Monday, August 3, 2009 - 4:20 PM

OOS 2-9: Using consumer-resource models to deduce the shape of density dependence

Peter A. Abrams, University of Toronto

Background/Question/Methods

How does its use of limiting resources determine the shape of density dependence in a consumer species?  While consumer-resource models have been used extensively to study interspecific competition, they have seldom been used to explore intraspecific competition (i.e., density dependence).  Differential equation models of consumer-resource systems that incorporate the possibility of adaptive behavior in either or both type of species are used to determine how the consumer's per capita growth rate varies with consumer density.  The approach asks how consumer population size changes with per capita harvest, which is equivalent to determining the relationship between per capita growth rate and population size.  Different models vary in the number of resources, their population growth functions, and the nature of adaptive behavior in both consumer and resources.

Results/Conclusions

The analysis shows that density dependence seldom fits the widely used logistic or theta-logistic models.  It is likely that the relationship between consumer population and per capita harvest has concave and convex sections, and population density often increases over some range of mortality rates.  Consumer functional and numerical response shape and the nature of resource density dependence interact in complex ways to determine the shape of consumer density dependence. Comparison of models that have or lack adaptive behavior suggests that such behavior will often make the population vs. harvest relationship more nearly linear.  Models that lack adaptive behavior are often characterized by a very rapid drop in population size as harvest rate approaches its maximum.  Adaptive behavior by predator and prey often makes this decline more gradual.  This suggests that understanding the natural and adaptive aspects of consumer resource interactions is vital for formulating accurate management strategies for harvested populations.