Assessing the Effect of Estimation Error on Population Viability Analysis: An Example Using the Black-Capped Vireo

Population viability analysis (PVA) usually assumes that the values of factors that characterize average conditions as well as natural variability (stochasticity) are error-free. However, those values are often estimates of true parameters and, therefore, have an associated estimation error. This error, also referred to as uncertainty, arises from limitations of the methods used to estimate parameter values, such as sampling, measurement, and expert opinion error. Natural resource management decisions must he made in spite of incomplete information; therefore, the impact of uncertainty when establishing specific management objectives must he assessed. A strategy is proposed here to account for error in parameter estimates of PVA models and to assess the strategy's effect on establishment of endangered species conservation objectives. Using the computer simulation model VORTEX, this strategy was applied to the blackcapped vireo (Vireo atricapillus), an endangered neotropical migrant land bird species. The two conservation goals used in this study were probability of persistence and retention of genetic diversity of at least 95 percent and 90 percent, respectively, over the next 100 years. Two situations were evaluated, one accounting for uncertainty, the other not. Achieving the conservation goals while explicitly accounting for estimate uncertainty required more demanding management objectives than that assuming no uncertainty. Under static carrying capacity, fecundity had to be increased 40 percent from 2.5 to 3.5 young fledged per female per year to meet the conservation goals. By explicitly incorporating estimation error, the range of possible circumstances and outcomes faced by a given species can be assessed in a way that reflects current knowledge about stochastic and average system conditions. Prepared in collabration with NOrthern Arizona Univ.