Key management practices to prevent high infestation levels of Varroa destructor in honey bee colonies at the beginning of the honey yield season

Abstract

Varroa destructor is considered one of the main threats to worldwide apiculture causing a variety of physiological effects at individual and colony level. Also, Varroa mites are often associated with several honey bee viruses presence. Relatively low levels of Varroa during the spring, at the beginning of the honey yield season, can have a significant economic impact on honey production and colony health. Winter treatments against Varroa and certain management practices may delay mite population growth during following spring and summer improving colonies performance during the honey yield season. The aim of this study was to identify risk factors associated with the presence of Varroa destructor in late spring in apiaries from temperate climate. A longitudinal study was carried out in 48 apiaries, randomly selected to evaluate V. destructor infestation level throughout the year. The percentage of infestation with V. destructor was assessed four times during one year and the beekeepers answered a survey concerning all management practices applied in the colonies. We used a generalized linear mixed model to determine association between risk of achieving 2% infestation on adult bees at the beginning of the honey yield season and all potential explanatory variables. The complete dataset was scanned to identify colonies clusters with a higher probability of achieving damage thresholds throughout the year. Colonies that achieved ¡Ý2% of infestation with V. destructor during spring were owned by less experienced beekeepers. Moreover, as Varroa populations increase exponentially during spring and summer, if the spring sampling time is later this growth remains unobserved. Monitoring and winter treatment can be critical for controlling mite population during the honey production cycle. Spatial distribution of colonies with a higher risk of achieving high Varroa levels seems to be better explained by management practices than a geographical condition.