Modelling the drivers of natural fire activity: the bias created by cropland fires
İsmail Bekar A B and Çağatay Tavşanoğlu A C
+ Author Affiliations
- Author Affiliations
A Fire Ecology and Seed Research Laboratory, Department of Biology, Hacettepe University, Beytepe TR-06800, Ankara, Turkey.
B Present address: Forest Ecology, Institute of Terrestrial Ecosystems, ETH Zurich, Universitätstrasse 16, CH-8092 Zürich, Switzerland.
C Corresponding author. Email: ctavsan@hacettepe.edu.tr
International Journal of Wildland Fire 26(10) 845-851 https://doi.org/10.1071/WF16183
Submitted: 9 October 2016 Accepted: 18 July 2017 Published: 20 September 2017
Journal Compilation © IAWF 2017 Open Access CC BY-NC-ND
Abstract
Wildland and cropland fires, which differ considerably in fire regime characteristics, have often been evaluated jointly to estimate regional or global fire regimes using satellite-based fire activity data. We hypothesised that excluding cropland fires will change the output of the models regarding the drivers of natural fire activity. We modelled MODIS fire activity data of western and southern Turkey for the years 2000–2015 using binomial generalised linear models in which many climatic, anthropogenic and geographic factors were included as predictor variables. For modelling, we used different datasets created by the exclusion of various cropland and vegetation land cover classes. More fire activity was observed as the number of cropland-dominated cells increased in a dataset. The explained deviance (%) of the binomial GLM differed substantially in the separate datasets for most of the variables. Moreover, excluding croplands gradually from the overall dataset resulted in a substantial decrease in the explained deviance (%) in the models for all variables. The results suggest that cropland fires have a significant effect on the output of fire regime models. Therefore, a clear distinction should be drawn between wildland and cropland fires in such models for a better understanding of natural fire activity.
Additional keywords: agricultural fire, climate, land cover, Mediterranean Basin, Turkey.
References
Abdul Malak D, Pausas JG, Pardo Pascual J, Ruiz LA (2015) Fire recurrence and the dynamics of Enhanced Vegetation Index in a Mediterranean ecosystem. International Journal of Applied Geospatial Research 6, 18–35.| Fire recurrence and the dynamics of Enhanced Vegetation Index in a Mediterranean ecosystem.Crossref | GoogleScholarGoogle Scholar |
Amraoui M, Liberato MLR, Calado TJ, DaCamara CC, Coelho LP, Trigo RM, Gouveia CM (2013) Fire activity over Mediterranean Europe based on information from Meteosat-8. Forest Ecology and Management 294, 62–75.
| Fire activity over Mediterranean Europe based on information from Meteosat-8.Crossref | GoogleScholarGoogle Scholar |
Andreae MO, Merlet P (2001) Emissions of trace gases and aerosols from biomass burning. Global Biogeochemical Cycles 15, 955–966.
| Emissions of trace gases and aerosols from biomass burning.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38XjtV2iuw%3D%3D&md5=1ac0221ddfbbb96a857a32afd6cc7fb5CAS |
Archibald S, Lehmann CER, Gómez-Dans JL, Bradstock RA (2013) Defining pyromes and global syndromes of fire regimes. Proceedings of the National Academy of Sciences of the United States of America 110, 6442–6447.
| Defining pyromes and global syndromes of fire regimes.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXnvVelsb0%3D&md5=6a78b6b6e6e09b0cb78630c53cbf0be6CAS |
Atalay I (1994) ‘Vegetation Geography of Turkey’. (Aegean University Press: İzmir, Turkey)
Bekar İ (2016) The role of anthropogenic and natural factors in shaping recent fire regimes in Mediterranean ecosystems. MSc thesis, Hacettepe University. [In Turkish with English summary]
Benali A, Mota B, Carvalhais N, Oom D, Miller LM, Campagnolo ML (2017) Bimodal fire regimes unveil a global-scale anthropogenic fingerprint. Global Ecology and Biogeography 26, 799–811.
| Bimodal fire regimes unveil a global-scale anthropogenic fingerprint.Crossref | GoogleScholarGoogle Scholar |
Bontemps S, Defourny P, Bogaert E Van, Kalogirou V, Perez JR (2011) GLOBCOVER 2009: Products Description and Validation Report. (Université catholique de Louvain and European Space Agency)
Brown CD, Liu J, Yan G, Johnstone JF (2015) Disentangling legacy effects from environmental filters of postfire assembly of boreal tree assemblages. Ecology 96, 3023–3032.
