Abstract. Recently, many remote-sensing datasets providing features of individual fire events from gridded global burned area products have been released. Although very promising, these datasets still lack a quantitative estimate of their accuracy with respect to historical ground-based fire datasets. Here, we compared three state-of-the-art remote-sensing datasets (RSDs; Fire Atlas, FRY, and GlobFire) with a harmonized ground-based dataset (GBD) compiled by fire agencies monitoring systems across the southwestern Mediterranean Basin (2005–2015). We assessed the agreement between the RSDs and the GBD with respect to both burned area (BA) and number of fires (NF). RSDs and the GBD were aggregated at monthly and 0.25∘ resolutions, considering different individual fire size thresholds ranging from 1 to 500 ha. Our results show that all datasets were highly correlated in terms of monthly BA and NF, but RSDs severely underestimated both (by 38 % and 96 %, respectively) when considering all fires > 1 ha. The agreement between RSDs and the GBD was strongly dependent on individual fire size and strengthened when increasing the fire size threshold, with fires  > 100 ha denoting a higher correlation and much lower error (BA 10 %; NF 35 %). The agreement was also higher during the warm season (May to October) in particular across the regions with greater fire activity such as the northern Iberian Peninsula. The Fire Atlas displayed a slightly better performance with a lower relative error, although uncertainty in the gridded BA product largely outpaced uncertainties across the RSDs. Overall, our findings suggest a reasonable agreement between RSDs and the GBD for fires larger than 100 ha, but care is needed when examining smaller fires at regional scales.

Wildland fire effects are strongly associated with fire regime characteristics. Here, we developed the first European pyrogeography based on different fire regime components to better understand fire regimes across the continent. We identified four large-scale pyroregions: a non-fire-prone (NFP) pyroregion featuring nominal fire activity across central and northern Europe; a cool-season fire (CSF) pyroregion scattered throughout Europe; a fire-prone (FP) pyroregion extending mostly across southern Europe; and a highly fire-prone (HFP) pyroregion spanning across northern Portugal, Sicily, and western Balkans. Land cover analysis indicates that pyroregions were first shaped by vegetation and then by anthropogenic factors. On interannual timescales the spatial extent of pyroregions was found to vary, with NFP showing more stability. Interannual correlations between climate and burned area, fire frequency, and the length of fire period exhibited distinct patterns, strengthening in fire-prone pyroregions (FP and HFP) and weakening in NFP and CSF. Proportion of cool-season fires and large fires were related to fuel accumulation in fire-prone pyroregions. Overall, our findings indicate that such a pyrogeography should allow a more accurate estimate of the effects of climate on fire regimes while providing an appropriate framework to better understand fire in Europe.

This work explores the main climate teleconnections influencing the Western Mediterranean Basin to outline homogeneous fire‐prone weather domains combining cross‐correlation time series and cluster analysis. We found a zonal effect of the Scandinavian pattern over the entire region with an interesting alternation of phases from positive during winter‐spring (increased rainfall leading to fuel accumulation) to negative (dry conditions) modes during summer controlling burned area and fire size. The North Atlantic Oscillation (NAO) dominates the number of fires over the Iberian Peninsula (IP) while the Western Mediterranean Oscillation pattern modulates fire activity over the Mediterranean coast in the IP (linked to westerly winds), Southern France, Corsica and Sardinia (rainfall regulation). These distinctive influence traits resulted in three different domains splitting the IP into a Mediterranean rim along the coast (from southern Spain to southwestern France) and an inland and western region (Portugal plus western Spain); and a third in southeastern France, Corsica and Sardinia.

