Assessing wildfire occurrence probability in Pinus pinaster Ait. Stands in Portugal;Evaluación de la probabilidad de ocurrencia de fuegos en rodales de Pinus pinaster en Portugal

Forest Systems

Volumn 21, Issue 1, 2012, Pages 111-120

  Marques, S ^a   Garcia Gonzalo, J ^a   Botequim, B ^a   Ricardo, A ^a   Borges, J G ^a   Tome, M ^a   Oliveira, M M ^a,b  

^a INSTITUTO SUPERIOR DE AGRONOMIA   (Portugal)

^b UNIVERSITY OF ÉVORA   (Portugal)

Author keywords

Fire occurrence model; Forest management; Pinus pinaster Ait; Risk

Indexed keywords

CONIFEROPHYTA; PINUS PINASTER;

EID: 84860119127     PISSN: 21715068     EISSN: None     Source Type: Journal    
DOI: 10.5424/fs/2112211-11374     Document Type: Article

References (57)

1. Atlas do Ambiente [on line]. Available in: http://sniamb.apambiente.pt/webatlas/ [April 5th 2011].
2. Botequim B., Borges P., Carreiras J., Oliveira M. M. O., Borges J., 2009 Development of a shrub growth model in understory conditions (preliminary model), Technical Report - 7, FORCHANGE, Instituto Superior de Agronomia, Lisboa.
3. Brown J.K., 1971. A planar intersect method for sampling fuel volume and surface area. Forest Sciences 17(1): 96-102.
4. Burnham K. P., Anderson D. R., 2003. Model selection and multi model in ference: A practical information-theoretic approach. New York: Springer.
5. Careay H., Shumann, M., 2003. Modifying Wildfire Behaviour - The Effectiveness of Fuel Treatments: The Status of Our Knowledge, National Community Forestry Center, Southwest Region Working Paper, 31 pp.
6. Carreiras J. M. B., Pereira J. M. C., 2006. An inductive fire risk map for Portugal. V International Conference on Forest Fire Research, Portugal.
7. Castro F.X., Tudela A., Sebastià M.T., 2003, Modeling moisture content in shrubs to predict fire risk in Catalonia (Spain), Agricultural and Forest Meteorology 116: 49-59.
8. Catry F, X., Rego F. C., Bacao F., Moreira F., 2009. Modelling and mapping wildfire ignition risk in Portugal. International Journal of Wildland Fire 2009, 18, 921-931.
9. Catry F. X., Rego F. C., Moreira, F., Bacao, F., 2008. Characterizing and modelling the spatial patterns of wildfire ignitions in Portugal: fire initiation and resulting burned area. In: Eds: de la Heras, J., Brebbia, C. A., Viegas, D., and Leone, V., Modelling, Monitoring and Management of Forest Fires. WIT Transactions on Ecology and the Environment, vol 199: 213-221. DOI: 10.2495/FIVA080221.
10. Ceccato P., Gobron N., Flasse S., Pinty B., Tarantola S., 2002. Designing a spectral index to estimate vegetation water content from remote sensing data: Part 1 Theoretical approach, Remote Sensing of Environment 82:188-197.
11. Chuvieco E., Aguado I., Yebra M., Nieto H., Salas J., Martín M. P., Vilar L., Martínez J., Martín S., Ibarra P., Riva J., Baeza J., Rodríguez F., Molina J. R., Herrera M. A., Zamora R., 2010, Development of a framework for fire risk assessment using remote sensing and geographic information system technologies, Ecological Modelling 221: 46-58.
12. Cumming S.G. 2001. Forest type and wildfire in the Alberta boreal mixedwood: what do fires burn? Ecological Applications 11: 97-110.
13. DGRF., 2006. Resultados do IFN 2005/2006, Lisboa, 70 pp. [In Portuguese].
14. Durão R. M., Pereira M. J., Branquinho C., Soares A., 2010. Assessing spatial uncertainty of the Portuguese fire risk through direct sequential simulation, Ecological Modelling 221: 27-33.
15. Falcão A., 1997. Dunas. - A growth model for the National Forest of Leiria, in Empirical and process-based models for forest tree and stand growth simulation, 20-26 September, Oeiras, Portugal.
16. Fernandes P. M., Rigolot E., 2007. The fire ecology and management of maritime pine (Pinus pinaster Ait.), Forest Ecology and Management 241: 1-13.
