Environmental susceptibility model for predicting forest fire occurrence in the Western Ghats of India
Quentin Renard A , Raphaël Pélissier A B C , B. R. Ramesh A and Narendran Kodandapani A
+ Author Affiliations
- Author Affiliations
A Institut Français de Pondichéry (IFP), UMIFRE MAEE-CNRS 21, 11, St Louis Street, Puducherry 605001, India.
B Institut de Recherche pour le Développement (IRD), UMR AMAP, TA A51/PS2, F-34398 Montpellier cedex 05, France.
C Corresponding author. Email: raphael.pelissier@ird.fr
International Journal of Wildland Fire 21(4) 368-379 https://doi.org/10.1071/WF10109
Submitted: 20 September 2010 Accepted: 31 August 2011 Published: 2 March 2012
Abstract
Forest fires are a recurrent management problem in the Western Ghats of India. Although most fires occur during the dry season, information on the spatial distribution of fires is needed to improve fire prevention. We used the MODIS Hotspots database and Maxent algorithm to provide a quantitative understanding of the environmental controls regulating the spatial distribution of forest fires over the period 2003–07 in the entire Western Ghats and in two nested subregions with contrasting characteristics. We used hierarchical partitioning to assess the independent contributions of climate, topography and vegetation to the goodness-of-fit of models and to build the most parsimonious fire susceptibility model in each study area. Results show that although areas predicted as highly prone to forest fires were mainly localised on the eastern slopes of the Ghats, spatial predictions and model accuracies differed significantly between study areas. We suggest accordingly a two-step approach to identify: first, large fire-prone areas by paying special attention to the climatic conditions of the monsoon season before the fire season, which determine the fuels moisture content during the fire season; second, the most vulnerable sites within the fire-prone areas using local models mainly based on the type of vegetation.
Additional keywords: environmental controls, fire susceptibility model, Maxent, MODIS, nested study areas.
References
Bonell M, Purandara BK, Venkatesh B, Krishnaswamy J, Acharya HAK, Singh UV, Jayakumar R, Chappell N (2010) The impact of forest use and reforestation on soil hydraulic conductivity in the Western Ghats of India: implications for surface and sub-surface hydrology. Journal of Hydrology 391, 47–62.Brown S, Lugo A (1982) The storage and production of organic matter in tropical forests and their role in the global carbon cycle. Biotropica 14, 161–187.
Champion HG (1936) A preliminary survey of the forest types of India and Burma. Indian Forest Records 1, 1–286.
Chevan A, Sutherland M (1991) Hierarchical partitioning. The American Statistician 45, 90–96.
Chou YH (1990) Modeling fire occurrences for wildland fire management: a GIS Spatial analysis for fire control and prevention. In ‘Proceedings of the GIS/LIS ’90 Conference’, 7–10 November 1990, Anaheim, CA. pp. 440–449. (American Society for Photogrammetry and Remote Sensing: Bethesda, MD)
Chuvieco E (2003) ‘Wildland Fire Danger Estimation and Mapping: the Role of Remote Sensing Data.’ (World Scientific Publishing Co.: River Edge, NJ)
Cochrane MA, Laurance WF (2002) Fire as a large-scale edge effect in Amazonian forests. Journal of Tropical Ecology 18, 311–324.
Das A, Krishnaswamy J, Bawa KS, Kiran MC, Srinivas V, Kumar NS, Karanth KU (2006) Prioritization of conservation areas in the Western Ghats, India. Biological Conservation 133, 16–31.
Deblauwe V, Barbier N, Couteron P, Lejeune O, Bogaert J (2008) The global biogeography of semi-arid periodic vegetation patterns. Global Ecology and Biogeography 17, 715–723.
Elith J, Graham CH, Anderson RP, Dudik M, Ferrier S, Guisan A, Hijmans RJ, Huettmann F, Leathwick JR, Lehmann A, Li J, Lohmann LG, Loiselle BA, Manion G, Moritz C, Nakamura M, Nakazawa Y, Overton JM, Peterson AT, Phillips SJ, Richardson K, Scachetti-Pereira R, Schapire RE, Soberon J, Williams S, Wisz MS, Zimmermann NE (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29, 129–151.
