Stochastic Demography for Conservation Biology

Abstract

"The use of deterministic rather than stochastic models can only be justified by mathematical convenience."-Maynard Smith 1974 Models used in conservation biology often include demographic structure, but usually these models are deterministic. Stochastic models receive less attention perhaps because of data limitations or the intimidating appearance of the computations. Nevertheless, we believe that stochastic demography needs to be given more consideration by conservation biologists both because stochastic processes are fundamental to extinction and because population projections from stochastic models may differ substantially from those of deterministic models. It is our objective to provide a brief review of stochastic demography and to consider possible applications. We focus on simple matrix models of exponential growth in which vital rates vary randomly. Some analytical results exist for these models, and understanding these may be helpful in comprehending the behavior of more-realistic but complex models. These models include some important properties. First, in stochastic environments, population size assumes a skewed distribution in which very large populations occur only rarely. As a consequence of this skewness, mean population size tends to overestimate most populations. Second, stochas-tic growth rate is lower than deterministic growth rate based on average vital rates. Ignoring temporal variation in estimates of demographic parameters may lead to serious overestimates of actual growth rate. Third, increased variation in the vital rates produces a lower growth rate. Fourth, variation in vital rates with high sensi-S. Tuljapurkar et al. (eds.), Structured-Population Models in Marine, Terrestrial, and Freshwater Systems