17. Fernandes P., Luz, A., Loureiro, C., 2010. Changes in wildfire severity from maritime pine woodland to contiguous forest types in the mountain of northwestern Portugal, Forest Ecology and Management 260: 883-892.
18. Finney M. A., 2005. The challenge of quantitative risk analysis for wildland fire, Forest Ecology and Management 211: 97-108.
19. Garcia-Gonzalo J., Pukkala T., Borges J.G., 2011. Integrating fire risk in stand management scheduling. An application to Maritime pine stands in Portugal. Annals of Operational Research. DOI: 10.1007/s10479-011-0908-1.
20. González J.R., Palia M., Pukkala T. 2006. A fire probability model for forest stands in Catalonia (north-east Spain). Annals of Forest Science 63: 1-8.
21. González J. R, Pukkala T., 2007. Characterization of forest fires in Catalonia (northeast Spain). European Journal of Forest Research. 126(3):421-429.
22. González-Olabarria J. R., Palahí M., Trasobares A., 2008. Optimising the management of Pinus nigra Arn. Stands under endogenous risk of fire in Catalonia. Investigación Agraria: Sistemas y Recursos Forestales 2008 17(1), 10-17.
23. González-Olabarria J. R., Pukkala T., 2011. Integrating fire risk considerations in landscape-level forest planning, Forest Ecology and Management, 261(2): 278-287.
24. Hanewinkel M., Peltola H., Soares P., Gonzalez-Olabarria J.R., 2010. Advanced models for the risk of storm and fire to European forests and their integration into simulation and decision support tools. Forest Systems. 19 (SI), 30-47.
25. Hardy C.C., 2005. Wildland fire hazard and risk: Problems, definitions, and context. Forest Ecology and Management 211:73-82.
26. Hosmer D.W., Lemeshow S., 2000. Applied Logistic Regression, Second Edition, Wiley Series in Probability and Mathematical Statistics, New York, 307 pp.
27. Jactel H., Nicoll B.C., Branco M., González-Olabarria J.R., Grodzki W., Långström B., Moreira F., Netherer S., 2009. The influences of forest stand management on biotic and abiotic risks of damage. Annals of Forest Science 66 (2009) 701.
28. Jalkanen A, Mattila U., 2000 Logistic regression models for wind and snow damage in northern Finland based on the National Forest Inventory data. Forest Ecology and Management 135: 315-330.
29. Kleinbaum D.G., 1994. Logistic regression: a self- learning text. Stat Methods Med Res.1996; 5: 103-104.
30. Kozak A., Kozak R., 2003. Does cross validation provide additional information in the evaluation of regression models? Canadian Journal of Forest Research 33(6): 976-987.
31. Lohmander P, Helles F., 1987 Windthrow probability as a function of stand characteristics and shelter, Scandinavian Journal Forest Research. 2 227-238.
32. Marques S., Borges J.G., Garcia-Gonzalo J., Moreira F., Carreiras J.M.B., Oliveira M.M., Cantarinha A., Botequim B. and Pereira J. M. C., 2011. Characterization of wildfires in Portugal. European Journal of Forest Research, 130(5): 775-784 DOI 10.1007/s10342-010-0470-4.
33. Mercer D.E, Haigth R.G, Prestemon J.P., 2008. Analyzing trade-offs between fuels management, suppression, and damages from wildfire. In T.P. Holes et al. (eds). The Economics of Forest Disturbances: Wildfires, Storms, and Invasive Species. Forestry Sciences 79 (IV): 247-272.
34. Monserud R., Serba H., 1999. Modeling individual tree mortality for Austrian tree species,. Forest Ecology and Management 113 (2/3):109-123.
35. Moreira F., Vaz P., Catry F. X., Silva J.S., 2009. Regional variations in wildfire susceptibility of land-cover types in Portugal: implications for landscape management to minimize fire hazard, International Journal of Wildland Fire 18: 563-574.
36. Neter J., and Maynes E.S. 1970. On the appropriateness of the correlation coefficient with a 0,1 dependent variable. J. Am. Stat. Assoc. 65: 501-509.
