Forecasting insect species richness scores in poorly surveyed territories:the case of the Portuguese dung beetles (Col. Scarabaeinae)

Large-scale biodiversity assessment of faunal distribution is needed in poo rly sampled areas. In this paper, Scarabaeinae dung beetle species richness in Portugal is forecasted from a model built with a data set from areas id entified as well sampled. Generalized linear models are used to relate the number of Scarabaeinae species in each Portuguese UTM 50 x 50 grid square w ith a set of 25 predictor variables (geographic, topographic, climatic and land cover) extracted from a geographic information system (GIS). Between-s quares sampling effort unevenness, spatial autocorrelation of environmental data, non-linear relationships between variables and an assessment of the models' predictive power, the main shortcomings in geographic species richn ess modelling, are addressed. This methodological approach has proved to be reliable and accurate enough in estimating species richness distribution, thus providing a tool to identify areas as potential targets for conservati on policies in poorly inventoried countries.