Sustainability in Beekeeping: Improved Accuracy and Sensitivity of Sampling for the Honey Bee Parasite Varroa destructor

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Commodities

• Animals: bees
• Animal Products: honey

Practices

• Crop Production: beekeeping, pollinator health
• Education and Training: on-farm/ranch research
• Pest Management: disease vectors

Honey bee colonies experience much greater annual loss than historically, largely because of intense parasitism by the mite Varroa destructor and the viruses that parasite spreads. Annual losses of bee colonies are now exceeding 50%, far more than the 12-15% typically observed before the current crisis began around 2006. Varroa and the viruses are key contributors to those losses.

Early and accurate estimates of mite levels in a hive informs important management decisions, including whether or not and when to treat a colony. The two most common sampling methods, using either powdered sugar or isopropyl alcohol to dislodge varroa from a sample of worker bees, are insensitive to early season mite numbers which delays management decisions until the parasite’s levels are quite large and much tougher to control.

In early spring, when varroa are at their lowest numbers and most difficult to detect, they are 5-10x more abundant on drones than on workers—yet current methods sample workers only. In a “proof of concept” test, we will compare the sensitivity and accuracy of an early-season drone-focused sampling of Varroa to that of the standard alcohol wash method. We expect to learn if/how the new drone-focused sampling provides improved and timely estimates of varroa pressure within hives. In addition, we are measuring the amount of deformed wing virus in drone and worker bees in the sampled hive in order to compare the levels among sexes within hives, and between hives to measure the relationship between mite levels and virus load. Finally, we will develop a sequential sampling plan for hand-sampled drone varroa in order to reduce the amount of sampling needed to obtain estimates of varroa population sizes and threshold levels to trigger management actions. We will determine that it's an easier, earlier, and more accurate way to measure Varroa levels.

In early spring, when varroa are at their lowest numbers and most difficult to detect, they are 5-10x more abundant on drones than on workers—yet current methods sample workers only. In a “proof of concept” test, we will compare the sensitivity and accuracy of drone-focused sampling of Varroa to that of the standard alcohol wash method. We expect to learn if/how the new drone-focused sampling provides improved and timely estimates of varroa pressure and virus levels within hives. 

We will determine that it's an easier, earlier, and more accurate way to measure Varroa levels.