Wildfire burnt area patterns and trends in Western Mediterranean Europe via the application of a concentration index

Abstract

The most widely used metrics to characterize wildfire regime and estimate the impact of wildfires are total burnt area (BA) and the number of fire events (FE). However, these are insufficient to analyse the threat to society of a new fire regime characterized by a higher occurrence of very large events. To overcome this weakness, we propose the use of a Concentration Index (CI B ) which makes it possible to identify spatio-temporal patterns. The frequency distribution of BA follows a negative exponential distribution almost everywhere, in which a small minority of FE is responsible of the majority of BA. In this article, the spatio-temporal behaviour of BA is analysed in Western Mediterranean Europe, with particular focus on Portugal, Spain, France and Italy, using data from the European Forest Fire Information System and national wildfire databases. This is the first time that the CI has been applied to wildfire events. This research shows that, in most Mediterranean European countries, the amount of BA is increasingly related with a lower number of fires. The spatiotemporal distribution of CI B shows high variability in all of the countries analysed in Europe. Portugal and Spain show increasing significant trends of CI B + 7.6% (pvalue = 0.001) and + 1.3% per decade (p-value = 0.003). Statistically significant correlations for Portugal, Spain and Italy are also found between the annual CI B and several teleconnection indices. The application of the CI B demonstrates its discriminatory ability, which is a key point in detecting vulnerable areas and temporal trends under climate change. K E Y W O R D Sconcentration index, extreme wildfire events, fire size, southern Europe, spatio-temporal patterns

Spatio‐Temporal Domains of Wildfire‐Prone Teleconnection Patterns in the Western Mediterranean Basin

“…In line with Royé et al. (2020), we identified three CT domains spanning west‐to‐east and being mainly associated with the SCAND, the NAO and the WeMOi climate modes. From a spatial standpoint, the mediterranean coast CT domain (zone 2) largely matches fire regime zones delineated in the region (Rodrigues et al., 2020; Rodrigues, Costafreda‐Aumedes, et al., 2019; Rodrigues, Jiménez‐Ruano, & de la Riva, 2019; Rodrigues, González‐Hidalgo, et al., 2019; Trigo et al., 2016; Vieira et al., 2020).…”

“…Thus, the links between CTs and fire activity have been investigated in various regions (Cardil et al., 2021; Kitzberger et al., 2007; Mariani et al., 2018; Rodrigues et al., 2021). However, the role of large‐scale CTs on wildfire occurrence and spread has not yet been fully explored in the western Mediterranean region (Royé et al., 2020). Within this area, various CTs influence weather, including the North Atlantic Oscillation (NAO), the East Atlantic (EA), the Atlantic Multidecadal Oscillation, the El Niño Southern Oscillation (ENSO), the Mediterranean Oscillation (MOI), the Pacific Decadal Oscillation (PDO), the Scandinavian (SCAND) pattern and the Western Mediterranean oscillation (WeMOi).…”

Promoting Low-Risk Fire Regimes: An Agent-Based Model to Explore Wildfire Mitigation Policy Options

“…Wildfire research has gained increasing attention in recent years, and there is now abundant evidence on the crucial role of land cover in wildfire proneness and its effects on fire regimes [4,6,[12][13][14][15][16]. Fire regimes are used to depict combinations of fire frequency and severity [15,17,18]. Fire regimes are often characterized based on metrics such as total burn area, number of fire events, or spatiotemporal concentration indexes (e.g., Gini index), computed over a representative period of time [15,17,19].…”

“…Fire regimes are used to depict combinations of fire frequency and severity [15,17,18]. Fire regimes are often characterized based on metrics such as total burn area, number of fire events, or spatiotemporal concentration indexes (e.g., Gini index), computed over a representative period of time [15,17,19]. Climate, topography, and LUC are acknowledged drivers of fire regimes [18,20].…”

Wild, tamed, and domesticated: Three fire macroregimes for global pyrogeography in the Anthropocene

“…In parts of southern Europe, rural depopulation and agricultural land abandonment have led to the expansion of forests and shrublands, increasing the extent and continuity of areas with highly flammable, heavy fuel loadings (Loepfe et al, 2010; Moreira et al, 2011). The fire regime has experienced an increase in the interannual variability of area burned (Fernandes et al, 2020), and in the number and size of very larges fires, leading to more extreme fire size inequality (Royé et al, 2019). These changes represent a decrease in land use intensity and a fire regime turning feral (Bowman, 2003), that is, shifting to the right along the horizontal axis of Figure 7.…”