Bayesian meta-analysis of demographic parameters in three small, temperatepasserines

Accurate estimates of population parameters are vital for estimating extinc tion risk. Such parameters, however, are typically not available for threat ened populations. We used a recently developed software tool based on Marko v Chain Monte Carlo methods for carrying our Bayesian inference (the BUGS p ackage) to estimate four demographic parameters; the intrinsic growth rate. the strength of density dependence, and the demographic and enviromental v ariance, in three species of small temperate passerines from two sets of ti me series data taken from a dipper and a song sparrow population, and from previously obtained frequentist estimates of the same parameters in the gre at tit. By simultaneously modeling variation in these demographic parameter s across species and using the resulting distributions as priors in the est imation for individual species, we improve the estimates for each individua l species. This framework also allows us to make probabilistic statements a bout plausible parameter values for small passerines temperate birds in gen eral which is often critically needed in management of species for which li ttle or no data are available. We also discuss how our work relates to rece ntly developed theory on dynamic stochastic population models, and finally note some important differences between frequentist and Bayesian methods.