scholarly journals Linking Forest Flammability and Plant Vulnerability to Drought

Forests ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 779 ◽  
Author(s):  
Rachael H. Nolan ◽  
Chris J. Blackman ◽  
Víctor Resco de Dios ◽  
Brendan Choat ◽  
Belinda E. Medlyn ◽  
...  
Keyword(s):  
Moisture Content ◽  
Forest Fires ◽  
Plant Traits ◽  
Large Body ◽  
Fire Regimes ◽  
Leaf Mass Per Area ◽  
Plant Responses ◽  
Fuel Moisture ◽  
Eastern Australia ◽  
Live Fuels

Globally, fire regimes are being altered by changing climatic conditions. New fire regimes have the potential to drive species extinctions and cause ecosystem state changes, with a range of consequences for ecosystem services. Despite the co-occurrence of forest fires with drought, current approaches to modelling flammability largely overlook the large body of research into plant vulnerability to drought. Here, we outline the mechanisms through which plant responses to drought may affect forest flammability, specifically fuel moisture and the ratio of dead to live fuels. We present a framework for modelling live fuel moisture content (moisture content of foliage and twigs) from soil water content and plant traits, including rooting patterns and leaf traits such as the turgor loss point, osmotic potential, elasticity and leaf mass per area. We also present evidence that physiological drought stress may contribute to previously observed fuel moisture thresholds in south-eastern Australia. Of particular relevance is leaf cavitation and subsequent shedding, which transforms live fuels into dead fuels, which are drier, and thus easier to ignite. We suggest that capitalising on drought research to inform wildfire research presents a major opportunity to develop new insights into wildfires, and new predictive models of seasonal fuel dynamics.

Evaluation of the predictive capacity of dead fuel moisture models for Eastern Australia grasslands

2016 ◽  
Vol 25 (9) ◽  
pp. 995 ◽  
Author(s):  
Miguel G. Cruz ◽  
Susan Kidnie ◽  
Stuart Matthews ◽  
Richard J. Hurley ◽  
Alen Slijepcevic ◽  
...  
Keyword(s):  
Moisture Content ◽  
Process Model ◽  
Prediction Models ◽  
Percentage Error ◽  
Fuel Moisture ◽  
Fire Behaviour ◽  
Predictive Capacity ◽  
Eastern Australia ◽  
Physically Based ◽  
Community Information

The moisture content of dead grass fuels is an important input to grassland fire behaviour prediction models. We used standing dead grass moisture observations collected within a large latitudinal spectrum in Eastern Australia to evaluate the predictive capacity of six different fuel moisture prediction models. The best-performing models, which ranged from a simple empirical formulation to a physically based process model, yield mean absolute errors of 2.0% moisture content, corresponding to a 25–30% mean absolute percentage error. These models tended to slightly underpredict the moisture content observations. The results have important implications for the authenticity of fire danger rating and operational fire behaviour prediction, which form the basis of community information and warnings, such as evacuation notices, in Australia.

The 2019/20 eastern Australian mega forest fires - a global forest perspective

2020 ◽  
Author(s):  
Matthias Boer ◽  
Víctor Resco De Dios ◽  
Ross Bradstock
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Austral Summer ◽  
Fire Regimes ◽  
Burned Area ◽  
Fire Event ◽  
Data Set ◽  
Broadleaf Forest ◽  
Eastern Australia ◽  
Fire Activity

<p>The 2019/20 forest fires in eastern Australia burned over 5.8 million hectares of mainly temperate broadleaf forest between September 2019 and January 2020. This burned area figure is expected to rise over the remainder of the austral summer, but is already an order of magnitude larger than the mean annual burned area for Australian forest fires over the last 20 years, which is ~0.59 Mha per year. Here we show that this forest fire event is of a record-breaking scale, both nationally and globally, and was pre-conditioned by wide-spread prolonged drought and extreme heat.</p><p>We analysed global remotely sensed burned area data for 2000-2019 to estimate annual burned area fractions of all continental forest biomes. The annual burned area fraction, which is related to the length of fire intervals and other aspects of fire regimes, allows us to compare levels of fire activity across different forest biomes and continents.</p><p>Though very large fires occur in some forest biomes, such as the boreal forests of North-America and Asia, over the 20 years covered by our data set, annual burned area fractions have been very small (<0.03) for nearly all continental forest biomes including Australia’s temperate broadleaf forest biome. These findings provide a global historical reference for the interpretation of the scale of the 2019/20 eastern Australian mega forest fires.</p><p>With fire activity in all forest biomes strongly constrained by the moisture content of the fuels, explanations for the unconstrained burning of millions of hectares of temperate broadleaf forest in a single season must be sought in the extreme drought that has affected eastern Australia for the last two years. We use gridded daily soil moisture predictions for the continent to show how widespread and prolonged dryness set the stage for the unprecedented forest fire event of 2019/20.</p>

scholarly journals Influence of Fuel Moisture Content, Packing Ratio and Wind Velocity on the Ignition Probability of Fuel Beds Composed of Mongolian Oak Leaves via Cigarette Butts

