Short communication: On the effect of live fuel moisture content on fire-spread rate

Rossa, Carlos G.; Fernandes, Paulo M.

doi:10.5424/fs/2017263-12019

Cited by 23 publications

(19 citation statements)

References 22 publications

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“…Live fuel moisture content (LFMC) is a landscape-level management metric that, along with weather and topography, is incorporated into rate-of-spread models and fire danger ratings [1][2][3][4]. LFMC is expressed as the ratio of water content in fresh plant tissue to the dry weight and represents the amount of moisture that needs to evaporate from a fuel source before ignition can occur.…”

Section: Introductionmentioning

confidence: 99%

“…For example, wildfire risk increases as LFMC decreases until a critical threshold is reached, and then the fire risk is constant and high [9]. However, recent studies suggest that these breakpoints need to be considered with caution as field-based and laboratory-based studies often show differing results related to the magnitude of the effect of LFMC on fire rate-of-spread [2,4,10]. Hence, further LFMC studies are needed to resolve these issues.…”

Section: Introductionmentioning

confidence: 99%

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The Effect of Ecophysiological Traits on Live Fuel Moisture Content

Pivovaroff¹,

Emery

Witter

et al. 2019

Fire

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Live fuel moisture content (LFMC) is an important metric for fire danger ratings. However, there is limited understanding of the physiological control of LFMC or how it varies among co-occurring species. This is a problem for biodiverse yet fire-prone regions such as southern California. We monitored LFMC and water potential for 11 native woody species, and measured ecophysiological traits related to access to water, plant water status, water use regulation, and drought adaptation to answer: (1) What are the physiological mechanisms associated with changes in LFMC? and (2) How do seasonal patterns of LFMC differ among a variety of shrub species? We found that LFMC varied widely among species during the wet winter months, but converged during the dry summer months. Traits associated with LFMC patterns were those related to access to water, such as predawn and minimum seasonal water potentials (Ψ), and water use regulation, such as transpiration. The relationship between LFMC and Ψ displayed a distinct inflection point. For most species, this inflection point was also associated with the turgor loss point, an important drought-adaptation trait. Other systems will benefit from studies that incorporate physiological mechanisms into determining critical LFMC thresholds to expand the discipline of pyro-ecophysiology.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Effect of Ecophysiological Traits on Live Fuel Moisture Content

Pivovaroff¹,

Emery

Witter

et al. 2019

Fire

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“…So why did Alexander and Cruz (2013) [2] not detect a significant relationship between field fires RoS and live FMC? Rossa and Fernandes (2017) [7] presented a simple theory, which consists of two connected hypotheses: H1, live tree foliage FMC remains fairly constant over the year (except under severe drought); and H2, the seasonal variation of live shrubs' FMC correlates with average dead FMC. As a result, the effect of live FMC is not easily detected by statistical analysis; this detection is further impaired by the dominant influence of wind on RoS and by intrinsic correlations between fuel metrics (e.g., FMC, fuel bed height, load, and density) [26] that dilute the effect of live FMC.…”

Section: The Sources Of Uncertainty and A Unifying Theorymentioning

confidence: 99%

“…Alternatively, live fuels could be treated as very wet dead fuels [3], their combustion mechanisms can be considered different from dead fuels [4], or they could simply be neglected [5]. FMC and wind speed are the most important factors determining RoS [6,7]. As a result, a lack in understanding the effect of live FMC on RoS hinders the development of prediction systems that are applicable to generic fuel complexes, which often are composed of mixed live and dead vegetation.…”

Section: Introductionmentioning

confidence: 99%

Live Fuel Moisture Content: The ‘Pea Under the Mattress’ of Fire Spread Rate Modeling?

Rossa

Fernandes

2018

Fire

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Currently, there is a dispute on whether live fuel moisture content (FMC) should be accounted for when predicting a real-world fire-spread rate (RoS). The laboratory and field data results are conflicting: laboratory trials show a significant effect of live FMC on RoS, which has not been convincingly detected in the field. It has been suggested that the lack of influence of live FMC on RoS might arise from differences in the ignition of dead and live fuels: flammability trials using live leaves subjected to high heat fluxes (80–140 kW m−2) show that ignition occurs before all of the moisture is vaporized. We analyze evidence from recent studies, and hypothesize that differences in the ignition mechanisms between dead and live fuels do not preclude the use of overall fine FMC for attaining acceptable RoS predictions. We refer to a simple theory that consists of two connected hypotheses to explain why the effect of live FMC on field fires RoS has remained elusive so far: H1, live tree foliage FMC remains fairly constant over the year; and H2, the seasonal variation of live shrubs’ FMC correlates with the average dead FMC. As a result, the effect of live FMC is not easily detected by statistical analysis.

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“…The following steps are typically undertaken in empirical approaches [8]: fuel and terrain descriptions (e.g., vegetation characteristics, slope); atmospheric-related environment measurement (e.g., U, air temperature, relative humidity, fine fuel moisture content); fire measurement (e.g., R, flame geometry); and statistical analysis to develop relationships to predict fire behavior characteristics. Although empirical formulations can be derived from either laboratory or field fires, the latter option is frequently preferred [9], based on the premise that field experiments under natural conditions are a better proxy to real wildfires.…”

Section: Introductionmentioning

confidence: 99%

An Empirical Model for the Effect of Wind on Fire Spread Rate

Rossa

Fernandes

2018

Fire

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Predicting wind-driven rate of fire spread (RoS) has been the aim of many studies. Still, a field-tested model for general use, regardless of vegetation type, is currently lacking. We develop an empirical model for wind-aided RoS from laboratory fires (n = 216), assuming that it depends mainly on fire-released energy and on the extension of flame over the fuel bed in still air, and that it can be obtained by multiplying RoS in no-wind and no-slope conditions by a factor quantifying the wind effect. Testing against independent laboratory and field data (n = 461) shows good agreement between observations and predictions. Our results suggest that the fuel bed density effect detected by other work may be a surrogate for the amount of fuel involved in combustion, which depends on fuel load. Because RoS under windless conditions is unaffected by fuel load, the involved mechanisms differ from wind-aided propagation. Compared to shallow fuel beds, the wind effect is usually modest in deep vegetation, because tall fuel complexes are dominated by live fuels (high moisture content) and flames extend less above the vegetation when fuel moisture is high. The present work warrants further inspection in a broader range of field conditions.

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Short communication: On the effect of live fuel moisture content on fire-spread rate

Cited by 23 publications

References 22 publications

The Effect of Ecophysiological Traits on Live Fuel Moisture Content

The Effect of Ecophysiological Traits on Live Fuel Moisture Content

Live Fuel Moisture Content: The ‘Pea Under the Mattress’ of Fire Spread Rate Modeling?

An Empirical Model for the Effect of Wind on Fire Spread Rate

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