Results of international standardised beekeeper surveys of colony losses for winter 2012-2013: analysis of winter loss rates and mixed effects modelling of risk factors for winter loss.

Romee van der Zee, Robert Brodschneider, Valters Brusbardis, Jean-Daniel Charriere, Robert Chlebo, Mary F Coffey, BjØrn Dahle, Marica M Drazic, Lassi Kauko, Justinas Kretavicius, Preben Kristiansen, Franco Mutinelli, Christoph Otten, Magnus Peterson, Aivar Raudmets, Violeta Santrac, Ari Seppala, Victoria Soroker, Grazyna Topolska, Flemming VejsnaesAlison Gray

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Abstract

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.
Original languageEnglish
Pages (from-to)19-34
Number of pages16
JournalJournal of Apicultural Research and Bee World
Volume53
Issue number1
DOIs
Publication statusPublished - Feb 2014

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Keywords

  • honey bee colony loses
  • generalised linear mixed modelling (GLMM)
  • random effects
  • varroa destructor
  • beekeeper variation
  • regional variation
  • questionnaire data
  • COLOSS

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