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Regional Environmental Change

, Volume 19, Issue 2, pp 515–527 | Cite as

Spatiotemporal trends of area burnt in the Iberian Peninsula, 1975–2013

  • João M. N. SilvaEmail author
  • Maria Vanesa Moreno
  • Yannick Le Page
  • Duarte Oom
  • Ioannis Bistinas
  • José Miguel C. Pereira
Original Article

Abstract

In Portugal and Spain, fire regimes have been significantly altered due to changes in anthropogenic and climatic factors. The development of a fire management strategy should take into account the past trends of fire incidence. We analyse the spatial and temporal trends of burned area in the Iberian Peninsula, merging four decades of forest fire data from the two countries. Theil-Sen slope and a spatial version of Mann-Kendall test are used to test the significance of trends. Excluding some small cases, all significant clusters in Spain correspond to regions of decreasing trends of burnt area. Portugal exhibits contrasting trends, with a large cluster of increasing trend of burnt area in the northwestern part of the country and a large cluster of decreasing trend in central Portugal. A regression analysis performed between the burnt area and the Daily Severity Rating (DSR), a measure of fire suppression difficulty, for the largest significant clusters reveals that climatic factors explain only in part the burnt area trends. Anthropogenic factors also play an important role. In northwestern Spain, fire suppression has contributed to a decreasing trend of burnt area even if the area of forest and the population has increased in the last decades. In central Portugal, the decreasing trend in burnt area is mostly related to the population decrease and the rural abandonment. Regarding northwestern Portugal, it is a region where agriculture is the dominant land cover type and the urban area doubled since 1990. This is indicative of an extending urban-rural interface, which contributes to an increase in fire incidence.

Keywords

Forest fires Spatial incidence Time series Contextual Mann-Kendall Iberian Peninsula 

Notes

Acknowledgements

We would like to thank the Ministerio de Agricultura y Pesca, Alimentación y Medio Ambiente, Spain, for providing access to the Spanish fire statistics.

Funding

J. M. N. Silva was funded by a postdoctoral grant (SFRH/BPD/109535/2015) from the Fundação para a Ciência e Tecnologia (FCT), Ministro da Ciência, Tecnologia e Ensino Superior, Portugal. CEF is a research unit funded by Fundação para a Ciência e Tecnologia I.P. (FCT), Portugal (UID/AGR/00239/2013).

