The occurrence of forest fires in Mexico presents an altitudinal tendency: a geospatial analysis

  • José Manuel Zúñiga-Vásquez
  • Marín Pompa-GarcíaEmail author
Original Paper


Fire has become one of the main disturbances in terrestrial ecosystems worldwide. It is known that elevation influences the occurrence of fire events; however, this variable has been poorly studied, although it is of particularly relevance to the Mexican topography. The objective of this research was to analyze the altitudinal distribution of forest fires in Mexico over a period of 11 years. Elevation gradients were defined based on a Digital Elevation Model and the main ecoregions of the country: (1) shrubland and tropical forests (0–1000 masl), (2) grasslands (1001–2000 masl) and (3) temperate forests (> 2000 masl). Each ecoregion was divided into Climate Research Units and the number of fires per unit was quantified. The G Getis–Ord statistic was applied in order to define the spatial patterns presented by the fire events. A relationship between the occurrence of fires and the El Niño Southern Oscillation phenomenon was also determined through a Pearson correlation. The results showed that the occurrence of fire events presented variability along elevation gradients, with elevation a determining factor in their occurrence. Gradient 3, with the highest elevation, had the greatest number of fires and also presented the largest area of fire event clustering. These results contribute to the knowledge of the spatial distribution of forest fires in Mexico and are of value to appropriate decision-making for effective fire management.


Altitudinal gradient Ecoregions G statistic Spatial analysis ENSO phenomenon 



The authors acknowledge Dr. Dante Arturo Rodríguez-Trejo for his valuable comments on a previous version of this manuscript. Also, we are grateful to the editors and anonymous reviewers for their useful comments and suggestions.


This work was supported by Consejo Nacional de Ciencia y Tecnología (Grant No. CVU787063).

Supplementary material

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Supplementary material 1 (DOCX 13 kb)
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Supplementary material 2 (DOCX 14 kb)
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Supplementary material 3 (DOCX 13 kb)