| Disentangling legacy effects from environmental filters of postfire assembly of boreal tree assemblages.Crossref | GoogleScholarGoogle Scholar |
Bruinsma J (Ed.) (2003) ‘World Agriculture: Towards 2015/2030: an FAO Perspective’. (Earthscan Publishing: London, UK)
Chuvieco E, Giglio L, Justice CO (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 |
Consortium for Spatial Information (2016) Global Aridity and PET Database. Available at http://www.cgiar-csi.org/data/global-aridity-and-pet-database [Verified 1 August 2016]
Csiszar IA, Morisette JT, Giglio L (2006) Validation of active fire detection from moderate-resolution satellite sensors: The MODIS example in Northern Eurasia. IEEE Transactions on Geoscience and Remote Sensing 44, 1757–1764.
| Validation of active fire detection from moderate-resolution satellite sensors: The MODIS example in Northern Eurasia.Crossref | GoogleScholarGoogle Scholar |
Curt T, Borgniet L, Ibanez T, Moron V, Hély C (2015) Understanding fire patterns and fire drivers for setting a sustainable management policy of the New-Caledonian biodiversity hotspot. Forest Ecology and Management 337, 48–60.
| Understanding fire patterns and fire drivers for setting a sustainable management policy of the New-Caledonian biodiversity hotspot.Crossref | GoogleScholarGoogle Scholar |
Ganteaume A, Camia A, Jappiot M, San-Miguel-Ayanz J, Long-Fournel M, Lampin C (2013) A review of the main driving factors of forest fire ignition over Europe. Environmental Management 51, 651–662.
| A review of the main driving factors of forest fire ignition over Europe.Crossref | GoogleScholarGoogle Scholar |
Giglio L, Descloitres J, Justice CO, Kaufman Y (2003) An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment 87, 273–282.
| An enhanced contextual fire detection algorithm for MODIS.Crossref | GoogleScholarGoogle Scholar |
Giglio L, van der Werf GR, Randerson JT, Collatz GJ, Kasibhatla P (2006) Global estimation of burned area using MODIS active fire observations. Atmospheric Chemistry and Physics Discussion 5, 11091–11141.
| Global estimation of burned area using MODIS active fire observations.Crossref | GoogleScholarGoogle Scholar |
Godfray HCJ, Beddington JR, Crute IR, Haddad L, Lawrence D, Muir JF, Pretty J, Robinson S, Thomas SM, Toulmin C (2010) Food security: the challenge of feeding 9 billion people. Science 327, 812–818.
| Food security: the challenge of feeding 9 billion people.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXhslWisLo%3D&md5=8d31cafd84574a5639e5711cd4839bf9CAS |
Guisan A, Edwards TC, Hastie T (2002) Generalized linear and generalized additive models in studies of species distributions: setting the scene. Ecological Modelling 157, 89–100.
| Generalized linear and generalized additive models in studies of species distributions: setting the scene.Crossref | GoogleScholarGoogle Scholar |
Haklay M, Weber P (2008) OpenStreetMap: user-generated street maps. IEEE Pervasive Computing 7, 12–18.
| OpenStreetMap: user-generated street maps.Crossref | GoogleScholarGoogle Scholar |
Hall JV, Loboda TV, Giglio L, McCarty GW (2016) A MODIS-based burned area assessment for Russian croplands: Mapping requirements and challenges. Remote Sensing of Environment 184, 506–521.
| A MODIS-based burned area assessment for Russian croplands: Mapping requirements and challenges.Crossref | GoogleScholarGoogle Scholar |
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.
| Very high resolution interpolated climate surfaces for global land areas.Crossref | GoogleScholarGoogle Scholar |
Jackman S, Tahk A, Zeileis A, Maimone C, Fearon J, Jackman MS (2015) Package ‘pscl’. Available at https://cran.r-project.org/web/packages/pscl/index.html [Verified 1 August 2016]
Jarvis A, Reuter A, Nelson EG (2008) CSI SRTM 90m Database. Available at http://srtm.csi.cgiar.org [Verified 1 August 2016]
Justice CO, Giglio L, Korontzi S, Owens J, Morisette JT, Roy DP, Descloitres J, Alleaume S, Petitcolin F, Kaufman Y (2002) The MODIS fire products. Remote Sensing of Environment 83, 244–262.