Forests ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 507 ◽  
Author(s):  
Ping Sun ◽  
Yunlin Zhang ◽  
Long Sun ◽  
Haiqing Hu ◽  
Futao Guo ◽  
...  
Keyword(s):  
Moisture Content ◽  
Prediction Model ◽  
Forest Fires ◽  
Logistic Model ◽  
Fuel Moisture ◽  
Ignition Probability ◽  
Cigarette Butts ◽  
Mongolian Oak ◽  
Fuel Moisture Content ◽  
Oak Leaves

Cigarette butts are an important human firebrand and account for a significant amount of man-made fires. To better address forest fires caused by cigarette butts, the influencing factors governing the ignition probability of cigarette butts can be used to establish a prediction model. This study obtains the influencing factors of the ignition probability of cigarette butts in order to establish a prediction model by constructing fuel beds composed of Mongolian oak leaves with varied fuel moisture content and packing ratios. A total of 2520 ignition experiments were then conducted by dropping cigarette butts on the fuel beds to test the burning probability of the fuels under varied wind speeds. Moisture content, wind speed, and their interaction significantly influenced ignition probability. In the absence of wind, the ignition probability is zero. The maximum moisture content of Mongolian oak leaves that could be ignited by cigarette butts was 15%. A logistic model and self-built model for predicting the ignition probability were established using these results; the mean absolute error values for the two models were 2.71% and 1.13%, respectively, and the prediction error of the self-built model was lower than that of the logistic model. This is important research to mitigate the threat of forest fires due to cigarette butts given the frequent occurrence of these events.

scholarly journals Live fuel moisture content time series in Catalonia since 1998

2021 ◽  
Vol 78 (2) ◽  
Author(s):  
Eva Gabriel ◽  
Ruth Delgado-Dávila ◽  
Miquel De Cáceres ◽  
Pere Casals ◽  
Antoni Tudela ◽  
...  
Keyword(s):  
Time Series ◽  
Moisture Content ◽  
R Package ◽  
Fire Danger ◽  
Plant Responses ◽  
Fuel Moisture ◽  
Data Set ◽  
Link Type ◽  
Live Fuel Moisture ◽  
Fuel Moisture Content

Abstract Key message We present a structured and curated database covering 21 years of LFMC measurements in the Catalan region, along with an associated R package to manage updates and facilitate quality processing and visualisation. The data set provides valuable information to study plant responses to drought and improve fire danger prediction. Dataset access is at10.5281/zenodo.4675335, and associated metadata are available athttps://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/583fdbae-3200-4fa7-877c-54df0e6c5542.

Predicting hourly litter moisture content of larch stands in Daxinganling Region, China using three vapour-exchange methods

2015 ◽  
Vol 24 (1) ◽  
pp. 114 ◽  
Author(s):  
Ping Sun ◽  
Hongzhou Yu ◽  
Sen Jin
Keyword(s):  
Moisture Content ◽  
Forest Fires ◽  
Absolute Error ◽  
Model Parameters ◽  
Observation Data ◽  
Fuel Moisture ◽  
Fire Behaviour ◽  
Accuracy Requirement ◽  
Similar Accuracy ◽  
Direct Regression

Fuel moisture affects fuel ignition potential and fire behaviour. To accurately model fire behaviour, predict fuel ignition potential and plan fuel reduction, fuel moisture content must be assessed regularly and often. To establish models for Daxinganling Region, which has the most severe forest fires in China, hourly measurements were taken of moisture content in litter beds of larch stands sampled under different shading and slope conditions. Models were established using three vapour-exchange methods. The Nelson and Simard methods employed a direct timelag method using a timelag concept and the Nelson and Simard equilibrium moisture content (EMC) functions and estimating model parameters directly from fuel moisture and weather observation data in the field. The direct regression method used equations directly derived from linear regression of fuel moisture and field weather variation. The mean absolute error and mean relative error were determined for the Nelson (0.78%, 4.98%), Simard (1.04%, 5.57%) and direct regression (1.48%, 9.01%) methods. Only the models established using the direct timelag methods met the 1% accuracy requirement using either the Nelson or Simard EMC function, confirming the suitability and robustness of the direct timelag methods. The Simard and Nelson methods had similar accuracy, but Simard was more robust and only needed estimation of one parameter and hence is recommended for predicting litter moisture in this region.

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

Fire ◽  
2018 ◽  
Vol 1 (3) ◽  
pp. 43 ◽  
Author(s):  
Carlos Rossa ◽  
Paulo Fernandes
Keyword(s):  
Moisture Content ◽  
Fire Spread ◽  
High Heat ◽  
Heat Fluxes ◽  
Fuel Moisture ◽  
Spread Rate ◽  
Live Fuels ◽  
Live Fuel Moisture ◽  
Live Tree ◽  
Fuel Moisture Content

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.

