Register      Login
International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Predicting wildfire spread and behaviour in Mediterranean landscapes

Michele Salis A B I , Bachisio Arca C , Fermin Alcasena D , Margarita Arianoutsou E , Valentina Bacciu B , Pierpaolo Duce C , Beatriz Duguy F , Nikos Koutsias G , Giorgos Mallinis E , Ioannis Mitsopoulos E , José M. Moreno H , José Ramón Pérez H , Itziar R. Urbieta H , Fotios Xystrakis G , Gonzalo Zavala H and Donatella Spano A B
+ Author Affiliations
- Author Affiliations

A University of Sassari, Department of Science for Nature and Environmental Resources (DIPNET), Via Enrico De Nicola 9, 07100, Sassari, Italy.

B Euro-Mediterranean Center on Climate Change (CMCC), Impacts on Agriculture, Forests and Ecosystem Services (IAFES) Division, Via De Nicola 9, 07100, Sassari, Italy.

C National Research Council (CNR), Institute of Biometeorology (IBIMET), Traversa La Crucca 3, 07100, Sassari, Italy.

D University of Lleida, Agriculture and Forest Engineering Department (EAGROF), Alcalde Rovira Roure 191, 25198, Lleida, Spain.

E University of Athens, School of Sciences, Faculty of Biology, Department of Ecology and Systematics, Panepistimiopolis, 15784, Athens, Greece.

F University of Barcelona, Department of Evolutionary Biology, Ecology and Environmental Sciences, Avinguda Diagonal 643, 08028, Barcelona, Spain.

G University of Patras, Department of Environmental and Natural Resources Management, G. Seferi 2, 30100, Agrinio, Greece.

H University of Castilla–La Mancha, Department of Environmental Sciences, Avenida Carlos III, 45071, Toledo, Spain.

I Corresponding author. Email: miksalis@uniss.it

International Journal of Wildland Fire 25(10) 1015-1032 https://doi.org/10.1071/WF15081
Submitted: 7 April 2015  Accepted: 10 June 2016   Published: 2 August 2016

Abstract

The use of spatially explicit fire spread models to assess fire propagation and behaviour has several applications for fire management and research. We used the FARSITE simulator to predict the spread of a set of wildfires that occurred along an east–west gradient of the Euro-Mediterranean countries. The main purpose of this work was to evaluate the overall accuracy of the simulator and to quantify the effects of standard vs custom fuel models on fire simulation performance. We also analysed the effects of different fuel models and slope classes on the accuracy of FARSITE predictions. To run the simulations, several input layers describing each study area were acquired, and their effect on simulation outputs was analysed. Site-specific fuel models and canopy inputs were derived either from existing vegetation information and field sampling or through remote-sensing data. The custom fuel models produced an increase in simulation accuracy, and results were nearly unequivocal for all the case studies examined. We suggest that spatially explicit fire spread simulators and custom fuel models specifically developed for the heterogeneous landscapes of Mediterranean ecosystems can help improve fire hazard mapping and optimise fuel management practices across the Euro-Mediterranean region.

Additional keywords: ecosystems, fire management, fuel, modelling, propagation.


References

Ager AA, Vaillant NM, Finney MA (2010) A comparison of landscape fuel treatment strategies to mitigate wildland fire risk in the urban interface and preserve old forest structure. Forest Ecology and Management 259, 1556–1570.
A comparison of landscape fuel treatment strategies to mitigate wildland fire risk in the urban interface and preserve old forest structure.Crossref | GoogleScholarGoogle Scholar |

Ager AA, Vaillant N, Finney MA (2011) Integrating fire behavior models and geospatial analysis for wildland fire risk assessment and fuel management planning. Journal of Combustion 572452
Integrating fire behavior models and geospatial analysis for wildland fire risk assessment and fuel management planning.Crossref | GoogleScholarGoogle Scholar |

Ager AA, Preisler H, Arca B, Spano D, Salis M (2014) Wildfire risk estimation in the Mediterranean area. Environmetrics 25, 384–396.
Wildfire risk estimation in the Mediterranean area.Crossref | GoogleScholarGoogle Scholar |

Ager AA, Day MA, McHugh CW, Short K, Gilbertson-Day J, Finney MA, Calkin DE (2014) Wildfire exposure and fuel management on western US national forests. Journal of Environmental Management 145, 54–70.
Wildfire exposure and fuel management on western US national forests.Crossref | GoogleScholarGoogle Scholar | 24997402PubMed |

Agresti A (1996) ‘An introduction to categorical data analysis.’ (Wiley: New York)

Albini FA (1979) Spot fire distance from burning trees – a predictive model. USDA Forest Service, Intermountain Forest and Range Experiment Station, General Technical Report INT-GTR-56. (Ogden, UT)

