Non-linear loss of suitable wine regions over Europe in response to increasing global warming.

Evaluating the potential climatic suitability for premium wine production is crucial for adaptation planning in Europe. While new wine regions may emerge out of the traditional boundaries, most of the present-day renowned winemaking regions may be threatened by climate change. Here, we analyse the future evolution of the geography of wine production over Europe, through the definition of a novel climatic suitability indicator, which is calculated over the projected grapevine phenological phases to account for their possible contractions under global warming. Our approach consists in coupling six different de-biased downscaled climate projections under two different scenarios of global warming with four phenological models for different grapevine varieties. The resulting suitability indicator is based on fuzzy logic and is calculated over three main components measuring (i) the timing of the fruit physiological maturity, (ii) the risk of water stress and (iii) the risk of pests and diseases. The results demonstrate that the level of global warming largely determines the distribution of future wine regions. For a global temperature increase limited to 2°C above the pre-industrial level, the suitable areas over the traditional regions are reduced by about 4%/°C rise, while for higher levels of global warming, the rate of this loss increases up to 17%/°C. This is compensated by a gradual emergence of new wine regions out of the traditional boundaries. Moreover, we show that reallocating better-suited grapevine varieties to warmer conditions may be a viable adaptation measure to cope with the projected suitability loss over the traditional regions. However, the effectiveness of this strategy appears to decrease as the level of global warming increases. Overall, these findings suggest the existence of a safe limit below 2°C of global warming for the European winemaking sector, while adaptation might become far more challenging beyond this threshold.

Water status and must composition in grapevine cv. Chardonnay with different soils and topography and a mini meta-analysis of the δ13 C/water potentials correlation.

BACKGROUND: The measurement of carbon isotopic discrimination in grape sugars at harvest (δ13 C) is an integrated assessment of water status during ripening. It is an efficient alternative to assess variability in the field and discriminate between management zones in precision viticulture, but further work is needed to completely understand the signal. RESULTS: This work, spanning over 3 years, performed in a hillslope toposequence in Burgundy, delineates the relationships between main soil properties (gravel amount, slope, texture) and the grapevine water status assessed by δ13 C. The highest δ13 C, indicating most severe water deficit, was recorded in gravelly soils on steep slopes. The amount of sugars and malic and tartaric acids was also related to δ13 C. The relationship between δ13 C and predawn leaf water potentials (Ψpd ) was also investigated, because the absolute values of measured δ13 C were lower than the values currently found in the literature. CONCLUSIONS: A mini-meta-analysis was performed, which showed that the slope of the relationships between minimum Ψpd and δ13 C was stable across studies (a change of 1‰ in δ13 C corresponded to a change of -0.2 MPa in the minimum Ψpd ), while the intercept of the comparison δ13 C/Ψpd changed, probably because of genetic variations between varieties, or environmental differences. © 2017 Society of Chemical Industry.

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

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.

High-Resolution Mass Spectrometry-Based Metabolomics for Increased Grape Juice Metabolite Coverage.

The composition of the juice from grape berries is at the basis of the definition of technological ripeness before harvest, historically evaluated from global sugar and acid contents. If many studies have contributed to the identification of other primary and secondary metabolites in whole berries, deepening knowledge about the chemical composition of the sole flesh of grape berries (i.e., without considering skins and seeds) at harvest is of primary interest when studying the enological potential of widespread grape varieties producing high-added-value wines. Here, we used non-targeted DI-FT-ICR-MS and RP-UHPLC-Q-ToF-MS analyses to explore the extent of metabolite coverage of up to 290 grape juices from four Vitis vinifera grape varieties, namely Chardonnay, Pinot noir, Meunier, and Aligoté, sampled at harvest from 91 vineyards in Europe and Argentina, over three successive vintages. SPE pretreatment of samples led to the identification of more than 4500 detected C,H,O,N,S-containing elemental compositions, likely associated with tens of thousands of distinct metabolites. We further revealed that a major part of this chemical diversity appears to be common to the different juices, as exemplified by Pinot noir and Chardonnay samples. However, it was possible to build significant models for the discrimination of Chardonnay from Pinot noir grape juices, and of Chardonnay from Aligoté grape juices, regardless of the geographical origin or the vintage. Therefore, this metabolomic approach opens access to a remarkable holistic molecular description of the instantaneous composition of such a biological matrix, which is the result of complex interplays among environmental, biochemical, and vine growing practices.

