Future Scenarios of Bioclimatic Viticulture Indices in the Eastern Mediterranean: Insights into Sustainable Vineyard Management in a Changing Climate
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area, Data Collection, and Preliminary Analysis
2.1.1. Observed Air Temperature and Precipitation
2.1.2. CIMP5 Climate Projection (CanESM2)
2.2. Bioclimatic Viticulture Indices (BVIs)
- (i)
- The hydrothermal coefficient (HTC) was introduced by Branas et al. [11] as a measure that combines the influence of seasonal precipitation and temperature specifically during the growing season. Its purpose is to assess water availability for vineyards and determine the suitability of rainfed viticulture [55]. In areas where HTC values fall below 0.5 mm/°C, grape production can only be sustained with high air humidity or irrigation. The HTC ranges from 1.5 to 2.5 mm/°C, with an optimal value of 1.0 mm/°C [55].
- (ii)
- The Winkler Index (WI-GDD) is commonly used to estimate the heat accumulation during the growing season for vineyards. Traditionally, this index calculates the total daily average temperatures from April to the end of October, using a base temperature of 10 °C, as proposed by Amerine and Winkler [8]. In our study, due to the warm climate in the region compared to higher altitude areas, we extended the calculation period from March to the end of September. The WI-GDD can be expressed as follows:
- (iii)
- The Huglin Index (HI) was developed by Huglin [9] and is calculated similarly to the WI-GDD, but with a greater emphasis on maximum temperature and an adjustment based on latitude, specifically the length of the day coefficient [9]. The HI provides more detailed information on the sugar potential of specific grape varieties and offers qualitative insights when combined with the values of the CI cool night index [10]. Jones et al. [56] and Hall and Jones [14] have updated the HI formula to accommodate all latitudes, considering the months from April to September in the Northern Hemisphere and excluding October, as they believe that the values become less significant during the harvest period [17,20]. In this study, we began accumulating daily average temperatures from March, using a coefficient length of the day of “d = 1”.
- (iv)
- The cool night index (CI) was developed by Tonietto and Carbonneau [10] to assess the degree of coolness during nighttime by considering the average minimum temperatures in the ripening month, typically September in the Northern Hemisphere. This climatic factor significantly influences grape and wine characteristics, including color and aromas. The CI is particularly useful for evaluating the qualitative aspects of wine grapes, specifically the presence of secondary metabolites such as aromas and polyphenols in grape juice [57]. To calculate CI, the minimum air temperatures in September are averaged and expressed in degrees Celsius for the Northern Hemisphere. In the Southern Hemisphere, the calculation involves averaging the minimum air temperatures in March, also expressed in degrees Celsius [10]. These climate-viticulture indices, which also include the previously mentioned ones, enable the assessment of the optimal climatic suitability in terms of heat, water availability, phenological development throughout the growing season, and ripening conditions [58]. See Table 2 for more details regarding the climate-viticulture indices zones.
- (v)
- The growing season temperatures (GST) is a climate-maturity zoning system created by Jones [59] to classify regions based on the correlation between phenological needs and growing season temperatures. It encompasses a range of climates, from cool to hot, to cultivate high-quality grapevines in globally recognized regions and for commonly grown grape varieties. The GST system assists in identifying the favorable climate conditions required for optimal grapevine growth and maturity during the growing season.
2.3. Fine-Scale Modeling of BVIs Using Regression-Kriging (RK)
3. Results
3.1. Projected Change in Temperatures and Precipitation
3.2. Current Temporal Trends and Projected Change in BVIs
3.3. Delineation of BVIs Zones under Projected Climate Change
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Vivier, M.A.; Pretorius, I.S. Genetically Tailored Grapevines for the Wine Industry. Trends Biotechnol. 2002, 20, 472–478. [Google Scholar] [CrossRef]
- Ponti, L.; Gutierrez, A.P.; Boggia, A.; Neteler, M. Analysis of Grape Production in the Face of Climate Change. Climate 2018, 6, 20. [Google Scholar] [CrossRef]
- Alsafadi, K.; Mohammed, S.; Habib, H.; Kiwan, S.; Hennawi, S.; Sharaf, M. An Integration of Bioclimatic, Soil, and Topographic Indicators for Viticulture Suitability Using Multi-Criteria Evaluation: A Case Study in the Western Slopes of Jabal Al Arab—Syria. Geocarto Int. 2020, 35, 1466–1488. [Google Scholar] [CrossRef]
- Huggett, J.M. Geology and Wine: A Review. In Proceedings of the Geologists’ Association; Elsevier: Amsterdam, The Netherlands, 2006; Volume 117. [Google Scholar]
- Jackson, D.I.; Lombard, P.B. Environmental and Management Practices Affecting Grape Composition and Wine Quality—A Review. Am. J. Enol. Vitic. 1993, 44, 409–430. [Google Scholar] [CrossRef]
- Cardoso, A.S.; Alonso, J.; Rodrigues, A.S.; Araújo-Paredes, C.; Mendes, S.; Valín, M.I. Agro-Ecological Terroir Units in the North West Iberian Peninsula Wine Regions. Appl. Geogr. 2019, 107, 51–62. [Google Scholar] [CrossRef]
- OIV Guidelines for Vitiviniculture Zoning. Methodologies on a Soil and Climate Level. Resolution OIV-VITI 423-2012 REV1. (Izmir). 2012. Available online: https://www.oiv.int/public/medias/400/viti-2012-1-en.pdf (accessed on 25 June 2023).
