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

Producción Científica

Detalles Bibliográficos
Autores: Espinosa Prieto, Juncal, Rodríguez De Rivera, Óscar, Madrigal, Javier, Guijarro, Mercedes, Hernando, Carmen
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Universidad de Valladolid
Repositorio:UVaDOC. Repositorio Documental de la Universidad de Valladolid
OAI Identifier:oai:uvadoc.uva.es:10324/59011
Acceso en línea:https://doi.org/10.3390/f11091006
https://uvadoc.uva.es/handle/10324/59011
Access Level:acceso abierto
Palabra clave:Pinos
Pino negro
Pinos - España - Castilla La Mancha
Bosques y silvicultura
Vulnerabilidad
The Cuenca Mountains
Bayesian Modeling
3106 Ciencia Forestal
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spelling 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 standsEspinosa Prieto, JuncalRodríguez De Rivera, ÓscarMadrigal, JavierGuijarro, MercedesHernando, CarmenPinosPino negroPinos - España - Castilla La ManchaBosques y silviculturaVulnerabilidadThe Cuenca MountainsBayesian Modeling3106 Ciencia ForestalProducción CientíficaResearch 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.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)MDPI2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.3390/f11091006https://uvadoc.uva.es/handle/10324/59011reponame:UVaDOC. Repositorio Documental de la Universidad de Valladolidinstname:Universidad de ValladolidIngléshttps://www.mdpi.com/1999-4907/11/9/1006info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/oai:uvadoc.uva.es:10324/590112026-06-13T12:44:47Z
dc.title.none.fl_str_mv 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
title 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
spellingShingle 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
Espinosa Prieto, Juncal
Pinos
Pino negro
Pinos - España - Castilla La Mancha
Bosques y silvicultura
Vulnerabilidad
The Cuenca Mountains
Bayesian Modeling
3106 Ciencia Forestal
title_short 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_sort 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
dc.creator.none.fl_str_mv Espinosa Prieto, Juncal
Rodríguez De Rivera, Óscar
Madrigal, Javier
Guijarro, Mercedes
Hernando, Carmen
author Espinosa Prieto, Juncal
author_facet Espinosa Prieto, Juncal
Rodríguez De Rivera, Óscar
Madrigal, Javier
Guijarro, Mercedes
Hernando, Carmen
author_role author
author2 Rodríguez De Rivera, Óscar
Madrigal, Javier
Guijarro, Mercedes
Hernando, Carmen
author2_role author
author
author
author
dc.subject.none.fl_str_mv Pinos
Pino negro
Pinos - España - Castilla La Mancha
Bosques y silvicultura
Vulnerabilidad
The Cuenca Mountains
Bayesian Modeling
3106 Ciencia Forestal
topic Pinos
Pino negro
Pinos - España - Castilla La Mancha
Bosques y silvicultura
Vulnerabilidad
The Cuenca Mountains
Bayesian Modeling
3106 Ciencia Forestal
description Producción Científica
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.3390/f11091006
https://uvadoc.uva.es/handle/10324/59011
url https://doi.org/10.3390/f11091006
https://uvadoc.uva.es/handle/10324/59011
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://www.mdpi.com/1999-4907/11/9/1006
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:UVaDOC. Repositorio Documental de la Universidad de Valladolid
instname:Universidad de Valladolid
instname_str Universidad de Valladolid
reponame_str UVaDOC. Repositorio Documental de la Universidad de Valladolid
collection UVaDOC. Repositorio Documental de la Universidad de Valladolid
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300724

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