonies with/without plant species present in bee bread.</p

Risk factors for colony loss: results from the best explaining model for the 75 colonies used.

<p>⁽¹⁾ Number of positive cases,</p><p>⁽²⁾ Odds Ratio with 95% confidence interval,</p><p>⁽³⁾ Slope parameter,</p><p>⁽⁴⁾ Standard Error,</p><p>⁽⁵⁾ Z-test statistics</p><p>Risk factors for colony loss: results from the best explaining model for the 75 colonies used.</p

Percentage of colonies lost, with 95% confidence intervals, for colonies with/without acetamiprid or thiacloprid present.

<p>Percentage of colonies lost, with 95% confidence intervals, for colonies with/without acetamiprid or thiacloprid present.</p

Analysis of the best explaining model M1.

<p>⁽¹⁾ DF = Degrees of Freedom for the term dropped,</p><p>⁽²⁾AIC = Akaike’s Information Criterion,</p><p>⁽³⁾LRT = Likelihood Ratio Test statistic for the change in model fit and the p-value of the test.</p><p>Signif. codes: 0</p><p>'***' 0.001</p><p>'**' 0.01</p><p>'*' 0.05 '.' 0.1 ' ' 1</p><p>Analysis of the best explaining model M1.</p

Choropleth map showing the spatial variation in the postal code level random effects.

<p>These effects were estimated from a binomial GLMM allowing for significant fixed effects for beekeeper risk of colony loss in the Netherlands and also with a beekeeper random effect, for the 1 to 50 colony operations used in the model fitting. The data are derived from the Dutch National Monitoring Survey for Honey Bee Winter Loss 2012. The legend within the figure shows the key to the colour coding. Darker green indicates areas of lower risk and darker red areas of higher risk of loss. The value of the postal code effect was used as a predictor in the final model of the data in the present study.</p

Odds Ratios for the fixed effects from the final model, with 95% confidence intervals.

<p>Fixed model terms are acetamiprid or thiacloprid present in honey, bee bread or bees in summer 2011, rape/mustard present in bee bread in summer 2011, attributed postal code random effects 2011–2012 (PC 2012 effects) and varroa mite load in October 2011. For the categorical factors, the odds ratio is the odds of loss for colonies with acetamiprid/thiacloprid present divided by the odds for colonies with these absent, and similarly for oilseed rape/mustard, i.e. the proportional increase or decrease in the odds. For the continuous terms, the odds ratio is the proportional increase in the odds of loss for an increase of 1 unit in the value of the continuous variable.</p