Anthropogenic effects on global mean fire size
Stijn Hantson A B D , Gitta Lasslop C , Silvia Kloster C and Emilio Chuvieco A
+ Author Affiliations
- Author Affiliations
A Environmental Remote Sensing Research Group, Department of Geology, Geography and Environment, University of Alcala, C/ Colegios 2, 28801 Alcala de Henares, Spain.
B Institute of Meteorology and Climate Research/Atmospheric Environmental Research (IMK/IFU), Karlsruhe Institute of Technology, 82467 Garmisch-Partenkirchen, Germany.
C Max Planck Institute for Meteorology, Land in the Earth System, Bundesstr. 53, 20146 Hamburg, Germany.
D Corresponding author. Email: stijn.hantson@kit.edu
International Journal of Wildland Fire 24(5) 589-596 https://doi.org/10.1071/WF14208
Submitted: 20 March 2014 Accepted: 20 February 2015 Published: 15 June 2015
Abstract
Wildland fires are an important agent in the earth’s system. Multiple efforts are currently in progress to better represent wildland fires in earth system models. Although wildland fires are a natural disturbance factor, humans have an important effect on fire occurrence by directly igniting and suppressing fires and indirectly influencing fire behaviour by changing land cover and landscape structure. Although these factors are recognised, their quantitative effect on fire growth and burned area are not well understood and therefore only partly taken into account in current process-based fire models. Here we analyse the influence of humans on mean fire size globally. The mean fire size was extracted from the global Moderate Resolution Imaging Spectroradiometer (MODIS) burned area product MCD45. We found a linear decreasing trend between population density and observed mean fire size over the globe, as well as a negative effect of cropland cover and net income. We implemented the effect of population density on fire growth in a global vegetation model including a process-based fire model (SPITFIRE–JSBACH). When including this demographic control, spatial trends in modelled fraction of burned area generally improved when compared with satellite-derived burned area data. More process-based solutions to limit fire spread are needed in the future, but the empirical relations described here serve as an intermediate step to improve current fire models.
Additional keywords: fire model, fragmentation, land use, JSBACH, SPITFIRE, wildland fire.
References
Amraoui M, DaCamara CC, Pereira JMC (2010) Detection and monitoring of African vegetation fires using MSG-SEVIRI imagery. Remote Sensing of Environment 114, 1038–1052.| Detection and monitoring of African vegetation fires using MSG-SEVIRI imagery.Crossref | GoogleScholarGoogle Scholar |
Archibald S, Roy DP (2009) Identifying individual fires from satellite-derived burned area data. In ‘2009 IEEE International Geoscience and Remote Sensing Symposium’, 12–17 July 2009, Cape Town, South Africa. Vol. 3 pp. III-160–III-163. (Institute of Electrical and Electronics Engineers: Piscataway, NJ)
Archibald S, Scholes RJ, Roy DP, Roberts G, Boschetti L (2010) Southern African fire regimes as revealed by remote sensing. International Journal of Wildland Fire 19, 861–878.
| Southern African fire regimes as revealed by remote sensing.Crossref | GoogleScholarGoogle Scholar |
Bak P, Tang C, Wiesenfeld K (1987) Self-organized criticality: an explanation of the 1/f noise. Physical Review Letters 59, 381–384.
| Self-organized criticality: an explanation of the 1/f noise.Crossref | GoogleScholarGoogle Scholar | 10035754PubMed |
Bistinas I, Harrison S, Prentice I, Pereira J (2014) Causal relationships versus emergent patterns in the global controls of fire frequency. Biogeosciences 11, 5087–5101.
| Causal relationships versus emergent patterns in the global controls of fire frequency.Crossref | GoogleScholarGoogle Scholar |
Bond WJ, Woodward FI, Midgley GF (2005) The global distribution of ecosystems in a world without fire. New Phytologist 165, 525–538.
| The global distribution of ecosystems in a world without fire.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD2M%2Fpt1OktQ%3D%3D&md5=e841393c065742821621e1b15ab1c8a2CAS | 15720663PubMed |
Bond-Lamberty B, Peckham SD, Ahl DE, Gower ST (2007) Fire as the dominant driver of central Canadian boreal forest carbon balance. Nature 450, 89–92.