Alcasena F, Salis M, Ager AA, Arca B, Molina D, Spano D (2015) Assessing fine-scale wildfire exposure for highly valued resources in a Mediterranean area. Environmental Management 55, 1200–1216.
Assessing fine-scale wildfire exposure for highly valued resources in a Mediterranean area.Crossref | GoogleScholarGoogle Scholar | 25613434PubMed |

Alcasena F, Salis M, Vega-Garcia C (2016) A fire modeling approach to assess wildfire exposure in central Navarra, Spain. European Journal of Forest Research 135, 87–107.
A fire modeling approach to assess wildfire exposure in central Navarra, Spain.Crossref | GoogleScholarGoogle Scholar |

Alexander ME, Cruz MG (2013) Are the applications of wildland fire behaviour models getting ahead of their evaluation again? Environmental Modelling & Software 41, 65–71.
Are the applications of wildland fire behaviour models getting ahead of their evaluation again?Crossref | GoogleScholarGoogle Scholar |

Anderson HE (1982) Aids to determining fuel models for estimating fire behaviour. USDA Forest Service, Intermountain Forest and Range Experiment Station, General Technical Report INT-GTR-122. (Ogden, UT)

Anderson WR, Cruz MG, Fernandes PM, Mccaw L, Vega J, Bradstock RA, Fogarty L, Gould J, McCarthy G, Marsden-Smedley JB, Matthews S, Mattingley G, Pearce H, van Wilgen B (2015) A generic, empirical-based model for predicting rate of fire spread in shrublands. International Journal of Wildland Fire 24, 443–460.
A generic, empirical-based model for predicting rate of fire spread in shrublands.Crossref | GoogleScholarGoogle Scholar |

Andrews PL (1986) BEHAVE: fire behavior prediction and fuel modeling subsystem – BURN subsystem, Part 1. USDA Forest Service, Intermountain Forest and Range Experiment Station General Technical Report INT-GTR-194. (Ogden, UT)

Arca B, Bacciu V, Duce P, Pellizzaro G, Salis M, Spano D (2007a) Use of FARSITE simulator to produce fire probability maps in a Mediterranean area. In ‘Proceedings of the 7th symposium on fire and forest meteorology’, Bar Harbor, ME, 23–25 October 2007. (Ed. American Meteorological Society) Available at https://ams.confex.com/ams/pdfpapers/127440.pdf [Verified 29 June 2016]

Arca B, Duce P, Laconi M, Pellizzaro G, Salis M, Spano D (2007b) Evaluation of FARSITE simulator in Mediterranean maquis. International Journal of Wildland Fire 16, 563–572.
Evaluation of FARSITE simulator in Mediterranean maquis.Crossref | GoogleScholarGoogle Scholar |

Arca B, Bacciu V, Pellizzaro G, Salis M, Ventura A, Duce P, Spano D, Brundu G (2009) Fuel model mapping by IKONOS imagery to support spatially explicit fire simulators. In ‘7th International workshop on advances in remote sensing and GIS applications in forest fire management towards an operational use of remote sensing in forest fire management’, 2–5 September 2009, Matera, Italy. (Eds E. Chuvieco, R Lasaponara) (Il Segno – Arti Grafiche, Societa’ Cooperativa Sociale: Potenza, Italy)

Arca B, Ventura A, Casula M, Pintus GV, Munoz O, Jahdi R, Bacciu V, Diana G, Pirisi AM, Gruppo GAUF, Salis M (2015) Evaluating the capabilities of foams in limiting fire spread. In ‘Book of abstracts of the second international conference on fire behaviour and risk’, Alghero, Italy, 26–29 May 2015. (Eds P Duce, D Spano, M Vannini, A Navarra) (Euro–Mediterranean Center on Climate Change: Sassari, Italy)

Arroyo LA, Pascual C, Manzanera JA (2008) Fire models and methods to map fuel types: the role of remote sensing. Forest Ecology and Management 256, 1239–1252.
Fire models and methods to map fuel types: the role of remote sensing.Crossref | GoogleScholarGoogle Scholar |

Ascoli D, Bovio G, Ceccato R, Marzano R (2007) Experimental analysis of the relationship between fire behaviour and biomass in fuel break management. Italian Journal of Forest and Mountain Environments 62, 369–383.
Experimental analysis of the relationship between fire behaviour and biomass in fuel break management.Crossref | GoogleScholarGoogle Scholar |

Bilgili E, Saglam B (2003) Fire behavior in maquis fuels in Turkey. Forest Ecology and Management 184, 201–207.
Fire behavior in maquis fuels in Turkey.Crossref | GoogleScholarGoogle Scholar |

Cai L, He HS, Wu Z, Lewis BL, Liang Y (2014) Development of standard fuel models in boreal forests of north-east China through calibration and validation. PLoS One 9, e94043
Development of standard fuel models in boreal forests of north-east China through calibration and validation.Crossref | GoogleScholarGoogle Scholar | 24714164PubMed |

