Spatial analysis of winter chilling accumulation in the current scenario of climate change in Spain. An application to some cherry cultivars.

In the current context of climate change, understanding the chilling requirements necessary for breaking dormancy and flowering in fruit trees is crucial for selecting suitable cultivars for different geographical locations. Recent data is essential for precise estimates regarding the area's suitability. Temperature data from 72 weather stations, spanning the period from 1975 to 2015, were analyzed using three models to assess winter chilling accumulation (Chilling Hours, Utah Model, and Positive Utah Model). This aimed to estimate the spatial pattern across Spain. The mapping of accumulated winter chilling was achieved through an integrated geographic information system (GIS), combined with multivariate geostatistics (regression-kriging) and algebraic mapping

As chilling accumulation is greatly influenced by the elevation of each location, elevation was utilized as a secondary variable to establish linear relationships between it and each chilling model. These relationships enhanced estimates at unsampled locations when incorporated into the regression-kriging algorithm, resulting in more accurate maps.

The findings indicated a strong correlation among the measurements from the three models, facilitating visualization of the spatial variability in accumulated winter chilling for each model. Additionally, when considering a high probability of meeting chilling requirements, quantile maps can be used instead of mean value maps, allowing for the integration of uncertainty.

Finally, the potential spatial distributions of three sweet cherry cultivars were mapped using these findings. This information aids in advising farmers on which cultivars are most appropriate for their geographical area and which regions of Spain are best suited for sweet cherry production, utilizing the most recent temporal series that incorporate climate change's impacts on climatic data.