title: Consequences of hierarchical allocation for the evolution of life-history traits.
abstract: Resource allocation within individuals may often be hierarchical, and this may have important effects on genetic correlations and on trait evolution. For example, organisms may divide energy between reproduction and somatic growth and then subdivide reproductive resources. Genetic variation in allocation to pathways early in such hierarchies (e.g., reproduction) can cause positive genetic correlations between traits that trade off (e.g., offspring size and number) because some individuals invest more resources in reproduction than others. We used quantitative-genetic models to explore the evolutionary implications of allocation hierarchies. Our results showed that when variation in allocation early in the hierarchy exceeds subsequent variation in allocation, genetic covariances and initial responses to selection do not reflect trade-offs occurring at later levels in the hierarchy. This general pattern was evident for many starting allocations and optima and for whether traits contributed multiplicatively or additively to fitness. Finally, artificial selection on a single trait revealed masked trade-offs when variation in early allocation was comparable to subsequent variation in allocation. This result confirms artificial selection as a powerful, but not foolproof, method of detecting trade-offs. Thus, allocation hierarchies can profoundly affect life-history evolution by causing traits to evolve in the opposite direction to that predicted by trade-offs.
authors.affiliation: Department of Botany, University of Toronto, Toronto, Ontario M5S 3B2, Canada. worleyac@ms.umanitoba.ca
authors.forename: Anne C
authors.initials: AC
authors.lastname: Worley
authors.forename: David
authors.initials: D
authors.lastname: Houle
authors.forename: Spencer C H
authors.initials: SC
authors.lastname: Barrett
mesh_terms: D000828:Animal Population Groups / Q000235:genetics* / Q000502:physiology*; D000818:Animals; D005075:Biological Evolution; D003198:Computer Simulation; D004734:Energy Metabolism; D014644:Genetic Variation; D008957:Models, Genetic; D012641:Selection, Genetic