- Amerine, M.A.; Winkler, A.J. Composition and Quality of Musts and Wines of California Grapes. Hilgardia 1944, 15, 493–675. [Google Scholar] [CrossRef]
- Huglin, P. Nouveau mode d’évaluation des possibilités héliothermiques d’un milieu viticole. Comptes Rendus L’acad. D’agricul. Fr. 1978, 64, 89–98. [Google Scholar]
- Tonietto, J.; Carbonneau, A. A Multicriteria Climatic Classification System for Grape-Growing Regions Worldwide. Agric. For. Meteorol. 2004, 124, 81–97. [Google Scholar] [CrossRef]
- Branas, J.; Bernon, G.; Levadoux, L. Elements de Viticultura Generale; Imp. Dehan: Bordeaux, France, 1946. [Google Scholar]
- Cabré, F.; Nuñez, M. Impacts of Climate Change on Viticulture in Argentina. Reg. Environ. Change 2020, 20, 12. [Google Scholar] [CrossRef]
- Cabré, M.F.; Quénol, H.; Nuñez, M. Regional Climate Change Scenarios Applied to Viticultural Zoning in Mendoza, Argentina. Int. J. Biometeorol. 2016, 60, 1325–1340. [Google Scholar] [CrossRef] [PubMed]
- Hall, A.; Jones, G.V. Spatial Analysis of Climate in Winegrape-Growing Regions in Australia. Aust. J. Grape Wine Res. 2010, 16, 389–404. [Google Scholar] [CrossRef]
- Jarvis, C.; Barlow, E.; Darbyshire, R.; Eckard, R.; Goodwin, I. Relationship between Viticultural Climatic Indices and Grape Maturity in Australia. Int. J. Biometeorol. 2017, 61, 1849–1862. [Google Scholar] [CrossRef]
- Santos, J.; Malheiro, A.; Pinto, J.; Jones, G. Macroclimate and Viticultural Zoning in Europe: Observed Trends and Atmospheric Forcing. Clim. Res. 2012, 51, 89–103. [Google Scholar] [CrossRef]
- Anderson, J.D.; Jones, G.V.; Tait, A.; Hall, A.; Trought, M.C.T. Analysis of Viticulture Region Climate Structure and Suitability in New Zealand. OENO One 2012, 46, 149. [Google Scholar] [CrossRef]
- Omazić, B.; Telišman Prtenjak, M.; Prša, I.; Belušić Vozila, A.; Vučetić, V.; Karoglan, M.; Karoglan Kontić, J.; Prša, Ž.; Anić, M.; Šimon, S.; et al. Climate Change Impacts on Viticulture in Croatia: Viticultural Zoning and Future Potential. Int. J. Clim. 2020, 40, 5634–5655. [Google Scholar] [CrossRef]
- Montes, C.; Perez-Quezada, J.F.; Peña-Neira, A.; Tonietto, J. Climatic Potential for Viticulture in Central Chile. Aust. J. Grape Wine Res. 2012, 18, 20–28. [Google Scholar] [CrossRef]
- Jones, G.V.; Duff, A.A.; Hall, A.; Myers, J.W. Spatial Analysis of Climate in Winegrape Growing Regions in the Western United States. Am. J. Enol. Vitic. 2010, 61, 313–326. [Google Scholar] [CrossRef]
- Gaál, M.; Moriondo, M.; Bindi, M. Modelling the Impact of Climate Change on the Hungarian Wine Regions Using Random Forest. Appl. Ecol. Environ. Res. 2012, 10, 121–140. [Google Scholar] [CrossRef]
- Vukovic, A.; Vujadinovic, M.; Ruml, M.; Rankovic-Vasic, Z.; Przic, Z.; Beslic, Z.; Matijasevic, S.; Vujovic, D.; Todic, S.; Markovic, N.; et al. Implementation of Climate Change Science in Viticulture Sustainable Development Planning in Serbia. Web Conf. 2018, 50, 01005. [Google Scholar] [CrossRef]
- Patriche, C.V.; Irimia, L.M. Mapping the Impact of Recent Climate Change on Viticultural Potential in Romania. Theor. Appl. Clim. 2022, 148, 1035–1056. [Google Scholar] [CrossRef]
- Jones, N.K. An Investigation of Trends in Viticultural Climatic Indices in Southern Quebec, a Cool Climate Wine Region. J. Wine Res. 2018, 29, 120–129. [Google Scholar] [CrossRef]
- Badr, G.; Hoogenboom, G.; Abouali, M.; Moyer, M.; Keller, M. Analysis of Several Bioclimatic Indices for Viticultural Zoning in the Pacific Northwest. Clim. Res. 2018, 76, 203–223. [Google Scholar] [CrossRef]
- Blanco-Ward, D.; García Queijeiro, J.M.; Jones, G.V. Spatial Climate Variability and Viticulture in the Miño River Valley of Spain. Vitis—J. Grapevine Res. 2007, 46, 63. [Google Scholar]
- Köse, B. Phenology and Ripening of Vitis Vinifera, L. and Vitis Labrusca, L. Varieties in the Maritime Climate of Samsun in Turkey’s Black Sea Region. S. Afr. J. Enol. Vitic. 2014, 35, 90–102. [Google Scholar] [CrossRef]
- Blanco-Ward, D.; Ribeiro, A.; Barreales, D.; Castro, J.; Verdial, J.; Feliciano, M.; Viceto, C.; Rocha, A.; Carlos, C.; Silveira, C.; et al. Climate Change Potential Effects on Grapevine Bioclimatic Indices: A Case Study for the Portuguese Demarcated Douro Region (Portugal). BIO Web Conf. 2019, 12, 01013. [Google Scholar] [CrossRef]
