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

Romee van der Zee, Alison Gray, Celine Holzmann, Lennard Pisa, Robert Brodschneider, Robert Chlebo, Mary F Coffey, Aykut Kence, Preben Kristiansen, Franco Mutinelli, Bach Kim Nguyen, Adjlane Noureddine, Magnus Peterson, Victoria Soroker, Grazyna Topolska, Flemming Vejsnaes, Selwyn Wilkins

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65 Citations (Scopus)
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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.
Original languageEnglish
Number of pages35
JournalJournal of Apicultural Research and Bee World
Issue number4
Publication statusPublished - Sept 2013


  • estimating colony losses
  • Apis mellifera
  • surveys
  • questionnaire
  • random/randomized sampling
  • non-random sampling
  • generalized lienar models (GZLMs)


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