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.
Friedl MA, Sulla-Menashe D, Tan B, Schneider A, Ramankutty N, Sibley A, Huang XM (2010) MODIS Collection 5 global land cover: algorithm refinements and characterization of new datasets. Remote Sensing of Environment 114, 168–182.
Giglio L, Descloitres J, Justice CO, Kaufman Y (2003) An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment 87, 273–282.
Goldammer JG (1990) ‘Fire in the Tropical Biota. Ecosystem Processes and Global Challenges.’ Ecological Studies 84 (Springer-Verlag: Berlin)
Gunnell Y (1997) Relief and climate in south India: the influence of the Western Ghats on the current climate pattern of peninsular India. International Journal of Climatology 17, 1169–1182.
Guisan A, Zimmerman NE (2000) Predictive habitat distribution models in ecology. Ecological Modelling 135, 147–186.
Hernandez PA, Graham CH, Master LL, Albert DL (2006) The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography 29, 773–785.
Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very-high-resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25, 1965–1978.
Jarvis A, Reuter HI, Nelson A, Guevara E (2008) Hole-filled SRTM for the globe, Version 4. The CGIAR-CSI SRTM 90m Database. (CGIAR Consortium for Spatial Information) Available at http://srtm.csi.cgiar.org [Verified 15 December 2011]
Jiménez-Valvarde A (2011) Insights into the area under the ROC curve (AUC) as a discrimination measure in species distribution modelling. Global Ecology and Biogeography.
| Insights into the area under the ROC curve (AUC) as a discrimination measure in species distribution modelling.Crossref | GoogleScholarGoogle Scholar |
Kaufman Y, Justice C (1998) Algorithm technical background document. MODIS Fire Products Version 2.2, 10 November 1998. NASA, Earth Observing System report ID#2741. (Washington, DC)
Kodandapani N, Cochrane MA, Sukumar R (2004) Conservation threat of increasing fire frequencies in the Western Ghats, India. Conservation Biology 18, 1553–1561.
Kodandapani N, Cochran MA, Sukumar R (2008) A comparative analysis of spatial, temporal, and ecological characteristics of forest fires in seasonally dry tropical ecosystems in the Western Ghats, India. Forest Ecology and Management 256, 607–617.
Krishnaswamy J, Bawa KS, Ganeshaiah KN, Kiran MC (2009) Quantifying and mapping biodiversity and ecosystem services: utility of a multi-season NDVI based Mahalanobis distance surrogate. Remote Sensing of Environment 113, 857–867.
Langner A, Siegert F (2009) Spatiotemporal fire occurrence in Borneo over a period of 10 years. Global Change Biology 15, 48–62.
Mac Nally R (2000) Regression and model-building in conservation biology, biogeography and ecology: the distinction between – and reconciliation of – ‘predictive’ and ‘explanatory’ models. Biodiversity and Conservation 9, 655–671.
Manokaran N, Uniyal VK, Kumar CS (1997) The biodiversity wealth and its conservation in Kerala. In ‘Conservation and Economic Evaluation of Biodiversity’. (Eds P Pushpangadan, K Ravi, V Santosh) pp. 103–124. (Oxford University Press & India Book House: New Delhi)
Mueller-Dombois D, Goldammer JG (1990) Fire in tropical ecosystems and global environmental change: an introduction. In ‘Fire in the Tropical Biota’. (Ed. JG Goldammer) Ecological Studies Vol. 84, pp. 1–10. (Springer-Verlag: Berlin)
Murthy MSR, Badarinath KVS, Gharai B, Rajshekhar G, Roy PS (2006) The Indian Forest Fire Response and Assessment System (INFFRAS). International Forest Fire News 34, 72–77.
Myers N, Mittermeier RA, Mittermeier CG, Da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403, 853–858.
Olea PP, Mateo-Tomás P, de Frutos A (2010) Estimating and modelling bias of the hierarchical partitioning public-domain software: implications in environmental management and conservation. PLoS ONE 5, e11698.
Parisien MA, Moritz MA (2009) Environmental controls on the distribution of wildfire at multiple spatial scales. Ecological Monographs 79, 127–154.