- Santos, J.A.; Malheiro, A.C.; Karremann, M.K.; Pinto, J.G. Statistical Modelling of Grapevine Yield in the Port Wine Region under Present and Future Climate Conditions. Int. J. Biometeorol. 2011, 55, 119–131. [Google Scholar] [CrossRef] [PubMed]
- Alba, V.; Gentilesco, G.; Tarricone, L. Climate Change in a Typical Apulian Region for Table Grape Production: Spatialisation of Bioclimatic Indices, Classification and Future Scenarios. OENO One 2021, 55, 317–336. [Google Scholar] [CrossRef]
- Gentilesco, G.; Coletta, A.; Tarricone, L.; Alba, V. Bioclimatic Characterization Relating to Temperature and Subsequent Future Scenarios of Vine Growing across the Apulia Region in Southern Italy. Agriculture 2023, 13, 644. [Google Scholar] [CrossRef]
- Xyrafis, E.G.; Fraga, H.; Nakas, C.T.; Koundouras, S. A Study on the Effects of Climate Change on Viticulture on Santorini Island. OENO One 2022, 56, 259–273. [Google Scholar] [CrossRef]
- Mohammed, S.; Alsafadi, K.; Talukdar, S.; Kiwan, S.; Hennawi, S.; Alshihabi, O.; Sharaf, M.; Harsanyie, E. Estimation of Soil Erosion Risk in Southern Part of Syria by Using RUSLE Integrating Geo Informatics Approach. Remote Sens. Appl. Soc. Environ. 2020, 20, 100375. [Google Scholar] [CrossRef]
- Alsafadi, K.; Bi, S.; Abdo, H.G.; Almohamad, H.; Alatrach, B.; Srivastava, A.K.; Al-Mutiry, M.; Bal, S.K.; Chandran, M.A.S.; Mohammed, S. Modeling the Impacts of Projected Climate Change on Wheat Crop Suitability in Semi-Arid Regions Using the AHP-Based Weighted Climatic Suitability Index and CMIP6. Geosci. Lett. 2023, 10, 20. [Google Scholar] [CrossRef]
- Mohammed, S.; Alsafadi, K.; Hennawi, S.; Mousavi, S.M.N.; Kamal-Eddin, F.B.; Harsanyie, E. Effects of Long-Term Agricultural Activities on the Availability of Heavy Metals in Syrian Soil: A Case Study in Southern Syria. J. Saudi Soc. Agric. Sci. 2021, 20, 497–505. [Google Scholar] [CrossRef]
- Mohammed, S.; Alsafadi, K.; Enaruvbe, G.O.; Harsányi, E. Assessment of Soil Micronutrient Level for Vineyard Production in Southern Syria. Model. Earth Syst. Environ. 2021, 8, 407–416. [Google Scholar] [CrossRef]
- Hall, A.; Blackman, J. Modelling Within-Region Spatiotemporal Variability in Grapevine Phenology with High Resolution Temperature Data. Oeno One 2019, 53, 147–159. [Google Scholar] [CrossRef]
- Sturman, A.; Zawar-Reza, P.; Soltanzadeh, I.; Katurji, M.; Bonnardot, V.; Parker, A.K.; Trought, M.C.T.; Quénol, H.; Le Roux, R.; Gendig, E.; et al. The Application of High-Resolution Atmospheric Modelling to Weather and Climate Variability in Vineyard Regions. OENO One 2017, 51, 99. [Google Scholar] [CrossRef]
- Le Roux, R.; de Rességuier, L.; Corpetti, T.; Jégou, N.; Madelin, M.; van Leeuwen, C.; Quénol, H. Comparison of Two Fine Scale Spatial Models for Mapping Temperatures inside Winegrowing Areas. Agric. For. Meteorol. 2017, 247, 159–169. [Google Scholar] [CrossRef]
- Morari, F.; Castrignanò, A.; Pagliarin, C. Application of Multivariate Geostatistics in Delineating Management Zones within a Gravelly Vineyard Using Geo-Electrical Sensors. Comput. Electron. Agric. 2009, 68, 97–107. [Google Scholar] [CrossRef]
- Blanco-Ward, D.; Monteiro, A.; Lopes, M.; Borrego, C.; Silveira, C.; Viceto, C.; Rocha, A.; Ribeiro, A.; Andrade, J.; Feliciano, M.; et al. Climate Change Impact on a Wine-Producing Region Using a Dynamical Downscaling Approach: Climate Parameters, Bioclimatic Indices and Extreme Indices. Int. J. Clim. 2019, 39, 5741–5760. [Google Scholar] [CrossRef]
- Hofmann, M.; Volosciuk, C.; Dubrovský, M.; Maraun, D.; Schultz, H.R. Downscaling of Climate Change Scenarios for a High-Resolution, Site-Specific Assessment of Drought Stress Risk for Two Viticultural Regions with Heterogeneous Landscapes. Earth Syst. Dyn. 2022, 13, 911–934. [Google Scholar] [CrossRef]
- Le Roux, R.; Katurji, M.M.; Zawar-Reza, P.; de Resseguier, L.; Sturman, A.P.; van Leeuwen, C.; Parker, A.; Trought, M.; Quenol, H. A fine scale approach to map bioclimatic indices using and comparing dynamical and geostatistical methods. In Proceedings of the 11th International Terroir Congress, Willamette Valley, OR, USA, 10–14 July 2016. [Google Scholar]
- Zorer, R.; Rocchini, D.; Metz, M.; Delucchi, L.; Zottele, F.; Meggio, F.; Neteler, M. Daily MODIS Land Surface Temperature Data for the Analysis of the Heat Requirements of Grapevine Varieties. IEEE Trans. Geosci. Remote Sens. 2013, 51, 2128–2135. [Google Scholar] [CrossRef]
