Quantifying conservation concern – Bayesian statistics, birds and the red lists

For species that are still widespread, obtaining accurate and precise measures of population change inevitably means gathering representative sample data rather than undertaking a complete census. In the UK, a system of raising 'alerts' utilises stochastic models for such data to identify species in rapid (>50%) or moderate (25-50%) decline across various temporal and spatial scales. Considerable improvements in interpretation can be made by explaining annual fluctuations in terms of explicit population models (rather than trends of an arbitrary mathematical form); through the simultaneous modelling of data from a complete or partial census with those providing information on the demographic rates employed in these models; and through adopting a Bayesian rather than a frequentist statistical approach. A Bayesian approach is natural for quantifying, in the form of a probability, the support provided by the data for assigning a species to each of the categories. Based on territory mapping and ringing data for the lapwing Vanellus vanellus, we describe such an approach. Trends are estimated more precisely than those under models previously employed in the alerts context. Some smoothing is induced, but realistic responses to years of severe weather are retained, and these are expressed also via model-averaged trends in key demographic parameters. We discuss the conservation implications for this declining species, and the wider potential arising from the ability to quantify confidence that population change has exceeded a threshold either generating conservation concern or justifying a subsequent programme of action for recovery. (C) 2008 Elsevier Ltd. All rights reserved.