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    • Dpto. Producción Vegetal y Recursos Forestales
    • DEP57 - Artículos de revista
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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/59011

    Título
    Use of bayesian modeling to determine the effects of meteorological conditions, prescribed burn season, and tree characteristics on litterfall of Pinus nigra and Pinus pinaster stands
    Autor
    Espinosa Prieto, JuncalAutoridad UVA Orcid
    Rodríguez De Rivera, Óscar
    Madrigal, Javier
    Guijarro, Mercedes
    Hernando, Carmen
    Año del Documento
    2020
    Editorial
    MDPI
    Descripción
    Producción Científica
    Documento Fuente
    Forests, 2020, Vol. 11, Nº. 9, 1006
    Abstract
    Research 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.
    Materias (normalizadas)
    Pinos
    Pino negro
    Pinos - España - Castilla La Mancha
    Bosques y silvicultura
    Vulnerabilidad
    Materias Unesco
    3106 Ciencia Forestal
    Palabras Clave
    The Cuenca Mountains
    Bayesian Modeling
    ISSN
    1999-4907
    Revisión por pares
    SI
    DOI
    10.3390/f11091006
    Patrocinador
    Unión Europea y Fondo Europeo de Desarrollo Regional (FEDER) - (Projects RTA2014-00011-C06-01 y RTA2017-00042-C05-01)
    Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) y Fondo Social Europeo - (Project FPI-SGIT 2015)
    Version del Editor
    https://www.mdpi.com/1999-4907/11/9/1006
    Propietario de los Derechos
    © 2020 The Authors
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/59011
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
    Collections
    • DEP57 - Artículos de revista [101]
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