Assessment of weather-related risk on chestnut productivity
Abstract. Due to its economic and nutritional value, the world production of chestnuts is increasing as new stands are being planted in various regions of the world. This work focuses on the relation between weather and annual chestnut production to model the role of weather, to assess the impacts of climate change and to identify appropriate locations for new groves. The exploratory analysis of chestnut production time series and the striking increase of production area have motivated the use for chestnut productivity. A large set of meteorological variables and remote sensing indices were computed and their role on chestnut productivity evaluated with composite and correlation analyses. These results allow for the identification of the variables cluster with a high correlation and impact on chestnut production. Then, different selection methods were used to develop multiple regression models able to explain a considerable fraction of productivity variance: (i) a simulation model (R2-value = 87%) based on the winter and summer temperature and on spring and summer precipitation variables; and, (ii) a model to predict yearly chestnut productivity (R2-value of 63%) with five months in advance, combining meteorological variables and NDVI. Goodness of fit statistic, cross validation and residual analysis demonstrate the model's quality, usefulness and consistency of obtained results.