Mostrar el registro sencillo del ítem

dc.contributorFacultad de Ciencias Biologicas y Ambientaleses_ES
dc.contributor.authorFernández Guisuraga, José Manuel 
dc.contributor.authorSuárez-Seoane, Susana 
dc.contributor.authorFernandes, Paulo M.
dc.contributor.authorFernández García, Víctor 
dc.contributor.authorFernández Manso, Alfonso 
dc.contributor.authorQuintano Pastor, Carmen
dc.contributor.authorCalvo Galván, María Leonor 
dc.contributor.otherEcologiaes_ES
dc.date2022-03
dc.date.accessioned2022-03-22T12:41:01Z
dc.date.available2022-03-22T12:41:01Z
dc.identifier.issn2197-5620
dc.identifier.urihttp://hdl.handle.net/10612/14320
dc.description100022es_ES
dc.description.abstractBackground: The characterization of surface and canopy fuel loadings in fire-prone pine ecosystems is critical for understanding fire behavior and anticipating the most harmful ecological effects of fire. Nevertheless, the joint consideration of both overstory and understory strata in burn severity assessments is often dismissed. The aim of this work was to assess the role of total, overstory and understory pre-fire aboveground biomass (AGB), estimated by means of airborne Light Detection and Ranging (LiDAR) and Landsat data, as drivers of burn severity in a megafire occurred in a pine ecosystem dominated by Pinus pinaster Ait. in the western Mediterranean Basin. Results: Total and overstory AGB were more accurately estimated (R2 equal to 0.72 and 0.68, respectively) from LiDAR and spectral data than understory AGB (R2 ¼ 0.26). Density and height percentile LiDAR metrics for several strata were found to be important predictors of AGB. Burn severity responded markedly and non-linearly to total (R2 ¼ 0.60) and overstory (R2 ¼ 0.53) AGB, whereas the relationship with understory AGB was weaker (R2 ¼ 0.21). Nevertheless, the overstory plus understory AGB contribution led to the highest ability to predict burn severity (RMSE ¼ 122.46 in dNBR scale), instead of the joint consideration as total AGB (RMSE ¼ 158.41). Conclusions: This study novelty evaluated the potential of pre-fire AGB, as a vegetation biophysical property derived from LiDAR, spectral and field plot inventory data, for predicting burn severity, separating the contribution of the fuel loads in the understory and overstory strata in Pinus pinaster stands. The evidenced relationships between burn severity and pre-fire AGB distribution in Pinus pinaster stands would allow the implementation of threshold criteria to support decision making in fuel treatments designed to minimize crown fire hazard.es_ES
dc.languageenges_ES
dc.publisherSpringeres_ES
dc.subjectEcología. Medio ambientees_ES
dc.subjectIngeniería agrícolaes_ES
dc.subject.otherAboveground biomasses_ES
dc.subject.otherBurn severityes_ES
dc.subject.otherLandsates_ES
dc.subject.otherLiDARes_ES
dc.subject.otherPinus pinasteres_ES
dc.titlePre-fire aboveground biomass, estimated from LiDAR, spectral and field inventory data, as a major driver of burn severity in maritime pine (Pinus pinaster) ecosystemses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.identifier.doihttps://doi.org/10.1016/j.fecs.2022.100022
dc.description.peerreviewedSIes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.journal.titleForest Ecosystemses_ES
dc.volume.number9es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES
dc.subject.unesco2417 Biología Vegetal (Botánica)es_ES
dc.subject.unesco31 Ciencias Agrariases_ES
dc.subject.unesco25 Ciencias de la Tierra y del Espacioes_ES


Ficheros en el ítem

Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem