Cross-regional modelling of fire occurrence in the Alps and the Mediterranean Basin
İsmail Bekar
A F , Çağatay Tavşanoğlu B , G. Boris Pezzatti C , Harald Vacik D , Juli G. Pausas E , Harald Bugmann A and Gunnar Petter A
+ Author Affiliations
- Author Affiliations
A Forest Ecology, Institute of Terrestrial Ecosystems, Swiss Federal Institute of Technology, ETH Zurich, Universitätstrasse 16, 8092 Zürich, Switzerland.
B Division of Ecology, Department of Biology, Hacettepe University, Beytepe 06800, Ankara, Turkey.
C Insubric Ecosystems Research Group, Swiss Federal Research Institute for forest, snow and landscape research WSL, Campus Cadenazzo, A Ramel 18, 6593 Cadenazzo, Switzerland.
D Institute of Silviculture, University of Natural Resources and Life Sciences (BOKU), Peter Jordan Str. 82, 1190 Vienna, Austria.
E Centro de Investigaciones sobre Desertificación, Consejo Superior de Investigaciones Científicas (CIDE-CSIC), 46113 Valencia, Spain.
F Corresponding author. Email: ibekar@ethz.ch
International Journal of Wildland Fire 29(8) 712-722 https://doi.org/10.1071/WF19158
Submitted: 1 October 2019 Accepted: 9 March 2020 Published: 6 April 2020
Abstract
In recent decades, changes in fire activity have been observed in Europe. Fires can have large consequences for the provisioning of ecosystem services and for human well-being. Therefore, understanding the drivers of fire occurrence and improving the predictive capability of fire occurrence models is of utmost importance. So far, most studies have focused on individual regions with rather low spatial resolution, and have lacked the ability to apply the models in different regions. Here, a species distribution modelling approach (Maxent) was used to model fire occurrence in four regions across the Mediterranean Basin and the Alps using several environmental variables at two spatial resolutions. Additionally, a cross-regional model was developed and spatial transferability tested. Most models showed good performance, with fine resolution models always featuring somewhat higher performance than coarse resolution models. When transferred across regions, the performance of regional models was good only under similar environmental conditions. The cross-regional model showed a higher performance than the regional models in the transfer tests. The results suggest that a cross-regional approach is most robust when aiming to use fire occurrence models at the regional scale but beyond current environmental conditions, for example in scenario analyses of the impacts of climate change.
Additional keywords: fire ignition, grain size, Maxent, spatial resolution, species distribution model.
References
Arndt N, Vacik H, Koch V, Arpaci A, Gossow H (2013) Modeling human-caused forest fire ignition for assessing forest fire danger in Austria. IForest 6, 315–325.| Modeling human-caused forest fire ignition for assessing forest fire danger in Austria.Crossref | GoogleScholarGoogle Scholar |
Arpaci A, Malowerschnig B, Sass O, Vacik H (2014) Using multi variate data mining techniques for estimating fire susceptibility of Tyrolean forests. Applied Geography 53, 258–270.
| Using multi variate data mining techniques for estimating fire susceptibility of Tyrolean forests.Crossref | GoogleScholarGoogle Scholar |
Bekar İ (2016) Akdeniz ekosistemlerinde günümüz yangin rejimlerinin şekillenmesinde doğal ve antropojen faktörlerin rolü. Translated title: The role of anthropogenic and natural factors in shaping recent fire regimes in Mediterranean ecosystems. M.Sc. Thesis, Hacettepe University, Ankara, Turkey. [In Turkish] Available at http://www.openaccess.hacettepe.edu.tr:8080/xmlui/handle/11655/4914 [Verified March 2020]
Bekar İ, Tavşanoğlu Ç (2017) Modelling the drivers of natural fire activity: the bias created by cropland fires. International Journal of Wildland Fire 26, 845–851.
| Modelling the drivers of natural fire activity: the bias created by cropland fires.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 | 15720663PubMed |
Camp PE, Krawchuk MA (2017) Spatially varying constraints of human-caused fire occurrence in British Columbia, Canada. International Journal of Wildland Fire 26, 219–229.
