A Soil Burn Severity Index for Understanding Soil-fire Relations in Tropical Forests

Jain, Theresa B.; Gould, William A.; Graham, Russell T.; Pilliod, David S.; Lentile, Leigh B.; González, Grizelle

doi:10.1579/0044-7447-37.7.563

Cited by 22 publications

(17 citation statements)

References 41 publications

(57 reference statements)

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“…In general, a burned site is more likely to support vegetation if some surface organic materials are present after a fire [41], but the post-fire amounts and disposition are highly variable [3,5,9,42,43]. Wildfires, and more often prescribed fires, typically do not burn organic materials (horizons) uniformly [12,44]. For example, humus often burns along with litter, but in some cases it will burn and leave the litter scorched and intact.…”

Section: Resultsmentioning

confidence: 99%

“…Post-fire conditions-the characteristics of the environment following a fire-affect chemical, biological, and physical aspects of soil responses. In turn, soil responses affect vegetation composition, structure, and successional dynamics through time and across multiple spatial scales [5,[11][12][13]. The post-fire environment is the baseline for a forest's recovery after a fire because it provides an array of habitat niches and post-fire conditions that result in future forest productivity, and species diversity and recovery (both plant and animal) [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

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Index for Characterizing Post-Fire Soil Environments in Temperate Coniferous Forests

Jain

Pilliod

Graham

et al. 2012

Forests

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Many scientists and managers have an interest in describing the environment following a fire to understand the effects on soil productivity, vegetation growth, and wildlife habitat, but little research has focused on the scientific rationale for classifying the post-fire environment. We developed an empirically-grounded soil post-fire index (PFI) based on available science and ecological thresholds. Using over 50 literature sources, we identified a minimum of five broad categories of post-fire outcomes: (a) unburned, (b) abundant surface organic matter (>85% surface organic matter), (c) moderate amount of surface organic matter (≥40 through 85%), (d) small amounts of surface organic matter (<40%), and (e) absence of surface organic matter (no organic matter left). We then subdivided each broad category on the basis of post-fire mineral soil colors providing a more fine-tuned post-fire soil index. We related each PFI category to characteristics such as soil temperature and duration of heating during fire, and physical, chemical, and biological responses. Classifying or describing post-fire soil conditions consistently will improve interpretations of fire effects research and facilitate communication of potential responses or outcomes (e.g., erosion potential) from fires of varying severities. OPEN ACCESSForests 2012, 3 446

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Index for Characterizing Post-Fire Soil Environments in Temperate Coniferous Forests

Jain

Pilliod

Graham

et al. 2012

Forests

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“…Soil color changes if the soil is subjected to deforestation and slash-and-burn cultivation (Jain et al 2008). In the processes of land degradation, some soil characteristics change.…”

Section: Nonlinear Relationships Between Soil Color Variations and Thmentioning

confidence: 99%

“…Fire, as the dominant factor of the deciduous forest, appealed to be the cause of this lack of relationship (Certini 2005). The deciduous forest soil accumulated ash that darkens soil color (Jain et al 2008). …”

Section: Nonlinear Relationships Between Soil Color Variations and Thmentioning

confidence: 99%

Semiquantitative color profiling of soils over a land degradation gradient in Sakaerat, Thailand

Doi

Wachrinrat

Teejuntuk

et al. 2009

Environ Monit Assess

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In this study, we attempted multivariate color profiling of soils over a land degradation gradient represented by dry evergreen forest (original vegetation), dry deciduous forest (moderately disturbed by fire), and bare ground (severely degraded) in Sakaerat, Thailand. The soils were sampled in a dry-to-wet seasonal transition. Values of the red-green-blue (RGB), cyan-magenta-yellow-key black (CMYK), L*a*b*, and hue-intensity-saturation (HIS) color models were determined using the digital software Adobe Photoshop. Land degradation produced significant variations (p<0.05) in R, C, Y, L*, a*, b*, S, and I values (p<0.05). The seasonal transition produced significant variations (p<0.05) in R, G, B, C, M, K, L*, b*, and I values. In discriminating the soils, the color models did not differ in discriminatory power, while discriminatory power was affected by seasonal changes. Most color variation patterns had nonlinear relationships with the intensity of the land degradation gradient, due to effects of fire that darkened the deciduous forest soil, masking the nature of the soil as the intermediate between the evergreen forest and the bare ground soils. Taking these findings into account, the utilization of color profiling of soils in land conservation and rehabilitation is discussed.

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“…As the dew point rates increase, the danger of fire increases.4.1. d. Soil TemperatureSoil is affected directly by the air temperature and sun radiation absorbed by the micro substances between layers(Theresa et al 2008). It has been assumed that high temperatures affect seedlings, first, by increasing evaporative demand, and second, by direct tissue damage where seedlings are in contact with hot surfaces which increase the drought in soil and thus increase the chance of fire occurrence(Hälgrenet al 1991).…”

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confidence: 99%

Using correlative data analysis to develop weather index that estimates the risk of forest fires in Lebanon & Mediterranean: Assessment versus prevalent meteorological indices

Hamadeh

Karouni

Daya

et al. 2017

Case Studies in Fire Safety

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Forest fires are among the most dangerous natural threats that bring calamities to a community and can turn it totally upside down.In this paper, to enable a prevention mechanism, we rely on analytics to build a novel fire danger index model that predicts the risk of a developing fire in north Lebanon. We use correlation methods such as statistical regression, Pearson, Spearman and Kendall's Tau correlation to identify the most affecting parameters on fire ignition during the last six years in north Lebanon.The correlations of these attributes with fire occurrence are studied in order to develop the fire danger index. The strongly correlated attributes are then derived. We rely on linear regression to model the fire index as function of a reduced set of weather parameters that are easy to measure.This is critical as it facilitates the application of such prevention models in developing countries like Lebanon. The outcomes resulting from validation tests of the proposed index show high performance in the Lebanese regions. An assessment versus common widespread weather models is then made and has showed the significance the selected parameters.It is strongly believed that this index will help improve the ability of fire prevention measures in the Mediterranean basin area.

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A Soil Burn Severity Index for Understanding Soil-fire Relations in Tropical Forests

Cited by 22 publications

References 41 publications

Index for Characterizing Post-Fire Soil Environments in Temperate Coniferous Forests

Index for Characterizing Post-Fire Soil Environments in Temperate Coniferous Forests

Semiquantitative color profiling of soils over a land degradation gradient in Sakaerat, Thailand

Using correlative data analysis to develop weather index that estimates the risk of forest fires in Lebanon & Mediterranean: Assessment versus prevalent meteorological indices

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