| The MODIS fire products.Crossref | GoogleScholarGoogle Scholar |
Kaniewski D, De Laet V, Paulissen E, Waelkens M (2007) Long-term effects of human impact on mountainous ecosystems, western Taurus Mountains, Turkey. Journal of Biogeography 34, 1975–1997.
| Long-term effects of human impact on mountainous ecosystems, western Taurus Mountains, Turkey.Crossref | GoogleScholarGoogle Scholar |
Kaniewski D, Paulissen E, De Laet V, Waelkens M (2008) Late Holocene fire impact and post-fire regeneration from the Bereket basin, Taurus Mountains, southwest Turkey. Quaternary Research 70, 228–239.
| Late Holocene fire impact and post-fire regeneration from the Bereket basin, Taurus Mountains, southwest Turkey.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 |
Korontzi S, McCarty J, Loboda T, Kumar S, Justice C (2006) Global distribution of agricultural fires in croplands from 3 years of Moderate Resolution Imaging Spectroradiometer (MODIS) data. Global Biogeochemical Cycles 20, GB2021
| Global distribution of agricultural fires in croplands from 3 years of Moderate Resolution Imaging Spectroradiometer (MODIS) data.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
| Global pyrogeography: the current and future distribution of wildfire.Crossref | GoogleScholarGoogle Scholar |
Le Page Y, Oom D, Silva JMN, Jönsson P, Pereira JMC (2010) Seasonality of vegetation fires as modified by human action: Observing the deviation from eco-climatic fire regimes. Global Ecology and Biogeography 19, 575–588.
| Seasonality of vegetation fires as modified by human action: Observing the deviation from eco-climatic fire regimes.Crossref | GoogleScholarGoogle Scholar |
Leone V, Lovreglio R, Martín MP, Martínez J, Vilar L (2009) Human factors of fire occurrence in the Mediterranean. In ‘Earth Observation of Wildland Fires in Mediterranean Ecosystems’. (Ed. E Chuvieco) pp. 149–170. (Springer: Berlin)
Li H, Han Z, Cheng T, Du H, Kong L, Chen J, Zhang R, Wang W (2010) Agricultural fire impacts on the air quality of Shanghai during summer harvest time. Aerosol and Air Quality Research 10, 95–101.
| Agricultural fire impacts on the air quality of Shanghai during summer harvest time.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXpvFKltrk%3D&md5=87fb00f8d42e29bb96875ff68953e1bbCAS |
Magi BI, Rabin S, Shevliakova E, Pacala S (2012) Separating agricultural and non-agricultural fire seasonality at regional scales. Biogeosciences 9, 3003–3012.
| Separating agricultural and non-agricultural fire seasonality at regional scales.Crossref | GoogleScholarGoogle Scholar |
McCarty JL (2011) Remote sensing-based estimates of annual and seasonal emissions from crop residue burning in the contiguous United States. Journal of the Air & Waste Management Association (1995) 61, 22–34.
| Remote sensing-based estimates of annual and seasonal emissions from crop residue burning in the contiguous United States.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXhsFOqsLc%3D&md5=f0e9e24b4de53788de85263e0bce300bCAS |
McCarty JL, Ellicott EA, Romanenkov V, Rukhovitch D, Koroleva P (2012) Multi-year black carbon emissions from cropland burning in the Russian Federation. Atmospheric Environment 63, 223–238.
| Multi-year black carbon emissions from cropland burning in the Russian Federation.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38Xhs1SrurnL&md5=c637a2632116115af3e26b0b2a23c303CAS |
Murphy BP, Bradstock RA, Boer MM, Carter J, Cary GJ, Cochrane MA, Fensham R, Russell-Smith J, Williamson GJ, Bowman DMJS (2013) Fire regimes of Australia: A pyrogeographic model system. Journal of Biogeography 40, 1048–1058.
| Fire regimes of Australia: A pyrogeographic model system.Crossref | GoogleScholarGoogle Scholar |
National Aeronautics and Space Administration (2016) Vegetation Index. Available at http://go.nasa.gov/1UMSkgb [Verified 31 July 2016]
O’Hara RB, Kotze DJ (2010) Do not log-transform count data. Methods in Ecology and Evolution 1, 118–122.