Pascal J-P (1982) Bioclimatic maps of South India. Travaux de la Section Scientifique et Technique Hors Serie 17. (Institut Français de Pondichéry: Pondicherry, India)
Pascal J-P (1986) Explanatory booklet on the forest map of south India – sheets: Belgaum–Dharwar–Panaji; Shimoga; Mercara–Mysore. Travaux de la Section Scientifique et Technique Hors Série 18. (Institut Français de Pondichéry: Pondicherry, India)
Pascal J-P (1988) Wet evergreen forests of the Western Ghats: ecology, structure, floristic composition and succession dynamics. Travaux de la Section Scientifique et Technique 20 bis. (Institut Français de Pondichéry: India)
Pascal J-P, Shyam Sunder S, Meher-Homji VM (1997a) Forest map of south India – Mercara–Mysore sheet. Travaux de la Section Scientifique et Technique Hors Série 18a. (Institut Français de Pondichéry: Pondicherry, India)
Pascal J-P, Shyam Sunder S, Meher-Homji VM (1997b) Forest map of South India – Shimoga sheet. Travaux de la Section Scientifique et Technique Hors Série 18b. (Institut Français de Pondichéry: Pondicherry, India)
Pascal J-P, Shyam Sunder S, Meher-Homji VM (1997c) Forest map of south India – Belgaum–Dharwar–Panaji sheet. Travaux de la Section Scientifique et Technique Hors Série 18c. (Institut Français de Pondichéry: Pondicherry, India)
Phillips SJ (2005) ‘A Brief Tutorial on Maxent.’ Research report (AT&T Labs-Research: Florham Park, NJ)
Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distribution. Ecological Modelling 190, 231–259.
Phillips SJ, Dudik M (2008) Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31, 161–175.
Pyne SJ, Andrews PL, Laven RD (1996) ‘Introduction to Wildland Fire.’ (Wiley: New York)
Ramesh BR, Gurrkkal R (2007) Forest landscapes of the southern Western Ghats, India: biodiversity, human ecology and management strategies. Collection Ecologie 40. (Institut Français de Pondichéry: Pondicherry,India
Ramesh BR, De Franceschi D, Pascal J-P (1997) Forest map of south India – Tiruvananthapuram–Tirunelveli sheet. Publications du département d'écologie, hors série 22a. (Institut Français de Pondichéry: Pondicherry, India)
Ramesh BR, De Franceschi D, Pascal J-P (2002) Forest map of south India – Coimbatore–Thrissur sheet. Publications du département d'écologie, hors série 22b. (Institut Français de Pondichéry: Pondicherry, India)
Ramesh BR, Venugopal PD, Pélissier R, Patil SV, Swaminath MH, Couteron P (2010) Mesoscale patterns in the floristic composition of forests in the central Western Ghats of Karnataka, India. Biotropica 42, 435–443.
R Development Core Team (2010) ‘R: a Language and Environment for Statistical Computing.’ (R Foundation for Statistical Computing: Vienna, Austria)
Renard Q, Muthusankar G, Pélissier R (2009) Data Paper – High-resolution topographic and bioclimatic data for the southern Western Ghats of India. Pondy Papers in Ecology 8, 1–21.
Renard Q, Ramesh BR, Muthusankar G, Pélissier R (2010) Data paper – high-resolution vegetation cover data for the southern Western Ghats of India. Pondy Papers in Ecology 9, 1–12.
Roy DP, Boschetti L, Justice CO, Ju J (2008) The collection 5 MODIS burned area product – Global evaluation by comparison with the MODIS active fire product. Remote Sensing of Environment 112, 3690–3707.
Scott JM, Heglund PJ, Morrison ML, Haufler JB, Raphael MG, Wall WA, Samson FB (2002) ‘Predicting Species Occurrences. Issues of Accuracy and Scale.’ (Island Press: Washington DC)
Vega-Garcia C, Woodward PM, Lee BS (1993) Mapping risk of wildfires from human sources of ignition with a GIS. In ‘Proceedings of the Thirteenth Annual ESRI User Conference’, 24–28 May 1993, Palm Springs, CA. pp. 419–426. (Environmental Systems Research Institute: Redlands, CA)
