Predictive accuracy of population viability analysis in conservation biology

Population viability analysis (PVA) is widely applied in conservation biolo gy to predict extinction risks for threatened species and to compare altern ative options for their mangement(1-4). It can also be used as a basis for listing species as endangered under World Conservation Union criteria(5), H owever, there is considerable scepticism regarding the predictive accuracy of PVA, mainly because of a lack of validation in real systems(2,6-8). Here we conducted a retrospective test of PVA based on 21 long-term ecological studies-the first comprehensive and replicated evaluation of the predictive powers of PVA. Parameters were estimated from the first half of each data set and the second half was used to evaluate the performance of the model. Contrary to recent criticisms, we found that PVA predictions were surprisin gly accurate. The risk of population decline closely matched observed outco mes, there was no significant bias, and population size projections did not differ significantly from reality. Furthermore, the predictions of the fiv e PVA software packages were highly concordant. We conclude that PVA is a v alid and sufficiently accurate tool for categorizing and managing endangere d species.