Use of GIS to predict potential distribution areas for wild boar (Sus scrofa Linnaeus 1758) in Mediterranean regions (SE Spain)

Identificador:  imarina:9285194

Handle: https://hdl.handle.net/20.500.11797/imarina9285194

Autors:  Belda, A; Zaragozi, B; Martinez-Perez, J E; Peiro, V; Ramon, A; Seva, E; Arques, J

Resum:
The wild boar is the target species selected for developing a GIS model of potential habitat for big game species, mainly using many GIS layers and kilometric abundance indices (KAI). We identify and weight environmental factors that determine the suitability for wild boar populations in a Mediterranean region, highly influenced by urban and agro-forestry activities. Marina Baja region (Spain) is selected to make a regional analysis. In the GIS modelling process, a suitability value is assigned to each pixel, which represents the habitat preference of the species. In the potential habitat model some variables were considered, the most important being land use. Voronoi polygons are generated by calculating the centroid of census transects located with GPS. These polygons are combined with the 'suitability' layer to obtain potentiality values, involving the displacement of the wild boar impedances within each Voronoi polygon. Finally, it performs the cartographic generalization process to obtain the resulting potential areas. We have obtained six potential areas that represent 39% of the region and they are best for the species. Natural vegetation is the most important landcover type in these areas. The cost-distance model is an efficient tool that gives good results in line with existing knowledge of species distribution. The model is constructed in order to explain, understand and predict the relations of analysed species using a determinate number of environmental variables. Thus, the use of GIS has allowed the information coming from different sources to be integrated in a simple way, allowing wild boar observations (KAI) to be combined with the cost-distance analysis result. © 2012 Copyright 2012 Unione Zoologica Italiana.