Page 104 - Panuccio2012

Southbound direction of colonization of Short-toed Snake Eagle

Table 1 - Environmental variables measured in each sampling units.

Category Variable

LAND USE Proportion of meadows and pastures
AVAILABILITY OF PREY Proportion of crops and orchards
Proportion of Forests
SPATIAL DISTRIBUTION OF Proportion of Shrubs
ENVIRONMENTAL ELEMENTS Proportion of urbanized areas
(LAND USE -PATCH ANALYSIS) Proportion of bare rocks
Proportion of wetlands
GEOMORPHOLOGY Number of reptile species (Snakes and Lizards)
GEOGHRAPHY Area Weighted Mean Shape Index
Mean Shape Index
Mean Perimeter-Area Ratio
Mean Patch Fractal Dimension
Area Weighted Mean Patch Fractal Dimension
Total Edge
Edge Density
Mean Patch Edge
Mean Patch Size
Number of Patches
Median Patch Size
Patch Size Coefficient of Variation
Patch Size Standard Deviation
Mean Altitude
Maximum Altitude
Minimum Altitude
Altitudinal Range (MAX – MIN)
Altitude Standard Deviation
Mean Altitude
Coefficient of Variation of Altitude
Longitude - X coordinate of cell’s centroide
Latitude - Y coordinate of cell’s centroide

Statistical models and procedure: after transformation), in addiction we generated
At first step we tested the correlation value of new variables by squaring those variables that did
variables within the categories inside the sampling not show linear relation with the presence of the
units in order to select variables to use in the species. Variables belonging to the same group
models. To do this we tested the normality of that was highly related were not used in the same
variables with Kolmogorov-Smirnov test, and if run of model evaluation.
any variables were not normally distributed we Method used to run Logistic Regression was the
proceeded with a transformation of data (square Enter method that uses all the variables selected
root, arcsine or natural logarithm depending on in the same run without stepwise procedure.
the variable). We used a logistic regression to test Model selection was made by the correct Akaike
which predictive variables affect the distribution Information Criterion (AICc) selecting the “best”
of Short-toed Snake Eagle in Italy, to perform this model from those being considered as the model
statistical analysis we used SPSS 13.0. In order to with the smallest value of AICc. (Manly et al.
verify which variables influence the presence of 2002).
Short-toed Snake Eagles we compared variables The AIC for a model is:
in squares with presence data (N=94) with the
same number of cells with absence data (n=94); AIC = -2{logc­(LM)}+2k
these cells were randomly selected among those in
which the species was not present according to the WthehenruemLbMeirs the Likelihood of the Model and k is
distribution reported in the atlas we consulted. of unknown parameters that must be
In the analysis were used only variables that estimated (Akaike 1973), while AICc is:
showed normal distribution (as they were or
AICc = -2{logc­(LM)}+2k{n/(n-k-1)}

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