| Do not log-transform count data.Crossref | GoogleScholarGoogle Scholar |
Pausas JG, Ribeiro E (2013) The global fire-productivity relationship. Global Ecology and Biogeography 22, 728–736.
| The global fire-productivity relationship.Crossref | GoogleScholarGoogle Scholar |
Pekin BK (2016) Anthropogenic and topographic correlates of natural vegetation cover within agricultural landscape mosaics in Turkey. Land Use Policy 54, 313–320.
| Anthropogenic and topographic correlates of natural vegetation cover within agricultural landscape mosaics in Turkey.Crossref | GoogleScholarGoogle Scholar |
Rabin SS, Magi BI, Shevliakova E, Pacala SW (2015) Quantifying regional, time-varying effects of cropland and pasture on vegetation fire. Biogeosciences 12, 6591–6604.
| Quantifying regional, time-varying effects of cropland and pasture on vegetation fire.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2sXms1GksLk%3D&md5=3bcbf55fc7213e407ba33ff7b7365af3CAS |
Şekercioğlu ÇH, Anderson S, Akçay E, Bilgin R, Can ÖE, Semiz G, Tavşanoğlu Ç, Yokeş MB, Soyumert A, İpekdal K, Sağlam İK, Yücel M, Nüzhet DH (2011) Turkey’s globally important biodiversity in crisis. Biological Conservation 144, 2752–2769.
| Turkey’s globally important biodiversity in crisis.Crossref | GoogleScholarGoogle Scholar |
Stohl A, Berg T, Burkhart JF, Fjæraa AM, Forster C, Herber A, Hov Ø, Lunder C, McMillan WW, Oltmans S, Shiobara M, Simpson D, Solberg S, Stebel K, Ström J, Tørseth K, Treffeisen R, Virkkunen K, Yttri KE (2006) Arctic smoke – record high air pollution levels in the European Arctic due to agricultural fires in Eastern Europe. Atmospheric Chemistry and Physics Discussion 6, 9655–9722.
| Arctic smoke – record high air pollution levels in the European Arctic due to agricultural fires in Eastern Europe.Crossref | GoogleScholarGoogle Scholar |
Tilman D, Balzer C, Hill J, Befort BL (2011) Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences of the United States of America 108, 20260–20264.
| Global food demand and the sustainable intensification of agriculture.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXhs1yqsbnM&md5=5463db0f9e045deddb31796ed9bcf0c6CAS |
Tulbure MG, Wimberly MC, Roy DP, Henebry GM (2011) Spatial and temporal heterogeneity of agricultural fires in the central United States in relation to land cover and land use. Landscape Ecology 26, 211–224.
| Spatial and temporal heterogeneity of agricultural fires in the central United States in relation to land cover and land use.Crossref | GoogleScholarGoogle Scholar |
Turner R, Roberts N, Eastwood WJ, Jenkins E, Rosen A (2010) Fire, climate and the origins of agriculture: Micro-charcoal records of biomass burning during the last glacial-interglacial transition in Southwest Asia. Journal of Quaternary Science 25, 371–386.
| Fire, climate and the origins of agriculture: Micro-charcoal records of biomass burning during the last glacial-interglacial transition in Southwest Asia.Crossref | GoogleScholarGoogle Scholar |
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=a817c81d5376e1166c2fb915665887eeCAS |
Xie H, Du L, Liu S, Chen L, Gao S, Liu S, Pan H, Tong X (2016) Dynamic monitoring of agricultural fires in China from 2010 to 2014 using MODIS and GlobeLand30 data. ISPRS International Journal of Geo-Information 5, 172
| Dynamic monitoring of agricultural fires in China from 2010 to 2014 using MODIS and GlobeLand30 data.Crossref | GoogleScholarGoogle Scholar |
Zeileis A, Kleiber C, Jackman S (2008) Regression models for count data in R. Journal of Statistical Software 27, 1–25.
| Regression models for count data in R.Crossref | GoogleScholarGoogle Scholar |
Zhu Z, Woodcock CE (2012) Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment 118, 83–94.
| Object-based cloud and cloud shadow detection in Landsat imagery.Crossref | GoogleScholarGoogle Scholar |
