Background

To reverse biodiversity loss we need to understand the environmental and demographic causes of changes in distributions and abundances. Advances in Bayesian modelling and computing power have facilitated the recent development of Integrated Population Models (IPM), which allow the unified analysis of abundance and demographic data, leading to improved understanding of demographic processes and their interactions, such as density-dependence (Besbeas et al. 2002; Robinson et al. 2014).

Most IPM analyses have been for single populations, although these range in scale from individual study areas to whole countries. It is difficult to scale-up conclusions from small study areas, while models covering larger areas are likely to average out spatial variation in demogra