PROPOSAL OF A METHOD TO INCREASE THE NUMEROUSNESS OF BIOMETRICAL PARAMETERS USEFUL FOR WILDLIFE MANAGEMENT

The study of size (biometry) and shape (geometric morphometry) of bone structures in Ungulates are practices of extreme importance in the management of wildlife populations [1-2]. The collection of biometric data allows to characterize the populations, to evaluate their performances year after year, helping to estimate their status and trend of population features. Geometric morphometry, on the other side, plays an important role in the analysis and description of the shape of bone structures and related modifications. Unlike classical biometry, which involves the use of a calibre for measurements, geometric morphometry acquires, through software (e.g. GeoGebra), a series of reference points (landmarks) from digital photos, also providing a series of potentially linear measures, not taken by classic biometry, that could be used in assessing the relationship among body parameters and environmental features. However, the linear measurements recorded by GeoGebra represent distances between Cartesian coordinates. So, a conversion index is needed to be able to use this pool of extra-data [3-4]. We attempted to individuate the conversion index using 27 mandibles pertaining to Roe deer (Capreolus capreolus) of different age classes obtained by wildlife selective hunting in the Territorial Hunting Zone ATC-MC2 in Macerata Province (Central Italy). We focused the attention on two parameters: 1) Mandible Length (ML) which extends from the first incisive tooth to mandible angle for biometry, and from the first incisive tooth to the half of mandible angle for GeoGebra, and 2) Teeth Row Length (TRL) which extends from aboral limit of diastema to mesial limit of last molar tooth for both the measurement methods. The photos of the mandibles must be taken at the same time of the measurement with the calibre. The results showed that the two series of measurements are correlated (R2 > 0.8) and that the GeoGebra/Calibre ratio was 0,04. This coefficient could be used as a conversion index, allowing to obtain additional data derived from GeoGebra. Obtained additional data can be used to improve the database of parameters suitable to study the relationship with environmental features and, therefore, to assess the status of the Roe deer populations.