Quantifying economic losses from wildfires in black pine afforestations of northern Spain |
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| Institution: | 1. Agriculture and Forest Engineering Department (EAGROF), University of Lleida, Alcalde Rovira Roure 191, 25198 Lleida, Spain;2. IAFES Division, Euro-Mediterranean Center on Climate Change (CMCC), Via De Nicola 9, Sassari 07100, Italy;3. Division of Atmospheric Sciences, Desert Research Institute, 2215 Raggio Parkway Reno, 89512 Nevada, USA;4. Guarderío Forestal, Departamento de Desarrollo Rural y Administración Local, Gobierno de Navarra, Calle González Tablas 9, 31005 Pamplona, Navarra, Spain;5. Forest Science Center of Catalonia (CTFC), Pujada del Seminari s/n, 25280 Solsona, Catalonia, Spain;1. Department of Earth and Environmental Studies, Montclair State University, Montclair, NJ, 07043, United States;2. School of Forestry & Wildlife Sciences, Auburn University, Auburn, AL 36849, United States;3. Department of Forest Resources & Environmental Conservation, Virginia Polytechnic and State University, Blacksburg, VA 24061, United States;1. Agriculture and Forest Engineering Department (EAGROF), University of Lleida, Alcalde Rovira Roure 191, 25198 Lleida, Catalonia, Spain;3. National Research Council, Institute of Biometeorology (CNR-IBIMET), Regione Baldinca, 07100 Sassari, Italy;4. Euro-Mediterranean Center on Climate Change (CMCC), IAFES Division, Via Enrico De Nicola 9, 07100 Sassari, Italy;5. Oregon State University, College of Forestry, Forest Ecosystems & Society, 321 Richardson Hall, Corvallis, OR 97331, USA;6. Forest Sciences Centre of Catalonia, Carretera de Sant Llorenç de Morunys km 2, Solsona 25280, Catalonia, Spain |
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| Abstract: | We implemented a fire risk assessment framework that combines spatially-explicit burn probabilities, post-fire mortality models and public auction timber prices, to estimate expected economic losses from wildfires in 155 black pine stands covering about 450 ha in the Juslapeña Valley of central Navarra, northern Spain. A logit fire occurrence model was generated from observed historic fires to provide required fire ignition input data. Wildfire likelihood and intensity were estimated by modeling 50,000 fires with the minimum travel time algorithm (MTT) at 30 m resolution under 97th percentile fire weather conditions. Post-fire tree mortality due to burning fire intensity at different successional stages ranged from 0.67% in the latest stages to 9.22% in the earliest. Stands showed a wide range of potential economic losses, and intermediate successional stage stands presented the highest values, with about 124 € ha? 1 on average. A fire risk map of the target areas was provided for forest management and risk mitigation purposes at the individual stand level. The approach proposed in this work has a wide potential for decision support, policy making and risk mitigation in southern European commercial conifer forests where large wildfires are the main natural hazard. |
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