- Morin, G.; Roux, R.; Lemasle, P.-G.; Quénol, H. Mapping Bioclimatic Indices by Downscaling Modis Land Surface Temperature: Case Study of the Saint-Emilion Area. Remote. Sens. 2021, 13, 4. [Google Scholar] [CrossRef]
- Moral, F.J.; Rebollo, F.J.; Paniagua, L.L.; García, A. Climatic Spatial Variability in Extremadura (Spain) Based on Viticultural Bioclimatic Indices. Int. J. Biometeorol. 2014, 58, 2139–2152. [Google Scholar] [CrossRef]
- Alsafadi, K.; Mohammed, S.; Mokhtar, A.; Sharaf, M.; He, H. Fine-Resolution Precipitation Mapping over Syria Using Local Regression and Spatial Interpolation. Atmos. Res. 2021, 256, 105524. [Google Scholar] [CrossRef]
- Alsafadi, K.; Bi, S.; Bashir, B.; Sharifi, E.; Alsalman, A.; Kumar, A.; Shahid, S. High-Resolution Precipitation Modeling in Complex Terrains Using Hybrid Interpolation Techniques: Incorporating Physiographic and MODIS Cloud Cover Influences. Remote Sens. 2023, 15, 2435. [Google Scholar] [CrossRef]
- Alexandersson, H. A Homogeneity Test Applied to Precipitation Data. J. Climatol. 1986, 6, 661–675. [Google Scholar] [CrossRef]
- Štěpánek, P.; Zahradníček, P.; Skalák, P. Data Quality Control and Homogenization of Air Temperature and Precipitation Series in the Area of the Czech Republic in the Period 1961–2007. Adv. Sci. Res. 2009, 3, 23–26. [Google Scholar] [CrossRef]
- Wilby, R.L.; Dawson, C.W.; Barrow, E.M. SDSM—A Decision Support Tool for the Assessment of Regional Climate Change Impacts. Environ. Model. Softw. 2002, 17, 145–157. [Google Scholar] [CrossRef]
- Tavakol-Davani, H.; Nasseri, M.; Zahraie, B. Improved Statistical Downscaling of Daily Precipitation Using SDSM Platform and Data-Mining Methods. Int. J. Clim. 2013, 33, 2561–2578. [Google Scholar] [CrossRef]
- Meenu, R.; Rehana, S.; Mujumdar, P.P. Assessment of Hydrologic Impacts of Climate Change in Tunga-Bhadra River Basin, India with HEC-HMS and SDSM. Hydrol. Process. 2013, 27, 1572–1589. [Google Scholar] [CrossRef]
- Gebrechorkos, S.H.; Hülsmann, S.; Bernhofer, C. Statistically Downscaled Climate Dataset for East Africa. Sci. Data 2019, 6, 31. [Google Scholar] [CrossRef]
- Mesterházy, I.; Mészáros, R.; Pongrácz, R. The Effects of Climate Change on Grape Production in Hungary. Idojaras 2014, 118, 193–206. [Google Scholar]
- Jones, G.V.; Duff, A.A.; Hall, A. Updated analysis of climate-viticulture structure and suitability in the Western United States. In Proceedings of the 16th International GiESCO Symposium-Davis, Viticulture and Enology, Davis, CA, USA, 12–15 July 2009. [Google Scholar]
- Kliewer, W.M. Berry Composition of Vitis Vinifera Cultivars as Influenced by Photo- and Nycto-Temperatures During Maturation. J. Am. Soc. Hortic. Sci. 1973, 98, 153–159. [Google Scholar] [CrossRef]
- Fraga, H.; Malheiro, A.C.; Moutinho-Pereira, J.; Cardoso, R.M.; Soares, P.M.M.; Cancela, J.J.; Pinto, J.G.; Santos, J.A. Integrated Analysis of Climate, Soil, Topography and Vegetative Growth in Iberian Viticultural Regions. PLoS ONE 2014, 9, e108078. [Google Scholar] [CrossRef] [PubMed]
- Jones, G.V. Climate and Terroir: Impacts of Climate Variability and Change on Win. In Fine Wine and Terroir—The Geoscience Perspective; Macqueen, R.W., Meinert, L.D., Eds.; Geoscience Canada Reprint Series Number 9; Geological Association of Canada: St. John’s, NL, Canada, 2006; 247p. [Google Scholar]
- Odeh, I.O.A.; McBratney, A.B.; Chittleborough, D.J. Further Results on Prediction of Soil Properties from Terrain Attributes: Heterotopic Cokriging and Regression-Kriging. Geoderma 1995, 67, 215–226. [Google Scholar] [CrossRef]
- Hengl, T.; Heuvelink, G.B.M.; Rossiter, D.G. About Regression-Kriging: From Equations to Case Studies. Comput. Geosci. 2007, 33, 1301–1315. [Google Scholar] [CrossRef]
- Danielson, J.J.; Gesch, D.B. Global Multi-Resolution Terrain Elevation Data 2010 (GMTED2010); US Department of the Interior, US Geological Survey: Reston, VA, USA, 2011; p. 101.
- IPCC. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; IPCC: Geneva, Switzerland, 2014. [Google Scholar]
- Mokhtar, A.; Elbeltagi, A.; Maroufpoor, S.; Azad, N.; He, H.; Alsafadi, K.; Gyasi-Agyei, Y.; He, W. Estimation of the Rice Water Footprint Based on Machine Learning Algorithms. Comput. Electron. Agric. 2021, 191, 106501. [Google Scholar] [CrossRef]
