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Behavioral Ecology Vol. 12 No. 1: 111119 The adaptive value of inactive foragers and

Summary: Behavioral Ecology Vol. 12 No. 1: 111119
The adaptive value of inactive foragers and
the scout-recruit system in honey bee
(Apis mellifera) colonies
Carl Anderson
Department of Genetics and Ecology, University of Aarhus, DK-8000 Aarhus C, Denmark, and
Department of Biology, Duke University, Durham, NC 27708-0338, USA
In honey bee (Apis mellifera) colonies, scouts search for productive forage sites and then recruit other workers to those locations
using a waggle dance. A simple and tractable mathematical model of the honey bee scout-recruit system was developed to study
the relationship between nectar availability, the efficiency of the honey bee's recruitment system, and the optimal proportion
of scouts that maximizes net gain (benefit cost), or, energetic efficiency (benefit/cost 1). The models consider both the
energetic costs and benefits of active scouts and recruits as well as the cost of an inactive forager reserve. They predict conditions
when individual foraging is favored over the honey bee's recruitment system, when the colony should abandon foraging alto-
gether, and the optimal proportion of scouts (when the scout-recruit system is favored). The models' predictions qualitatively
match empirical data. Surprisingly, previous empirical data from the honey bee suggest that recruits' costs are greater than
scouts'--recruits spend significantly longer searching for a forage patch than do scouts--thereby causing researchers to rethink
how the scout-recruit system might be adaptive. Using average returns, the models demonstrate how the scout-recruit system is
adaptive despite these apparent higher recruit costs relative to the scouts'. A sensitivity analysis demonstrates that the results
are robust to a broad range of relative costs of active workers, inactive workers, and the energetic benefits of the forage.
Consequently, the model is demonstrated to be relevant to many insect societies that employ a scout-recruit system. Key words:


Source: Anderson, Carl - Synthetic Intelligence, Qbit, LLC, Bethesda, MD


Collections: Environmental Sciences and Ecology; Engineering; Mathematics