Modeling grapevine phenology at local scale in the context of climate change: An example in the Bordeaux area

Abstract

Predicting the key phenological stages in grapevine in response to increased temperatures due to climate change is essential to assess the potential risk of the growth cycle shifting to less suitable periods, such as frost periods or periods with unfavorable ripening conditions. This understanding is crucial for selecting grape varieties that are well-suited to specific production areas under current and future climatic conditions. Temperature and phenology at the local scale can be highly variable depending on the environmental context. Most studies have attempted to represent phenology at large scale, with few studies considering the local scale, critical for winegrower’s adaptation strategies. This research aimed to explore phenology modeling at the local scale by developing temperature-based models for budburst, flowering, veraison, and sugar concentration of 200 g/L for Vitis vinifera L. cv. Merlot in Saint-´ Emilion and surrounding appellations (Bordeaux, France). Fixed start dates versus phenophase based models, as well as simple versus more complex models, were tested and compared to current models in the literature. Selected phenological models were also compared under different warmer temperature scenarios. High-performance models were parameterized for all stages, showing few differences between approaches. However, the easy-to-use linear growing degree day models were slightly less accurate than the more complex curvilinear models, which are considered closer to plant development. Phenophase models performed better in predicting phenology with external validation data. The developed models outperformed existing models in literature, especially for the budburst stage. Little differences were observed in phenology projections among models with a 1ºC increase. In contrast, a 4 ◦ C increase showed significant differences between models, suggesting a need for deeper understanding of plant development under extreme temperatures. In addition to methodological findings on model selection, these results could help professionals optimize vineyard management and plant material adaptations to terroir and climate change