Document: BRU-3-81-10

Individual variability reduces demographic stochasticity.

KENDALL, B.E.* ¹ and G.A.FOX ²

University of California Santa Barbara CA 93106 USA U.S.A. ¹
University of South Florida Tampa FL USA ²

Abstract:
Population viability analysis uses stochastic demographic models of a population to predict extinction risk. All else being equal, higher variance in a demographic rate leads to a lower long-term population growth rate and greater extinction risk. By "demographic stochasticity," ecologists mean variance due to differences among individuals. In practice, this is implemented as sampling error. However, this assumes that each individual's expected fate is identical. For example, demographic stochasticity in survival is modeled as a random draw from a binomial distribution. We show that if there is individual variation in expected survival, then existing models overestimate the variance due to demographic stochasticity. This is a consequence of Jensen's inequality and the fact that the binomial sampling variance is a concave function of mean survival. The effect of individual variability on demographic stochasticity in fecundity depends on the mean-variance relationship for individual reproductive success, which is not presently known. If fecundity patterns mirror those of survival, then individual variability will reduce the extinction risk of small populations.

Keywords: population viability analysis, demographic stochasticity, extinction risk, individual variability

This abstract is being presented at: 1:45 PM in session:
Oral Session #46: Modeling Populations and Statistical Ecology.