- Mokhtar, A.; He, H.; Alsafadi, K.; Li, Y.; Zhao, H.; Keo, S.; Bai, C.; Abuarab, M.; Zhang, C.; Elbagoury, K.; et al. Evapotranspiration as a Response to Climate Variability and Ecosystem Changes in Southwest, China. Environ. Earth Sci. 2020, 79, 312. [Google Scholar] [CrossRef]
- Fraga, H.; Pinto, J.G.; Santos, J.A. Climate Change Projections for Chilling and Heat Forcing Conditions in European Vineyards and Olive Orchards: A Multi-Model Assessment. Clim. Change 2019, 152, 179–193. [Google Scholar] [CrossRef]
- Piña-Rey, A.; González-Fernández, E.; Fernández-González, M.; Lorenzo, M.N.; Rodríguez-Rajo, F.J. Climate Change Impacts Assessment on Wine-Growing Bioclimatic Transition Areas. Agriculture 2020, 10, 605. [Google Scholar] [CrossRef]
- Petriashvili, A.; Mach, J.; Štěbeták, M.; Prášilová, M.; Svoboda, R.; Navrátilová, M.; Beranová, M.; Veselá, K.; Hofman, V.; Němec, O. The Impact of Climate Change on the Sustainability of Wine Production and the Structure of Its Consumption in Czechia. Heliyon 2023, 9, e17882. [Google Scholar] [CrossRef]
- Ramos, M.C.; Jones, G.V.; Martínez-Casasnovas, J.A. Structure and Trends in Climate Parameters Affecting Winegrape Production in Northeast Spain. Clim. Res. 2008, 38, 1–15. [Google Scholar] [CrossRef]
- Arias, L.A.; Berli, F.; Fontana, A.; Bottini, R.; Piccoli, P. Climate Change Effects on Grapevine Physiology and Biochemistry: Benefits and Challenges of High Altitude as an Adaptation Strategy. Front. Plant Sci. 2022, 13, 835425. [Google Scholar] [CrossRef] [PubMed]
- Cardell, M.F.; Amengual, A.; Romero, R. Future Effects of Climate Change on the Suitability of Wine Grape Production across Europe. Reg. Environ. Change 2019, 19, 2299–2310. [Google Scholar] [CrossRef]
- Sgubin, G.; Swingedouw, D.; Mignot, J.; Gambetta, G.A.; Bois, B.; Loukos, H.; Noël, T.; Pieri, P.; de Cortázar-Atauri, I.; Ollat, N.; et al. Non-Linear Loss of Suitable Wine Regions over Europe in Response to Increasing Global Warming. Glob. Change Biol. 2023, 29, 808–826. [Google Scholar] [CrossRef] [PubMed]
- Jones, G.V. Climate, Grapes, and Wine: Structure and Suitability in a Changing Climate. In Proceedings of the Acta Horticulturae, Alnarp, Sweden, 31 May–3 June 2015; Volume 931. [Google Scholar]
- Coombe, B.G. Distribution of Solutes within the Developing Grape Berry in Relation to Its Morphology. Am. J. Enol. Vitic. 1987, 38, 120–127. [Google Scholar] [CrossRef]
- Van Leeuwen, C.; Tregoat, O.; Choné, X.; Bois, B.; Pernet, D.; Gaudillére, J.P. Vine Water Status Is a Key Factor in Grape Ripening and Vintage Quality for Red Bordeaux Wine. How Can It Be Assessed for Vineyard Management Purposes? Oeno One 2009, 43, 121–134. [Google Scholar] [CrossRef]
- Jones, G.V.; White, M.A.; Cooper, O.R.; Storchmann, K. Climate Change and Global Wine Quality. Clim. Change 2005, 73, 319–343. [Google Scholar] [CrossRef]
- Sadras, V.O.; Moran, M.A. Elevated Temperature Decouples Anthocyanins and Sugars in Berries of Shiraz and Cabernet Franc. Aust. J. Grape Wine Res. 2012, 18, 115–122. [Google Scholar] [CrossRef]
- Clemente, N.; Santos, J.A.; Fontes, N.; Graça, A.; Gonçalves, I.; Fraga, H. Grapevine Sugar Concentration Model (GSCM): A Decision Support Tool for the Douro Superior Winemaking Region. Agronomy 2022, 12, 1404. [Google Scholar] [CrossRef]
- Mira de Orduña, R. Climate Change Associated Effects on Grape and Wine Quality and Production. Food Res. Int. 2010, 43, 1844–1855. [Google Scholar] [CrossRef]
- Lakatos, L.; Mitre, Z. Effect of Drought on the Future Sugar Content of Wine Grape Varieties till 2100: Possible Adaptation in the Hungarian Eger Wine Region. Biomolecules 2023, 13, 1143. [Google Scholar] [CrossRef] [PubMed]
- Valori, R.; Costa, C.; Figorilli, S.; Ortenzi, L.; Manganiello, R.; Ciccoritti, R.; Cecchini, F.; Morassut, M.; Bevilacqua, N.; Colatosti, G.; et al. Advanced Forecasting Modeling to Early Predict Powdery Mildew First Appearance in Different Vines Cultivars. Sustainability 2023, 15, 2837. [Google Scholar] [CrossRef]
- Ausseil, A.G.E.; Law, R.M.; Parker, A.K.; Teixeira, E.I.; Sood, A. Projected Wine Grape Cultivar Shifts Due to Climate Change in New Zealand. Front. Plant Sci. 2021, 12, 618039. [Google Scholar] [CrossRef]