Carmel Y, Paz S, Jahashan F, Shoshany M (2009) Assessing fire risk using Monte Carlo simulations of fire spread. Forest Ecology and Management 257, 370–377.
Assessing fire risk using Monte Carlo simulations of fire spread.Crossref | GoogleScholarGoogle Scholar |

Carvalho AC, Miranda AI, Borrego C (1997) Numerical simulation of wind field over complex terrain Transactions on Ecology and the Environment 13, 273–282. . [Verified 5 July 2016]http://www.witpress.com/Secure/elibrary/papers/MMEP97/MMEP97027FU.pdf

Cheyette D, Rupp TS, Rodman S (2008) Developing fire behavior fuel models for the wildland–urban interface in Anchorage, Alaska. Western Journal of Applied Forestry 23, 149–155.

Congalton RG (1991) A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment 37, 35–46.
A review of assessing the accuracy of classifications of remotely sensed data.Crossref | GoogleScholarGoogle Scholar |

Cruz MG, Fernandes PM (2008) Development of fuel models for fire behaviour prediction in maritime pine (Pinus pinaster Ait.) stands. International Journal of Wildland Fire 17, 194–204.
Development of fuel models for fire behaviour prediction in maritime pine (Pinus pinaster Ait.) stands.Crossref | GoogleScholarGoogle Scholar |

Cruz MG, Viegas DX (1998) Fire behaviour in some common central Portugal fuel complexes: evaluation of fire behaviour models performance. In ‘Proceedings of the third international conference on forest fire research/14th fire and forest meteorology conference’, Luso, 16–20 November 1998. (Ed. DX Viegas) pp. 859–875. (ADAI, University of Coimbra: Coimbra)

Curt T, Borgniet L, Bouillon C (2013) Wildfire frequency varies with the size and shape of fuel types in south-eastern France: implications for environmental management. Journal of Environmental Management 117, 150–161.
Wildfire frequency varies with the size and shape of fuel types in south-eastern France: implications for environmental management.Crossref | GoogleScholarGoogle Scholar | 23369835PubMed |

De Luis M, Baeza MJ, Raventós J, Hidalgo JCG (2004) Fuel characteristics and fire behavior in mature Mediterranean gorse shrublands. International Journal of Wildland Fire 13, 79–87.
Fuel characteristics and fire behavior in mature Mediterranean gorse shrublands.Crossref | GoogleScholarGoogle Scholar |

Deeming JE, Lancaster JW, Fosberg MA, Furman RW, Schroeder MJ (1972) The National Fire Danger Rating System. USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, Research Paper RM-84. (Fort Collins, CO)

Diana G, Salis M, Farris G, Farris O, Licheri F, Musina G, Peluffo L, Orotelli S, Pirisi AM, Bacciu V, Casula F, Fois C, Sirca C, Spano D (2011) Prescribed burning and tactical fires potential effects on fire risk mitigation: the Sardinian experience. In ‘Proceedings of the international conference on fire behaviour and risk’, Alghero, Italy, 4–6 October 2011. (Eds D Spano, P Duce) (TAS Tipografi Associati Sassari: Sassari, Italy)

Dimitrakopoulos AP (2001) A statistical classification of Mediterranean species based on their flammability components. International Journal of Wildland Fire 10, 113–118.
A statistical classification of Mediterranean species based on their flammability components.Crossref | GoogleScholarGoogle Scholar |

Dimitrakopoulos AP (2002) Mediterranean fuel models and potential fire behavior in Greece. International Journal of Wildland Fire 11, 127–130.
Mediterranean fuel models and potential fire behavior in Greece.Crossref | GoogleScholarGoogle Scholar |

Dimitrakopoulos AP, Panov PI (2001) Pyric properties of some dominant Mediterranean vegetation species. International Journal of Wildland Fire 10, 23–27.
Pyric properties of some dominant Mediterranean vegetation species.Crossref | GoogleScholarGoogle Scholar |

Dimitrakopoulos AP, Gogi C, Stamatelos G, Mitsopoulos I (2011) Statistical analysis of fire environment of large forest fires (>1000 ha) in Greece. Polish Journal of Environmental Studies 20, 327–332.

