Population Viability Analysis and Risk Assessment

Abstract

Stochastic models to estimate extinction risks and recovery probabilities offer an effective alternative to the mostly qualitative or deterministic methods used in wildlife population modeling and viability analysis. The risk analysis approach is demonstrated by three models developed for single and multiple populations (metapopulations). These models simulate population dynamics with age, stage, and spatial structure. They are used to study the dynamics of rare or endangered species, to design nature reserves, to evaluate wildlife management practices, and to assess human impact on natural populations. The age- and stage-structured models can take into account species-specific demographic information, environmental and demographic stochasticity, and density dependence. The metapopulation model uses these types of data for each population in a metapopulation, and connects the populations by incorporating information on the number, size and geographic configuration of habitat patches, and dispersal phenomena. The models use Monte Carlo methods to simulate future population trajectories and compute risks of population extinction and chances of recovery from a disturbance. The models, implemented as interactive microcomputer programs, move population modeling and viability analysis from an academic domain to an operational one for conservation biologists and wildlife managers.