Are life-history traits equally affected by global warming? A case study combining a multi-trait approach with fine-grain climate modeling.

Predicting species responses to climate change requires tracking the variation in individual performance following exposure to warming conditions. One ecologically relevant approach consists of examining the thermal responses of a large number of traits, both related with population dynamics and trophic interactions (i.e. a multi-trait approach). Based on in situ climatic data and projections from climate models, we here designed two daily fluctuating thermal regimes realistically reflecting current and future conditions in Eastern France. These models detected an increase in mean temperature and in the range of daily thermal fluctuations as two local facets of global warming likely to occur in our study area by the end of this century. We then examined the responses of several fitness-related traits in caterpillars of the moth Lobesia botrana - including development, pupal mass, survival rates, energetic reserves, behavioral and immune traits expressed against parasitoids - to this experimental imitation of global warming. Increasing temperatures positively affected development (leading to a 31% reduction in the time needed to complete larval stage), survival rates (+19%), and movement speed as a surrogate for larval escape ability to natural enemies (+60%). Conversely, warming elicited detrimental effects on lipid reserves (-26%) and immunity (total phenoloxidase activity: -34%). These findings confirm that traits should differ in their sensitivity to global warming, underlying complex consequences for population dynamics and trophic interactions. Our study strengthens the importance of combining a multi-trait approach with the use of realistic fluctuating regimes to forecast the consequences of global warming for individuals, species and species assemblages.

Ecophysiological Modeling of Grapevine Water Stress in Burgundy Terroirs by a Machine-Learning Approach.

In a climate change scenario, successful modeling of the relationships between plant-soil-meteorology is crucial for a sustainable agricultural production, especially for perennial crops. Grapevines (Vitis vinifera L. cv Chardonnay) located in eight experimental plots (Burgundy, France) along a hillslope were monitored weekly for 3 years for leaf water potentials, both at predawn (Ψpd) and at midday (Ψstem). The water stress experienced by grapevine was modeled as a function of meteorological data (minimum and maximum temperature, rainfall) and soil characteristics (soil texture, gravel content, slope) by a gradient boosting machine. Model performance was assessed by comparison with carbon isotope discrimination (δ(13)C) of grape sugars at harvest and by the use of a test-set. The developed models reached outstanding prediction performance (RMSE < 0.08 MPa for Ψstem and < 0.06 MPa for Ψpd), comparable to measurement accuracy. Model predictions at a daily time step improved correlation with δ(13)C data, respect to the observed trend at a weekly time scale. The role of each predictor in these models was described in order to understand how temperature, rainfall, soil texture, gravel content and slope affect the grapevine water status in the studied context. This work proposes a straight-forward strategy to simulate plant water stress in field condition, at a local scale; to investigate ecological relationships in the vineyard and adapt cultural practices to future conditions.

Image analysis methods for assessment of H2O2 production and Plasmopara viticola development in grapevine leaves: application to the evaluation of resistance to downy mildew.

The grapevine downy mildew (Plasmopara viticola) provokes severe damages and destroys the harvest in the absence of an effective protection. Numerous fungicide treatments are thus generally necessary. To promote a sustainable production, alternative strategies of protection including new antifungal molecules, resistant genotypes or elicitor-induced resistance are under trial. To evaluate the relevance of these strategies, resistance tests are required. In this context, three image analysis methods were developed to read the results of tests performed to assess P. viticola sporulation and mycelial development, and H(2)O(2) production in leaves. They have been validated using elicitors of plant defenses. These methods are reliable, innovative, rapid, and their modular concept allows their further adaptation to other host-pathogen systems.