Duguy B, Vallejo VR (2008) Land-use and fire history effects on post-fire vegetation dynamics in eastern Spain. Journal of Vegetation Science 19, 97–108.
Land-use and fire history effects on post-fire vegetation dynamics in eastern Spain.Crossref | GoogleScholarGoogle Scholar |

Duguy B, Alloza JA, Röder A, Vallejo R, Pastor F (2007) Modeling the effects of landscape fuel treatments on fire growth and behaviour in a Mediterranean landscape (eastern Spain). International Journal of Wildland Fire 16, 619–632.
Modeling the effects of landscape fuel treatments on fire growth and behaviour in a Mediterranean landscape (eastern Spain).Crossref | GoogleScholarGoogle Scholar |

Duguy B, Paula S, Pausas JG, Alloza JA, Gimeno T, Vallejo VR (2013) Effects of climate and extreme events on wildfire regime and their ecological impacts. In ‘Regional assessment of climate change in the Mediterranean, Vol. 2: Agriculture, forests and ecosystem services and people’. Advances in Global Change Research (Eds A Navarra, L Tubiana L) pp. 101–134. (Springer Science+Business Media: Dordrecht, the Netherlands)

EEA (2002) CORINE land cover update 2000 – technical guidelines. European Environment Agency, Technical Report 89. (European Environment Agency: Copenhagen, Denmark). Available at http://land.copernicus.eu/user-corner/technical-library/techrep89.pdf [Verified 5 July 2016].

Fernandes PAM (2001) Fire spread prediction in shrub fuels in Portugal. Forest Ecology and Management 144, 67–74.
Fire spread prediction in shrub fuels in Portugal.Crossref | GoogleScholarGoogle Scholar |

Fernandes PM, Catchpole WR, Rego FC (2000) Shrubland fire behaviour modelling with microplot data. Canadian Journal of Forest Research 30, 889–899.
Shrubland fire behaviour modelling with microplot data.Crossref | GoogleScholarGoogle Scholar |

Filippi J-B, Morandini F, Balbi JH, Hill DR (2010) Discrete event front-tracking simulation of a physical fire-spread model. Simulation 86, 629–646.
Discrete event front-tracking simulation of a physical fire-spread model.Crossref | GoogleScholarGoogle Scholar |

Filippi J-B, Mallet V, Nader B (2014) Representation and evaluation of wildfire propagation simulations. International Journal of Wildland Fire 23, 46–57.
Representation and evaluation of wildfire propagation simulations.Crossref | GoogleScholarGoogle Scholar |

Finney MA (1998) FARSITE: Fire Area Simulator – model development and evaluation. USDA Forest Service, Rocky Mountain Research Station, Research Paper RMRS-RP-4. (Fort Collins, CO)

Finney MA (2002) Fire growth using minimum travel time methods. Canadian Journal of Forest Research 32, 1420–1424.
Fire growth using minimum travel time methods.Crossref | GoogleScholarGoogle Scholar |

Finney MA, Bradshaw L, Butler B (2009) Delivery and demonstration of surface wind simulation tool for fire management decision support. Joint Fire Science Program Research Project Reports, Paper 109. Available at http://digitalcommons.unl.edu/jfspresearch/109 [Verified 29 June 2016]

Foody GM (2004) Thematic map comparison: evaluating the statistical significance of differences in classification accuracy. Photogrammetric Engineering and Remote Sensing 70, 627–633.
Thematic map comparison: evaluating the statistical significance of differences in classification accuracy.Crossref | GoogleScholarGoogle Scholar |

Forthofer JM (2007) Modeling wind in complex terrain for use in fire spread prediction. MSc Thesis, Colorado State University, Fort Collins, CO.

Forthofer JM, Butler BW (2007) Differences in simulated fire spread over Askervein Hill using two advanced wind models and a traditional uniform wind field. In ‘The fire environment – innovations, management, and policy; conference proceedings’, 26–30 March 2007, Destin, FL. (Eds BW Butler, W Cook) USDA Forest Service, Rocky Mountain Research Station, Proceedings RMRS-P-46CD, pp. 123–127. (Fort Collins, CO)

Forthofer JM, Butler BW, Wagenbrenner NS (2014) A comparison of three approaches for simulating fine-scale surface winds in support of wildland fire management. Part I. Model formulation and comparison against measurements. International Journal of Wildland Fire 23, 969–981.
A comparison of three approaches for simulating fine-scale surface winds in support of wildland fire management. Part I. Model formulation and comparison against measurements.Crossref | GoogleScholarGoogle Scholar |

Forthofer JM, Butler BW, McHugh CW, Finney MA, Bradshaw LS, Stratton RD, Shannon KS, Wagenbrenner NS (2014) A comparison of three approaches for simulating fine-scale surface winds in support of wildland fire management. Part II. An exploratory study of the effect of simulated winds on fire growth simulations. International Journal of Wildland Fire 23, 982–994.
A comparison of three approaches for simulating fine-scale surface winds in support of wildland fire management. Part II. An exploratory study of the effect of simulated winds on fire growth simulations.Crossref | GoogleScholarGoogle Scholar |

Fujioka FM (2002) A new method for the analysis of fire spread modeling errors. International Journal of Wildland Fire 11, 193–203.
A new method for the analysis of fire spread modeling errors.Crossref | GoogleScholarGoogle Scholar |

Ganteaume A, Jappiot M (2013) What causes large fires in southern France. Forest Ecology and Management 294, 76–85.
What causes large fires in southern France.Crossref | GoogleScholarGoogle Scholar |

