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Título
The Effects of Fire Severity on Vegetation Structural Complexity Assessed Using SAR Data Are Modulated by Plant Community Types in Mediterranean Fire-Prone Ecosystems
Autor
Facultad/Centro
Área de conocimiento
Título de la revista
Fire
Número de la revista
12
Cita Bibliográfica
Jimeno-Llorente, L., Marcos, E. & Fernández-Guisuraga, J. M. (2023). The effects of fire severity on vegetation structural complexity assessed using SAR data are modulated by plant community types in Mediterranean fire-prone ecosystems. Fire, 6(12), Article e450. https://doi.org/10.3390/FIRE6120450
Editorial
MDPI
Fecha
2023
Resumen
[EN] Vegetation structural complexity (VSC) plays an essential role in the functioning and the stability of fire-prone Mediterranean ecosystems. However, we currently lack knowledge about the effects of increasing fire severity on the VSC spatial variability, as modulated by the plant community type in complex post-fire landscapes. Accordingly, this study explored, for the first time, the effect of fire severity on the VSC of different Mediterranean plant communities one year after fire by leveraging field inventory and Sentinel-1 C-band synthetic aperture radar (SAR) data. The field-evaluated VSC retrieved in post-fire scenarios from Sentinel-1 γ0 VV and VH backscatter data featured high fit ( R2 = 0.878) and low predictive error (RMSE = 0.112). Wall-to-wall VSC estimates showed that plant community types strongly modulated the VSC response to increasing fire severity, with this response strongly linked to the regenerative strategies of the dominant species in the community. Moderate and high fire severities had a strong impact, one year after fire, on the VSC of broom shrublands and Scots pine forests, dominated by facultative and obligate seeder species, respectively. In contrast, the fire-induced impacts on VSC were not significantly different between low and moderate fire-severity scenarios in communities dominated by resprouter species, i.e., heathlands and Pyrenean oak forests
Materia
Palabras clave
Peer review
SI
ID proyecto
- info:eu-repo/grantAgreement/AEI/Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia/PID2022-139156OB-C21/ES/Susceptibilidad y vulnerabilidad del paisaje frente a megaincendios severos en el eje atlántico-mediterráneo: soluciones basadas en la naturaleza para una gestión proactiva/LANDSUSFIRE
- info:eu-repo/grantAgreement/MICIN//TED2021-130925B-I00/ES/Tecnologías disruptivas para la toma de decisiones en la gestión post-incendio basadas en las soluciones de computación en la nube/FIREMAP
- info:eu-repo/grantAgreement/Junta de Castilla y León//LE081P23/ES/IA Aplicación de técnicas de inteligencia artificial para evaluar el impacto del historial de uso del suelo en la vulnerabilidad de los ecosistemas de Castilla y León frente a incendios forestales extremos/IA-FIREXTCyL
- info:eu-repo/grantAgreement/Portuguese Foundation for Science and Technology//UIDB/04033/2020/PT
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