Valutazione del rischio legato ai cambiamenti climatici per il frumento duro

Recently, the availability of multi-model ensemble prediction methods has permitted to moving from the scenario-based approach to the risk-based approach in assessing the effects of climate change. This provides more useful information for decision-makers who need probability estimates to assess the seriousness of the projected impacts. In this study a probabilistic framework for evaluating the risk of durum wheat yield shortfall was exploited. An artificial neural network, trained to emulate outputs of a process-based crop growth model, was adopted to create yield response surfaces over which the probabilistic projections of future temperature and precipitation changes were overlaid to estimate probabilistic projections of future yields. The risk was calculated as the relative frequency of projected yield that not overcome the selected threshold. In contrast to previous studies suggesting that the beneficial effects of elevated atmospheric CO2 concentration over the next few decades would outweigh the detrimental effects of the early stages of climatic warming and drying, the results of our study are of more concern. Early in the next decades, the risk of reductions in yield below the long term yield average is likely (>66%). As the century progresses, the risk still increases, reaching its maximum by mid century (very likely). In the last decades, the risk slightly decreases as the effect of larger uncertainty in climate projections simulated for the end of the century.