# Developing a GIS Model for Identifying Bear Corridors with Open-Source Data: The Romanian Context
## 2 Materials and Methods
Considering the increasingly frequent occurrences both near and inside the settlements located in the mountainous and hilly area of the Carpathians and Subcarpathians, the distance from the inner city of the localities was classified as follows: 0-100 m (10 points) 100-500 m (7 points), 500-1000 m (4 points), and over 1000 m (1 point). Given the almost three-fold increase in the number of bears nationwide, they travel great distances in search of new areas to inhabit, crossing important roadways. In fact, in the last five years, the number of bears hit by motor vehicles has increased dramatically. This phenomenon is exacerbated during the mating season, when the distances covered increase, as this exploratory behavior is used to find a mating partner. The scores have been awarded in accordance with the research carried out by the Institute of Forestry Research and Management (now the National Institute of Forestry Research and Development) over several decades. From an ethological point of view, the bear is a solitary animal, except during the mating season and rearing of cubs, preferring wooded areas of the order of thousands of hectares, with stands belonging to age classes V and VI, where it finds favorable conditions for habituation. At the same time, it is opportunistic when it comes to food sources, which leads to their presence in urban areas and inevitable human-bear conflicts, not infrequently resulting in fatalities. Each land use class can be a favorable or unfavorable factor for brown bear habitats and maintaining connectivity (Table 2). The most unfavorable category of factors includes all classes related to human development (built-up surface, reservoirs, transport infrastructure, agriculture, mining areas, etc. ), but also some natural surfaces (beaches, swamps). Considering the ecological needs of the studied species, the following categories of factors become favorable for the bear in terms of food resources and the possibility to move in safe conditions through the habitat [32]. Three main analytical spatial analysis stages based on GIS spatial analysis are identified in the development of the general model (database development, actual spatial analysis, and digital mapping of potential ecological corridors). A distinct stage consists of the validation stage based on field surveys and the collection of data on human-bear observations and conflicts from media data sources, derived from both officials and local authorities (Figure 3). \begin{table}
\begin{tabular}{c c} \hline \hline
**Scoring** & **Land-Use Classes** \\ \hline
10 points & 111—continuous urban areas, 112—Artificial areas, 121—Industrial, commercial and transport units, 122—Road and rail networks and associated lands, 124—Airports, 131—Mineral extraction sites, 132—Dump sites, 133—Construction sites, 141—Green urban areas, 142—Sport and leisure facilities, 331—Beaches, dunes, sands, 512—Water bodies, 242-Complex cultivation patterns, 211-non-irrigated agricultural land, 212—Permanently irrigated land, 213—Arabe land, 221—Vineyards, 411—Inland marshes; \\ \hline
8 points & 243—Land mainly occupied by agriculture with significant areas of natural vegetation, 231—pastures, 321—natural meadows, 322—Moors and heathland, 511—Water courses; \\ \hline
6 points & 222—Fruit trees and berry plantations; \\ \hline
5 points & 333—Sparsely vegetated areas; \\ \hline
4 points & 332—Bare rocks, 324—Transitional woodland-shrub; \\ \hline
3 points & 312—coniferous forests; \\ \hline
1 point & 313 mixed forests, 311—deciduous forests; \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Land-use scoring classes. Figure 3: Favorability for _Ursus arctos_ at the level of hunting grounds. The spatial analysis stage puts in the foreground the integrated management of specific digital databases by means of the weighted sum procedure to obtain the cost raster use in stage II.3 (Cost Connectivity from ArcGIS Software).