This research simulates the impact of climate change on the distribution of the most important European wine regions using a comprehensive suite of spatially informative layers, including bioclimatic indices and water deficit, as predictor variables. More specifically, a machine learning approach (Random Forest, RF) was first calibrated for the present period and applied to future climate conditions as simulated by HadCM3 General Circulation Model (GCM) to predict the possible spatial expansion and/or shift in potential grapevine cultivated area in 2020 and 2050 under A2 and B2 SRES scenarios. Projected changes in climate depicted by the GCM and SRES scenarios results in a progressive warming in all bioclimatic indices as well as increasing water deficit over the European domain, altering the climatic profile of each of the grapevine cultivated areas. The two main responses to these warmer and drier conditions are 1) progressive shifts of existing grapevine cultivated area to the north-northwest of their original ranges, and 2) expansion or contraction of the wine regions due to changes in within region suitability for grapevine cultivation. Wine regions with climatic conditions from the Mediterranean basin today (e.g., the Languedoc, Provence, Ctes Rhne M,ridionales, etc.) were shown to potentially shift the most over time. Overall the results show the potential for a dramatic change in the landscape for winegrape production in Europe due to changes in climate.