Hollingsworth LT, Kurth LL, Parresol BR, Ottmar RD, Prichard SJ (2012) A comparison of geospatially modeled fire behavior and fire management utility of three data sources in the south-eastern United States. Forest Ecology and Management 273, 43–49.
A comparison of geospatially modeled fire behavior and fire management utility of three data sources in the south-eastern United States.Crossref | GoogleScholarGoogle Scholar |

INFC (2005) Inventario nazionale delle foreste e dei serbatoi forestali di carbonio. Inventario Nazionale delle Foreste e dei Serbatoi Forestali di Carbonio. Ministero delle Politiche Agricole Alimentari e Forestali, Ispettorato Generale – Corpo Forestale dello Stato. Consiglio per la Ricerca e Sperimentazione in Agricoltura Unità di ricerca per il Monitoraggio e la Pianificazione Forestale (CRA-MPF). Available at http://www.sian.it/inventarioforestale/jsp/condizioni_uso.jsp [Verified 29 June 2016]

Jahdi R, Salis M, Darvishsefat AA, Mostafavi MA, Alcasena F, Etemad V, Lozano O, Spano D (2015) Calibration of FARSITE simulator in northern Iranian forests. Natural Hazards and Earth System Sciences 15, 443–459.
Calibration of FARSITE simulator in northern Iranian forests.Crossref | GoogleScholarGoogle Scholar |

Jahdi R, Salis M, Darvishsefat AA, Alcasena FJ, Mostafavi MA, Etemad V, Lozano OM, Spano D (2016) Evaluating fire modelling systems in recent wildfires of the Golestan National Park, Iran. Forestry 89, 136–149.
Evaluating fire modelling systems in recent wildfires of the Golestan National Park, Iran.Crossref | GoogleScholarGoogle Scholar |

Kalabokidis K, Palaiologou P, Gerasopoulos E, Giannakopoulos C, Kostopoulou E, Zerefos C (2015) Effect of climate change projections on forest fire behavior and values-at-risk in south-western Greece. Forests 6, 2214–2240.
Effect of climate change projections on forest fire behavior and values-at-risk in south-western Greece.Crossref | GoogleScholarGoogle Scholar |

Keane RE, Burgan R, van Wagtendonk J (2001) Mapping wildland fuels for fire management across multiple scales: integrating remote sensing, GIS, and biophysical modeling. International Journal of Wildland Fire 10, 301–319.
Mapping wildland fuels for fire management across multiple scales: integrating remote sensing, GIS, and biophysical modeling.Crossref | GoogleScholarGoogle Scholar |

Koutsias N, Arianoutsou M, Kallimanis AS, Mallinis G, Halley JM, Dimopoulos P (2012) Where did the fires burn in Peloponnisos, Greece the summer of 2007? Evidence for a synergy of fuel and weather. Agricultural and Forest Meteorology 156, 41–53.
Where did the fires burn in Peloponnisos, Greece the summer of 2007? Evidence for a synergy of fuel and weather.Crossref | GoogleScholarGoogle Scholar |

Linn R, Reisner J, Colman JJ, Winterkamp J (2002) Studying wildfire behavior using FIRETEC. International Journal of Wildland Fire 11, 233–246.
Studying wildfire behavior using FIRETEC.Crossref | GoogleScholarGoogle Scholar |

Linn R, Winterkamp J, Edminster C, Colman JJ, Smith WS (2007) Coupled influences of topography and wind on wildland fire behaviour. International Journal of Wildland Fire 16, 183–195.
Coupled influences of topography and wind on wildland fire behaviour.Crossref | GoogleScholarGoogle Scholar |

Massaiu A (1999) Il fuoco come tecnica di gestione territoriale. Applicazione di fuoco prescritto in Sardegna. BSc thesis, University of Florence, Italy. Available at Univeristy of Florence library.

Miller C, Ager AA (2013) A review of recent advances in risk analysis for wildfire management. International Journal of Wildland Fire 22, 1–14.
A review of recent advances in risk analysis for wildfire management.Crossref | GoogleScholarGoogle Scholar |

Miller JD, Yool SR (2002) Modeling fire in semi-desert grassland/oak woodland: the spatial implications. Ecological Modelling 153, 229–245.
Modeling fire in semi-desert grassland/oak woodland: the spatial implications.Crossref | GoogleScholarGoogle Scholar |

Milne GJ, Kelso JK, Mellor D, Murphy ME (2014) Evaluating wildfire simulators using historical fire data. In ‘Advances in forest fire research’. (Ed. DX Viegas) pp. 1366–1375. (Imprensa da Universidade de Coimbra: Coimbra, Portugal)10.14195/978-989-26-0884-6_150

