Articles producció científica> Geografia

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

  • Identification data

    Identifier: imarina:9285194
  • Authors:

    Belda A
    Zaragozí B
    Martínez-Pérez JE
    Peiró V
    Ramón A
    Seva E
    Arques J
  • Others:

    Author, as appears in the article.: Belda A; Zaragozí B; Martínez-Pérez JE; Peiró V; Ramón A; Seva E; Arques J
    Department: Geografia
    URV's Author/s: Zaragozí Zaragozí, Benito Manuel
    Keywords: Sus scrofa Suidae Spatial distribution Spain Se spain and wild boar Prediction Population distribution Pig Mediterranean region Marina baja Map generalization Land use Land cover Habitat selection Gps Gis modelling Gis Environmental factor Distribution Comunidad valencia Cartography Alicante [comunidad valencia] Abundance index
    Abstract: 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.
    Thematic Areas: Zoology Medicina veterinaria Interdisciplinar Farmacia Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências agrárias i Biodiversidade Animal science and zoology
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: benito.zaragozi@urv.cat
    Author identifier: 0000-0003-2501-484X
    Record's date: 2024-07-20
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.tandfonline.com/doi/full/10.1080/11250003.2011.631944
    Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Italian Journal Of Zoology. 79 (2): 252-265
    APA: Belda A; Zaragozí B; Martínez-Pérez JE; Peiró V; Ramón A; Seva E; Arques J (2012). Use of GIS to predict potential distribution areas for wild boar (Sus scrofa Linnaeus 1758) in Mediterranean regions (SE Spain). Italian Journal Of Zoology, 79(2), 252-265. DOI: 10.1080/11250003.2011.631944
    Article's DOI: 10.1080/11250003.2011.631944
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2012
    Publication Type: Journal Publications
  • Keywords:

    Animal Science and Zoology,Zoology
    Sus scrofa
    Suidae
    Spatial distribution
    Spain
    Se spain and wild boar
    Prediction
    Population distribution
    Pig
    Mediterranean region
    Marina baja
    Map generalization
    Land use
    Land cover
    Habitat selection
    Gps
    Gis modelling
    Gis
    Environmental factor
    Distribution
    Comunidad valencia
    Cartography
    Alicante [comunidad valencia]
    Abundance index
    Zoology
    Medicina veterinaria
    Interdisciplinar
    Farmacia
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências agrárias i
    Biodiversidade
    Animal science and zoology
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