- Costa, R.; Fraga, H.; Fonseca, A.; De Cortázar-Atauri, I.G.; Val, M.C.; Carlos, C.; Reis, S.; Santos, J.A. Grapevine Phenology of Cv. Touriga Franca and Touriga Nacional in the Douro Wine Region: Modelling and Climate Change Projections. Agronomy 2019, 9, 210. [Google Scholar] [CrossRef]
- Verdugo-Vásquez, N.; Acevedo-Opazo, C.; Valdés-Gómez, H.; Araya-Alman, M.; Ingram, B.; García de Cortázar-Atauri, I.; Tisseyre, B. Spatial Variability of Phenology in Two Irrigated Grapevine Cultivar Growing under Semi-Arid Conditions. Precis. Agric. 2016, 17, 218–245. [Google Scholar] [CrossRef]
- Sadras, V.O.; Moran, M.A. Nonlinear Effects of Elevated Temperature on Grapevine Phenology. Agric. For. Meteorol. 2013, 173, 107–115. [Google Scholar] [CrossRef]
- Caffarra, A.; Rinaldi, M.; Eccel, E.; Rossi, V.; Pertot, I. Modelling the Impact of Climate Change on the Interaction between Grapevine and Its Pests and Pathogens: European Grapevine Moth and Powdery Mildew. Agric. Ecosyst. Environ. 2012, 148, 89–101. [Google Scholar] [CrossRef]
- Droulia, F.; Charalampopoulos, I. A Review on the Observed Climate Change in Europe and Its Impacts on Viticulture. Atmosphere 2022, 13, 837. [Google Scholar] [CrossRef]
- Nesbitt, A.; Kemp, B.; Steele, C.; Lovett, A.; Dorling, S. Impact of Recent Climate Change and Weather Variability on the Viability of UK Viticulture—Combining Weather and Climate Records with Producers’ Perspectives. Aust. J. Grape Wine Res. 2016, 22, 324–335. [Google Scholar] [CrossRef]
- Comte, V.; Schneider, L.; Calanca, P.; Rebetez, M. Effects of Climate Change on Bioclimatic Indices in Vineyards along Lake Neuchatel, Switzerland. Theor. Appl. Clim. 2022, 147, 423–436. [Google Scholar] [CrossRef]
- Cataldo, E.C.; Salvi, L.S.; Paoli, F.P.; Fucile, M.F.; Masciandaro, G.M.; Manzi, D.M.; Masini, C.M.M.; Mattii, G.B.M. Effects of Natural Clinoptilolite on Physiology, Water Stress, Sugar, and Anthocyanin Content in Sanforte (Vitis vinifera L.) Young Vineyard. J. Agric. Sci. 2021, 159, 488–499. [Google Scholar] [CrossRef]
- Mosedale, J.R.; Abernethy, K.E.; Smart, R.E.; Wilson, R.J.; Maclean, I.M.D. Climate Change Impacts and Adaptive Strategies: Lessons from the Grapevine. Glob. Change Biol. 2016, 22, 3814–3828. [Google Scholar] [CrossRef] [PubMed]
- Bernetti, I.; Menghini, S.; Marinelli, N.; Sacchelli, S.; Sottini, V.A. Assessment of Climate Change Impact on Viticulture: Economic Evaluations and Adaptation Strategies Analysis for the Tuscan Wine Sector. Wine Econ. Policy 2012, 1, 73–86. [Google Scholar] [CrossRef]
- Santos, J.A.; Fraga, H.; Malheiro, A.C.; Moutinho-Pereira, J.; Dinis, L.-T.; Correia, C.; Moriondo, M.; Leolini, L.; Dibari, C.; Costafreda-Aumedes, S.; et al. A Review of the Potential Climate Change Impacts and Adaptation Options for European Viticulture. Appl. Sci. 2020, 10, 3092. [Google Scholar] [CrossRef]
- Lereboullet, A.L.; Beltrando, G.; Bardsley, D.K. Socio-ecological adaptation to climate change: A comparative case study from the Mediterranean wine industry in France and Australia. Agric. Ecosyst. Environ. 2013, 164, 273–285. [Google Scholar] [CrossRef]
- Battaglini, A.; Barbeau, G.; Bindi, M.; Badeck, F.W. European winegrowers’ perceptions of climate change impact and options for adaptation. Reg. Environ. Change 2009, 9, 61–73. [Google Scholar] [CrossRef]
- Resco, P.; Iglesias, A.; Bardají, I.; Sotés, V. Exploring Adaptation Choices for Grapevine Regions in Spain. Reg. Environ. Change 2016, 16, 979–993. [Google Scholar] [CrossRef]
- Salvi, L.; Brunetti, C.; Cataldo, E.; Storchi, P.; Mattii, G.B. Eco-Physiological Traits and Phenylpropanoid Profiling on Potted Vitis vinifera L. cv Pinot Noir Subjected to Ascophyllum nodosum Treatments under Post-Veraison Low Water Availability. Appl. Sci. 2020, 10, 4473. [Google Scholar] [CrossRef]
- Van Leeuwen, C.; Destrac-Irvine, A.; Dubernet, M.; Duchêne, E.; Gowdy, M.; Marguerit, E.; Pieri, P.; Parker, A.; De Rességuier, L.; Ollat, N. An Update on the Impact of Climate Change in Viticulture and Potential Adaptations. Agronomy 2019, 9, 514. [Google Scholar] [CrossRef]
- Delrot, S.; Grimplet, J.; Carbonell-Bejerano, P.; Schwandner, A.; Bert, P.F.; Bavaresco, L.; Costa, L.D.; Di Gaspero, G.; Duchêne, E.; Hausmann, L.; et al. Genetic and Genomic Approaches for Adaptation of Grapevine to Climate Change. In Genomic Designing of Climate-Smart Fruit Crops; Springer: Berlin/Heidelberg, Germany, 2020. [Google Scholar]