| Fire as the dominant driver of central Canadian boreal forest carbon balance.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXht1CgtbnJ&md5=58318c29cd7cf56f3302d7153f7f6194CAS | 17972883PubMed |
Boschetti L, Roy DP, Justice CO, Giglio L (2010) Global assessment of the temporal reporting accuracy and precision of the MODIS burned area product. International Journal of Wildland Fire 19, 705–709.
| Global assessment of the temporal reporting accuracy and precision of the MODIS burned area product.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXhtFOkur%2FO&md5=4bbee89edd2e2be2be46e921863e70ecCAS |
Bowman DMJS, Balch JK, Artaxo P, Bond WJ, Carlson JM, Cochrane MA, D’Antonio CA, DeFries RS, Doyle JC, Harrison SP, Johnston FH, Keeley JE, Krawchuk MA, Kull CA, Marston JB, Moritz MA, Prentice IC, Roos CI, Scott AC, Swetnam TW, van der Werf GR, Pyne SJ (2009) Fire in the Earth System. Science 324, 481–484.
| Fire in the Earth System.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXkvVGmtb8%3D&md5=acf0f16875fe2576863ea8a4f6d043c7CAS |
Chuvieco E, Giglio L, Justice C (2008) Global characterization of fire activity: toward defining fire regimes from Earth observation data. Global Change Biology 14, 1488–1502.
| Global characterization of fire activity: toward defining fire regimes from Earth observation data.Crossref | GoogleScholarGoogle Scholar |
DeWilde L, Chapin FS (2006) Human impacts on the fire regime of interior Alaska: interactions among fuels, ignition sources, and fire suppression. Ecosystems 9, 1342–1353.
| Human impacts on the fire regime of interior Alaska: interactions among fuels, ignition sources, and fire suppression.Crossref | GoogleScholarGoogle Scholar |
Drossel B, Schwabl F (1992) Self-organized critical forest-fire model. Physical Review Letters 69, 1629–1632.
| Self-organized critical forest-fire model.Crossref | GoogleScholarGoogle Scholar | 10046273PubMed |
Giglio L, Randerson JT, van der Werf G, Kasibhatla PS, Collatz GJ, Morton DC, DeFries RS (2010) Assessing variability and long-term trends in burned area by merging multiple satellite fire products. Biogeosciences 7, 1171–1186.
| Assessing variability and long-term trends in burned area by merging multiple satellite fire products.Crossref | GoogleScholarGoogle Scholar |
Giorgetta MA, Jungclaus J, Reick CH, Legutke S, Bader J, Böttinger M, Brovkin V, Crueger T, Esch M, Fieg K, Glushak K, Gayler V, Haak H, Hollweg HD, Ilyina T, Kinne S, Kornblueh L, Matei D, Mauritsen T, Mikolajewicz U, Mueller W, Notz D, Pithan F, Raddatz T, Rast S, Redler R, Roeckner E, Schmidt H, Schnur R, Segschneider J, Six KD, Stockhause M, Timmreck C, Wegner J, Widmann H, Wieners KH, Claussen M, Marotzke J, Stevens B (2013) Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5. Journal of Advances in Modeling Earth Systems 5, 572–597.
| Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5.Crossref | GoogleScholarGoogle Scholar |
Goldewijk KK (2001) Estimating global land use change over the past 300 years. Global Biogeochemical Cycles 15, 417–433.
| Estimating global land use change over the past 300 years.Crossref | GoogleScholarGoogle Scholar |
Hansen M, DeFries R, Townshend J, Carroll M, Dimiceli C, Sohlberg R (2003) Global percent tree cover at a spatial resolution of 500 meters: first results of the MODIS vegetation continuous fields algorithm. Earth Interactions 7, 1–15.
| Global percent tree cover at a spatial resolution of 500 meters: first results of the MODIS vegetation continuous fields algorithm.Crossref | GoogleScholarGoogle Scholar |
Hantson S, Pueyo S, Chuvieco E (2015) Global fire size distribution is driven by human impact and climate. Global Ecology and Biogeography 24, 77–86.
| Global fire size distribution is driven by human impact and climate.Crossref | GoogleScholarGoogle Scholar |
Hurtt GC, Chini LP, Frolking S, Betts RA, Feddema J, Fischer G, Fisk JP, Hibbard K, Houghton RA, Janetos A, Jones CD, Kindermann G, Kinoshita T, Klein Goldewijk K, Riahi K, Shevliakova E, Smith S, Stehfest E, Thomson A, Thornton P, van Vuuren DP, Wang YP (2011) Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. Climatic Change 109, 117–161.
| Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands.Crossref | GoogleScholarGoogle Scholar |
Kantzas E, Lomas M, Quegan S (2013) Fire at high latitudes: data–model comparisons and their consequences. Global Biogeochemical Cycles 27, 677–691.
| Fire at high latitudes: data–model comparisons and their consequences.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhs1SgtrvM&md5=5bc8654e34339f0683e9a8636a5e80f4CAS |
Kloster S, Mahowald NM, Randerson JT, Thornton PE, Hoffman FM, Levis S, Lawrence PJ, Feddema JJ, Oleson KW, Lawrence DM (2010) Fire dynamics during the 20th century simulated by the Community Land Model. Biogeosciences 7, 1877–1902.
| Fire dynamics during the 20th century simulated by the Community Land Model.Crossref | GoogleScholarGoogle Scholar |
Kloster S, Mahowald NM, Randerson JT, Lawrence PJ (2012) The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN. Biogeosciences 9, 509–525.
| The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN.Crossref | GoogleScholarGoogle Scholar |
Knorr W, Kaminski T, Arneth A, Weber U (2014) Impact of human population density on fire frequency at the global scale. Biogeosciences 11, 1085–1102.
| Impact of human population density on fire frequency at the global scale.Crossref | GoogleScholarGoogle Scholar |
Krawchuk MA, Moritz MA, Parisien MA, Van Dorn J, Hayhoe K (2009) Global pyrogeography: the current and future distribution of wildfire. PLoS ONE 4, e5102
Lasslop G, Kloster S, Thonicke K. (2014) SPITFIRE within the MPI Earth system model: model development and evaluation. Journal of Advances in Modeling Earth Systems 6, 740–755.
| SPITFIRE within the MPI Earth system model: model development and evaluation.Crossref | GoogleScholarGoogle Scholar |
Li F, Zeng X, Levis S (2012) A process-based fire parameterization of intermediate complexity in a Dynamic Global Vegetation Model. Biogeosciences 9, 2761–2780.
| A process-based fire parameterization of intermediate complexity in a Dynamic Global Vegetation Model.Crossref | GoogleScholarGoogle Scholar |
Lloret F, Calvo E, Pons X, Díaz-Delgado R (2002) Wildfires and landscape patterns in the eastern Iberian peninsula. Landscape Ecology 17, 745–759.
| Wildfires and landscape patterns in the eastern Iberian peninsula.Crossref | GoogleScholarGoogle Scholar |
Minnich RA (1983) Fire mosaics in southern California and northern Baja California. Science 219, 1287–1294.
| Fire mosaics in southern California and northern Baja California.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC3cvhvVymsQ%3D%3D&md5=ded9817f4a68522eb92f484caa757678CAS | 17735593PubMed |
Padilla M, Stehman SV, Ramo R, Corti D, Hantson S, Oliva P, Alonso-Canas I, Bradley AV, Tansey K, Mota B, Pereira JM, Chuvieco E (2015) Comparing the accuracies of remote sensing global burned area products using stratified random sampling and estimation. Remote sensing of environment
| Comparing the accuracies of remote sensing global burned area products using stratified random sampling and estimation.Crossref | GoogleScholarGoogle Scholar |
Pausas J, Fernández-Muñoz S (2012) Fire regime changes in the western Mediterranean basin: from fuel-limited to drought-driven fire regime. Climatic Change 110, 215–226.
| Fire regime changes in the western Mediterranean basin: from fuel-limited to drought-driven fire regime.Crossref | GoogleScholarGoogle Scholar |
Pfeiffer M, Spessa A, Kaplan J (2013) A model for global biomass burning in preindustrial time: Lpj-lmfire (v1. 0). Geoscientific Model Development 6, 643–685.
| A model for global biomass burning in preindustrial time: Lpj-lmfire (v1. 0).Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2MXkvFKruro%3D&md5=424fd2ef166794ecc504355519b8408dCAS |
Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team (2014). nlme: linear and nonlinear mixed effects models. R package version 3.1–117.
