A predictive model of avian natal dispersal distance provides prior information for investigating response to landscape change

The use of Bayesian statistical methods is becoming more prevalent in ecology (Clark 2005; McCarthy 2007). A key feature of these methods is that they can use prior information when modelling systems and making predictions. Prior information is usually incorporated into the modelling process in the form of a probability density function, which may be estimated from existing data or through expert elicitation (McCarthy 2007; Michielsens et al. 2008). Informative Bayesian priors have been used to improve the precision of parameter estimates (McCarthy & Masters 2005; Michielsens et al. 2008; Lukacs et al. 2009) and to provide informative a priori estimates of ecological parameters in the absence of species-specific information (Martin et al. 2005; McCarthy, Citroen & McCall 2008). Nonetheless, the use of strongly informative priors remains rare in ecology. One reason for this is that there are a few examples of syntheses performed with the explicit aim of determining Bayesian prior estimates for relevant ecological parameters and evaluating their utility. The synthesis of existing data will aid the development of estimates that may serve as informative priors in ecological studies.