首页> 外文期刊>The Italian Journal of Zoology >Use of GIS to predict potential distribution areas for wild boar (Sus scrofa Linnaeus 1758) in Mediterranean regions (SE Spain).
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Use of GIS to predict potential distribution areas for wild boar (Sus scrofa Linnaeus 1758) in Mediterranean regions (SE Spain).

机译:利用GIS预测地中海地区(西班牙东南部)野猪( Sus scrofa Linnaeus 1758)的潜在分布区域。

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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.Digital Object Identifier http://dx.doi.org/10.1080/11250003.2011.631944
机译:野猪是选择的目标物种,主要用于开发大型猎物物种的潜在栖息地的GIS模型,主要使用许多GIS层和公里丰度指数(KAI)。我们确定并权衡环境因素,这些因素决定了受城市和农林业活动的强烈影响的地中海地区野猪种群的适宜性。选择了滨海巴哈地区(西班牙)进行区域分析。在GIS建模过程中,为每个像素分配一个适用性值,该值代表物种的栖息地偏好。在潜在的栖息地模型中,考虑了一些变量,其中最重要的是土地利用。 Voronoi多边形是通过计算GPS定位的人口普查样线的质心生成的。这些多边形与“适应性”层组合以获得电位值,其中涉及每个Voronoi多边形内野猪阻抗的位移。最后,它执行制图一般化过程以获得潜在的面积。我们已经获得了代表该地区39%的六个潜在区域,它们最适合该物种。天然植被是这些地区最重要的土地覆被类型。成本-距离模型是一种有效的工具,可以根据现有的物种分布知识提供良好的结果。建立该模型是为了使用确定数量的环境变量来解释,理解和预测所分析物种的关系。因此,使用GIS可以使来自不同来源的信息以一种简单的方式集成在一起,从而可以将野猪观测(KAI)与成本距离分析结果结合起来。数字对象标识符http://dx.doi .org / 10.1080 / 11250003.2011.631944

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