- Alsafadi, K.J. Climate and Its Impact on Cultivation of Apple and Grapes Crops in Alswuydaa Governorate-Syria. Unpublished Master’s Thesis, Alexandria University, Alexandria, Egypt, 2016. (In Arabic). [Google Scholar]
Variable | Data Type | Number of Station/Point | Temporal Scale | Reference Period | Source |
---|---|---|---|---|---|
Precipitation (mm) | Rain gauge and | 57 | Monthly | 1984–2014 | SMA, SMOAAR, and JMD |
climatic stations | Daily | ||||
Temperature (°C) | Climatic stations | 15 | Daily | 1984–2014 | SMA, SMOAAR, and JMD |
Temperature (°C) | Gridded data | 9 | Daily | 1984–2014 | NASA Power Data release 8.0.1 |
https://power.larc.nasa.gov | |||||
(Accessed on 15 February 2023) |
BVIs | Unit | Class of BVIs, and Class Interval | Reference | |
---|---|---|---|---|
Growing season temperatures (GST) | °C | Cool (C) | 13–15 | [59] |
Temperate (T) | 15–17 | |||
Warm (W) | 17–19 | |||
Hot (H) | 19–24 | |||
Hydrothermal coefficient (HTC) | – | Excessively dry (ED) | <0.25 | [11] |
Dry (D) | 0.25–0.5 | |||
Moderately dry (MD) | 0.5–1.5 | |||
Moderately wet (MW) | 1.5–2 | |||
Wet (W) | 2–2.5 | |||
Excessively wet (EW) | >2.5 | |||
Winkler Index growing degree days (WI-GDD) | GDD | Too cold (TC) | <850 | [8] |
Cold (C) | 850–1390 | |||
Moderately cold (MC) | 1391–1670 | |||
Warm (W) | 1671–1940 | |||
Moderately warm (MW) | 1941–2220 | |||
Hot (H) | 2221–2700 | |||
Too hot (TH) | >2700 | |||
Huglin Heliothermal index (HI) | GDD | Too cold (TC) | <1200 | [9] |
Very cool (VC) | 1200–1500 | |||
Cool (C) | 1500–1800 | |||
Temperate (T) | 1800–2100 | |||
Temperate warm (TW) | 2100–2400 | |||
Warm (W) | 2400–2700 | |||
Very warm (VW) | 2700–3000 | |||
Too hot | >3000 | |||
Too cold (TC) | <1200 | |||
Cool night index (CI) | °C | Very cool nights (VCN) | <12 | [10] |
Cool nights (CN) | >12 ≤ 14 | |||
Temperate nights (TN) | >14 ≤ 18 | |||
Warm nights (WN) | >18 |
Regions | RCPs | WI-GDD | HI | HTC | CI |
---|---|---|---|---|---|
RCP2.6 | 6.6 | 5.9 | −14.5 | 6.0 | |
Ain Arab | RCP4.5 | 16.1 | 15.8 | −46.9 | −3.9 |
RCP8.5 | 22.9 | 21.0 | −38.3 | 39.1 | |
Kafer | RCP2.6 | 17.6 | 14.3 | −18.0 | 9.4 |
RCP4.5 | 28.0 | 22.5 | −47.4 | 0.4 | |
RCP8.5 | 33.6 | 26.6 | −41.7 | 19.9 | |
Orman | RCP2.6 | 18.5 | 16.2 | −51.9 | 11.5 |
RCP4.5 | 29.5 | 25.9 | −71.2 | 1.6 | |
RCP8.5 | 35.8 | 30.8 | −67.7 | 22.2 |
BVI | Zone | 1984–2014 | 2015–2100 | ||
---|---|---|---|---|---|
RCP2.6 | RCP4.5 | RCP8.5 | |||
GST | C | 0.2 | 0 (−0.2) | 0 (−0.2) | 0 (−0.2) |
T | 7.8 | 0.3 (−7.5) | 0 (−7.8) | 0 (−7.8) | |
W | 20.3 | 7.7 | 3.5 | 2.1 | |
H | 71.7 | 92 (+20.3) | 96.5 (+24.8) | 97.9 (+26.2) | |
WI-GDD | C | 2.9 | 0 (−2.9) | 0 (−2.9) | 0 (−2.9) |
MC | 8 | 1.7 (−6.3) | 0 (−8) | 0 (−8) | |
W | 15.8 | 6.4 (−9.4) | 3.8 (−12) | 1.1 (−14.7) | |
MW | 30.3 | 11.8 (−18.5) | 7 (−23.3) | 5.2 (−25.1) | |
H | 40.3 | 43.6 (+3.3) | 28.5 (−11.8) | 21.2 (−19.1) | |
TH | 2.6 | 36.5 (+33.9) | 60.7 (+58.1) | 72.5 (+69.6) | |
HI | C | 1.3 | 0 (−1.3) | 0 (−1.3) | 0 (−1.3) |
T | 7.2 | 0 (−7.2) | 0 (−7.2) | 0 (−7.2) | |
TW | 13.3 | 2.3 (−11) | 0.2 (−13.1) | 0 (−13.3) | |
W | 21.3 | 7.2 (−14.1) | 4.1 (−17.2) | 2.5 (−18.8) | |
VW | 26.5 | 13.8 (−12.7) | 8.5 (−18) | 7.3 (−19.2) | |
TH | 30.4 | 76.7 (+46.3) | 87.2 (+56.8) | 90.2 (+59.8) | |
HTC | ED | 52.8 | 75.5 (+22.7) | 91.3 (+38.5) | 88.9 (+36.1) |
D | 34.9 | 19.6 (−15.3) | 8.7 (−26.2) | 11.1 (−23.8) | |
MD | 12.3 | 4.9 (−7.4) | 0 (−12.3) | 0 (−12.3) | |
CI | VCN | 4.2 | 0 (−4.2) | 2.2 (−2) | 0 (−4.2) |
CN | 6.7 | 3.1 (−3.6) | 5.1 (−1.6) | 1.7 (−5) | |
TN | 85.8 | 43.3 (−42.5) | 77.1 (−8.7) | 22.4 (−63.4) | |
WN | 3.3 | 53.6 (+50.3) | 15.6 (+12.3) | 75.9 (+72.6) |
Scenario | Region | W-GDD | HI | HTC | CI | ||||
---|---|---|---|---|---|---|---|---|---|
Mean | Zone | Mean | Zone | Mean | Zone | Mean | Zone | ||
Baseline 1982–2014 | Alkars | 1826.9 | W | 2368.9 | TW | 0.46 | D | 14.6 | TN |
Euyun | 1784.4 | W | 2318.8 | TW | 0.475 | D | 14.4 | TN | |
Orman | 1859.4 | W | 2408.6 | W | 0.375 | D | 14.7 | TN | |
Qanawat | 1626.5 | MC | 2140.9 | TW | 0.702 | MD | 12.7 | CN | |
Mafeila | 1809.5 | W | 2289.3 | TW | 0.605 | MD | 14.2 | TN | |
Mayamas | 1493.3 | MC | 1999.6 | T | 0.73 | MD | 12.1 | CN | |
Kafer | 1631.6 | MC | 2137.7 | TW | 0.626 | MD | 12.8 | CN | |
Sahwat Kh | 1657.6 | MC | 2183.5 | TW | 0.573 | MD | 13.3 | CN | |
Hobran | 1855.4 | W | 2413 | W | 0.45 | D | 14.5 | TN | |
