Increased likelihood of heat-induced large wildfires in the Mediterranean Basin

Ruffault, Julien; Curt, Thomas; Moron, Vincent; Trigo, Ricardo M.; Mouillot, Florent; Koutsias, Nikos; Pimont, François; Martin‐StPaul, Nicolas; Barbero, Renaud; Dupuy, Jean‐Luc; Russo, Ana; Belhadj-Kheder, Chiraz

doi:10.1101/2020.01.09.896878

Cited by 35 publications

(48 citation statements)

References 42 publications

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“…A large part of these knowledge gaps is undoubtedly due to the fact that LFMC dynamic remain poorly understood and difficult to predict. Most studies that explore the drought-fire relationships do not consider explicitly the role of fuel moisture content in wildfire dynamics (Abatzoglou and Williams 2016;Turco et al 2018;Ruffault et al 2020). Instead, they rely on physical drivers of fuel moisture dynamics such as the vapor pressure deficit (VPD), or on empirical drought indices that are correlated with FMC, including dead FMC (Resco de Dios et al 2015) and live FMC .…”

Section: Introductionmentioning

confidence: 99%

Modelling live fuel moisture content at leaf and canopy scale under extreme drought using a lumped plant hydraulic model

Martin‐StPaul¹,

Ruffault²,

Blackmann³

et al. 2020

Preprint

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Ø Water content in living vegetation (or live fuel moisture content, LFMC), is increasingly recognized as a key factor linked to vegetation mortality and wildfire ignition and spread. Most often, empirical indices are used as surrogates for direct LFMC measurements. Ø In this paper, we explore the functional and ecophysiological drivers of LFMC during drought at the leaf and canopy scale using the SurEau-Ecos model, and a three years dataset of leaf and canopy scale measurements on a mature Quercus ilex forest, including an extreme drought. The model is based on forest hydrology and plant hydraulics and allows to simulate temporal variations of water potential and content at a daily time step. At leaf level, it simulates the relationship between water potential and water content by separating the apoplasm and the symplasm. Symplasm water content is modeled using the pressure volume curve theory, and apoplasm water content is modelled using the xylem vulnerability to cavitation. Fuel moisture content was upscaled to the canopy level by accounting for foliage mortality estimated from drought induced cavitation. Ø The model was parameterized either with site-measured traits or using a calibration procedure, and compared with water potential and LFMC measured at leaf level, and NDVI variation measured at canopy level and taken as a surrogate for foliage mortality. Ø At leaf level, LFMC prediction using measured hydraulic traits could be improved by considering year-to-year osmotic adjustments. At canopy level, foliage mortality due to drought induced cavitation was a key driver of LFMC decline during the most extreme drought. Ø A sensitivity analysis showed that parameters driving soil water balance (leaf area index, soil water capacity, and regulation of transpiration) and parameters determining pressure volume curves are key traits driving LFMC dynamics at leaf level. At the canopy level, parameters that drives hydraulic failure were the most sensitive and included, both soil water balance parameters and hydraulic traits (the leaf vulnerability to cavitation) were the main drivers of LFMC decline during extreme drought. Ø We also showed that under normal historic weather conditions, most variation of LFMC are linked to reversible symplasm dehydration, however under future, hotter and dryer conditions, most variations are due to the decline canopy of LFMC driven by foliage mortality.

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Section: Introductionmentioning

confidence: 99%

Modelling live fuel moisture content at leaf and canopy scale under extreme drought using a lumped plant hydraulic model

Martin‐StPaul¹,

Ruffault²,

Blackmann³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

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“…CC BY 4.0 License. ongoing climate change (Dupuy et al, 2020;Ruffault et al, 2020;Turco et al, 2018a). Additional factors such as landscape changes as well as changes in forest and fire management may also shape future fire activity (Moreira et al, 2020;Pausas and Fernández-Muñoz, 2012).…”

Section: Introductionmentioning

confidence: 99%

Assessing the accuracy of remotely-sensed fire datasets across the Southwestern Mediterranean basin

Galizia¹,

Curt²,

Barbero³

et al. 2020

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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.

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“…Evidence for human influence is found in fire seasons of unprecedented magnitude in the modern era in regions as diverse as California (Goss et al, 2020), the Mediterranean basin (e.g. Ruffault et al, 2020), Canada (Kirchmeier-Young et al, 2019, the Arctic and Siberia (McCarty et al, 2020) and Chile (Bowman et al, 2019). Assessments of this attribution can now assign at least medium confidence to human influence not only on trends in fire weather but also on fire events (e.g.…”

Section: Insight 3: Climate Change Forces Fire Extremes To Reach New Dimension With Drastic Impactsmentioning

confidence: 99%

Ten new insights in climate science 2021: a horizon scan

et al. 2021

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Non-technical summaryWe summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding about the remaining options to achieve the Paris Agreement goals, through overcoming political barriers to carbon pricing, taking into account non-CO 2 factors, a well-designed implementation of demand-side and nature-based solutions, resilience building of ecosystems and the recognition that climate change mitigation costs can be justified by benefits to the health of humans and nature alone. We consider new insights about what to expect if we fail to include a new dimension of fire extremes and the prospect of cascading climate tipping elements.

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Increased likelihood of heat-induced large wildfires in the Mediterranean Basin

Cited by 35 publications

References 42 publications

Modelling live fuel moisture content at leaf and canopy scale under extreme drought using a lumped plant hydraulic model

Modelling live fuel moisture content at leaf and canopy scale under extreme drought using a lumped plant hydraulic model

Assessing the accuracy of remotely-sensed fire datasets across the Southwestern Mediterranean basin

Ten new insights in climate science 2021: a horizon scan

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