Indicadores de degradación del suelo en el parque forestal “Monte Gibralfaro” (Málaga, España).

dc.centroFacultad de Filosofía y Letrases_ES
dc.contributor.authorSillero-Medina, José Antonio
dc.contributor.authorMenjíbar-Romero, Mario
dc.contributor.authorGonzález Pérez, Javier
dc.contributor.authorRuiz-Sinoga, José Damián
dc.date.accessioned2025-10-21T10:43:32Z
dc.date.available2025-10-21T10:43:32Z
dc.date.issued2025
dc.departamentoGeografíaes_ES
dc.description.abstractSoil conservation in natural areas within urban environments is essential for promoting environmental sustainability. These zones act as vital green lungs, providing key ecosystem services. Effective soil management in urban areas enhances air quality, human well-being, and resilience to extreme climatic events, fostering a sustainable balance between urban growth and environmental conservation. In the context of climate change, particularly in Mediterranean regions, soil degradation poses a significant threat. Therefore, implementing sustainable strategies for assessing, conserving, restoring, and rewilding these spaces is crucial to promoting more resilient land management. This study focuses on an urban forest area in the city of Málaga (Spain)—Monte Gibralfaro—characterized by low biodiversity and a lack of territorial connectivity with the natural matrix, which increases its susceptibility to climate change effects. The research aims to conduct a detailed assessment of soil degradation in this site. Specifically, the study seeks to: (i) Determine soil erosion rates using the RUSLE model; (ii) Estimate organic carbon sequestration (SOC stock); and (iii) Evaluate soil quality through the relationship between organic carbon and clay content (SOC:Clay Ratio). To achieve these objectives, a total of 23 soil samples were collected, evenly distributed across the forest park, and analyzed in the laboratory to assess their main physical, chemical, and hydrological properties. Subsequently, the established indicators were calculated and mapped using innovative machine learning techniques, such as the Random Forest algorithm.es_ES
dc.identifier.urihttps://hdl.handle.net/10630/40370
dc.language.isospaes_ES
dc.relation.eventdate14-17 octubre 2025es_ES
dc.relation.eventplaceCácereses_ES
dc.relation.eventtitleXXIX CONGRESO DE LA ASOCIACIÓN ESPAÑOLA DE GEOGRAFÍA "DESAFÍOS DE LA GEOGRAFÍA ANTE EL CAMBIO GLOBAL"es_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSuelos - Conservaciónes_ES
dc.subjectCambio medioambiental globales_ES
dc.subjectEcosistemas - Gestiónes_ES
dc.subject.otherConservación del sueloes_ES
dc.subject.otherCambio climáticoes_ES
dc.subject.otherServicios ecosistémicoses_ES
dc.subject.otherRandom Forestes_ES
dc.titleIndicadores de degradación del suelo en el parque forestal “Monte Gibralfaro” (Málaga, España).es_ES
dc.typeconference outputes_ES
dspace.entity.typePublication
relation.isAuthorOfPublication6111f7d2-5155-4205-9561-a709d67b12ca
relation.isAuthorOfPublication7c5c24ed-60c5-40e2-b609-c277df719430
relation.isAuthorOfPublication.latestForDiscovery6111f7d2-5155-4205-9561-a709d67b12ca

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