| Spatially varying constraints of human-caused fire occurrence in British Columbia, Canada.Crossref | GoogleScholarGoogle Scholar |
Cardille JA, Ventura SJ, Turner MG (2001) Environmental and social factors influencing wildfires in the Upper Midwest, United States. Ecological Applications 11, 111–127.
| Environmental and social factors influencing wildfires in the Upper Midwest, United States.Crossref | GoogleScholarGoogle Scholar |
Chergui B, Fahd S, Santos X, Pausas JG (2017) Socioeconomic factors drive fire-regime variability in the Mediterranean Basin. Ecosystems 21, 1–10.
Conedera M, Tonini M, Oleggini L, Vega Orozco C, Leuenberger M, Pezzatti GB (2015) Geospatial approach for defining the wildland–urban interface in the alpine environment. Computers, Environment and Urban Systems 52, 10–20.
| Geospatial approach for defining the wildland–urban interface in the alpine environment.Crossref | GoogleScholarGoogle Scholar |
Conedera M, Krebs P, Valese E, Cocca G, Schunk C, Menzel A, Vacik H, Cane D, Japelj A, Muri B, Ricotta C, Oliveri S, Pezzatti GB (2018) Characterizing alpine pyrogeography from fire statistics. Applied Geography 98, 87–99.
| Characterizing alpine pyrogeography from fire statistics.Crossref | GoogleScholarGoogle Scholar |
De Angelis A, Ricotta C, Conedera M, Pezzatti GB (2015) Modelling the meteorological forest fire niche in heterogeneous pyrologic conditions. PLoS One 10, e0116875
| Modelling the meteorological forest fire niche in heterogeneous pyrologic conditions.Crossref | GoogleScholarGoogle Scholar | 25679957PubMed |
Dimitrakopoulos AP, Vlahou M, Anagnostopoulou CG, Mitsopoulos ID (2011) Impact of drought on wildland fires in Greece: implications of climatic change? Climatic Change 109, 331–347.
| Impact of drought on wildland fires in Greece: implications of climatic change?Crossref | GoogleScholarGoogle Scholar |
Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annual Review of Ecology Evolution and Systematics 40, 677–697.
| Species distribution models: ecological explanation and prediction across space and time.Crossref | GoogleScholarGoogle Scholar |
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.
| Novel methods improve prediction of species’ distributions from occurrence data.Crossref | GoogleScholarGoogle Scholar |
Fick SE, Hijmans RJ (2017) WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37, 4302–4315.
| WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas.Crossref | GoogleScholarGoogle Scholar |
Gottschalk TK, Aue B, Hotes S, Ekschmitt K (2011) Influence of grain size on species-habitat models. Ecological Modelling 222, 3403–3412.
| Influence of grain size on species-habitat models.Crossref | GoogleScholarGoogle Scholar |
Grima N (2011) Forest fire hazard mapping in Carinthia (Southern Austria). M.Sc. Thesis, University of Natural Resources and Applied Life Sciences (BOKU), Vienna. Available at http://bit.ly/2EwTETb [Verified March 2020]
Guisan A, Zimmermann NE (2000) Predictive habitat distribution models in ecology. Ecological Modelling 135, 147–186.
| Predictive habitat distribution models in ecology.Crossref | GoogleScholarGoogle Scholar |
Guisan A, Graham CH, Elith J, Huettmann F, Dudik M, Ferrier S, Hijmans R, Lehmann A, Li J, Lohmann LG, Loiselle B, Manion G, Moritz C, Nakamura M, Nakazawa Y, Overton JMC, Peterson AT, Phillips SJ, Richardson K, Scachetti-Pereira R, Schapire RE, Williams SE, Wisz MS, Zimmermann NE (2007a) Sensitivity of predictive species distribution models to change in grain size. Diversity & Distributions 13, 332–340.
| Sensitivity of predictive species distribution models to change in grain size.Crossref | GoogleScholarGoogle Scholar |
Guisan AA, Zimmermann NE, Elith J, Graham CH, Phillips S, Guisan A, Zimmermann NE, Elith J, Graham CH, Phillips S, Peterson AT (2007b) What matters for predicting the occurrences of trees: techniques, data, or species’ characteristics? Ecological Monographs 77, 615–630.
