Assessing the effectiveness of correlative ecological niche models temporal projection through floristic data.

Correlative ecological niche models (ENMs) are methods used to get insight about species environment relationships. These approaches are based on the possibility to associate to each geographic location multiple environmental values, useful for its characterization. In light of the wide use of ENM in issues related to the future distribution of the species under climate change scenarios we aimed to highlight the different results that can be achieved by using different algorithms together with selected plant primary biodiversity data and geospatial environmental variables lacking true absence data, conditions frequently used in ENM and SDM research. To test the reliability of transfers to future conditions, historical and modern data were used to build models. In particular, to evaluate differences in algorithms responses, we planned an analysis based on the comparison of models based on historical climatic and distribution data projected to present climatic conditions, with models built based on current climatic and distribution data. By estimating the overlap between potential distributions generated by models built with historical data (then projected) and models built with modern data, an experimental check of the effectiveness of model transferability to future, in this case simulated by modern conditions, was achieved. We expect that good algorithms are capable to return similar potential distributions in the two cases.