RCP26 2015–2100 | Alkars | 2206.3 | MW | 2947.6 | VW | 0.325 | D | 16.6 | TN |
Euyun | 2159 | MW | 2900.6 | VW | 0.331 | D | 16.4 | TN | |
Orman | 2244 | H | 2997.1 | VW | 0.252 | D | 16.6 | TN | |
Qanawat | 1995 | MW | 2693.1 | W | 0.50 | MD | 14.6 | TN | |
Mafeila | 2191.4 | MW | 2843.7 | VW | 0.440 | D | 16.1 | TN | |
Mayamas | 1852.6 | W | 2546.2 | W | 0.522 | MD | 14.1 | TN | |
Kafer | 1989.5 | MW | 2694.8 | W | 0.452 | D | 14.9 | TN | |
Sahwat Kh | 2023.2 | MW | 2754.2 | VW | 0.407 | D | 15.4 | TN | |
Hobran | 2242.2 | H | 2980.9 | VW | 0.324 | D | 16.6 | TN | |
RCP45 2015–2100 | Alkars | 2407.7 | H | 3142.2 | TH | 0.191 | ED | 15.4 | TN |
Euyun | 2361.4 | H | 3095.2 | TH | 0.195 | ED | 15.1 | TN | |
Orman | 2448 | H | 3191.7 | TH | 0.142 | ED | 15.4 | TN | |
Qanawat | 2166.7 | MW | 2884.8 | VW | 0.307 | D | 13.5 | CN | |
Mafeila | 2382.6 | H | 3036.5 | TH | 0.278 | D | 15 | TN | |
Mayamas | 2013 | MW | 2740.6 | VW | 0.331 | D | 12.9 | CN | |
Kafer | 2163.1 | MW | 2887.5 | VW | 0.279 | D | 13.6 | CN | |
Sahwat Kh | 2211.3 | MW | 2948.3 | VW | 0.250 | D | 14.1 | TN | |
Hobran | 2434.1 | H | 3173.2 | TH | 0.195 | ED | 15.3 | TN | |
RCP85 2015–2100 | Alkars | 2551.5 | H | 3223.6 | TH | 0.219 | ED | 17.8 | TN |
Euyun | 2506.6 | H | 3181.4 | TH | 0.223 | ED | 17.6 | TN | |
Orman | 2596.5 | H | 3284.4 | TH | 0.162 | ED | 17.85 | TN | |
Qanawat | 2320.7 | H | 2971.6 | VW | 0.352 | D | 15.7 | TN | |
Mafeila | 2537.2 | H | 3123.1 | TH | 0.318 | D | 17.3 | TN | |
Mayamas | 2168 | MW | 2823.2 | VW | 0.365 | D | 15.4 | TN | |
Kafer | 2309.3 | H | 2964.4 | VW | 0.3123 | D | 16.2 | TN | |
Sahwat Kh | 2360.3 | H | 3032.4 | TH | 0.278 | D | 16.7 | TN | |
Hobran | 2577.6 | H | 3245.9 | TH | 0.220 | ED | 18 | WN |
Baseline and Scenario | Region | TGS (°C) | Recommended Grapevine Cultivars Based on Climate-Maturity Zoning | |
---|---|---|---|---|
Range | Zone | |||
Baseline 1982–2014 | Alkars | 17.6–18.6 | W | Cabernet Franc, Tempranillo, Dolcetto, Merlot, Viognier Syrah, and Table grapes |
Euyun | 17.8–18.4 | W | ||
Mayamas | 15.4–17 | T | Pinot Noir, Chardonay, Sauvignon Blanc, and Semillon | |
Qanawat | 14.9–19.8 | T–W | Chardonnay, Sauvignon Blanc, Semillon, Cabernet Franc, Tempranillo, Dolcetto, and Merlot | |
Mafeila | 16.2–19 | T–W | ||
Kafer | 16.2–18.4 | T–W | ||
Sahwat Kh | 15.7–18 | T–W | ||
Orman | 17.7–19.5 | W–H | Cabernet Franc, Tempranillo, Dolcetto, Merlot, Viognier, Syrah, Cabernet Sauvignon, Sangiovese, Grenache Carignane, and Table grapes, | |
Hobran | 17.8–19.7 | W–H | ||
RCP26 2015–2100 | Alkars | 19.6–20.6 | H | Table grapes, Grenache, Carignane, Zinfandel, Nebbiolo, and Raisins |
Euyun | 19.8–20.4 | H | ||
Orman | 19.7–21.5 | H | ||
Hobran | 19.8–21.6 | H | ||
Mayamas | 17.4–19 | W | Cabernet Franc, Tempranillo, Dolcetto, Merlot, Viognier Syrah, and Table grapes | |
Mafeila | 18.1–21.9 | W–H | Cabernet Franc, Tempranillo, Dolcetto, Merlot, Viognier Syrah, Table grapes, Cabernet Sauvignon Sangiovese, Grenache, Carignane, and Table grapes | |
Kafer | 18.1–20.3 | W–H | ||
Sahwat Kh | 17.7–20.1 | W–H | ||
Qanawat | 16.9 –21.8 | W–H |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Alsafadi, K.; Bi, S.; Bashir, B.; Alsalman, A.; Srivastava, A.K. Future Scenarios of Bioclimatic Viticulture Indices in the Eastern Mediterranean: Insights into Sustainable Vineyard Management in a Changing Climate. Sustainability 2023, 15, 11740. https://doi.org/10.3390/su151511740
Alsafadi K, Bi S, Bashir B, Alsalman A, Srivastava AK. Future Scenarios of Bioclimatic Viticulture Indices in the Eastern Mediterranean: Insights into Sustainable Vineyard Management in a Changing Climate. Sustainability. 2023; 15(15):11740. https://doi.org/10.3390/su151511740
Chicago/Turabian StyleAlsafadi, Karam, Shuoben Bi, Bashar Bashir, Abdullah Alsalman, and Amit Kumar Srivastava. 2023. "Future Scenarios of Bioclimatic Viticulture Indices in the Eastern Mediterranean: Insights into Sustainable Vineyard Management in a Changing Climate" Sustainability 15, no. 15: 11740. https://doi.org/10.3390/su151511740
APA StyleAlsafadi, K., Bi, S., Bashir, B., Alsalman, A., & Srivastava, A. K. (2023). Future Scenarios of Bioclimatic Viticulture Indices in the Eastern Mediterranean: Insights into Sustainable Vineyard Management in a Changing Climate. Sustainability, 15(15), 11740. https://doi.org/10.3390/su151511740