References

  1. Alcaraz-Segura D, Paruelo J, Cabello J (2006) Identification of current ecosystem functional types in the Iberian Peninsula. Glob Ecol Biogeogr 15:200–212.  https://doi.org/10.1111/j.1466-822x.2006.00215.x CrossRefGoogle Scholar
  2. Asner GP, Elmore AJ, Olander LP, Martin RE, Harris AT (2004) Grazing systems, ecosystem responses, and global change. Annu Rev Environ Resour 29:261–299.  https://doi.org/10.1146/annurev.energy.29.062403.102142 CrossRefGoogle Scholar
  3. Bowman DMJS, Williamson GJ, Abatzoglou JT, Kolden CA, Cochrane MA, Smith AMS (2017) Human exposure and sensitivity to globally extreme wildfire events. Nat Ecol Evol 1.  https://doi.org/10.1038/s41559-016-0058
  4. Camia A, Amatulli G, San-Miguel-Ayanz J (2008) Past and future trends of forest fire danger in Europe. European Commission, LuxembourgGoogle Scholar
  5. Carvalhais N, Reichstein M, Collatz GJ, Mahecha MD, Migliavacca M, Neigh CSR, Tomelleri E, Benali AA, Papale D, Seixas J (2010) Deciphering the components of regional net ecosystem fluxes following a bottom-up approach for the Iberian Peninsula. Biogeosciences 7:3707–3729.  https://doi.org/10.5194/bg-7-3707-2010 CrossRefGoogle Scholar
  6. Castro EB et al (1996) Los Bosques Ibérico. Una Interpretación Goegotánica, Planeta, BarcelonaGoogle Scholar
  7. Catry FX, Rego FC, Bacao F, Moreira F (2009) Modeling and mapping wildfire ignition risk in Portugal. Int J Wildland Fire 18:921–931.  https://doi.org/10.1071/Wf07123 CrossRefGoogle Scholar
  8. Chandler RE, Scott EM (2011) Statistical methods for trend detection and analysis in the environmental sciences. Chichester, United KingdomCrossRefGoogle Scholar
  9. Costa L, Thonicke K, Poulter B, Badeck FW (2011) Sensitivity of Portuguese forest fires to climatic, human, and landscape variables: subnational differences between fire drivers in extreme fire years and decadal averages. Reg Environ Chang 11:543–551.  https://doi.org/10.1007/s10113-010-0169-6 CrossRefGoogle Scholar
  10. Czerwinski CJ, King DJ, Mitchell SW (2014) Mapping forest growth and decline in a temperate mixed forest using temporal trend analysis of Landsat imagery, 1987-2010. Remote Sens Environ 141:188–200.  https://doi.org/10.1016/j.rse.2013.11.006 CrossRefGoogle Scholar
  11. Dewes CF, Rangwala I, Barsugli JJ, Hobbins MT, Kumar S (2017) Drought risk assessment under climate change is sensitive to methodological choices for the estimation of evaporative demand. PLoS One 12(3):e0174045.  https://doi.org/10.1371/journal.pone.0174045 CrossRefGoogle Scholar
  12. Doerr SH, Santin C (2016) Global trends in wildfire and its impacts: perceptions versus realities in a changing world. Philos Trans R Soc B 371:20150345.  https://doi.org/10.1098/rstb.2015.0345 CrossRefGoogle Scholar
  13. Douglas EM, Vogel RM, Kroll CN (2000) Trends in floods and low flows in the United States: impact of spatial correlation. J Hydrol 240:90–105.  https://doi.org/10.1016/S0022-1694(00)00336-X CrossRefGoogle Scholar
  14. Durbin J, Watson GS (1950) Testing for serial correlation in least squares regression. Biometrika 37:409–428.  https://doi.org/10.2307/2332391 Google Scholar
  15. Field RD, Spessa AC, Aziz NA, Camia A, Cantin A, Carr R, de Groot WJ, Dowdy AJ, Flannigan MD, Manomaiphiboon K, Pappenberger F, Tanpipat V, Wang X (2015) Development of a global fire weather database. Nat Hazards Earth Syst Sci 15:1407–1423.  https://doi.org/10.5194/nhess-15-1407-2015 CrossRefGoogle Scholar
  16. Fuller DO, Wang Y (2014) Recent trends in satellite vegetation index observations indicate decreasing vegetation biomass in the Southeastern Saline Everglades wetlands. Wetlands 34:67–77.  https://doi.org/10.1007/s13157-013-0483-0 CrossRefGoogle Scholar
  17. Higuera PE, Abatzoglou JT, Littell JS, Morgan P (2015) The changing strength and nature of fire-climate relationships in the northern Rocky Mountains, U.S.A., 1902-2008. PLoS ONE 10(6):e0127563.  https://doi.org/10.1371/journal.pone.0127563 CrossRefGoogle Scholar
  18. Jiménez-Ruano A, Rodrigues Mimbrero M, de la Riva Fernández J (2017) Exploring spatial–temporal dynamics of fire regime features in mainland Spain. Nat Hazards Earth Syst Sci 17:1697–1711.  https://doi.org/10.5194/nhess-17-1697-2017 CrossRefGoogle Scholar
  19. Jolly WM, Cochrane MA, Freeborn PH, Holden ZA, Brown TJ, Williamson GJ, Bowman DMJS (2015) Climate-induced variations in global wildfire danger from 1979 to 2013. Nat Commun 6:7537.  https://doi.org/10.1038/ncomms8537 CrossRefGoogle Scholar
