气候变化领域集成服务门户(CCPortal): Environmental drivers of fire severity in extreme fire events that affect Mediterranean pine forest ecosystems

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DOI	10.1016/j.foreco.2018.10.051
	Environmental drivers of fire severity in extreme fire events that affect Mediterranean pine forest ecosystems
	García-Llamas P.; Suárez-Seoane S.; Taboada A.; Fernández-Manso A.; Quintano C.; Fernández-García V.; Fernández-Guisuraga J.M.; Marcos E.; Calvo L.
发表日期	2019
ISSN	0378-1127
起始页码	24
结束页码	32
卷号	433
英文摘要	The increasing occurrence of large and severe fires in Mediterranean forest ecosystems produces major ecological and socio-economic damage. In this study, we aim to identify the main environmental factors driving fire severity in extreme fire events in Pinus fire prone ecosystems, providing management recommendations for reducing fire effects. The study case was a megafire (11,891 ha) that occurred in a Mediterranean ecosystem dominated by Pinus pinaster Aiton in NW Spain. Fire severity was estimated on the basis of the differenced Normalized Burn Ratio from Landsat 7 ETM +, validated by the field Composite Burn Index. Model predictors included pre-fire vegetation greenness (normalized difference vegetation index and normalized difference water index), pre-fire vegetation structure (canopy cover and vertical complexity estimated from LiDAR), weather conditions (spring cumulative rainfall and mean temperature in August), fire history (fire-free interval) and physical variables (topographic complexity, actual evapotranspiration and water deficit). We applied the Random Forest machine learning algorithm to assess the influence of these environmental factors on fire severity. Models explained 42% of the variance using a parsimonious set of five predictors: NDWI, NDVI, time since the last fire, spring cumulative rainfall, and pre-fire vegetation vertical complexity. The results indicated that fire severity was mostly influenced by pre-fire vegetation greenness. Nevertheless, the effect of pre-fire vegetation greenness was strongly dependent on interactions with the pre-fire vertical structural arrangement of vegetation, fire history and weather conditions (i.e. cumulative rainfall over spring season). Models using only physical variables exhibited a notable association with fire severity. However, results suggested that the control exerted by the physical properties may be partially overcome by the availability and structural characteristics of fuel biomass. Furthermore, our findings highlighted the potential of low-density LiDAR for evaluating fuel structure throughout the coefficient of variation of heights. This study provides relevant keys for decision-making on pre-fire management such as fuel treatment, which help to reduce fire severity. © 2018 Elsevier B.V.
英文关键词	CBI; Fire history; Landsat; LiDAR; Physical properties; Vegetation structure; Weather conditions
语种	英语
scopus关键词	Decision making; Decision trees; Ecosystems; Fire hazards; Forestry; Fuels; Learning algorithms; Learning systems; Optical radar; Physical properties; Rain; Vegetation; Actual evapotranspiration; Fire history; LANDSAT; Mediterranean forest ecosystems; Normalized difference vegetation index; Normalized difference water index; Structural characteristics; Vegetation structure; Fires; algorithm; coniferous forest; environmental factor; extreme event; fire; fire history; forest ecosystem; index method; Landsat; Mediterranean environment; physical property; vegetation structure; weather; Decision Making; Ecosystems; Forestry; Fuels; Physical Properties; Rain; Spain; Pinus pinaster
来源期刊	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156305
作者单位	Biodiversity and Environmental Management Dpt., Faculty of Biological and Environmental Sciences, University of León, Campus de Vegazana s/n, León, 24071, Spain; Institute of Environmental Research (IMA), University of Léon, León, 24071, Spain; Agrarian Science and Engineering Department, Universidad of León, Av. Astorga s/n, Ponferrada, 24400, Spain; Electronic Technology Department, Sustainable Forest Management Research Institute, Universidad of Valladolid, Spanish National Institute for Agriculture and Food Research and Technology (INIA), C/Francisco Mendizábal s/n, Valladolid, 47014, Spain
推荐引用方式 GB/T 7714	García-Llamas P.,Suárez-Seoane S.,Taboada A.,et al. Environmental drivers of fire severity in extreme fire events that affect Mediterranean pine forest ecosystems[J],2019,433.
APA	García-Llamas P..,Suárez-Seoane S..,Taboada A..,Fernández-Manso A..,Quintano C..,...&Calvo L..(2019).Environmental drivers of fire severity in extreme fire events that affect Mediterranean pine forest ecosystems.Forest Ecology and Management,433.
MLA	García-Llamas P.,et al."Environmental drivers of fire severity in extreme fire events that affect Mediterranean pine forest ecosystems".Forest Ecology and Management 433(2019).