Assessment of climate impact on grape productivity: A new application for bioclimatic indices in Italy

被引:11
|
作者
Massano, Laura [1 ]
Fosser, Giorgia [1 ]
Gaetani, Marco [1 ]
Bois, Benjamin [2 ,3 ]
机构
[1] Scuola Univ Super IUSS, Pavia, Italy
[2] Univ Bourgogne Franche Comte, Ctr Rech Climatol, Biogeosci UMR6282, CNRS, Dijon, France
[3] Univ Bourgogne, Inst Univ Vigne & Vin, Dijon, France
关键词
Environment; Impact; Grape productivity; Climate variability; Bioclimatic indices; E-OBS; PLASMOPARA-VITICOLA; DOWNY MILDEW; WINE; TEMPERATURE; VITICULTURE; TRENDS; PROJECTIONS; PHENOLOGY; SIMULATIONS; VARIABILITY;
D O I
10.1016/j.scitotenv.2023.167134
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Italy is a world leader for viticulture and wine business with an export valued 7 billion of euros in 2021, and wine being the second most exported product within the national agri-food sector. However, these figures might be threatened by climate change and winegrowers call for more reliable local information on future impacts of climate change on viticulture.The study aims to understand the impact of climate on wine production in Italy using grape productivity data and bioclimatic indices. Using temperature and precipitation observations from the E-OBS gridded dataset, a set of bioclimatic indices recommended by the International Organisation of Vine and Wine guidelines is calculated and correlated with grape productivity data at the regional scale (Nomenclature of territorial units for statistics, NUTS, level 2) over the last 39 years (1980-2019). The study investigates how both long-term change and natural variability of the bioclimatic indices impacted on grape productivity. Both single and multi-regression approaches are applied to assess the portion of grape productivity variability explained by the selected indices.When the single-regression approach is applied, the correlations between bioclimatic indices and grape productivity explain up to the 45 % of total production variability, however they are statistically significant only in few regions. Conversely, the multi-regression approach improves the proportion of variance explained and gives statistically significative results in region where the single regression is not statically significant.The multi-regressive approach shows the added value of considering the interplay of different bioclimatic indices in explaining the overall variability of productivity. The possibility of using bioclimatic indicators as a proxy for grape productivity provides a simple tool that grape growers, wine consortia and policy makers can use to adapt to future climate.
引用
收藏
页数:12
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