Climate change induced declines in fuel moisture may turn currently fire-free Pyrenean mountain forests into fire-prone ecosystems

Dios, Víctor Resco de; Hedo, Javier; Camprubí, Àngel Cunill; Thapa, P.; Castillo, Edurne Martínez del; Aragón, Juán Martínez de; Bonet, J. A.; Balaguer‐Romano, Rodrigo; Díaz‐Sierra, Rubén; Yebra, Marta; Boer, Matthias M.

doi:10.1016/j.scitotenv.2021.149104

Cited by 36 publications

(23 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The observed relationships between ignition drivers and predicted likelihood are in line with the expected behavior, i.e., fuel moisture as the most influential factor modulating ignition followed by topography. The important role of the moisture of the live/dead fuels causing the ignition and propagation of new fire events have been documented in many works previously (Baranovskiy & Kirienko, 2022;Resco de Dios et al, 2021Rodrigues et al, 2021). However, our findings were non-conclusive in terms of the role of the characteristics of the fire-prone flash.…”

Section: Discussioncontrasting

confidence: 75%

Modeling daily natural-caused ignition probability in the Iberian Peninsula

Jiménez-Ruano¹,

Gelabert²,

Dios³

et al. 2022

Advances in Forest Fire Research 2022

View full text Add to dashboard Cite

In the European Mediterranean region natural-caused wildfires are a small fraction of total ignitions. Lightning strikes are the most common source of non-human fires, being strongly tied to specific synoptic conditions and patterns associated with atmospheric instability, such as dry thunderstorms. Likewise, lightning-related ignitions often associate with dry fuels and dense vegetation layers. In the case of Iberian Peninsula, the confluence of these factors favors recurrent lightning fires in the eastern Mediterranean mountain ranges and the. However, under appropriate conditions lightning fires can start elsewhere, holding the potential to propagate over vast distances. In this work, we assessed the likelihood of ignition leveraging a large dataset of lightning strikes and historical fires available in Spain. We trained and tested a machine learning model to evaluate the probability of ignition provided that a lightning strikes the ground. Our model was calibrated in the period 2009-2015 using data for mainland Spain plus the Balearic Islands. To build the binary response variable we classified lightning strikes between that triggered a fire event. For each lightning strike we extracted a set of covariates relating fuel moisture conditions, the presence and density of the vegetation layer and the shape of the relief. The final model was subsequently applied to forecast daily probabilities at 1x1 km resolution for the entire Iberian Peninsula. Although the model was originally calibrated in Spain, we extended the predictions to the entire Iberian Peninsula. By doing so we were able to validate in the future our outputs against the Portuguese dataset of recent natural-caused fires (bigger than 1 ha) from 2001 to 2021. Overall, the model attained a great predictive performance with a median AUC of 0.82. Natural-caused ignitions triggered mainly in low dead (dFMC 250) fuel moisture conditions. Lightning strikes with negative polarity seem to trigger fires more frequently when the mean density of discharger was greater than 5. Finally, natural wildfires usually started at higher elevations (above 500 m.a.s.l.).

show abstract

Section: Discussioncontrasting

confidence: 75%

Modeling daily natural-caused ignition probability in the Iberian Peninsula

Jiménez-Ruano¹,

Gelabert²,

Dios³

et al. 2022

Advances in Forest Fire Research 2022

View full text Add to dashboard Cite

show abstract

“…Each group of tasks is important in terms of minimizing damage from forest fires. This is equally true for the Russian Federation, Canada, Australia or the countries of Southern Europe [111][112][113][114][115][116][117][118][119][120][121][122][123][124][125]. Perhaps, for the Mediterranean region, these tasks are even more important, since catastrophic forest fires have been observed there in recent years.…”

Section: Discussionmentioning

confidence: 99%

Mathematical Simulation of Forest Fuel Pyrolysis and Crown Forest Fire Impact for Forest Fire Danger and Risk Assessment

Baranovskiy

Kirienko

2022

Processes

View full text Add to dashboard Cite

In order to predict and assess the danger from crown forest fires, it is necessary to study the thermal degradation of different forest fuels in a high-temperature environment. In this paper, the main characteristics of pyrolysis accompanied by moisture evaporation in a foliage sample of angiosperms (birch) were investigated within conditions typical for a crown forest fire. The heat and mass transfer in the forest fuel element is described by the system of non-stationary non-linear heat conduction equations with corresponding initial and boundary conditions. The considered problem is solved within the framework of the three-dimensional statement by the finite difference method. The locally one-dimensional method was used to solve three-dimensional equations for heat conduction. The simple iteration method was applied to solve nonlinear effects caused by the forest fuel pyrolysis and moisture evaporation. The fourth kind of boundary conditions are applicable at the interface between the sub-areas. Software implementation of the mathematical model is performed in the high-level programming language Delphi in the RAD Studio software. The characteristic changes in the sample temperature field and the phase composition under high-temperature exposure from a forest fire are presented. The induction period of the thermal decomposition of dry organic matter in the sample was determined. Recommendations are made about key features of accounting for the pyrolysis and evaporation processes when predicting forest fire danger. The research results can be used in the development and improvement of systems for predicting forest fire danger and environmental consequences of the forest fires.

show abstract

“…We employed data from the EFFIS real-time burned area and GlobFire databases, based on the MODIS Collection 6 (C6) MCD64A1 burned area product (Giglio et al, 2018). We retrieved daily burned area data over the full period, aggregating it at weekly level using the regional divisions by Calheiros et al (2020) for Portugal, López Santalla & López García (2019) for Spain and Resco de Dios et al (2021) for France.…”

Section: Methodsmentioning

confidence: 99%

Drivers and implications of the extreme 2022 wildfire season in Southwest Europe

Rodrígues

Camprubí²,

Balaguer‐Romano

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Wildfire is a common phenomenon in Mediterranean countries but the 2022 fire season has been extreme in southwest Europe (Portugal, Spain and France). Burned area has exceeded the 2001-2021 median by a factor of 52 in some regions and large wildfires started to occur in June- July, earlier than the traditional fire season. These anomalies were associated with record-breaking values of fuel dryness, atmospheric water demand and pyrometeorological conditions. For instance, live fuel moisture content was below the historical minima for almost 50% of the season in some regions. Wildfire impacts are primarily social and economical in these fire-prone landscapes, but they may prompt large- scale degradation if this anomaly becomes more common under climate change, as is expected. As climate changes intensify, we can expect this to become the new normal in large parts of the continent. Climate change is already here and delaying fuel management will only worsen the wildfire problem. Here we provide a preliminary though comprehensive analysis of 2022 wildfire season in southwest Europe.

show abstract

Climate change induced declines in fuel moisture may turn currently fire-free Pyrenean mountain forests into fire-prone ecosystems

Cited by 36 publications

References 54 publications

Modeling daily natural-caused ignition probability in the Iberian Peninsula

Modeling daily natural-caused ignition probability in the Iberian Peninsula

Mathematical Simulation of Forest Fuel Pyrolysis and Crown Forest Fire Impact for Forest Fire Danger and Risk Assessment

Drivers and implications of the extreme 2022 wildfire season in Southwest Europe

Contact Info

Product

Resources

About