Coincidence of temperature extremes and phenological events of grapevines

Abstract

A growing number of studies have highlighted the consequences of climate change on agriculture, including the impacts of climate extremes such as drought, heat waves and frost. The aim of this study was to assess the influence of temperature extremes on various phenological events of grapevine varieties in Southwest Switzerland (Leytron, Canton of Valais). We aimed to capture the occurrence of extreme events in specific years in various grapevine varieties and at different phenological phases to rank the varieties based on their sensitivity to temperature extremes and thus quantify their robustness. Phenological observations (1978–2018) of six Vitis vinifera varieties (Arvine, Chardonnay, Chasselas, Gamay, Pinot noir and Syrah) were subjected to event coincidence analysis. Extreme events were defined as values in the uppermost or lowermost percentiles of the timing of the phenophases and daily temperatures within a 30-day window before the phenophase event occurred. Significantly more extreme temperature and phenological events occurred in Leytron between 2003 and 2017 than in the earlier years, with the years 2007, 2011, 2014 and 2017 being remarkable in terms of the number of extreme coincidence events. Moreover, bud development and flowering experienced significantly more extreme coincidence events than other phenophases; however, the occurrence rate of extreme coincidence events was independent of the phenophase. Based on the total number of extreme events, the varieties did not differ in their responses to temperature extremes. Therefore, event coincidence analysis is an appropriate tool to quantify the occurrence of extreme events. The occurrence of extreme temperature events clearly affected the advancement of the timings of phenological events in various grapevines. However, there were no varietal differences in terms of response to extreme temperatures; thus, additional research is warranted to outline the best adaptation measures.