The effect of fuel moisture content on the spread rate of forest fires in the absence of wind or slope

2017 ◽  
Vol 26 (1) ◽  
pp. 24 ◽  
Author(s):  
Carlos G. Rossa
Keyword(s):  
Moisture Content ◽  
Forest Fires ◽  
Field Experiments ◽  
Heat Content ◽  
Current Theory ◽  
Rate Variation ◽  
Fuel Moisture ◽  
Spread Rate ◽  
Wide Range ◽  
Fuel Moisture Content

Most studies on the effect of fuel moisture content (FMC) on forest fire behaviour focus on dead fuel moisture; mechanisms of fire spread in live vegetation are considered to remain unexplained by current theory and modelling. In this work, an empirical model for quantifying the effect of FMC on the ratio between spread rate and fuel bed height of fires in the absence of wind or slope was proposed. The model was fitted using data from laboratory experiments, carried out in fuel beds representative of natural litter and shrubland fuel complexes in a wide range of FMC (6–179%), and tested against data from field experiments and wildfires. The pattern of spread rate variation with FMC, namely its reduced rate for values above ~80%, was explained by the ratio between fuel low heat content and energy required for ignition.

A laboratory-based quantification of the effect of live fuel moisture content on fire spread rate

2016 ◽  
Vol 25 (5) ◽  
pp. 569 ◽  
Author(s):  
Carlos G. Rossa ◽  
Ricardo Veloso ◽  
Paulo M. Fernandes
Keyword(s):  
Moisture Content ◽  
Laboratory Experiments ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Drying Process ◽  
Spread Rate ◽  
Rate Of Spread ◽  
Live Fuels ◽  
Fuel Moisture Content ◽  
Content Range

Observational evidence of an effect of live vegetation moisture content on fire spread rate remains extremely scarce despite the significance of fire activity in fuel complexes dominated by live components. This study assessed the moisture content effect of quasi-live fuels on fire spread rates measured in laboratory experiments. Fuel beds were built by vertically placing vegetation clippings to reproduce the natural upright fuel structure. The fuel drying process during storage resulted in a wide moisture content range (13–180%). An exponential damping function was fitted to rate of spread observations in four fuel types, indicating that rate of spread is halved by an increase in live moisture content from 50 to 180%. This effect, especially at higher moisture contents, was weaker than that predicted by theoretical formulations and from studies in mixtures of dead and live fuel.

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

2018 ◽  
Vol 26 (3) ◽  
pp. eSC08 ◽  
Author(s):  
Carlos G. Rossa ◽  
Paulo M. Fernandes
Keyword(s):  
Moisture Content ◽  
Short Communication ◽  
Experimental Studies ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Rate Of Spread ◽  
Mediterranean Shrubland ◽  
Live Fuels ◽  
Live Fuel Moisture ◽  
Fuel Moisture Content

Aim of study: To reconcile the effects of live fuel moisture content (FMC) on fire rate of spread (ROS) derived from laboratory and field fires.Methods: The analysis builds on evidence from previous fire-spread experimental studies and on a comparison between two functions for the FMC damping effect: one derived from field burns, based on dead FMC, and another derived from laboratory trials, based on a weighted FMC (dead and live fuels).Main results: In a typical Mediterranean shrubland, laboratory and field-derived FMC damping functions are linearly related, which is explained by the correlation between monthly average live and dead FMC variation throughout the year. This clarifies why the effect of live FMC on real-world fires ROS has remained elusive.Research highlights: By providing evidence that the most significant effect of FMC on ROS is independent of vegetation phenology (dead or live condition), and explaining why in specific situations dead FMC is sufficient to provide satisfactory ROS predictions, our results can assist future modelling efforts.

Monitoring live fuel moisture content of heathland, shrubland and sclerophyll forest in south-eastern Australia using MODIS data

2012 ◽  
Vol 21 (3) ◽  
pp. 257 ◽  
Author(s):  
G. Caccamo ◽  
L. A. Chisholm ◽  
R. A. Bradstock ◽  
M. L. Puotinen ◽  
B. G. Pippen
Keyword(s):  
Moisture Content ◽  
Empirical Model ◽  
Fuel Moisture ◽  
Vegetation Types ◽  
South Eastern ◽  
Eastern Australia ◽  
Sclerophyll Forest ◽  
Live Fuel Moisture ◽  
Fuel Moisture Content ◽  
South Eastern Australia

Live fuel moisture content is an important variable for assessing fire risk. Satellite observations provide the potential for monitoring fuel moisture across large areas. The objective of this study was to use data from the Moderate Resolution Imaging Spectroradiometer to monitor live fuel moisture content of three fire-prone vegetation types (shrubland, heathland and sclerophyll forest) in south-eastern Australia. The performances of four spectral indices (Normalised Difference Vegetation Index, Visible Atmospherically Resistant Index, Normalised Difference Infrared Index centred on 1650 nm and Normalised Difference Water Index) were compared. Models based on Visible Atmospherically Resistant Index and Normalised Difference Infrared Index centred on 1650 nm provided the best results (R2 values of 0.537 and 0.586). An empirical model based on these two indices was developed and its performance compared with a meteorological index traditionally used in this context, the Keetch–Byram Drought Index. The empirical model (R2 = 0.692) outperformed the meteorological index (R2 = 0.151), showing an enhanced capability to predict live fuel moisture content of the fire-prone vegetation types considered.

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