Article Figures & Data
Figures
- Figure 1
Schematic representation of the workflow of the study, including the collection and integration of different sets of data prior to analysis. Tmax, maximum temperature; Tmin, minimum temperature; Tavg, average temperature; VPDmin, minimum vapor pressure deficit; VPDmax, maximum vapor pressure deficit; GDD, growing degree days; BB, budbreak; FL, flowering; VER, veraison; H, harvest; DOY, day of year.
- Figure 2
Schematic step-by-step representation of the procedure followed to link weather-based clusters to yield, harvest date, and fruit composition. Harvest date records for one vineyard at site 4 (S4) from 2016 to 2023 are shown as an example. POST-V, postveraison heat; PRE-V, preveraison heat; Cool, cool season; DOY, day of year; C3, Cluster 3.
- Figure 3
Hierarchical clustering analysis (HCA) of historical weather observations (1981 to 2023) at five vineyard sites in California (S1 to S5). A) Clusters (n = 3) identified using HCA, shown using a principal component analysis score plot. B1 to B3) Temperature radials (April to October) showing unique patterns associated with each cluster. In each graph, temperatures are shown for a single site and year for exemplification purposes. Green bars represent the range between daily minimum and maximum temperatures (Tmin and Tmax, respectively; °C); yellow points indicate daily average temperatures (Tavg). The shaded yellow band marks temperatures above the critical threshold of 38°C.
- Figure 4
Cluster validation using bootstrap random forest classification. A) Test error rate (TER) representing the percentage of misclassified observations at each iteration. Green points represent the error rate at each iteration. The red dotted line represents the average TER; the value is reported in the label at the top of the graph. B) Variables with the highest contribution for cluster classification, represented by the mean decrease accuracy (MDA). The full list of weather features and their description is available in Supplemental Table 1. Only variables with MDA > 0.5% are reported in this chart. Variables with MDA > 1% are marked in orange and represent the most important features driving cluster classification. FL, flowering; VER, veraison; HWU, heatwave units; BB, budbreak; H, harvest.
- Figure 5
Intensity and distribution of heat events for three clusters identified using hierarchical clustering analysis. A) Maximum temperature (Tmax; °C): distribution by month for each cluster, season (April to October), monthly Tmax by cluster, and comparison of Tmax distributions by phenological stage and month intervals to approximate pre- (May to July) and postveraison (August to October). B) Number of heat days (Tmax ≥ 38°C): total heat days in the growing season (April to October), by month (June to September), and by phenological stage. C) Number of heatwaves (two or more days with Tmax ≥ 38°C) in the growing season (April to October), by month (June to September), and by phenological stage. Density curves represent distributions by cluster. Points and error bars or ribbons represent means ± 95% confidence intervals. Letters denote significant differences (p ≤ 0.05) according to one- or two-way analysis of variance and Tukey’s adjusted post-hoc test in case of normal data, or Kruskal-Wallis followed by pairwise Wilcoxon test for non-normally distributed data. FL, flowering; VER, veraison; H, harvest.
- Figure 6
Effect of heat extremes on Cabernet Sauvignon grape harvest date (A to B) and yield (C to D). Differences in heat patterns during the growing season are represented by three clusters: Cluster 1 (POST-V, postveraison heat), Cluster 2 (PRE-V, preveraison heat), and Cluster 3 (Cool, cool seasons). In A and C, points represent averages for individual vineyard blocks and density plots show distributions for each cluster. Gray lines connect averages belonging to an individual vineyard block across cluster types. In B and D, small points represent changes for C1 and C2 compared to C3, and density plots show distributions by cluster. The large point represents the mean effect, and error bars represent 95% confidence intervals (CI). The red dotted line represents no effect. Averages and CIs by cluster are annotated in text boxes above the data. Across the board, p values denote statistical significance of cluster effects according to a linear mixed model (fixed effect: cluster; random effect: vineyard block ID) and letters denote differences across means by clusters according to Tukey’s adjusted post-hoc test (p ≤ 0.05). *** indicates statistically significant differences at p < 0.001. DOY, day of year.
- Figure 7
Effect of heat extremes on the concentration of key grape analytes in Cabernet Sauvignon fruit. Each analyte is reported in a separate panel and respective units are reported on each chart. Differences in heat patterns during the growing season are represented by three clusters: Cluster 1 (C1), Cluster 2 (C2), and Cluster 3 (C3). Points represent averages for individual vineyard blocks and density plots show distributions for each cluster. Across cluster types, gray lines connect averages belonging to an individual vineyard block. Across the board, p values denote statistical significance of cluster effects according to a linear mixed model (fixed effect: cluster; random effect: vineyard block ID) and letters denote differences across means by clusters according to Tukey’s adjusted post-hoc test (p ≤ 0.05). IBMP, 3-isobutyl-2-methoxypyrazine; TSS, total soluble solids; YAN, yeast assimilable nitrogen.
