Valid auto-models for spatially autocorrelated occupancy and abundance data

Abstract

Spatially autocorrelated species abundance or distribution data sets typically generate spatially autocorrelated residuals in generalized linear models a broader modelling framework is therefore required. Auto-logistic and related auto-models, implemented approximately as autocovariate regression, provide simple and direct modelling of spatial population processes. The auto-logistic model has been widely applied in ecology since Augustin, Mugglestone and Buckland (Journal of Applied Ecology, 1996, 33, 339) analysed red deer census data using a hybrid estimation approach, combining maximum pseudo-likelihood estimation with Gibbs sampling of missing data. However, Dormann (Ecological Modelling..