| What matters for predicting the occurrences of trees: techniques, data, or species’ characteristics?Crossref | GoogleScholarGoogle Scholar |
Haklay M, Weber P (2008) OpenStreetMap: user-generated street maps. Pervasive Computing 7, 12–18.
| OpenStreetMap: user-generated street maps.Crossref | GoogleScholarGoogle Scholar |
Hanberry BB (2013) Finer grain size increases effects of error and changes influence of environmental predictors on species distribution models. Ecological Informatics 15, 8–13.
| Finer grain size increases effects of error and changes influence of environmental predictors on species distribution models.Crossref | GoogleScholarGoogle Scholar |
Hijmans RJ, Phillips S, Leathwick J, Elith J (2017) ‘dismo: species distribution modeling.’ R package version 1.1–4. Available at https://cran.r-project.org/web/packages/dismo/index.html [Verified March 2020]
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. Nature Communications 6, 7537
| Climate-induced variations in global wildfire danger from 1979 to 2013.Crossref | GoogleScholarGoogle Scholar | 26172867PubMed |
Koutsias N, Martínez-Fernández J, Chuvieco E, Allgöwer B (2005) Modelling wildland fire occurrence in southern Europe by geographically weighted regression approach. In ‘Proceedings of the 5th International Workshop on Remote Sensing and GIS Applications to Forest Fire Management: Fire Effects Assessment’, 16–18 June 2005, Zaragoza, Spain. (Eds J De La Riva, F Pérez-Cabello, E Chuvieco) pp. 57–60. (Universidad de Zaragoza: Zaragoza, Spain)
Koutsias N, Martínez-Fernández J, Allgöwer B (2010) Do factors causing wildfires vary in space? Evidence from geographically weighted regression. GIScience & Remote Sensing 47, 221–240.
| Do factors causing wildfires vary in space? Evidence from geographically weighted regression.Crossref | GoogleScholarGoogle Scholar |
Martínez-Fernández J, Chuvieco E, Koutsias N (2013) Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression. Natural Hazards and Earth System Sciences 13, 311–327.
| Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression.Crossref | GoogleScholarGoogle Scholar |
Moreira F, Rego FC, Ferreira PG (2001) Temporal (1958–1995) pattern of change in a cultural landscape of northwestern Portugal: implications for fire occurrence. Landscape Ecology 16, 557–567.
| Temporal (1958–1995) pattern of change in a cultural landscape of northwestern Portugal: implications for fire occurrence.Crossref | GoogleScholarGoogle Scholar |
Müller M, Vacik H, Valese E (2015) Anomalies of the Austrian forest fire regime in comparison with other alpine countries: a research note. Forests 6, 903–913.
| Anomalies of the Austrian forest fire regime in comparison with other alpine countries: a research note.Crossref | GoogleScholarGoogle Scholar |
Padilla M, Vega-García 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. International Journal of Wildland Fire 20, 46–58.
| 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.Crossref | GoogleScholarGoogle Scholar |
Parisien MA, Moritz MA (2009) Environmental controls on the distribution of wildfire at multiple spatial scales. Ecological Monographs 79, 127–154.
| Environmental controls on the distribution of wildfire at multiple spatial scales.Crossref | GoogleScholarGoogle Scholar |
Parisien MA, Snetsinger S, Greenberg JA, Nelson CR, Schoennagel T, Dobrowski SZ, Moritz MA (2012) Spatial variability in wildfire probability across the western United States. International Journal of Wildland Fire 21, 313–327.
| Spatial variability in wildfire probability across the western United States.Crossref | GoogleScholarGoogle Scholar |
Pausas JG (2004) Changes in fire and climate in the eastern Iberian Peninsula (Mediterranean Basin). Climatic Change 63, 337–350.