Tables
- Table 1
General description of the five vineyard sites used in this study. AVA, American Viticultural Area.
Site Location Geographical classification Average elevation (m) No. Cabernet Sauvignon blocks Average vineyard block size (ha) S1 38°38’N;
-122°27’ENapa Valley 340 30 4.62 S2 38°20’N;
-122°28’EMoon Mountain AVA 280 56 2.16 S3 38°27’N;
-122°18’EAtlas Peak AVA 455 218 1.18 S4 38°38’N;
-122°27’ENapa Valley 340 18 3.12 S5 38°21’N;
-122°16’ENapa Valley 114 33 2.20
Supplemental Table 1 List of summary features extracted from PRISM long-term weather observations. GDD, growing degree day; Tmax, maximum temperature; HWU, heatwave units; DOY, day of year; Tmean, mean temperature; Tmin, minimum temperature; VPD, vapor pressure deficit.
Supplemental Table 2 Statistical outputs of harvest date, yield, and fruit composition parameters by cluster (C1, cluster 1, postveraison heat; C2, cluster 2, preveraison heat; C3, cluster 3, cool season). P values of cluster effects were computed using linear mixed models (fixed effect: cluster; random effect: vineyard block ID). Data by cluster are presented as means ± 95% confidence intervals and different letters denote significant differences between means according to Tukey’s adjusted post-hoc test at p ≤ 0.05. Significant p values (i.e., ≤0.05) are marked in bold formatting. DOY, day of year; TSS, total soluble solids; YAN, yeast assimilable nitrogen; IBMP, 3-isobutyl-2-methoxypyrazine.
Supplemental Figure 1 Map of vineyard site (S1 to S5) locations and closest American Viticultural Areas (AVA).
Supplemental Figure 2 Relationships between observed phenological stages (BB, budbreak; FL, flowering; VER, veraison; H, harvest) and cumulative growing degree day (GDD) calculated from A) 1 January or B) 1 March. Cumulative GDD were calculated using PRISM daily data.
Supplemental Figure 3 Heatmap of scaled historical weather data submitted to clustering analysis. Columns represent combinations of a vineyard site (S1 to S5) and season (1981 to 2023), rows show normalized values (mean = 0, standard deviation = 1) for each weather feature extracted from historical series. Dendrograms group rows and columns using hierarchical clustering analysis. Gray boxes represent categories of features (generic weather and heat-related) and specify whether growth stages were based on calendar days or phenological stages.
Supplemental Figure 4 Comparison between daily temperature values from PRISM (gridded climate data) and a local weather station at one of the study sites (April to October): average (Tavg; A and B), maximum (Tmax; C and D), and minimum temperature (Tmin; E and F). In A, C, and D, lines connect daily temperature values and colors differentiate between data sources. B, D, and F show daily differences between PRISM and local station data.
Supplemental Figure 5 Hierarchical clustering analysis outputs by varying number of clusters from 2 to 10 clusters. The three-cluster solution was selected as the optimal number of clusters for further analysis.
Supplemental Figure 6 Hierarchical clustering analysis (HCA) optimization with clustering performance metrics. Three different indexes were assessed in response to varying number of clusters from 1 to 10: A) within sum of squares (WSS); B) silhouette width; C) gap statistic.
Supplemental Figure 7 Cluster validation using iterative bootstrap random forest classification with three clusters. Each panel represents the test error rate (TER) for a given number of iterations, from 50 to 500. Green points represent TER values for each iteration. The red dashed line represents the average TER across all iterations, with the value annotated in red at the top of each graph.
Supplemental Figure 8 Growing degree day (GDD) features summarized by weather cluster. A) Distribution of total GDD (April to October) by cluster; B) monthly distribution of GDD averages by cluster; C) GDD by cluster early and late in the growing season; and D) monthly distribution of GDD values by cluster. Colors differentiate between clusters, indicating seasons with different heat levels: Cluster 1, postveraison heat; Cluster 2, preveraison heat; Cluster 3, cool seasons. When present, points and error bars represent means ± standard error by cluster.
