# Developing a GIS Model for Identifying Bear Corridors with Open-Source Data: The Romanian Context
## 2 Materials and Methods
The cost raster generated in ArcMap provided a spatial representation of these movement costs, enabling us to identify optimal ecological corridors and assess connectivity between favorable habitats. The choice of the weighting of the factors (using Weighted Overlay Tool from ArcGIS Software) that are the basis for obtaining the cost grid results from the fact that each factor influences the bear's movement in the study area in a different way. Thus, for the factors favoring an easier movement of the bear, high weighting values were chosen (20% for the slope, aspect, and proximity to the localities) and weighting with low values (10% for the curvature in the profile, land use, proximity to roads) for the factors influencing the bear's movement. The different importance in terms of movement behavior required the weighting of the spatial databases obtained as a result of the reclassification, according to their influence, and obtaining the digital support necessary to implement the cost connectivity function, the database in cost raster format with weighted values between 1 and 10. Thus, it was decided, for an easier implementation of the second stage of spatial analysis, to identify ecological corridors based on the cost connectivity function. For the implementation of the Cost Connectivity function, the cost grid obtained as a result of the implementation of the Weighted Overlay function was classified as a single valuation with values between 1 and 10 (1 representing maximum favorability at displacement and 10 representing minimum favorability at displacement). The second stage of the spatial analysis is the integration of previously obtained databases and the derivation of specific databases (Optimal Region Connection by ArcGIS Software) by means of the cost connectivity function and obtaining the main migration lanes. Their transition to digital mapping (the third stage of the general model) is based on the raster-vector conversion technique of digital databases and their mapping. The finality of the model and the appreciation of its degree of prediction is established through the direct validation part (stage IV), which is composed based on direct sources (identification in the field of locations with sporadic or regular occurrence of bears) and indirect sources (by consulting local media sources). The results of the current research highlight the analysis of all hunting grounds that have a high degree of favorability within the 27 counties in Romania where the bear population is present. Out of the total 2151 hunting grounds in Romania, the study area includes 1440. For each hunting area, the degree of favorability is determined based on the key (matrix) for the ecological diagnosis of bear lands [33], the analyzed territory totaling an area of 164,000 km\({}^{2}\). In order to determine the favorability of hunting areas, spatial analysis submodels were created that generate spatial output databases with information about the most important favorable and restrictive factors that make up the brown bear habitat (abiotic, biotic, and negative anthropogenic) [33], starting from open-source databases: the determined relief necessary for winter sleep; the thickness of the snow cover in the period March-May; the percentage of afforestation; forest composition; the distribution and composition of agricultural crops; the presence of fruit-bearing shrubs (raspberries, blackberries, brambles, rose hips); grazing; and roads and railways. The factors that influence the favorability and restrictiveness of the habitats for the studied species were incorporated into specific submodels for digital mapping, quantitative and qualitative analysis of suitable habitats, as well as the classification of territories at topographic scales by means of GIS spatial analysis [34; 35; 36; 37]. The probable identification of the bear's movement routes within the analyzed territory based on the implemented spatial analysis model requires the creation of a cost raster that highlights the different degrees of favorability when drawing such a route.