A model-based decision aid for species protection under uncertainty

Abstract

A method of decision making is presented that can be used to compare alternative management actions under ecological uncertainty and to identify which one is likely to have the strongest effect on population viability. The method combines decision analysis with population modelling and uses both information about population patterns (e.g. spatio-temporal) and processes (e.g. reproduction). The process knowledge is used to construct the population model and determine plausible ranges for its parameters. The values of these parameters are likely to have an impact on the rank order of the most effective management actions, and unless their ranges are small, there is uncertainty in the management rank order. This uncertainty is encompassed by considering a number of different population parameter combinations, called scenarios. For each of them a sensitivity analysis is performed and a management rank order determined. In the following decision analysis each key scenario contributes with a certain weight that reflects its biological plausibility. To determine the weight of a particular scenario, the population dynamics are simulated and the generated patterns are compared with those observed in the real population. The higher the similarity between the two patterns the higher the weight assigned to the scenario. The decision analysis finally synthesises the results of sensitivity and pattern analyses and generates a single rank order of the most promising management actions. The method is demonstrated on a case study of the endangered Orange-bellied Parrot Neophema chrysogaster (Australia).