title: Survival and production in variable resource environments.
abstract: A dynamic energy budget (DEB) model describes the rates at which organisms assimilate and utilize energy from food for maintenance, growth, reproduction and development. We study the dynamic behavior of one particular DEB model, Kooijman's kappa-rule model, whose key assumption is that somatic and reproductive tissues are competing for energy. We assume an environment in which the food density fluctuates either periodically or stochastically (pink noise). Both types of fluctuations stimulate growth; the magnitude of the (average) increase in size depends on both the strength and duration of the fluctuations. In a stochastic environment, the risk of mortality due to starvation increases with increasing fluctuation intensity. The mean lifespan is also a function of the model parameter kappa characterizing the partitioning of energy between somatic and reproductive tissues. Organisms committing a large fraction of resources to reproduction endure periods of food shortage relatively well. The effects of food fluctuations on reproduction are complex. With stochastic food, reproduction in survivors increases with increasing fluctuation intensities, but lifetime reproduction decreases. Periodic fluctuations may enhance reproduction, depending on the value of kappa. Thus, a variable food supply stimulates growth, increases mortality and may enhance reproduction, depending on life history.
authors: Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, CA 93106-9610, USA. muller@lifesci.ucsb.edu
authors: E B
authors: EB
authors: Muller
authors: R M
authors: RM
authors: Nisbet
mesh_terms: D000818:Animals; D049872:Bivalvia / Q000254:growth & development / Q000502:physiology*; D002149:Energy Intake / Q000502:physiology*; D004734:Energy Metabolism / Q000502:physiology*; D005508:Food Deprivation / Q000502:physiology*; D008954:Models, Biological; D009716:Numerical Analysis, Computer-Assisted; D012621:Seasons; D013269:Stochastic Processes