Modelling the meteorological forest fire niche in heterogeneous pyrologic conditions

PLoS ONE

Volumn 10, Issue 2, 2015, Pages

  De Angelis, Antonella ^a   Ricotta, Carlo ^b   Conedera, Marco ^a   Pezzatti, Gianni Boris ^a  

^a SWISS FEDERAL RESEARCH INSTITUTE WSL   (Switzerland)

^b SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; FIRE; FOREST; METEOROLOGICAL PHENOMENA; PREVALENCE; RECEIVER OPERATING CHARACTERISTIC; SUMMER; SWITZERLAND; WINTER; RISK; THEORETICAL MODEL; WEATHER;

FIRES; FORESTS; MODELS, THEORETICAL; RISK; SWITZERLAND; WEATHER;

EID: 84923067534     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0116875     Document Type: Article

References (75)

1. Cardille JA, Ventura SJ, Turner MG (2001) Environmental and social factors influencing wildfires in the Upper Midwest, United States. Ecological Applications 11: 111-127.
2. Mermoz M, Kitzberger T, Veblen TT (2005) Landscape influences on occurrence and spread of wildfires in Patagonian forests and shrublands. Ecology 86: 2705-2715.
3. Krebs P, Pezzatti GB, Mazzoleni S, Talbot LM, Conedera M (2010) Fire regime: history and definition of a key concept in disturbance ecology. Theory in Biosciences 129: 53-69. doi: 10.1007/s12064-010-0082-z PMID: 20502984
4. Cumming SG (2001) Forest type and wildfire in the Alberta boreal mixedwood: what do fires burn? Ecological Applications 11: 97-110.
5. Dube OP (2007) Fire Weather and Land Degradation. In: Sivakumarvand Ndegwa Ndiangui M.V.K. (Eds.) Climate and Land Degradation. Springer, Berlin. pp. 106-132.
6. Krawchuk MA, Cumming SG, Flannigan MD, Wein RW (2006) Biotic and abiotic regulation of lightning fire initiation in the mixedwood boreal forest. Ecology 87: 458-468. PMID: 16637370
7. Syphard AD, Radeloff VC, Keeley JE, Hawbaker TJ, Clayton MK, et al. (2007) Human influence on California fire regimes. Ecological Applications 17: 1388-1402. PMID: 17708216
8. Gustafson EJ, Zollner PA, Sturtevant BR, He HS, Mladenoff DJ (2004). Influence of forest management alternatives and land type on susceptibility to fire in northern Wisconsin, USA. Landscape Ecology 19: 327-341.
9. Zumbrunnen T, Menendez P, Bugmann H, Conedera M, Gimmi U, et al. (2012) Human impacts on fire occurrence: a case study of hundred years of forest fires in a dry alpine valley in Switzerland. Regional Environmental Change 12: 935-949.
10. Pezzatti GB, Zumbrunnen T, Bürgi M, Ambrosetti P, Conedera M (2013) Fire regime shifts as a consequence of fire policy and socio-economic development: An analysis based on the change point approach. Forest Policy and Economics 29: 7-18.
11. Wotton BM (2009) Interpreting and using outputs from the Canadian forest fire danger rating system in research applications. Environmental and Ecological Statistics 16: 107-131.
12. Sharples JJ, McRae RHD, Weber RO, Gill AM (2009) A simple index for assessing fire danger rating. Environmental Modelling and Software 24: 764-774.
13. Taylor SW, Alexander ME (2006) Science, technology, and human factors in fire danger rating: the Canadian experience. International Journal of Wildland Fire 15: 121-135.
14. Stocks BJ, Lawson BD, Alexander ME, Van Wagner CE, McAlpine RS, et al. (1989) The Canadian Forest Fire Danger Rating System: an overview. The Forestry Chronicle 65: 450-457.
15. Van Wagner CE (1987) Development and Structure of the Canadian Forest Fire Weather Index System. Ottawa, ON, Canadian Forest Service, Technical Report 35.
16. Fogarty LG, Pearce HG, Catchpole WR, Alexander ME (1998) Adoption vs. adaptation: lessons from applying the Canadian Forest Fire Danger Rating System in New Zealand. In Proceedings, 3rd International Conference on Forest Fire Research and 14th Fire and Forest Meteorology Conference, Luso, Coimbra, Portugal. pp. 1011-1028.
17. Taylor SW (2001) Considerations for applying the Canadian Forest Fire Danger Rating System in Argentina. Natural Resources Canada, Canadian Forest Service, Contract report. (Pacific Forestry Centre: Victoria, BC).
18. Dimitrakopoulos AP, Mitsopoulos ID, Gatoulas K (2010) Assessing ignition probability and moisture of extinction in a Mediterranean grass fuel. International Journal of Wildland Fire 19(1): 29-34.
19. Mölders N (2010) Comparison of Canadian Forest Fire Danger Rating System and National Fire Danger Rating System fire indices derived from Weather Research and Forecasting (WRF) model data for the June 2005 Interior Alaska wildfires. Atmospheric Research 95(2-3): 290-306.
20. Tian XR, McRae DJ, Jin JZ, Shu LF, Zhao FJ, et al. (2011) Wildfires and the Canadian Forest Fire Weather Index system for the Daxinganling region of China. International Journal of Wildland Fire 20(8): 963-973.
