The Sensitivity of Population Viability Analysis to Uncertainty about Habitat Requirements: Implications for the Management of the Endangered Southern Brown Bandicoot
Whenever population viability analysis (PVA) models are built to help guide decisions about the management of rare and threatened species, an important component of model building is the specification of a habitat model describing how a species is related to landscape or bioclimatic variables. Model-selection uncertainty may arise because there is often a great deal of ambiguity about which habitat model structure best approximates the true underlying biological processes. The standard approach to incorporate habitat models into PVA is to assume the best habitat model is correct, ignoring habitat-model uncertainty and alternative model structures that may lead to quantitatively different conclusions and management recommendations. Here we provide the first detailed examination of the influence of habitat-model uncertainty on the ranking of management scenarios from a PVA model. We evaluated and ranked 6 management scenarios for the endangered southern brown bandicoot (Isoodon obesulus) with PVA models, each derived from plausible competing habitat models developed with logistic regression. The ranking of management scenarios was sensitive to the choice of the habitat model used in PVA predictions. Our results demonstrate the need to incorporate methods into PVA that better account for model uncertainty and highlight the sensitivity of PVA to decisions made during model building. We recommend that researchers search for and consider a range of habitat models when undertaking model-based decision making and suggest that routine sensitivity analyses should be expanded to include an analysis of the impact of habitat-model uncertainty and assumptions.
Keywords: Isoodon obesulus; análisis de sensibilidad; análisis de viabilidad poblacional; decision-theoretic approach; dynamic landscape metapopulation modeling; habitat modeling; incertidumbre del modelo; logistic regression; model uncertainty; modelado de metapoblación en un paisaje dinámico; modelado del hábitat; método de decisión teórica; population viability analysis; regresión logística; sensitivity analysis; southern brown bandicoot
Document Type: Research Article
Affiliations: 1: Applied Environmental Decision Analysis Hub, School of Botany, University of Melbourne, Victoria 3010, Australia 2: School of Mathematical and Geospatial Science, RMIT University, Victoria 3001, Australia 3: Royal Botanical Gardens Cranbourne, 1000 Ballarto Road, Victoria 3977, Australia
Publication date: August 1, 2008