Ministerio de Agricultura (2007) Tercer Inventario Forestal Nacional (IFN3). Available at http://www.magrama.gob.es/es/biodiversidad/servicios/banco-datos-naturaleza/informacion-disponible/ifn3.aspx [Verified 5 July 2016]

Mitsopoulos I, Mallinis G, Arianoutsou M (2015) Wildfire risk assessment in a typical Mediterranean wildland–urban interface of Greece. Environmental Management 55, 900–915.
Wildfire risk assessment in a typical Mediterranean wildland–urban interface of Greece.Crossref | GoogleScholarGoogle Scholar | 25537157PubMed |

Mitsopoulos ID, Dimitrakopoulos AP (2014) Estimation of canopy fuel characteristics of Aleppo pine (Pinus halepensis Mill.) based on common stand parameters. European Journal of Forest Research 133, 73–79.
Estimation of canopy fuel characteristics of Aleppo pine (Pinus halepensis Mill.) based on common stand parameters.Crossref | GoogleScholarGoogle Scholar |

Moreira F, Viedma O, Arianoutsou M, Curt T, Koutsias N, Rigolot E, Barbati A, Corona P, Vaz P, Xanthopoulos G, Mouillot F, Bilgili E (2011) Landscape–wildfire interactions in southern Europe: implications for landscape management. Journal of Environmental Management 92, 2389–2402.
Landscape–wildfire interactions in southern Europe: implications for landscape management.Crossref | GoogleScholarGoogle Scholar | 21741757PubMed |

Moreno JM, Viedma O, Zavala G, Luna B (2011) Landscape variables influencing forest fires in central Spain. International Journal of Wildland Fire 20, 678–689.
Landscape variables influencing forest fires in central Spain.Crossref | GoogleScholarGoogle Scholar |

Mutlu M, Popescu SC, Zhao K (2008) Sensitivity analysis of fire behavior modeling with LIDAR-derived surface fuel maps. Forest Ecology and Management 256, 289–294.
Sensitivity analysis of fire behavior modeling with LIDAR-derived surface fuel maps.Crossref | GoogleScholarGoogle Scholar |

Papadopoulos GD, Pavlidou FN (2011) A comparative review on wildfire simulators. IEEE Systems Journal 5, 233–243.
A comparative review on wildfire simulators.Crossref | GoogleScholarGoogle Scholar |

Pastor E, Zarate L, Planas E, Arnaldos J (2003) Mathematical models and calculation systems for the study of wildland fire behaviour. Progress in Energy and Combustion Science 29, 139–153.
Mathematical models and calculation systems for the study of wildland fire behaviour.Crossref | GoogleScholarGoogle Scholar |

Pausas JG, Fernández-Muñoz S (2012) Fire regime changes in the western Mediterranean Basin: from fuel-limited to drought-driven fire regime. Climatic Change 110, 215–226.
Fire regime changes in the western Mediterranean Basin: from fuel-limited to drought-driven fire regime.Crossref | GoogleScholarGoogle Scholar |

Pausas JG, Vallejo R (1999) The role of fire in European Mediterranean ecosystems. In ‘Remote sensing of large wildfires in the European Mediterranean basin’. (Ed. E Chuvieco) pp. 3–16. (Springer: Berlin).

Paz S, Carmel Y, Jahshan F, Shoshany M (2011) Post-fire analysis of pre-fire mapping of fire risk: a recent case study from Mt Carmel (Israel). Forest Ecology and Management 262, 1184–1188.
Post-fire analysis of pre-fire mapping of fire risk: a recent case study from Mt Carmel (Israel).Crossref | GoogleScholarGoogle Scholar |

Pellizzaro G, Duce P, Ventura A, Zara P (2007) Seasonal variations of live moisture content and ignitability in shrubs of the Mediterranean Basin. International Journal of Wildland Fire 16, 633–641.
Seasonal variations of live moisture content and ignitability in shrubs of the Mediterranean Basin.Crossref | GoogleScholarGoogle Scholar |

Pereira MG, Trigo RM, da Camara CC, Pereira JMC, Leite SM (2005) Synoptic patterns associated with large summer forest fires in Portugal. Agricultural and Forest Meteorology 129, 11–25.
Synoptic patterns associated with large summer forest fires in Portugal.Crossref | GoogleScholarGoogle Scholar |

Perry GLW (1998) Current approaches to modelling the spread of wildland fire: a review. Progress in Physical Geography 22, 222–245.
Current approaches to modelling the spread of wildland fire: a review.Crossref | GoogleScholarGoogle Scholar |

Raposo JR, Cabiddu S, Viegas DX, Salis M, Sharples J (2015) Experimental analysis of fire spread across a two-dimensional ridge under wind conditions. International Journal of Wildland Fire
Experimental analysis of fire spread across a two-dimensional ridge under wind conditions.Crossref | GoogleScholarGoogle Scholar |

Rodríguez y Silva F, Molina-Martínez JR (2012) Modeling Mediterranean forest fuels by integrating field data and mapping tools. European Journal of Forest Research 131, 571–582.
Modeling Mediterranean forest fuels by integrating field data and mapping tools.Crossref | GoogleScholarGoogle Scholar |

Rothermel RC (1972) A mathematical model for predicting fire spread in wildland fuels. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Paper INT-115 (Ogden, UT).