  1. Adab H, Kanniah KD, Solaimani K (2013) Modeling forest fire risk in the northeast of Iran using remote sensing and GIS techniques. Nat Hazards 65(3):1723–1743. CrossRefGoogle Scholar
  2. Ahmad F, Goparaju L, Qayum A (2018) Himalayan forest fire characterization in relation to topography, socio-economy and meteorology parameters in Arunachal Pradesh, India. Spat Inf Res. CrossRefGoogle Scholar
  3. Anselin L (2003) GeoDa 0.9 user’s guide. Urbana, 51, 61801Google Scholar
  4. Ávila-Flores DY, González-Tagle MA, Jiménez-Pérez J, Aguirre-Calderón OA, Treviño-Garza E, Vargas-Larreta B, Alanís Rodríguez E (2014) Efecto de la severidad del fuego en las características de la estructura forestal en rodales de coníferas. Revista Chapingo Serie Ciencias Forestales y del Ambiente 20(1):34–45Google Scholar
  5. Bond WJ, Woodward FI, Midgley GF (2005) The global distribution of ecosystems in a world without fire. New Phytol 165(2):525–538CrossRefGoogle Scholar
  6. Cartus O, Kellndorfer J, Walker W, Franco C, Bishop J, Santos L, Fuentes J (2014) A national, detailed map of forest aboveground carbon stocks in Mexico. Remote Sens 6:5559–5588CrossRefGoogle Scholar
  7. Comisión Nacional Forestal (CONAFOR) (2016) Reporte semanal de resultados de incendios forestales 2016. Programa Nacional de Prevención de Incendios Forestales. Del 01 de enero al 25 de agosto del 2016Google Scholar
  8. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO) (2017) Modelo digital de elevaciones corregido resolución 1 km, escala: 1:4000000. edición: 1.
  9. Environmental Systems Research Institute, US (ESRI) (2012) ArcGIS, software GIS. Version 10.2Google Scholar
  10. Flannigan MD, Logan KA, Amiro BD, Skinner WR, Stocks BJ (2005) Future area burned in Canada. Clim Change 72(1–2):1–16CrossRefGoogle Scholar
  11. Fortin MJ, Dale MRT (2005) Spatial analysis: a guide for ecologists. Cambridge University Press, CambridgeGoogle Scholar
  12. García de Miranda E, Falcón de Gyves Z (1974) Nuevo atlas Porrúa de la República Mexicana. Editorial Porrúa S.A, MéxicoGoogle Scholar
  13. Getis A, Ord JK (1992) The analysis of spatial association by use of distance statistics. Geogr Anal 24:189–206CrossRefGoogle Scholar
  14. Gray CA, Jenkins MJ (2017) Climate warming alters fuels across elevational gradients in Great Basin bristlecone pine-dominated sky island forests. For Ecol Manag 392:125–136CrossRefGoogle Scholar
  15. Hayes GL (1942) Differences in fire danger with altitude, aspect, and time of day. J For 40(4):318–323Google Scholar
  16. Ibarra-Montoya JL, Huerta-Martínez FM (2016) Modelado espacial de incendios: una herramienta predictiva para el Bosque La Primavera, Jalisco México. Revista Ambiente & Água 11(1):35–49Google Scholar
  17. Instituto Nacional de Geografía y Estadistica (INEGI) (2016) Anuario Estadístico de los Estados Unidos Mexicanos. Accessed 5 Sept 2018
  18. Kumar S, Bairagi GD, Kumar A (2015) Identifying triggers for forest fire and assessing fire susceptibility of forests in Indian western Himalaya using geospatial techniques. Nat Hazards 78(1):203–217. CrossRefGoogle Scholar
  19. Littell JS, Peterson DL, Riley KL, Liu Y, Luce CH (2016) A review of the relationships between drought and forest fire in the United States. Glob Change Biol 22(7):2353–2369CrossRefGoogle Scholar
  20. Matin MA, Chitale VS, Murthy MS, Uddin K, Bajracharya B, Pradhan S (2017) Understanding forest fire patterns and risk in Nepal using remote sensing, geographic information system and historical fire data. Int J Wildland Fire 26(4):276–286CrossRefGoogle Scholar
  21. Minnich RA, Franco E (1998) Land of chamise and pines. historical accounts and current status of Northern Baja California’s vegetation. University of California Press, BerkeleyGoogle Scholar
  22. Moran PA (1950) Notes on continuous stochastic phenomena. Biometrika 37(1/2):17–23CrossRefGoogle Scholar
  23. Ord JK, Getis A (1995) Local spatial autocorrelation statistics: distributional issues and an application. Geogr Anal 27(4):286–306CrossRefGoogle Scholar
  24. Pompa MG, Hernández P (2012) Determinación de la tendencia espacial de los puntos de calor como estrategia para monitorear los incendios forestales en Durango, México. Bosque 33(1):63–68Google Scholar
  25. Pompa-García M, Sensibaugh M (2014) Ocurrencia de incendios forestales y su teleconexión con fenómenos ENSO. Ciencia UAT 8(2):6–10CrossRefGoogle Scholar
  26. Pompa-García M, Camarero JJ, Rodríguez-Trejo DA, Vega-Nieva DJ (2017) Drought and spatiotemporal variability of forest fires across Mexico. Chin Geogr Sci 28(1):25–37. CrossRefGoogle Scholar
  27. Rodrigues M, de la Riva J (2014) Assessing the effect on fire risk modelling of the uncertainty in the location and cause of forest fire. In: Viegas DX (ed) Advances in forest fire research. Coimbra University Press, Coimbra, pp 1061–1072Google Scholar
  28. Rodríguez-Trejo DA (2015) Ecología del fuego. Su Ecología, Manejo e Historia. Ed. Colegio de Postgraduados, Universidad Autónoma Chapingo, Semarnat, Programa de Prevención y Combate de Incendios Forestales, Conafor, Conanp, Parque Nacional Iztaccíhuatl-Popocatépetl, ANCF, AMPF, MéxicoGoogle Scholar
  29. Rodríguez-Trejo DA, Fulé PZ (2003) Fire ecology of Mexican pines and a fire management proposal. Int J Wildland Fire 12(1):23–37CrossRefGoogle Scholar
  30. Rogeau MP, Armstrong GW (2017) Quantifying the effect of elevation and aspect on fire return intervals in the Canadian Rocky Mountains. For Ecol Manag 384:248–261CrossRefGoogle Scholar
  31. Rzedowski J (2006) Vegetación de México. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad, MéxicoGoogle Scholar
  32. Secretaria de Medio Ambiente y Recursos Naturales (SEMARNAT) (2017) Incendios forestales, 90% provocados por el hombre. Accessed 5 Sept 2018
  33. Simental AJ, Pompa M (2016) Incendios forestales: autocorrelación espacial de topografía y temporalidad. Ciencia UANL 19(77):41–45Google Scholar
  34. Swetnam TW, Baisan CH, Morino K, Caprio AC (1998) Fire history along elevational transects in the Sierra Nevada, California. Final report to the Sierra Nevada global change research program. University of Arizona, Laboratory of Tree-Ring ResearchGoogle Scholar
  35. Vadrevu KP, Badarinath KVS, Anuradha E (2008) Spatial patterns in vegetation fires in the Indian region. Environ Monit Assess 147(1–3):1. CrossRefGoogle Scholar
  36. Vilchis-Francés AY, Díaz-Delgado C, Magaña-Lona D, Bâ KM, Gómez-Albores MÁ (2015) Modelado espacial para peligro de incendios forestales con predicción diaria en la cuenca del río Balsas. Agrociencia 49(7):803–820Google Scholar
  37. Williams AP, Seager R, Macalady AK et al (2015) Correlations between components of the water balance and burned area reveal new insights for predicting forest fire area in the southwest United States. Int J Wildland Fire 24(1):14–26CrossRefGoogle Scholar
  38. Wolter K, Timlin MS (2011) El Niño/Southern Oscillation behavior since 1871 as diagnosed in an extended multivariate ENSO index (MEI. ext). Int J Climatol 31:1074–1087CrossRefGoogle Scholar
  39. Yocom L, Fulé PZ (2012) Human and climate influences on frequent fire in a high-elevation tropical forest. J Appl Ecol 49:1356–1364CrossRefGoogle Scholar
  40. Zhang S, Zhang K (2007) Comparison between general Moran’s Index and Getis–Ord general G of spatial autocorrelation. Acta Scientiarum Naturalium Universitatis Sunyatseni 46(4):93–97Google Scholar
  41. Zúñiga-Vásquez JM, Cisneros-González D, Pompa-García M, Rodríguez-Trejo DA, Pérez-Verdín G (2017a) Spatial modeling of forest fires in Mexico: an integration of two data sources. Bosque 38(3):563–574CrossRefGoogle Scholar
  42. Zúñiga-Vásquez JM, Cisneros-González D, Pompa-García M (2017b) Drought regulates the burned forest areas in Mexico: the case of 2011, a record year. Geocarto Int. CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • José Manuel Zúñiga-Vásquez
    • 1
  • Marín Pompa-García
    • 1
    Email author
  1. 1.Facultad de Ciencias ForestalesUniversidad Juárez del Estado de DurangoDurangoMexico

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