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ANALYSIS OF THE SPATIAL CLIMATE STRUCTURE FROM A VITICULTURAL PERSPECTIVE. APPLICATION TO DETERMINE VITICULTURE SUITABILITY AND ZONIFICATION IN EXTREMADURA (SPAIN) Francisco J. Rebollo1 , Francisco J. Moral1*, Luis L. Paniagua2, Abelardo García2 1Department of Graphic Representation, University of Extremadura, Badajoz, Spain 2Department of Agronomic Engineering and Forestry, University of Extremadura, Badajoz, Spain *email: [email protected] 1 Introduction and Objectives. The evaluation of general suitability for viticulture in wine regions requires a knowledge of the spatial variation in temperature, which is also used to assess different grapevine cultivars and to delimit appropriate zones for winegrape production. However, usually temperature data and methods applied to properly delineate homogeneous areas are not adequate to generate accurate maps. In this work we aim to: (i) provide accurate maps of four temperature-based indices in Extremadura (Spain), and (ii) establish a comparison between different areas in this region and with other regions worldwide . 2 MtMater ilialsand MthdMethods. The study was conducted in Extremadura (Spain), where there are 28 natural regions (NR). A geostatistical analysis was conducted to determine the spatial distribution of each index. Daily meteorological observations at 117 georeferenced meteorological stations (points) were obtained. A period of 30 years, from 1980 to 2011, was utilized in this work. Four temperature-derived indices were used: growing season temperature (GST), Winkler index (WI), Huglin index (HI), and the biologically effective degree-day index (BEDD). Multivariate approach? 3 Results. Correlation matrix between bioclimatic indices, longitude, latitude, and elevation in Extremadura. The four indices are highly correlated across Extremadura and Elevation Longitude Latitude GST WI HI BEDD they are also highly correlated (negatively) with elevation Elevation 1 Longitude -0.231 1 Latitude 0.294 -0.125 1 GST -0.775 0.012 -0.486 1 is the most adequate interpolation algorithm WI -0. 775 0. 012 -0. 486 0. 999 1 Regression-kriging HI -0.811 -0.046 -0.443 0.971 0.971 1 (Elevation from DEM) BEDD -0.843 0.081 -0.485 0.968 0.968 0.969 1 Taking into account the WI: • Valle del Jerte NR (Region II) like Rioja (Spain), Vinho Verde (Portugal), Barolo and Montepulciano (Italy), Côtes du Rhône Méridionales (France), Bay of Islands (New Zealand), Coonawarra and Yarra Valley (Australia), and Walla Walla Valley (United States). • Valle del Ambroz and Las Hurdes NRs (Region III) like Porto (Portugal), Chianti Classico (Italy), Margaret River and Barossa Valley (Australia), Napa Valley and Paso Robles (California, USA), and La Mancha (Spain). • Las Villuercas, Los Ibores, Sierra de Gata, Tentudía, and Tierras de Granadilla NRs (Region IV) very similar to, for instance, Lodi, Hames Valley, Clarksburg, and Sierra Foothills regions in USA, and Peel, Adelaide Plains, and Perricoota regions, among others, in Southern Australia. - The HI and BEDD maps are similar to both GST and GDD maps, but there are differences in some NRs, probably because the HI and BEDD • Most of Extremaduran NR (Region V) like Temecula Valley, are calculated with modifications in the daytime temperature and day length. and Madera in USA, some regions in Australia (Cowra, Hasting - The highest spatial variability is observed in the BEDD map; this is due to the limit of the degree-day considered on any particular day, which River, Perth Hills, etc.), and Jerez in Southern Spain. gives place to lower BEDD increases at higher temperatures 4 Conclusions. - One of the novel aspects of this work is the use of regression-kriging algorithm to interpolate the index values at any location. It enables generation of more accurate estimates . - Spatial patterns of climate are different depending on the index taken into account. - Although warmer conditions predominate in most Extremaduran NRs, the BEDD index enables a better differentiation of the cooler zones, which is very important to make decisions when other winegrape varieties and practices have to be deve lope dithd in these areas, so thiidthis index is the more appropr itiate for dfiidefining grapev ine zones in EtExtrema dura. - One important characteristic of the present work is that it is based on data from the most recent time period, from 1980 to 2011. Thus, not only it is the first time all indices and maps are available for Extremadura but also it is updated information. As far as we know, there is no any similar work worldwide in which this broad and up-to-date temporal series has been used for viticultural zoning of a region. Acknowledgements: Gobierno de Extremadura, Project GR10038-Research Group TIC008 (Alcántara) and Research Group TPR009 (Ingeniería aplicada en hortofruticultura y jardinería, both co-financed by European funds (ERDF)..