Using trapped drones to assess the density of honey bee colonies: a simulation and empirical study to evaluate the accuracy of the method

Abstract

It is often necessary to assess the density of honey bee colonies in an environment. In theory, a random sample of males obtained at a mating lek (Drone Congregation Area) can be used to infer the number of queens that contributed sons to the sample, and thereby estimate colony density based on the area from which drones are drawn to a DCA. Because of its utility and efficiency, the technique is being increasingly used. However, the accuracy of the method has never been evaluated, and there are no recommendations for sample size. Here, we infer the genotypes of 322 mother queens from the genotypes of 2329 drones caught at a single DCA using the program COLONY. We then use this realistic pool of queen genotypes to generate multiple simulated data sets of drone genotypes, varying the number of queens and sons that each queen contributed to the sample. We find that the technique provides an accurate estimate (<10% error) of the total number of families present in a drone sample, provided that queens contribute at least six drones to the sample on average. This threshold can be reduced when colony density is low. Non‐sampling error only becomes significant when queens contribute fewer than three sons on average across simulated samples. We conclude that the technique is robust and can be used with confidence provided that the sample size is adequate.