title: Normalized mutual entropy in biology: quantifying division of labor.
abstract: Division of labor is one of the primary adaptations of sociality and the focus of much theoretical work on self-organization. This work has been hampered by the lack of a quantitative measure of division of labor that can be applied across systems. We divide Shannon's mutual entropy by marginal entropy to quantify division of labor, rendering it robust over changes in number of individuals or tasks. Reinterpreting individuals and tasks makes this methodology applicable to a wide range of other contexts, such as breeding systems and predator-prey interactions.
authors.affiliation: School of Life Sciences, Arizona State University, Tempe, Arizona 85287-4501, USA. cycad@asu.edu
authors.forename: Root
authors.initials: R
authors.lastname: Gorelick
authors.forename: Susan M
authors.initials: SM
authors.lastname: Bertram
authors.forename: Peter R
authors.initials: PR
authors.lastname: Killeen
authors.forename: Jennifer H
authors.initials: JH
authors.lastname: Fewell
mesh_terms: D000818:Animals; D001522:Behavior, Animal; D004463:Ecology / Q000379:methods; D019277:Entropy; D007257:Information Theory; D008954:Models, Biological