Supplemental Figure 9 Heatwave unit (HWU) features summarized by weather cluster. HWU was calculated as the cumulative deviation of Tmax -38°C, considering positive deviations only. A) Distribution of total HWU (April to October) by cluster; B) monthly distribution of HWU by cluster; C) HWU by cluster early (May to July) and late (August to October) in the growing season; D) summary of HWU by phenological stage (BB, budbreak; FL, flowering; VER, veraison; H, harvest); and E) monthly distribution of HWU values by cluster from May to October. Colors differentiate between clusters, indicating seasons with different heat levels: Cluster 1, postveraison; Cluster 2, preveraison heat; Cluster 3, cool seasons. When present, points and error bars represent means ± standard error (SE) by cluster. Ribbons represent SE values in line charts.
Supplemental Figure 10 Average temperature (Tavg) features summarized by weather cluster. A) Distribution of seasonal Tavg values by cluster (April to October); B) monthly distribution of Tavg values by cluster; C) Tavg values by cluster early (May to July) and late (August to October) in the growing season; and D) monthly distribution of Tavg values by cluster. Colors differentiate between clusters, indicating seasons with different heat levels: Cluster 1, postveraison heat; Cluster 2, preveraison heat; Cluster 3, cool seasons. When present, points and error bars represent means ± standard error (SE) by cluster. Ribbons represent SE values in line charts.
Supplemental Figure 11 Minimum temperature (Tmin) features summarized by weather cluster. A) Distribution of seasonal Tmin values by cluster (April to Oct); B) monthly distribution of Tmin values by cluster; C) Tmin values by cluster before the growing season (January to April) and early (May to July) and late (August to October) in the growing season; and D) monthly distribution of Tmin values by cluster. Colors differentiate between clusters, indicating seasons with different heat levels: Cluster 1, postveraison heat; Cluster 2, preveraison heat; Cluster 3, cool seasons. When present, points and error bars represent means ± standard error (SE) by cluster. Ribbons represent SE values in line charts.
Supplemental Figure 12 Changes in temperature by cluster according to phenological intervals (BB, budbreak; FL, flowering; VER, veraison; H, harvest). A) Minimum temperature (Tmin), B) average temperature (Tavg), and C) maximum temperature (Tmax). Points and ribbons represent means ± standard error. Colors differentiate between clusters, indicating seasons with different heat levels: Cluster 1, postveraison heat; Cluster 2, preveraison heat; Cluster 3, cool seasons.
Supplemental Figure 13 Rainfall features summarized by weather cluster. A) Distribution of seasonal rainfall by cluster (April to October); B) monthly distribution of rainfall by cluster; C) rainfall by cluster before the growing season (January to April) and early (May to July) and late (August to October) in the growing season; and D) rainfall by cluster according to phenological intervals (BB, budbreak; FL, flowering; VER, veraison; H, harvest). Colors differentiate between clusters, indicating seasons with different heat levels: Cluster 1, postveraison heat; Cluster 2, preveraison heat; Cluster 3, cool seasons. When present, points and error bars represent means ± standard error (SE) by cluster. Ribbons represent SE values in line charts.
Supplemental Figure 14 Exploratory analysis of harvest date (A) and yield (C) and cluster classification of seasons at the five sites (S1 to S5). In A and C, points represent data available at each site, with the number of observations by site annotated above the data distributions. In B, colors differentiate between clusters, indicating seasons with different heat levels: Cluster 1, postveraison heat; Cluster 2, preveraison heat; Cluster 3, cool seasons. DOY, day of year.
Supplemental Figure 15 Effect of weather clusters on Cabernet Sauvignon yield, according to vineyard age. The same analysis was repeated after classifying vineyard blocks as young (3 to 5 yr, left graph) or mature (>5 yr, right graph). Points represent average yield for individual blocks summarized by cluster. Colors differentiate between clusters: Cluster 1 (C1; POST-V, postveraison heat), Cluster 2 (C2; PRE-V, preveraison heat), and Cluster 3 (C3; Cool, cool season). Gray lines connect averages for the same vineyard block belonging to different clusters. Density plots represent distributions by cluster for each age group. Labels report cluster means and 95% confidence intervals (CI) by group, calculated using a linear mixed model where clusters were the fixed effect and vineyard blocks were the random effect on the model intercept. Different letters denote statistical differences between clusters for each age group according to Tukey’s adjusted multiple comparison post-hoc test with α ≤ 0.05.
Supplemental Figure 16 Exploratory analysis of grape analytes measured at five different sites. A to L represent single fruit composition parameters and points represent data available for each site (S1 to S5). The number of observations by site is annotated on top of data distributions in the first plot only. IBMP, 3-isobutyl-2-methoxypyrazine; TSS, total soluble solids; YAN, yeast assimilable nitrogen.
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