  20. Kendall MG (1975) Rank correlation methods, 2d edn. C. Griffin, LondonGoogle Scholar
  21. Lawson BD, Armitage OB (2008) Weather guide for the Canadian Forest Fire Danger Rating System. Northern Forestry Centre, EdmontonGoogle Scholar
  22. Le Page Y, Oom D, Silva JMN, Jonsson P, Pereira JMC (2010) Seasonality of vegetation fires as modified by human action: observing the deviation from eco-climatic fire regimes. Glob Ecol Biogeogr 19:575–588.  https://doi.org/10.1111/j.1466-8238.2010.00525.x Google Scholar
  23. Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259.  https://doi.org/10.2307/1907187 CrossRefGoogle Scholar
  24. Martínez J, Vega-Garcia C, Chuvieco E (2009) Human-caused wildfire risk rating for prevention planning in Spain. J Environ Manag 90:1241–1252.  https://doi.org/10.1016/j.jenvman.2008.07.005 CrossRefGoogle Scholar
  25. Mather AS (1992) The forest transition. Area 24:367–379Google Scholar
  26. Mishra NB, Chaudhuri G (2015) Spatio-temporal analysis of trends in seasonal vegetation productivity across Uttarakhand, Indian Himalayas, 2000-2014. Appl Geogr 56:29–41.  https://doi.org/10.1016/j.apgeog.2014.10.007 CrossRefGoogle Scholar
  27. Mishra NB, Crews KA, Neeti N, Meyer T, Young KR (2015) MODIS derived vegetation greenness trends in African Savanna: deconstructing and localizing the role of changing moisture availability, fire regime and anthropogenic impact. Remote Sens Environ 169:192–204.  https://doi.org/10.1016/j.rse.2015.08.008 CrossRefGoogle Scholar
  28. Moreno MV, Malamud BD, Chuvieco E (2011) Wildfire frequency-area statistics in Spain. Procedia Environ Sci 7:182–187.  https://doi.org/10.1016/j.proenv.2011.07.032 CrossRefGoogle Scholar
  29. Moreno M, Conedera M, Chuvieco E, Pezzatti G (2014) Fire regime changes and major driving forces in Spain from 1968 to 2010. Environ Sci Pol 37:11–22.  https://doi.org/10.1016/j.envsci.2013.08.005 CrossRefGoogle Scholar
  30. Neeti N, Eastman JR (2011) A contextual Mann-Kendall approach for the assessment of trend significance in image time series. Trans Gis 15:599–611.  https://doi.org/10.1111/j.1467-9671.2011.01280.x CrossRefGoogle Scholar
  31. Nunes A, Lourenco L, Meira A (2016) Exploring spatial patterns and drivers of forest fires in Portugal (1980-2014). Sci Total Environ 573:1190–1202.  https://doi.org/10.1016/j.scitotenv.2016.03.121 CrossRefGoogle Scholar
  32. Oliveira SLJ, Pereira JMC, Carreiras JMB (2011) Fire frequency analysis in Portugal (1975-2005), using Landsat-based burnt area maps. Int J Wildland Fire 21:48–60.  https://doi.org/10.1071/WF10131 CrossRefGoogle Scholar
  33. Oliveira TM, Guiomar N, Baptista FO, Pereira JMC, Claro J (2017a) Is Portugal’s forest transition going up in smoke? Land Use Policy 66:214–226.  https://doi.org/10.1016/j.landusepol.2017.04.046 CrossRefGoogle Scholar
  34. Oliveira S, Zêzere JL, Queirós M, Pereira JM (2017b) Assessing the social context of wildfire-affected areas. The case of mainland Portugal. Appl Geogr 88:104–117.  https://doi.org/10.1016/j.apgeog.2017.09.004 CrossRefGoogle Scholar
  35. Padilla M, Vega-Garcia C (2011) On the comparative importance of fire danger rating indices and their integration with spatial and temporal variables for predicting daily human-caused fire occurrences in Spain. Int J Wildland Fire 20:46–58.  https://doi.org/10.1071/Wf09139 CrossRefGoogle Scholar
  36. Parente J, Pereira MG, Amraouri M, Tedim F (2018) Negligent and intentional fires in Portugal: spatial distribution characterization. Sci Total Environ 624:424–437.  https://doi.org/10.1016/j.scitotenv.2017.12.013 CrossRefGoogle Scholar
  37. Pausas JG, Fernandez-Munoz S (2012) Fire regime changes in the Western Mediterranean Basin: from fuel-limited to drought-driven fire regime. Clim Chang 110:215–226.  https://doi.org/10.1007/s10584-011-0060-6 CrossRefGoogle Scholar
  38. Pereira MG, Trigo RM, da Camara CC, Pereira JMC, Leite SM (2005) Synoptic patterns associated with large summer forest fires in Portugal. Agric For Meteorol 129:11–25.  https://doi.org/10.1016/j.agrformet.2004.12.007 CrossRefGoogle Scholar
  39. Rodrigues M, San-Miguel-Ayanz J, Oliveira SLJ, Moreira F, Camia A (2013) An insight into spatial-temporal trends of fire ignitions and burned areas in the European Mediterranean countries. Journal of Earth Science and Engineering 3:497–505Google Scholar
  40. Rodrigues M, Jiménez A, de la Riva J (2016) Analysis of recent spatial–temporal evolution of human driving factors of wildfires in Spain. Nat Hazards 84:2049–2070.  https://doi.org/10.1007/s11069-016-2533-4 CrossRefGoogle Scholar
