The data source for this study was the Forest Inventory of Italy for the study area. It comprises 912 plots collected on the vertexes of a 3x3 km3 grid. The data were summarised for individual forest plots to calculate an Importance Value (IV) as a measure of abundance for each species according to the following formula:
Importance Value (x) = Density (x) + Dominance (x)
Density (x) = 100 NS (x) / NS (all species)
Dominance (x) = 100 BA (x) / BA (all species)
Where: x is one of the considered species, NS is the number of stems of a plot and BA is the basal area of the plot calculated using the diameter at breast height of each one of the stems. In monotypic stands, the IV could reach a maximum of 200.
Regression Tree Analysis (RTA) model was used to define the ecological niche of the tree species with respect to the chosen variables. RTA is based on a recursive data partitioning algorithm that splits the data into subsets based on a single best predictor variable. The algorithm proceeds by splitting these subsets using the remaining covariate values. The output is a tree with branches and terminal nodes. The predicted value at each terminal node is the average at that node, which can be considered as relatively homogeneous.
Tree diagrams produced by RTA analysis are shown as examples:
Fagus sylvatica - Eurosiberian
Quercus cerris - Sub-Mediterranean
Quercus ilex - Mediterranean
Fagus sylvatica is mainly found in areas with an average temperature of less than 24 °C for the hottest month. In areas above this climatic limit, the species can only be found in very small areas characterised by a high amount of summer precipitation (above 200 mm). In fact, in those areas, it is still possible to find remnant patches of Fagus sylvatica, residual of previous cycles of expansion of the species.
Quercus cerris, one of the most widespread species in the area, is influenced by the maximum temperature of the hottest month. In this case the species has a threshold of 27.8 °C, above which it can be found only in areas characterised by high winter precipitations (>260 mm), excluding the hyper humid areas (moisture index values >1).
is absent in areas characterised by very low winter temperature, where the average minimum temperature is <2 °C. The other important variables are: the presence of a geological substratum of carbonated rocks and summer aridity, since the species is well adapted to these conditions