Use of Phytosociological Databases for Species Distribution Models

Species Distribution Models are key in modern ecological studies. They employ information about species locations and environmental factors to generate statistical functions that predict the potential distribution of species on the basis of landscape suitability. Although these models are powerful and useful tools, often the required information about species distribution is lacking, and the only resources are pre-collected museum data. Phytosociological databases contain a myriad of relev,s with precious information, but are often considered to be the exclusive ownership of vegetation scientists. Our study tested the efficiency of a phytosociological database in the building of Species Distribution Models, including spatial autocorrelation (SAC) as a predictor to evaluate its effects on model performance. Spatial autocorrelation (SAC) is a natural characteristic of species distribution that depends on exogenous and endogenous processes. The latter's effects could be overestimated by a subjective sample choice. We chose Festuca riccerii, an Italian endemic species. We split the whole dataset (671 relev,s) into a calibration (443 relev,s) and testing set (228 relev,s) and performed a GLM on these data to identify the main ecological factors that lead distribution in order to build a Species Distribution Model. The dataset's efficiency was assessed by testing the predicting power of the calibrated model on the testing subset. The phytosociological database proved to be good for building model (AUC = 0.821), providing a useful basis for fast and low cost ecological analysis, and could be used subsequently for more detailed analyses.