| Changes in fire and climate in the eastern Iberian Peninsula (Mediterranean Basin).Crossref | GoogleScholarGoogle Scholar |
Pausas JG, 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 |
Pausas JG, Keeley JE (2009) A burning story: the role of fire in the history of life. Bioscience 59, 593–601.
| A burning story: the role of fire in the history of life.Crossref | GoogleScholarGoogle Scholar |
Pausas JG, Keeley JE (2014) Abrupt climate-independent fire regime changes. Ecosystems 17, 1109–1120.
| Abrupt climate-independent fire regime changes.Crossref | GoogleScholarGoogle Scholar |
Pausas JG, Keeley JE (2019) Wildfires as an ecosystem service. Frontiers in Ecology and the Environment 17, 289–295.
| Wildfires as an ecosystem service.Crossref | GoogleScholarGoogle Scholar |
Pearson RG, Dawson TP, Berry PM, Harrison PA (2002) SPECIES: a spatial evaluation of climate impact on the envelope of species. Ecological Modelling 154, 289–300.
| SPECIES: a spatial evaluation of climate impact on the envelope of species.Crossref | GoogleScholarGoogle Scholar |
Pezzatti GB, Zumbrunnen T, Bürgi M, Ambrosetti P, Conedera M (2013) Fire regime shifts as a consequence of fire policy and socio-economic development: an analysis based on the change point approach. Forest Policy and Economics 29, 7–18.
| Fire regime shifts as a consequence of fire policy and socio-economic development: an analysis based on the change point approach.Crossref | GoogleScholarGoogle Scholar |
Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling 190, 231–259.
| Maximum entropy modeling of species geographic distributions.Crossref | GoogleScholarGoogle Scholar |
Pradervand J-N, Dubuis A, Pellissier L, Guisan A, Randin C (2014) Very high resolution environmental predictors in species distribution models: moving beyond topography? Progress in Physical Geography 38, 79–96.
| Very high resolution environmental predictors in species distribution models: moving beyond topography?Crossref | GoogleScholarGoogle Scholar |
R Core Team (2018) ‘R: A Language and Environment for Statistical Computing.’ (R Foundation for Statistical Computing: Vienna) Available at https://www.R-project.org [Verified March 2020]
Randin CF, Dirnböck T, Dullinger S, Zimmermann NE, Zappa M, Guisan A (2006) Are niche-based species distribution models transferable in space? Journal of Biogeography 33, 1689–1703.
| Are niche-based species distribution models transferable in space?Crossref | GoogleScholarGoogle Scholar |
Renard Q, Ṕlissier R, Ramesh BR, Kodandapani N (2012) Environmental susceptibility model for predicting forest fire occurrence in the western ghats of India. International Journal of Wildland Fire 21, 368–379.
| Environmental susceptibility model for predicting forest fire occurrence in the western ghats of India.Crossref | GoogleScholarGoogle Scholar |
Ross LK, Ross RE, Stewart HA, Howell KL (2015) The influence of data resolution on predicted distribution and estimates of extent of current protection of three ‘listed’ deep-sea habitats. PLoS One 10, e0140061
| The influence of data resolution on predicted distribution and estimates of extent of current protection of three ‘listed’ deep-sea habitats.Crossref | GoogleScholarGoogle Scholar | 26496639PubMed |
Schelhaas M-J, Nabuurs G-J, Schuck A (2003) Natural disturbances in the European forests in the 19th and 20th Centuries. Global Change Biology 9, 1620–1633.
| Natural disturbances in the European forests in the 19th and 20th Centuries.Crossref | GoogleScholarGoogle Scholar |
Schumacher S, Bugmann H (2006) The relative importance of climatic effects, wildfires and management for future forest landscape dynamics in the Swiss Alps. Global Change Biology 12, 1435–1450.
| The relative importance of climatic effects, wildfires and management for future forest landscape dynamics in the Swiss Alps.Crossref | GoogleScholarGoogle Scholar |
Seidl R, Schelhaas MJ, Lexer MJ (2011) Unraveling the drivers of intensifying forest disturbance regimes in Europe. Global Change Biology 17, 2842–2852.
