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This study introduced the application of concepts and methods from extreme value theory (EVT) to estimate the probability that daily minimum temperatures exceed springtime critical temperature thresholds for Pinot noir buds and young shoots as a function of springtime phenology. The springtime frost risk estimates were computed spatially for Pinot noir throughout the Willamette Valley (WV) American Viticultural Area (AVA) using a gridded dataset of historical daily minimum surface air temperature data. EVT-based springtime frost risk maps can inform vineyard-management operations by identifying those locations throughout a wine region with a low risk for any cold injury where remedial action is likely not necessary when there is a forecasted frost event. Frost risk estimates were computed for 1991–2021 and 1991–2022 to examine a potentially changed risk profile for springtime frost events throughout the WV AVA due to the April 2022 advective frost event. The April 2022 advective frost event influenced the risk profile throughout the AVA such that an event of its magnitude is now modelled to occur more frequently. The EVT-based risk analysis can be readily updated each year as new data become available. While spatially varying budbreak calculations facilitated computation of the spring frost risk estimates, the EVT approach profiled in this study does not necessarily depend on potentially uncertain predetermined budbreak date estimates. Gridded maps of extreme daily minimum temperature exceedances, reclassified relative to the springtime phenology critical temperature thresholds for Pinot noir, were readily combined with a ripening potential map to identify optimal areas for vineyard site selection throughout the WV AVA. When simultaneously evaluating Pinot noir ripening potential with springtime frost risk using historical data, the limiting factor for vineyard site selection throughout the WV AVA was frost risk, not ripening potential. The study approach is also applicable for other winegrape-growing regions, assessments of winter freeze risk and summertime heatwaves, and with non-gridded observed temperature datasets. [ABSTRACT FROM AUTHOR]

Atmospheric carbon dioxide (CO2) concentration has continuously increased since pre-industrial times and has currently reached an average growth rate of 2.3 ppm per year. For the majority of plant species elevated CO2 (eCO2) improves photosynthesis and thus plant biomass production. To investigate the effects of eCO2 on leaf physiology and morphological leaf characteristics two Vitis vinifera L. cultivars, Riesling and Cabernet Sauvignon, grown in the VineyardFACE (Free Air Carbon dioxide Enrichment) system were used. The VineyardFACE is located at Geisenheim, Rheingau comparing future atmospheric CO2-concentrations (eCO2, predicted for the mid-21st century) with current ambient CO2-conditions (aCO2). Experiments were operated under rain-fed conditions for two consecutive years (2015 and 2016). For both varieties and CO2 treatments, leaf gas exchange measurements were performed as well as measures of epidermal flavonoid (Flav) and leaf chlorophyll (Chl) indices by using a portable leaf clip. Furthermore, leaves were sampled for spectrophotometric analysis of the leaf pigments chlorophyll a (Chl a), chlorophyll b (Chl b) and carotenoid (Car). Additionally, leaf cross-sections were produced as permanent preparations to investigate morphological characteristics of the leaf structure. Both cultivars did not differ in leaf chlorophyll meter readings or leaf pigments between the two CO2 treatments while net assimilation was highly stimulated under elevated CO2 for both seasons. Differences found in leaf cross-sections were detected in palisade parenchyma and epidermal thickness of Cabernet Sauvignon under eCO2, whereas Riesling net assimilation increased by 40% under a 20% CO2 enrichment while remaining unaffected in different leaf layer thickness. The observed results within grapevine leaf tissues provide insights to seasonal adaptation strategies of grapevines under elevated CO2 concentrations predicted in future. [ABSTRACT FROM AUTHOR]