How accurate are population models? Lessons from landscape-scale tests in a fragmented system

Abstract

There is a growing debate about the ability of Population Viability Analysis (PVA) to predict the risk of extinction. Previously, the debate has focused largely on models where spatial variation and species movement are ignored. We present a synthesis of the key results for an array of different species for which detailed tests of the accuracy of PVA models were completed. These models included spatial variation in habitat quality and the movement of individuals across a landscape. The models were good approximations for some species, but poor for others. Predictive ability was limited by complex processes typically overlooked in spatial population models, these being interactions between landscape structure and life history attributes. Accuracy of models could not be determined a priori, although model tests indicated how they might be improved. Importantly, model predictions were poor for some species that are among the best-studied vertebrates in Australia. This indicated that although the availability of good life history data is a key part of PVA other factors also influence model accuracy. We were also able to draw broad conclusions about the sorts of populations and life history characteristics where model predictions are likely to be less accurate. Predictions of extinction risk are often essential for real-world population management. Therefore, we believe that although PVA has been shown to be less than perfect, it remains a useful tool particularly in the absence of alternative approaches. Hence, tests of PVA models should be motivated by the cycle of testing and improvement.