21. Sturm T, Fernandes PM, Sumrada R (2012) The Canadian fire weather index system and wildfire activity in the Karst forest management area, Slovenia. European Journal of Forest Research 131: 829-834.
22. Hardy CC, Hardy CE (2007) Fire danger rating in the United States of America: an evolution since 1916. International Journal of Wildland Fire 16: 217-231.
23. Vega-Garcia C, Woodard PM, Titus SJ, Adamowicz WL, Lee BS (1995) A logit model for predicting the daily occurrence of human-caused forest fires. International Journal of Wildland Fire 5(2): 101-111.
24. Mandallaz D, Ye R (1997) Prediction of forest fires with Poisson models. Canadian Journal of Forest Research 27(10): 1685-1694.
25. de Vicente J, Crespo F (2012) A new wildland fire danger index for a Mediterranean region and some validation aspects. International Journal of Wildland Fire 21(8): 1030-1041.
26. Viegas DX, Bovio G, Ferreira A, Nosenzo A, Sol B (1999) Comparative study of various methods of fire danger evaluation in southern Europe. International Journal of Wildland Fire 9: 235-246.
27. Eastaugh CS, Vacik A (2012) Fire size/frequency modelling as a means of assessing wildfire database reliability. Austrian Journal of Forest Science 129(3-4): 222-241.
28. Holsten A, Dominic AR, Costa L, Kropp JP (2013) Evaluation of the performance of meteorological forest fire indices for German federal states. Forest Ecology and Management 287: 123-131.
29. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modelling of species geographic distributions. Ecological Modelling 190: 231-259.
30. Elith J, Graham CH, Anderson RP, Dudík M, Ferrier S, et al. (2006) Novel methods improve prediction of species' distributions from occurrence data. Ecography 29: 129-151. PMID: 16622301
31. Hernandez PA, Graham CH, Master LL, Albert DL (2006) The effect of sample size and species characteristics on performance of different species distribution modelling methods. Ecography 29: 773-785.
32. Siljander M (2009) Predictive fire occurrence modelling to improve burned area estimation at a regional scale: A case study in East Caprivi, Namibia. International Journal of Applied Earth Observation and Geoinformation 11(6): 380-393.
33. Viedma O, Angeler DG, Moreno JM (2009) Landscape structural features control fire size in a Mediterranean forested area of central Spain. International Journal of Wildland Fire 18: 575-583.
34. Bar Massada A, Syphard AD, Stewart SI, Radeloff VC (2012) Wildfire ignition-distribution modelling: a comparative study in the Huron - Manistee National Forest, Michigan, USA. International Journal of Wildland Fire 22(2): 174-183.
35. Spinedi F, Isotta F (2004) Il clima del Ticino negli ultimi 50 anni. Dati statistiche e società 4: 4-39.
36. Conedera M, Corti G, Piccini P, Ryser D, Guerini F, et al. (2004) La gestione degli incendi boschivi in Canton Ticino: tentativo di una sintesi storica. Schweizerische Zeitschrift für das Forstwesen 155: 263-277.
37. Ellenberg H, Klötzli F (1972) Waldgesellschaften und Waldstandorte der Schweiz Mitt Schweiz Anst Forst Versuchswes 48: 587-930.
38. Pezzatti GB, Bajocco S, Torriani D, Conedera M (2009) Selective burning of forest vegetation in Canton Ticino (Southern Switzerland). Plant Biosystems 143(3): 609-620.
39. th International Conference on Forest Fire Research. University of Coimbra, Figueira da Foz, Portugal.
40. Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration: guidelines for computing crop water requirements. FAO.
41. nd ed. Chapman & Hall, London.
42. Austin MP (2002) Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecological Modelling 157: 101-118.
43. Guisan A, Edwards TC Jr, Hastie T (2002) Generalized linear and generalized additive models in studies of species distributions: setting the scene. Ecological Modelling 157: 89-100.
44. Franklin J (2010) Mapping Species Distributions. Cambridge University Press, New York.
45. Warren DL, Seifert SN (2011) Ecological niche modelling in Maxent: The importance of model complexity and the performance of model selection criteria. Ecological Applications 21: 335-342. PMID: 21563566
46. Renard Q, Pelissier R, Ramesh BR, Kodandapani N (2012) Environmental susceptibility model for predicting forest fire occurrence in the western Ghats of India. International Journal of Wildland Fire 21: 368-379.
47. Parisien MA, Moritz MA (2009) Environmental controls on the distribution of wildfire at multiple spatial scales. Ecological Monographs 79(1): 127-154.