Safford HD, Stevens JT, Merriam K, Meyer MD, Latimer AM (2012) Fuel treatment effectiveness in California yellow pine and mixed-conifer forests. Forest Ecology and Management 274, 17–28.
Fuel treatment effectiveness in California yellow pine and mixed-conifer forests.Crossref | GoogleScholarGoogle Scholar |

Sağlam B, Küçük Ö, Bilgili E, Dinç Durmaz B, Baysal I (2007) Preliminary results of fire behavior in maquis fuels under varying weather and slope conditions in Turkey. In ‘The fire environment – innovations, management, and policy; conference proceedings’, 26–30 March 2007, Destin, FL. (Comps BW Butler, W Cook). USDA Forest Service, Rocky Mountain Research Station, Proceedings RMRS-P-46CD, pp. 249– 254. (CD-ROM) (Fort Collins, CO)

Sağlam B, Küçük Ö, Bilgili E, Dinç Durmaz B, Baysal I (2008) Estimating fuel biomass of some shrub (maquis) species in Turkey. Turkish Journal of Agriculture and Forestry 32, 349–356.

Salis M (2008) Fire behaviour simulation in Mediterranean maquis using FARSITE (Fire Area Simulator). PhD thesis, Università degli Studi di Sassari, Italy. Available at http://eprints.uniss.it/23/ [Verified 29 June 2016]

Salis M, Ager AA, Arca B, Finney MA, Bacciu V, Duce P, Spano D (2013) Assessing exposure of human and ecological values to wildfire in Sardinia, Italy. International Journal of Wildland Fire 22, 549–565.
Assessing exposure of human and ecological values to wildfire in Sardinia, Italy.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXpvFakt7k%3D&md5=9feb5053ae5b16f7d449090ef8d2bf58CAS |

Salis M, Ager AA, Arca B, Finney MA, Spano D (2014) Analyzing spatiotemporal changes in wildfire regime and exposure across a Mediterranean fire-prone area. Natural Hazards 71, 1389–1418.
Analyzing spatiotemporal changes in wildfire regime and exposure across a Mediterranean fire-prone area.Crossref | GoogleScholarGoogle Scholar |

Salis M, Ager AA, Alcasena F, Arca B, Finney MA, Pellizzaro G, Spano D (2015) Analyzing seasonal patterns of wildfire likelihood and intensity in Sardinia, Italy. Environmental Monitoring and Assessment 187, 4175
Analyzing seasonal patterns of wildfire likelihood and intensity in Sardinia, Italy.Crossref | GoogleScholarGoogle Scholar | 25471625PubMed |

Salis M, Laconi M, Ager AA, Arca B, Lozano O, Fernandes de Oliveira A, Spano D (2016) Evaluating competing fuel treatment strategies to reduce wildfire losses in a Mediterranean area. Forest Ecology and Management 368, 207–221.
Evaluating competing fuel treatment strategies to reduce wildfire losses in a Mediterranean area.Crossref | GoogleScholarGoogle Scholar |

Santoni PA, Balbi JH, Dupuy JL (1999) Dynamic modeling of upslope fire growth. International Journal of Wildland Fire 9, 285–292.
Dynamic modeling of upslope fire growth.Crossref | GoogleScholarGoogle Scholar |

Santoni PA, Filippi JB, Balbi JH, Bosseur F (2011) Wildland fire behaviour case studies and fuel models for landscape-scale fire modeling. Journal of Combustion 2011, 613424
Wildland fire behaviour case studies and fuel models for landscape-scale fire modeling.Crossref | GoogleScholarGoogle Scholar |

Schmuck G, San-Miguel-Ayanz J, Camia A, Durrant TH, Santos de Oliveira S, Boca R, Whitmore C, Giovando C, Libertá G, Corti P, Schulte E (2011) Forest fires in Europe 2010 (Report No. 11). (Publications Office of the European Union: Lusembourg)10.2788/46294

Scott JH, Burgan R (2005) Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire spread model. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-153. (Fort Collins, CO)

Sharples JJ, McRae RHD, Wilkes SR (2012) Wind–terrain effects on the propagation of wildfires in rugged terrain: fire channelling. International Journal of Wildland Fire 21, 282–296.
Wind–terrain effects on the propagation of wildfires in rugged terrain: fire channelling.Crossref | GoogleScholarGoogle Scholar |

Sorensen TA (1948) A method of establishing groups of equal amplitude in plant sociology based on similarity of species content, and its application to analyses of the vegetation on Danish commons Kongelige Danske Videnskabernes Selskab – Biologiske Skrifter 5, 1–34.