No abstract

In the last decades, eucalypt plantations are expanding across the Brazilian savanna, one of the most frequently burned ecosystems in the world. Wildfires are one of the main threats to forest plantations, causing economic and environmental loss. Modeling wildfire occurrence provides a better understanding of the processes that drive fire activity. Furthermore, the use of spatially explicit models may promote more effective management strategies and support fire prevention policies. In this work, we assessed wildfire occurrence combining Random Forest (RF) algorithms and cluster analysis to predict and detect changes in the spatial pattern of ignition probability over time. The model was trained using several explanatory drivers related to fire ignition: accessibility, proximity to agricultural lands or human activities, among others. Specifically, we introduced the progression of eucalypt plantations on a two-year basis to capture the influence of land cover changes over fire likelihood consistently. Fire occurrences in the period 2010-2016 were retrieved from the Brazilian Institute of Space Research (INPE) database. In terms of the AUC (area under the Receiver Operating Characteristic curve), the model denoted fairly good predictive accuracy (AUC ≈ 0.72). Results suggested that fire occurrence was mainly linked to proximity agricultural and to urban interfaces. Eucalypt plantation contributed to increased wildfire likelihood and denoted fairly high importance as an explanatory variable (17% increase of Mean Square Error [MSE]). Nevertheless, agriculture and urban interfaces proved to be the main drivers, contributing to decreasing the RF's MSE in 42% and 38%, respectively. Furthermore, eucalypt plantations expansion is progressing over clusters of high wildfire likelihood, thus increasing the exposure to wildfire events for young eucalypt plantations and nearby areas. Protective measures should be focus on in the mapped Hot Spot zones in order to mitigate the exposure to fire events and to contribute for an efficient initial suppression rather than costly firefighting.The savanna is a very important biome due to its large geographic extent, high levels of biodiversity and intense fire activity [6,7], being among the most frequently burned ecosystems in the world [8,9]. At the same time, this fire-prone biome is perceived as favorable land for agricultural expansion, which has emerged as a key factor transformation for this region [10]. Recently, Brazilian savanna, also known as 'Cerrado', is experiencing a significant land use transformation, with the native vegetation being replaced by intensive forestry, agricultural lands and urban areas [11]. The probability of a fire to occur depends on the occurrence of an ignition source (either human-related or natural) and favorable burning conditions within the environment [12]. In the Brazilian savanna, fire is used by humans as a management tool for vegetation removal, maintain grasslands, burn off agricultural residues or clean farm borders [6,13]. Nonetheless, fi...

Abstract. Recently, many remote-sensing (RS) based datasets providing features of individual fire events from gridded global burned area products have been released. Although very promising, these datasets still lack a quantitative estimate of their accuracy with respect to historical ground-based fire databases. Here, we compared three state-of-the-art RS datasets (Fire Atlas, FRY and GlobFire) with high-quality ground databases compiled by regional fire agencies (AG) across the Southwestern Mediterranean basin (2005–2015). We assessed the spatial and temporal accuracy in estimated RS burned area (BA) and number of fires (NF) aggregated at monthly and 0.25° resolutions, considering different individual fire size thresholds ranging from 1 to 500 ha. Our results show that RS datasets were highly correlated with AG in terms of monthly BA and NF but severely underestimated both (by 38 % and 96 %, respectively) when considering all fires > 1 ha. Stronger agreement was found when increasing the fire size threshold, with fires > 100 ha denoting higher correlation and much lower error (BA 10 %; NF 35%). The agreement between RS and AG was also the highest during the warm season (May to October) in particular across the regions with greater fire activity such as the Northern Iberian Peninsula. The Fire Atlas displayed a slightly better performance, with a lower relative error, although uncertainty in gridded BA product largely outpaced uncertainties across the RS datasets. Overall, our findings suggest a reasonable agreement between RS and ground-based datasets for fires larger than 100 ha, but care is needed when examining smaller fires at regional scales.

Wildland fire is expected to increase in response to global warming, yet little is known about future changes to fire regimes in Europe. Here, we developed a pyrogeography based on statistical fire models to better understand how global warming reshapes fire regimes across the continent. We identified five large‐scale pyroregions with different levels of area burned, fire frequency, intensity, length of fire period, size distribution, and seasonality. All other things being equal, global warming was found to alter the distribution of these pyroregions, with an expansion of the most fire prone pyroregions ranging respectively from 50% to 130% under 2° and 4°C global warming scenarios. Our estimates indicate a strong amplification of fire across parts of southern Europe and a subsequent shift toward new fire regimes, implying substantial socio‐ecological impacts in the absence of mitigation or adaptation measures.

Wildland fire is expected to increase in response to global warming, yet little is known about future changes to fire regimes in Europe. Here, we developed a pyrogeography based on statistical fire models to better understand how global warming reshapes fire regimes across the continent. We identified five large-scale pyroregions with different levels of area burned, fire frequency, intensity, length of fire period, size distribution, and seasonality. All other things being equal, global warming was found to alter the distribution of these pyroregions, with a spatial extension of the most fire prone pyroregions ranging respectively from 50% to 130% under 2 and 4 °C global warming scenarios. Our estimates indicate a strong amplification of fire across parts of southern Europe and subsequent shift towards new fire regimes, implying substantial socio-ecological impacts in the absence of mitigation or adaptation measures.