Sensitivity of Portuguese forest fires to climatic, human, and landscape variables: subnational differences between fire drivers in extreme fire years and decadal averages

Costa, Luís; Thonicke, Kirsten; Poulter, Benjamin; Badeck, Franz-W.

doi:10.1007/s10113-010-0169-6

Cited by 68 publications

(49 citation statements)

References 14 publications

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“…Other limitations come from the fact that the methodology does not account for the role of, and potential future changes in, many other important factors regarding fire occurrence and size that are not yet fully understood nor properly modelled, such as those related to changes in fuel structure (Pausas 2004, Pausas & Bradstock 2007; climate−vegetation dy namics and conservation planning (Krawchuk et al 2009); patterns of lightning strikes (Dissing & Verbyla 2003); and anthropogenic activities and drivers of fire, such as control over ignition, fire management, suppression activities, and land use/land cover changes (Krawchuk et al 2009, Costa et al 2010, Le Page et al 2010, Aldersley et al 2011, Kloster et al 2012). …”

Section: Discussionmentioning

confidence: 99%

Effects of regional climate change on rural fires in Portugal

Pereira¹,

Calado²,

DaCamara³

et al. 2013

Clim. Res.

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Section: Discussionmentioning

confidence: 99%

Effects of regional climate change on rural fires in Portugal

Pereira¹,

Calado²,

DaCamara³

et al. 2013

Clim. Res.

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“…Moreover, in some studies, it is pointed out that socio-economic and landscape factors would be more efficient on the burned area than climate conditions in local scale [67]. So, it will be necessary to take some social factors such as unemployment, population as well as road intensity into consideration in order that the number of fires and the amount of burned areas can be predicted more successfully [15].…”

Section: Resultsmentioning

confidence: 99%

Drought-Forest Fire Relationships

Varol¹,

Ertuğrul²,

Özel³

2017

Mediterranean Identities - Environment, Society, Culture

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This study was carried out to determine the methods that bear the most realistic results in predicting the number of fires and burned area under the climate conditions in future. Different indices and statistical methods were used in predicting the burned area and the number of fires. With this aim, in addition to the indices used in estimating the climate, Machine Learning and multivariate adaptive regression spline (MARS) models are also used in predicting these factors. According to the results obtained in several studies, the relationship between the drought and fire indices burned area and the number of fires changes from region to region. While better results are obtained in predicting the burned area and the number of fires via the drought indices being used in this study and the MARS models that the combinations of these indices use, it is seen that a 30-39% success was achieved for predicting the amount of burned area via Machine Learning methods (Kernel Nearest Neighbor (kNN), Recursive Partitioning and Regression Trees (RPART), Support Vector Machine (SVM) and RF), and this success ranges widely from 8 to 41% in terms of the number of fires. RPART, of these four algorithms, performed the best in fire prediction, but kNN was the worst.

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“…In Europe, human activities including negligence and arson cause more than 95 % of European forest fires (Ganteaume et al 2012;San-Miguel-Ayanz et al 2012). At the same time, overall trends are closely linked to weather conditions (Rogelj et al 2012), and climatic, socio-economic, and landscape fire drivers should be considered together to better understand inter-annual variations in burned areas (Costa et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Forest fires and adaptation options in Europe

et al. 2014

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This paper presents a quantitative assessment of adaptation options in the context of forest fires in Europe under projected climate change. A standalone fire model (SFM) based on a state-of-the-art large-scale forest fire modelling algorithm is used to explore fuel removal through prescribed burnings and improved fire suppression as adaptation options. The climate change projections are provided by three climate models reflecting the SRES A2 scenario. The SFM's modelled burned areas for selected test countries in Europe show satisfying agreement with observed data coming from two different sources (European Forest Fire Information System and Global Fire Emissions Database). Our estimation of the potential increase in burned areas in Europe under ''no adaptation'' scenario is about 200 % by 2090 (compared with 2000-2008). The application of prescribed burnings has the potential to keep that increase below 50 %. Improvements in fire suppression might reduce this impact even further, e.g. boosting the probability of putting out a fire within a day by 10 % would result in about a 30 % decrease in annual burned areas. By taking more adaptation options into consideration, such as using agricultural fields as fire breaks, behavioural changes, and long-term options, burned areas can be potentially reduced further than projected in our analysis.

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Sensitivity of Portuguese forest fires to climatic, human, and landscape variables: subnational differences between fire drivers in extreme fire years and decadal averages

Cited by 68 publications

References 14 publications

Effects of regional climate change on rural fires in Portugal

Effects of regional climate change on rural fires in Portugal

Drought-Forest Fire Relationships

Forest fires and adaptation options in Europe

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