Stratton RD (2006) Guidance on spatial wildland fire analysis: models, tools, and techniques. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-183. (Fort Collins, CO)

Sullivan AL (2009) Wildland surface fire spread modelling, 1990–2007. 1: Physical and quasi-physical models. International Journal of Wildland Fire 18, 349–368.
Wildland surface fire spread modelling, 1990–2007. 1: Physical and quasi-physical models.Crossref | GoogleScholarGoogle Scholar |

Sullivan AL (2009) Wildland surface fire spread modelling, 1990–2007. 3: Simulation and mathematical analogue models. International Journal of Wildland Fire 18, 387–403.
Wildland surface fire spread modelling, 1990–2007. 3: Simulation and mathematical analogue models.Crossref | GoogleScholarGoogle Scholar |

Taylor SW, Woolford DG, Dean CB, Martell DL (2013) Wildfire prediction to inform fire management: statistical science challenges. Statistical Science 28, 586–615.
Wildfire prediction to inform fire management: statistical science challenges.Crossref | GoogleScholarGoogle Scholar |

Vega-Garcia C, Duguy B, Pilar Monfort I, Costafreda-Aumedes S (2014) Characterization of custom fuel models for supporting fire modeling-based optimization of prescribed fire planning in relation to wildfire prevention (southern Catalonia, Spain). In ‘Advances in forest fire research’. (Ed. DX Viegas) Available at https://digitalis.uc.pt/en/livro/characterization_custom_fuel_models_supporting_fire_modeling_based_optimization_prescribed [Verified 5 July 2016]

Viedma O, Moity N, Moreno JM (2015) Changes in landscape fire-hazard during the second half of the 20th century: agriculture abandonment and the changing role of driving factors. Agriculture, Ecosystems & Environment 207, 126–140.
Changes in landscape fire-hazard during the second half of the 20th century: agriculture abandonment and the changing role of driving factors.Crossref | GoogleScholarGoogle Scholar |

Viegas DX (2004) Slope and wind effects on fire propagation. International Journal of Wildland Fire 13, 143–156.
Slope and wind effects on fire propagation.Crossref | GoogleScholarGoogle Scholar |

Viegas DX (2006) Parametric study of an eruptive fire behaviour model. International Journal of Wildland Fire 15, 169–177.
Parametric study of an eruptive fire behaviour model.Crossref | GoogleScholarGoogle Scholar |

Viegas DX, Pita LP (2004) Fire spread in canyons. International Journal of Wildland Fire 13, 253–274.
Fire spread in canyons.Crossref | GoogleScholarGoogle Scholar |

Viegas DX, Simeoni A, Xanthopoulos G, Rossa C, Ribeiro LM, Pita LP, Stipanicev D, Zinoviev A, Weber R, Dold J, Caballero D, San-Miguel-Ayanz J (2009) ‘Recent forest fire-related accidents in Europe’ pp. 1018–5593. (Luxembourg: Office for Official Publications of the European Communities) Available at http://forest.jrc.ec.europa.eu/media/cms_page_media/82/recent-forest-fire-related-accidents-in-europe.pdf [Verified 5 July 2016]

Vogler KC, Ager AA, Day MA, Jennings M, Bailey JD (2015) Prioritization of forest restoration projects: tradeoffs between wildfire protection, ecological restoration and economic objectives. Forests 6, 4403–4420.
Prioritization of forest restoration projects: tradeoffs between wildfire protection, ecological restoration and economic objectives.Crossref | GoogleScholarGoogle Scholar |

Weise DR, Biging GS (1997) A qualitative comparison of fire spread models incorporating wind and slope effects. Forest Science 43, 170–180.

Werth PA, Potter BE, Clements CB, Finney MA, Goodrick SL, Alexander ME, Cruz MG, Forthofer JA, McAllister SS (2011) Synthesis of knowledge of extreme fire behavior: Vol. I for fire managers. USDA Forest Service, Pacific Northwest Research Station, General Technical Report PNW-GTR-854. (Portland, OR)

Wu Z, He H, Liu Z, Liang Y (2013) Comparing fuel reduction treatments for reducing wildfire size and intensity in a boreal forest landscape of north-eastern China. The Science of the Total Environment 454–455, 30–39.
Comparing fuel reduction treatments for reducing wildfire size and intensity in a boreal forest landscape of north-eastern China.Crossref | GoogleScholarGoogle Scholar | 23542479PubMed |

Xystrakis F, Koutsias N (2013) Differences of fire activity and their underlying factors among vegetation formations in Greece i-Forest Biogeosciences and Forestry 6, 132–140.
Differences of fire activity and their underlying factors among vegetation formations in GreeceCrossref | GoogleScholarGoogle Scholar |