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对叶片和冠层燃料含水量进行的植物水力建模显示,在极端干旱条件下,地中海森林遭受野火的脆弱性日益增加。

Plant hydraulic modelling of leaf and canopy fuel moisture content reveals increasing vulnerability of a Mediterranean forest to wildfires under extreme drought.

作者信息

Ruffault Julien, Limousin Jean-Marc, Pimont François, Dupuy Jean-Luc, De Càceres Miquel, Cochard Hervé, Mouillot Florent, Blackman Chris J, Torres-Ruiz José M, Parsons Russell A, Moreno Myriam, Delzon Sylvain, Jansen Steven, Olioso Albert, Choat Brendan, Martin-StPaul Nicolas

机构信息

URFM, INRAE, 84000, Avignon, France.

CEFE, Univ Montpellier, CNRS, EPHE, IRD, 34000, Montpellier, France.

出版信息

New Phytol. 2023 Feb;237(4):1256-1269. doi: 10.1111/nph.18614. Epub 2022 Dec 9.

Abstract

Fuel moisture content (FMC) is a crucial driver of forest fires in many regions world-wide. Yet, the dynamics of FMC in forest canopies as well as their physiological and environmental determinants remain poorly understood, especially under extreme drought. We embedded a FMC module in the trait-based, plant-hydraulic SurEau-Ecos model to provide innovative process-based predictions of leaf live fuel moisture content (LFMC) and canopy fuel moisture content (CFMC) based on leaf water potential ( ). SurEau-Ecos-FMC relies on pressure-volume (p-v) curves to simulate LFMC and vulnerability curves to cavitation to simulate foliage mortality. SurEau-Ecos-FMC accurately reproduced and LFMC dynamics as well as the occurrence of foliage mortality in a Mediterranean Quercus ilex forest. Several traits related to water use (leaf area index, available soil water, and transpiration regulation), vulnerability to cavitation, and p-v curves (full turgor osmotic potential) had the greatest influence on LFMC and CFMC dynamics. As the climate gets drier, our results showed that drought-induced foliage mortality is expected to increase, thereby significantly decreasing CFMC. Our results represent an important advance in our capacity to understand and predict the sensitivity of forests to wildfires.

摘要

燃料含水量(FMC)是全球许多地区森林火灾的关键驱动因素。然而,森林冠层中FMC的动态变化及其生理和环境决定因素仍知之甚少,尤其是在极端干旱条件下。我们将一个FMC模块嵌入基于性状的植物水力模型SurEau-Ecos中,以便基于叶水势( )对叶活燃料含水量(LFMC)和冠层燃料含水量(CFMC)进行创新的基于过程的预测。SurEau-Ecos-FMC依靠压力-容积(p-v)曲线来模拟LFMC,并利用空化脆弱性曲线来模拟叶片死亡率。SurEau-Ecos-FMC准确地再现了地中海冬青栎林中的 和LFMC动态以及叶片死亡情况。几个与水分利用相关的性状(叶面积指数、土壤有效水分和蒸腾调节)、对空化的脆弱性以及p-v曲线(完全膨压渗透势)对LFMC和CFMC动态影响最大。我们的研究结果表明,随着气候变得更加干燥,干旱引起的叶片死亡率预计会增加,从而显著降低CFMC。我们的研究结果代表了我们在理解和预测森林对野火敏感性方面能力的一项重要进展。

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