Various studies have shown that model performance may vary depending on the species being modelled, the study área, or the number of sampled localities, and suggest that it is necessary to assess which model is better for a particular situation. Thus, in this study we evalúate the performance of different techniques for modelling the distribution of Patagonian insects. We applied eight of the most widely used modelling methods (artificial neural networks, BIOCLIM, classification and regression trees, DOMAIN, generalized additive models, GARP, generalized linear models, and Maxent) to the distribution of ten Patagonian insect species. We compared model performance with five accuracy measures. To overeóme the problem of not having reliable absence data with... |