Resumen: The accumulation of fuel and the homogenization of the landscape in Mediterranean forests are leading to an increasingly hazardous behavior of wildfires, fostering larger, more intense, severe, and frequent wildfires. The onset of climate change is intensifying this behavior, fostering the occurrence of extreme forest fires threatening the persistence of forest communities.
In this study we present an assessment of the post-fire recovery potential of the most representative tree-forest communities affected by fire in Spain: Pinus halepensis, Pinus nigra, Pinus pinaster and Quercus ilex. A large database of field data collected during specific campaigns -carried out 25 years after the fire- is used in combination with remote sensing, forest inventory and geospatial data to build an empirical model capable of predicting the chances of recovery. The model, calibrated using Random Forest, combines information on burn severity (remote sensing estimates of the Composite Burn Index), local topography (slope and terrain aspect) and climatic data (mean values and trends of temperature and precipitation) to provide information on the degree of similarity (vegetation height, horizontal cover of the vegetation layer along vertical strata, aboveground biomass and species diversity) between the plots burned in the summer of 1994 and the unburned control.
Overall, only 33 out of the 131 burned plots could be considered as recovered, that is, reaching a similar state to unburned stands in neighboring areas. Our results suggest a primary role played by burn severity (the higher the severity the lower the probability of recovery), but strongly modulated by local topographic features (higher probability of recovery on steep north-facing slopes). In turn, increasingly warm and wetter conditions increased the chance of recovery. Idioma: Inglés DOI: 10.1016/j.foreco.2023.121587 Año: 2024 Publicado en: Forest Ecology and Management 552 (2024), 121587 [10 pp] ISSN: 0378-1127 Financiación: info:eu-repo/grantAgreement/ES/DGA/S51-23R Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2020-116556RA-I00 Financiación: info:eu-repo/grantAgreement/ES/MINECO/CGL2014-57013-C2-2-R Financiación: info:eu-repo/grantAgreement/ES/NextGenerationEU/MS-240621 Tipo y forma: Artículo (Versión definitiva) Área (Departamento): Área Geografía Física (Dpto. Geograf. Ordenac.Territ.) Área (Departamento): Área Análisis Geográfico Regi. (Dpto. Geograf. Ordenac.Territ.)