Pueyo S (2007) Self-organised criticality and the response of wildland fires to climate change. Climatic Change 82, 131–161.
| Self-organised criticality and the response of wildland fires to climate change.Crossref | GoogleScholarGoogle Scholar |
Pueyo S, Graça PMLdA, Barbosa RI, Cots R, Cardona E, Fearnside PM (2010) Testing for criticality in ecosystem dynamics: the case of Amazonian rainforest and savanna fire. Ecology Letters 13, 793–802.
| Testing for criticality in ecosystem dynamics: the case of Amazonian rainforest and savanna fire.Crossref | GoogleScholarGoogle Scholar | 20528900PubMed |
Raddatz TJ, Reick CH, Knorr W, Kattge J, Roeckner E, Schnur R, Schnitzler KG, Wetzel P, Jungclaus J (2007) Will the tropical land biosphere dominate the climate carbon cycle feedback during the twenty-first century? Climate Dynamics 29, 565–574.
| Will the tropical land biosphere dominate the climate carbon cycle feedback during the twenty-first century?Crossref | GoogleScholarGoogle Scholar |
Ramankutty N, Evan AT, Monfreda C, Foley JA (2008) Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Global Biogeochemical Cycles 22, GB1003
| Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000.Crossref | GoogleScholarGoogle Scholar |
Rothermel RC (1972) A mathematical model for predicting fire spread in wildland fuels, USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Paper INT-115 (Ogden, Utah).
Roy DP, Boschetti L (2009) Southern Africa validation of the MODIS, L3JRC, and GlobCarbon burned-area products. IEEE Transactions on Geoscience and Remote Sensing 47, 1032–1044.
| Southern Africa validation of the MODIS, L3JRC, and GlobCarbon burned-area products.Crossref | GoogleScholarGoogle Scholar |
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.
| The collection 5 MODIS burned area product – global evaluation by comparison with the MODIS active fire product.Crossref | GoogleScholarGoogle Scholar |
Running SW, Nemani RR, Heinsch FA, Zhao M, Reeves M, Hashimoto H (2004) A continuous satellite-derived measure of global terrestrial primary production. Bioscience 54, 547–560.
| A continuous satellite-derived measure of global terrestrial primary production.Crossref | GoogleScholarGoogle Scholar |
Scott JH, Burgan RE (2005) Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire spread model. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-153. (Fort Collins, CO). Available at http://digitalcommons.usu.edu/barkbeetles/66/ [verified 6 March 2015].
Small C, Cohen JE (2004) Continental physiography, climate, and the global distribution of human population. Current Anthropology 45, 269–277.
| Continental physiography, climate, and the global distribution of human population.Crossref | GoogleScholarGoogle Scholar |
Thonicke K, Venevsky S, Sitch S, Cramer W (2001) The role of fire disturbance for global vegetation dynamics: coupling fire into a Dynamic Global Vegetation Model. Global Ecology and Biogeography 10, 661–677.
| The role of fire disturbance for global vegetation dynamics: coupling fire into a Dynamic Global Vegetation Model.Crossref | GoogleScholarGoogle Scholar |
Thonicke K, Spessa A, Prentice IC, Harrison SP, Dong L, Carmona-Moreno C (2010) The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: results from a process-based model. Biogeosciences 7, 1991–2011.
| The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: results from a process-based model.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXhtl2ksrvE&md5=f63babcbab3afc9c431d99c4b2d510deCAS |
van der Werf GR, Randerson JT, Giglio L, Collatz GJ, Mu M, Kasibhatla PS, Morton DC, DeFries RS, Jin Y, van Leeuwen TT (2010) Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009). Atmospheric Chemistry and Physics 10, 11707–11735.
| Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009).Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXmvFemsb0%3D&md5=e4141b6bc1ec84d7e5ca7cc2873c78beCAS |
Yue C, Ciais P, Cadule P, Thonicke K, Archibald S, Poulter B, Hao WM, Hantson S, Mouillot F, Friedlingstein P, Maignan F, Viovy N (2014) Modelling fires in the terrestrial carbon balance by incorporating spitfire into the global vegetation model orchidee – Part 1: simulating historical global burned area and fire regimes. Geoscientific Model Development 7, 2747–2767.
| Modelling fires in the terrestrial carbon balance by incorporating spitfire into the global vegetation model orchidee – Part 1: simulating historical global burned area and fire regimes.Crossref | GoogleScholarGoogle Scholar |