48. R Core Team (2013) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.
49. Bradley AP (1997) The use of the area under the roc curve in the evaluation of machine learning algorithms. Pattern Recognition 30: 1145-1159.
50. Hanley JA, McNeil BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143: 29-36. PMID: 7063747
51. Pontius RG Jr, Parmentier B (2014) Recommendations for using the Relative Operating Characteristic (ROC). Landscape Ecology 29(3): 367-382.
52. Lobo JM, Jiménez-Valverde A, Real R (2008) AUC: A misleading measure of the performance of predictive distribution models. Global Ecology and Biogeography 17: 145-151.
53. Fielding AH, Bell JF (1997) A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation 24: 38-49.
54. Deleo JM (1993) Receiver operating characteristic laboratory (ROCLAB): software for developing decision strategies that account for uncertainty. In Proceedings of the Second International Symposium on Uncertainty Modelling and analysis. IEEE, Computer Society Press, College Park, MD. pp. 318-325.
55. Zweig MH, Campbell G (1993) Receiver-operating characteristic (ROC) plots: A fundamental evaluation tool in clinical medicine. Clinical Chemistry 39: 561-577. PMID: 8472349
56. Pearce J, Ferrier S (2000) Evaluating the predictive performance of habitat models developed using logistic regression. Ecological Model 133: 225-245.
57. Wiley EO, McNyset KM, Peterson AT, Robins CR, Stewart AM (2003) Niche modelling and geographic range predictions in the marine environment using a machine-learning algorithm. Oceanography 16: 120-127.
58. th International Joint Conference on Artificial Intelligence - Volume 2, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA. pp. 1137-1143.
59. Hastie T, Tibshirani R, Friedman J (2009) The Elements of Statistical Learning: Prediction, Inference and Data Mining. Second edition. Springer-Verlag, New York, USA.
60. Francois D, Rossi F, Wertz V, Verleysen M (2007) Resampling methods for parameter-free and robust features election with mutual information. Neurocomputing 70(7-9): 1276-1288.
61. Gibson L, Barrett B, Burbidge A (2007) Dealing with uncertain absence sin habitat modelling: a case study of a rare ground-dwelling parrot. Diversity and Distribution 13(6): 704-713.
62. Elith J, Graham CH (2009) Do they? How do they? Why do they differ? On finding reasons for differing performances of species distribution models. Ecography 32: 66-77.
63. Roura-Pascual N, Brotons L, Peterson A, Thuiller W (2009) Consensual predictions of potential distributional areas for invasive species: a case study of Argentine ants in the Iberian Peninsula. Biological Invasions 11: 1017-1031.
64. Tognelli MF, Roig-Junent SA, Marvaldi AE, Flores GE, Lobo JM (2009) An evaluation of methods for modelling distribution of Patagonian insects. Revista Chilena de Historia Natural 82: 347-360.
65. Marini M, Barbet-Massin M, Lopes L, Jiguet F (2010) Predicting the occurrence of rare Brazilian birds with species distribution models. Journal of Ornithology 151(4): 857-866.
66. Reineking B, Weibel P, Conedera M, Bugmann H (2010) Environmental determinants of lightning-v. human - induced forest fire ignitions differ in a temperate mountain region of Switzerland. International Journal of Wildland Fire 19: 541-557.
67. Chandler C, Cheney P, Thomas P, Trabaud L, Williams D (1983) Fire in Forestry. Bd. 1, John Wiley and Sons, New York.
68. Baumgartner A, Klemmer L, Raschke E, Waldmann G (1967) Waldbrände in Bayern 1950 bis 1959. Mitteilungen aus der Staatsforstverwaltung Bayerns 36: 57-79.
69. Fosberg MA (1978) Weather in wildland fire management: the fire weather index. In Proceedings of the Conference on Sierra Nevada Meteorology, Lake Tahoe, California. Boston.
70. Keetch JJ, Byram GM (1968) A Drought Index for Forest Fire Control. Southeastern Forest Experiment Station, Asheville, North Carolina.
71. McArthur AG (1967) Fire behaviour in Eucalypt forests. Department of National Development, Forestry and Timber Bureau Leaflet 107, Canberra, ACT.
72. Munger TT (1916) Graphic method of representing and comparing drought intensities. Monthly Weather Review 44: 642-643.
73. Orieux A (1974) Conditions météorologiques et incendies en région méditerranéenne. Revue forestière franc¸aise no spécial Incendies de forêt: 122-129.
74. Nesterov VG (1949) Combustibility of the forest and methods for its determination (in Russian). USSR State Industry Press.
75. Sharples JJ, McRae RHD, Weber RO, Gill AM (2009) A simple index for assessing fuel moisture content. Environmental Modelling and Software 24(5): 637-646.