Non-stationary Similarity in Trends of Seasonal and Monthly Rainfall in the Tuscan Apennine Alps (Middle Italy)

Climate change raises several questions about its effects on a wide range of environmental factors. Forests are not immune to these effects, as the variability of rainfall over time affects several aspects, such as growth rate, water stress, regeneration, species composition and, possibly, population displacement. Assuming that the response of a tree species to climatic variability is territorially homogeneous within a common general trend may be erroneous. In fact, although the agglomerative hierarchical clustering technique revealed a certain similarity between the four weather stations analyzed, always greater than 0.62, both the amount of precipitation, and the similarity in the various months between them change, creating problems for the adaptation of silver fir especially in the summer season. With this in mind, it was also very important to evaluate through Fourier analysis possible cycles within the time series, in order to understand possible fluctuations that may influence the adaptation of the tree species analyzed. The annual precipitation required for a silver fir is over 1500 mm, and only one of the four rain gauges, the one with the highest altitude (Abetone, 2449 mm), is well above this threshold, while two others are well below (La Verna and Vallombrosa). Moreover, all the rain gauges investigated due to climate change show a significant trend (alpha level 0.05) of decreasing rainfall, which could lead to limitations in the growth of silver fir. The greatest problems occur in summer where the season is often dry and rainfall averages less than 200 mm at La Verna and Vallombrosa. This analysis is innovative, firstly because it identifies the recurring climatic and growth periods for the forest species in question, as well as understanding the influence that climate change has on vegetation in neighboring weather stations and assessing possible adaptation problems. This research can facilitate the development of strategies that favor the maintenance of environments. Therefore, effective adaptive forest management should take into account the variability of climatic factors at the local forest scale, as general models could be misleading.