| Unraveling the drivers of intensifying forest disturbance regimes in Europe.Crossref | GoogleScholarGoogle Scholar |
Suárez‐Seoane S, Virgós E, Terroba O, Pardavila X, Barea‐Azcón JM (2014) Scaling of species distribution models across spatial resolutions and extents along a biogeographic gradient. The case of the Iberian mole Talpa occidentalis. Ecography 37, 279–292.
| Scaling of species distribution models across spatial resolutions and extents along a biogeographic gradient. The case of the Iberian mole Talpa occidentalis.Crossref | GoogleScholarGoogle Scholar |
Turco M, Bedia J, Liberto FD, Fiorucci P, von Hardenberg J, Koutsias N, Llasat M-C, Xystrakis F, Provenzale A (2016) Decreasing fires in Mediterranean Europe. PLOS ONE 11, e0150663
| Decreasing fires in Mediterranean Europe.Crossref | GoogleScholarGoogle Scholar | 26982584PubMed |
Vilar L, Woolford DG, Martell DL, Martn MP (2010) A model for predicting human-caused wildfire occurrence in the region of Madrid, Spain. International Journal of Wildland Fire 19, 325–337.
| A model for predicting human-caused wildfire occurrence in the region of Madrid, Spain.Crossref | GoogleScholarGoogle Scholar |
Vilar L, Camia A, San-Miguel-Ayanz J, Martín MP (2016a) Modeling temporal changes in human-caused wildfires in Mediterranean Europe based on land use–land cover interfaces. Forest Ecology and Management 378, 68–78.
| Modeling temporal changes in human-caused wildfires in Mediterranean Europe based on land use–land cover interfaces.Crossref | GoogleScholarGoogle Scholar |
Vilar L, Gómez I, Martínez-Vega J, Echavarría P, Riaño D, Martín MP (2016b) Multitemporal modelling of socio-economic wildfire drivers in central Spain between the 1980s and the 2000s: comparing generalized linear models to machine learning algorithms. PLoS One 11, e0161344
| Multitemporal modelling of socio-economic wildfire drivers in central Spain between the 1980s and the 2000s: comparing generalized linear models to machine learning algorithms.Crossref | GoogleScholarGoogle Scholar | 27557113PubMed |
Weibel P (2009) Modelling and assessing fire regimes in mountain forests of Switzerland. Ph.D. Thesis, Swiss Federal Institute of Technology, Zürich. Available at https://www.research-collection.ethz.ch/handle/20.500.11850/21817 [Verified March 2020]
Westerling AL, Hidalgo HL, Cayan DR, Swetnam TW (2006) Warming and earlier spring increase western U.S. forest wildfire activity. Science 313, 940–943.
| Warming and earlier spring increase western U.S. forest wildfire activity.Crossref | GoogleScholarGoogle Scholar | 16825536PubMed |
Wiens JA (1989) Spatial scaling in ecology. Functional Ecology 3, 385–397.
| Spatial scaling in ecology.Crossref | GoogleScholarGoogle Scholar |
Yackulic CB, Chandler R, Zipkin EF, Royle JA, Nichols JD, Campbell Grant EH, Veran S (2013) Presence-only modelling using MAXENT: when can we trust the inferences? Methods in Ecology and Evolution 4, 236–243.
| Presence-only modelling using MAXENT: when can we trust the inferences?Crossref | GoogleScholarGoogle Scholar |
Zumbrunnen T (2010) Reconstructing and analyzing the fire history in a dry continental valley (Valais) of the Swiss Alps. Ph.D. Thesis, Swiss Federal Institute of Technology, Zürich. Available at https://www.research-collection.ethz.ch/handle/20.500.11850/114055 [Verified March 2020]
Zumbrunnen T, Menéndez P, Bugmann H, Conedera M, Gimmi U, Bürgi M (2012) Human impacts on fire occurrence: a case study of hundred years of forest fires in a dry alpine valley in Switzerland. Regional Environmental Change 12, 935–949.
| Human impacts on fire occurrence: a case study of hundred years of forest fires in a dry alpine valley in Switzerland.Crossref | GoogleScholarGoogle Scholar |
