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Differences in nestmate recognition for drones and workers in the honeybee, Apis mellifera (L.)
Authors:Robin FA Moritz  Peter Neumann
Institution:Institut für Zoologie, Martin-Luther-Universität Halle-Wittenberg, Germany
Abstract:Nestmate recognition is the basic mechanism for rejecting foreign individuals and is essential for maintaining colony integrity in insect societies. However, in honeybees, Apis mellifera, both workers and males occasionally gain access to foreign colonies in spite of nest guards (=drifting). Instead of conducting direct behavioural observations, we inferred nestmate recognition for males and workers from the genotypes of naturally drifting individuals in honeybee colonies. We evaluated the degree of polyandry of the resident queens, because nestmate recognition theory predicts that the genotypic composition of insect colonies may affect the recognition precision of guards. Workers (N=1346) and drones (N=407) from 38 colonies were genotyped using four DNA microsatellite loci. Foreign bees were identified by maternity testing. The proportion of foreign individuals in a host colony was defined as immigration. Putative mother queens were identified if a queen's genotype corresponded with the genotype of a drifted individual. The proportion of a colony's individuals in the total number of drifted individuals was defined as emigration. Drones immigrated significantly more frequently than workers. The impact of polyandry was significantly different between drones and workers. Whereas drones immigrated more readily into less polyandrous colonies, worker immigration was not correlated with the degree of polyandry of the host colony. Furthermore, colonies with high levels of emigrated drones did not show high levels of emigration for workers, and colonies that adopted many workers did not adopt many foreign drones. Our data indicate that genetically derived odour cues are important for honeybee nestmate recognition in drones and show that different nestmate recognition mechanisms are used to identify drones and workers.
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