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Using MaxEnt algorithm to assess habitat suitability of a potential Iberian lynx population in central Iberian Peninsula


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Title: Using MaxEnt algorithm to assess habitat suitability of a potential Iberian lynx population in central Iberian Peninsula
Authors : Alfaya, Pedro
García Casanovas, Jorge
Lobón-Rovira, Javier
Matallanas, Beatriz
Cruz Varona, Alejandra
Arana, Pilar
Alonso, Germán
Keywords: Iberian lynxMaximum entropy modellingSpecies potential distributionEcologyLynx pardinus
Publisher: Akademiai Kiado
Citation: Pedro Alfaya; Jorge García Casanovas; Javier Lobón-Rovira; Beatriz Matallanas; Alejandra Cruz; Pilar Arana; Germán Alonso (2019). Using MaxEnt algorithm to assess habitat suitability of a potential Iberian lynx population in central Iberian Peninsula. Community Ecology 20(3): 266-276. Diciembre 2019. Online: 26 diciembre 2019. Akademiai Kiado, Hungría.
Abstract: Iberian lynx distribution is currently restricted to the south of the Iberian Peninsula. Nevertheless, there is evidence of the presence of several small groups in the peninsular centre that have been forgotten by management and conservation actions. In this research, we gathered evidences of Iberian lynx presence along 21 transects located in the southwest of the Madrid province. In these transects lynx DNA was identified in 47 scats, which scientifically proves the presence of the species in that location. Using these locations (presence-only data) we built a maximum entropy model (MaxEnt) to estimate the suitability of the study area for the species. Our results show the existence of an almost continuous area that is approximately 744 km2 that is suitable for the Iberian lynx. Seventy-eight percent of this area is within the Natura 2000 network and, therefore, it falls under regulations to preserve and restore habitat types, flora and fauna. This study shows the suitability of this territory has for the Iberian lynx.
Description: Versión en acceso abierto cumpliendo política de la editorial
URI: http://hdl.handle.net/10637/15170
Rights : http://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
ISSN: 1588-2756
Issue Date: 1-Dec-2019
Center : Universidad San Pablo-CEU.
Appears in Collections:Medicina





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