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dc.contributor.authorEspinosa Prieto, Juncal 
dc.contributor.authorRodríguez De Rivera, Óscar
dc.contributor.authorMadrigal, Javier
dc.contributor.authorGuijarro, Mercedes
dc.contributor.authorHernando, Carmen
dc.date.accessioned2023-03-24T09:56:43Z
dc.date.available2023-03-24T09:56:43Z
dc.date.issued2020
dc.identifier.citationForests, 2020, Vol. 11, Nº. 9, 1006es
dc.identifier.issn1999-4907es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/59011
dc.descriptionProducción Científicaes
dc.description.abstractResearch Highlights: Litterfall biomass after prescribed burning (PB) is significantly influenced by meteorological variables, stand characteristics, and the fire prescription. Some of the fire-adaptive traits of the species under study (Pinus nigra and Pinus pinaster) mitigate the effects of PB on litterfall biomass. The Bayesian approach, tested here for the first time, was shown to be useful for analyzing the complex combination of variables influencing the effect of PB on litterfall. Background and Objectives: The aims of the study focused on explaining the influence of meteorological conditions after PB on litterfall biomass, to explore the potential influence of stand characteristic and tree traits that influence fire protection, and to assess the influence of fire prescription and fire behavior. Materials and Methods: An experimental factorial design including three treatments (control, spring, and autumn burning), each with three replicates, was established at two experimental sites (N = 18; 50 × 50 m2 plots). The methodology of the International Co-operative Program on Assessment and Monitoring of Air Pollution Effects on Forests (ICP forests) was applied and a Bayesian approach was used to construct a generalized linear mixed model. Results: Litterfall was mainly affected by the meteorological variables and also by the type of stand and the treatment. The effects of minimum bark thickness and the height of the first live branch were random. The maximum scorch height was not high enough to affect the litterfall. Time during which the temperature exceeded 60 °C (cambium and bark) did not have an important effect. Conclusions: Our findings demonstrated that meteorological conditions were the most significant variables affecting litterfall biomass, with snowy and stormy days having important effects. Significant effects of stand characteristics (mixed and pure stand) and fire prescription regime (spring and autumn PB) were shown. The trees were completely protected by a combination of low-intensity PB and fire-adaptive tree traits, which prevent direct and indirect effects on litterfall. Identification of important variables can help to improve PB and reduce the vulnerability of stands managed by this method.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherMDPIes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectPinoses
dc.subjectPino negroes
dc.subjectPinos - España - Castilla La Manchaes
dc.subjectBosques y silviculturaes
dc.subjectVulnerabilidades
dc.subject.classificationThe Cuenca Mountainses
dc.subject.classificationBayesian Modelinges
dc.titleUse of bayesian modeling to determine the effects of meteorological conditions, prescribed burn season, and tree characteristics on litterfall of Pinus nigra and Pinus pinaster standses
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2020 The Authorses
dc.identifier.doi10.3390/f11091006es
dc.relation.publisherversionhttps://www.mdpi.com/1999-4907/11/9/1006es
dc.identifier.publicationfirstpage1006es
dc.identifier.publicationissue9es
dc.identifier.publicationtitleForestses
dc.identifier.publicationvolume11es
dc.peerreviewedSIes
dc.description.projectUnión Europea y Fondo Europeo de Desarrollo Regional (FEDER) - (Projects RTA2014-00011-C06-01 y RTA2017-00042-C05-01)es
dc.description.projectInstituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) y Fondo Social Europeo - (Project FPI-SGIT 2015)es
dc.identifier.essn1999-4907es
dc.rightsAtribución 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco3106 Ciencia Forestales


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