37. NIR, 2009. Portuguese National Inventory Report on Greenhouse Gases,1990-2007 submitted under the United Nations Framework Convention on Climate Change and the Kyoto Protocol, Portuguese Environmental Agency, Amadora. [In Portuguese].
38. Nunes C.S., Vasconcelos J., Pereira J.M.C., Dasgupta N., Alldredge R.J. & Rego F.C., 2005. Land cover type and fire in Portugal: do fires burn land cover selectively?, Landscape Ecology, 20, 661-673.
39. Pasalodos-Tato M., Pukkala T. & Rojo Alboreca A., 2010. Optimal management of Pinus pinaster in Galicia (northwestern Spain) under endogenous risk of fire. International Journal of Wildland Fire. In press.
40. Pereira M. G., Trigo R. M., Camara C. C., Pereira J. M. C., Leite S. M., 2005. Synoptic patterns associated with large summer forest fires in Portugal, Agricultural and Forest Meteorology 129: 11-25.
41. Pereira J.M.C., Santos M.T.N., 2003. Áreas queimadas e risco de incêndio em Portugal, Direcção Geral das Florestas, Lisboa, 65 pp.
42. Pereira J.M.C., Carreiras J.M.B., Silva J.M.N., Vasconcelos M.J., 2006. Alguns conceitos básicos sobre fogos rurais em Portugal, in: Eds: Pereira J.S., Pereira J.M.C., Rego F.C., Silva J.M.N., Silva T.P., Incêndios Florestais em Portugal, ISAPress, Lisboa, 133:161. [In Portuguese].
43. Peterson D.L., Johnson M.C., Agee J.K., Jain T.B., Mckenzie D., and Reinhard E.D., 2005. Forest structure and fire hazard in dry forests of the Western United States. PNWGTR-628, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, Portland, Oregon, 30 pp.
44. Preisler H.K., Brillinger D.R., Burgan R.E., Benoit J.W., 2004. Probability based models for estimation of wildfire risk, International Journal of Wildland Fire 13: 133.
45. Reed W.J., 1994. Estimating the historic probability os standreplacement fire using the age-class distribuction of undisturbed forest. Forest Science 40 (1): 104-119.
46. Rothermel R.C., 1972. A mathematical model for predicting fire spread in wildland fuels. USDA For. Serv. Res. Pap. INT-115 Internt. For. and Range Exp. Stn. Ogden, Utah.
47. Rothermel R.C. and Philpot C.W., 1983. How to predict the spread and intensity of forest and range fires. GTR-INT-143, U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, 161 pp.
48. Ryan, K.C, Reinhardt, E.D. 1988. Predicting postfire mortality of seven western conifers. Canadian Journal of Forest Research 18: 1291-1297.
49. SAS Institute Inc. 2004. User's guide, SAS Institute Inc., Cary, NC.
50. Schmidt K.M.; Menakis J.P.; Hardy C.C.; Hann W.J., Bunnell D.L. 2002. Development of coarse-scale spatial data for wildland fire and fuel management. Gen. Tech. Rep. RMRS-GTR-87. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 41 pp.
51. Shapiro J.H., 1999. "Bounds on the area under the ROC curve", J. Opt. Soc. Am. A 16, 53-57.
52. Silva J.S., Moreira F., Vaz P., Catry F., Godinho-Ferreira P., 2009. Assessing the relative fire proneness of different forest types in Portugal, Plant Biosystems, 143(3): 597-608.
53. o2/2006, Dep. Engenharia Florestal, Instituto Superior de Agronomia, Universidade Técnica de Lisboa, Lisboa. [In Portuguese].
54. Vasconcelos M.J.P., Silva S., Tomé M., Alvim M., Pereira J.M.C., 2001. Spatial prediction of fire ignition probabilities: comparing logistic regression and neural networks. Photogrametric Engineering & Remote Sensing 67 (1): 73-81.
55. Velez R., 1990. Mediterranean forest fires: A regional perspective, Unasylva 162 10-12.
56. Wang M., Borders B., Zhao D., 2007. Parameter Estimation of Base-Age Invariant Site Index Models: Which Data Structure to Use? Forest Science 53(5):541-551.
57. Wittenberg L., Malkinson D. 2009. Spatio-Temporal perspectives of forest fires regimes in a maturing Mediterranean mixed pine landscapes, European Journal of Forest Research 128:297-304.