  41. Ruffault J, Mouillot F (2015) How a new fire-suppression policy can abruptly reshape the fire-weather relationship. Ecosphere 6(10):199.  https://doi.org/10.1890/ES15-00182.1 CrossRefGoogle Scholar
  42. San-Miguel-Ayanz J, Schulte E, Schmuck G, Camia A, Strobl P, Liberta G, Giovando C, Boca R, Sedano F, Kempeneers P, McInerney D, Withmore C, Oliveira SS, Rodrigues M, Durrant T, Corti P, Oehler F, Vilar L, Amatulli G (2012a) Comprehensive monitoring of wildfires in Europe: the European Forest Fire Information System (EFFIS). In: Tiefenbacher J (ed) Approaches to managing disaster - assessing hazards, emergencies and disaster impacts. IntechOpen, London, pp 77–108Google Scholar
  43. San-Miguel-Ayanz J, Rodrigues M, Oliveira SS, Pacheco CK, Moreira F, Duguy B, Camia A (2012b) Land cover change and fire regime in the European Mediterranean Region. In: Moreira et al (eds) Post-fire management and restoration of Southern European forests. Managing Forest Ecosystems, 24.  https://doi.org/10.1007/978-94-007-2208-8_2
  44. Sen PK (1968) Estimates of regression coefficient based on Kendall’s tau. J Am Stat Assoc 63:1379–1389CrossRefGoogle Scholar
  45. Spano D, Camia A (2014) Recent trends in forest fires in Mediterranean areas and associated changes in fire regimes. In: Moreno JM (ed) Forest fires under climate, social and economic changes in Europe, the Mediterranean and other fire–affected areas of the world. FUME: Lessons learned and outlook, pp 6–7Google Scholar
  46. Spinoni J, Naumann G, Vogt J, Barbosa P (2015) European drought climatologies and trends based on a multi-indicator approach. Glob Planet Chang 127:50–57.  https://doi.org/10.1016/j.gloplacha2015.01.012 CrossRefGoogle Scholar
  47. Theil H (1950) A rank-invariant method of linear and polynomial regression analysis. I, II, III. In: Royal Netherlands Academy of Sciences, Amsterdam, pp 386–392, 521–525, 1397–1412Google Scholar
  48. Thrupp LA, Hecht S, Browder J, Lynch OJ, Megateli N, O’Brien W (1997) The diversity and dynamics of shifting cultivation: myths, realities, and policy implications. World Resources Institute, Washington D.CGoogle Scholar
  49. Tonini M, Parente J, Pereira MG (2018) Global assessment of rural–urban interface in Portugal related to land cover changes. Nat Hazards Earth Syst Sci 18:1647–1664.  https://doi.org/10.5194/nhess-18-1647-2018 CrossRefGoogle Scholar
  50. Turco M, Bedia J, Di Liberto F, Fiorucci P, von Hardenberg J, Koutsias N, Llasat MC, Xystrakis F, Provenzale A (2016) Decreasing fires in Mediterranean Europe. PLoS One 11(3):e0150663.  https://doi.org/10.1371/journal.pone.0150663 CrossRefGoogle Scholar
  51. Van Wagner CE (1987) Development and structure of the Canadian Forest Fire Weather Index System. Canadian Forest Service, OttawaGoogle Scholar
  52. Venalainen A, Korhonen N, Hyvarinen O, Koutsias N, Xystrakis F, Urbieta IR, Moreno JM (2014) Temporal variations and change in forest fire danger in Europe for 1960-2012. Nat Hazards Earth Syst Sci 14:1477–1490.  https://doi.org/10.5194/nhess-14-1477-2014 CrossRefGoogle Scholar
  53. Verde JC (2015) Wildfire susceptibility modelling in mainland Portugal. Dissertation, University of LisbonGoogle Scholar
  54. Wang XLL, Swail VR (2001) Changes of extreme wave heights in Northern Hemisphere oceans and related atmospheric circulation regimes. J Clim 14:2204–2221.  https://doi.org/10.1175/1520-0442(2001)014<2204:Coewhi>2.0.Co;2 CrossRefGoogle Scholar
  55. Yang J, Tian HQ, Tao B, Ren W, Kush J, Liu YQ, Wang YH (2014) Spatial and temporal patterns of global burned area in response to anthropogenic and environmental factors: reconstructing global fire history for the 20th and early 21st centuries. J Geophys Res Biogeosci 119:249–263.  https://doi.org/10.1002/2013jg002532 CrossRefGoogle Scholar
  56. Yue S, Wang CY (2002) Regional streamflow trend detection with consideration of both temporal and spatial correlation. Int J Climatol 22:933–946.  https://doi.org/10.1002/joc.781 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Forest Research Centre, School of AgricultureUniversity of LisbonLisbonPortugal
  2. 2.Environmental Remote Sensing Group, Department of Geography and GeologyUniversity of AlcalaAlcalá de HenaresSpain
  3. 3.CEFE, UMR 5175, CNRS-Université de Montpellier-Université Paul Valéry Montpellier, EPHE-IRDMontpellierFrance
  4. 4.Faculty of Earth and Life SciencesVrije Universiteit AmsterdamAmsterdamThe Netherlands

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