Predicting slash depth for fire modeling /

Albini, F. A.; Brown, James K.; Forest, Intermountain; Station, Range Experiment

doi:10.5962/bhl.title.69039

Cited by 7 publications

(5 citation statements)

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“…Dead fuel is often more flammable than live foliage due to a lower heat of ignition and processes that control moisture absorption and retention [107,131]. Higher wind speeds are required to carry crown fire through the epidemic stands because dead foliage falls relatively quickly from bark beetle-attacked spruce [107,132]. Seasonal drying and prolonged drought may also cause both live and dead fuels to become even more flammable [133].…”

Section: Crown Fire Behaviormentioning

confidence: 99%

Spruce Beetle Biology, Ecology and Management in the Rocky Mountains: An Addendum to Spruce Beetle in the Rockies

Jenkins

Hebertson

Munson

2014

Forests

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Spruce beetle outbreaks have been reported in the Rocky Mountains of western North America since the late 1800s. In their classic paper, Spruce Beetle in the Rockies, Schmid and Frye reviewed the literature that emerged from the extensive outbreaks in Colorado in the 1940s. A new wave of outbreaks has affected Rocky Mountain subalpine spruce-fir forests beginning in the mid-1980s and continuing to the present. These outbreaks have spurred another surge of basic and applied research in the biology, ecology and management of spruce and spruce beetle populations. This paper is a review of literature on spruce beetle focusing on work published since the late 1970s and is intended as an addendum to Spruce Beetle in the Rockies.

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Section: Crown Fire Behaviormentioning

confidence: 99%

Spruce Beetle Biology, Ecology and Management in the Rocky Mountains: An Addendum to Spruce Beetle in the Rockies

Jenkins

Hebertson

Munson

2014

Forests

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“…The depth of the fuel bed determined as an output of the planar intercept method (Brown 1974) is called the "average high particle depth." Albini and Brown (1978) showed that for logging slash fuel beds, the Fuel Bed Depth is approximately 63.3 percent of the average high particle depth. For the special case fuel model, palmetto-gallberry (P-G), Fuel Bed Depth is calculated as 2/3 of the P-G Height of Understory variable entered on the worksheet.…”

Section: Second Fuel Modelmentioning

confidence: 99%

BehavePlus fire modeling system, version 5.0: Variables

Andrews¹

2009

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This publication has been revised to reflect updates to version 4.0 of the BehavePlus software. It was originally published as the BehavePlus fire modeling system, version 4.0: Variables in July, 2008.The BehavePlus fire modeling system is a computer program based on mathematical models that describe wildland fire behavior and effects and the fire environment. It is a flexible system that produces tables, graphs, and simple diagrams. It can be used for a host of fire management applications including projecting the behavior of an ongoing fire, planning prescribed fire, fuel hazard assessment, and training. The BehavePlus program automatically creates a worksheet that requests the required input variables based on the modules, output variables, and options selected by the user. This is a reference paper that describes the 189 variables in BehavePlus, with information on input and output relationships. A User's Guide describes operation of the program and can be accessed at http://www.fs.fed.us/rm/pubs/rmrs_gtr106.html.

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“…Since the late 1970s, live and dead woody and herbaceous fuel loading has been calculated through equations that use constant bulk densities over a management unit [22] or estimated using ocular estimates (e.g., [14,23]). They assume a constant fuel bulk density regardless of fuel height, which results in a monotonic increase in fuel load with depth [22,24]. Hence, fuels have historically been viewed through a coarse lens, despite the importance of fine scale fuel variation to fire ecology [17,25,26].…”

Section: Introductionmentioning

confidence: 99%

Non-Destructive Fuel Volume Measurements Can Estimate Fine-Scale Biomass across Surface Fuel Types in a Frequently Burned Ecosystem

Hiers

Loudermilk

Hawley

et al. 2021

Fire

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Measuring wildland fuels is at the core of fire science, but many established field methods are not useful for ecosystems characterized by complex surface vegetation. A recently developed sub-meter 3D method applied to southeastern U.S. longleaf pine (Pinus palustris) communities captures critical heterogeneity, but similar to any destructive sampling measurement, it relies on separate plots for calculating loading and consumption. In this study, we investigated how bulk density differed by 10-cm height increments among three dominant fuel types, tested predictions of consumption based on fuel type, height, and volume, and compared this with other field measurements. The bulk density changed with height for the herbaceous and woody litter fuels (p < 0.001), but live woody litter was consistent across heights (p > 0.05). Our models predicted mass well based on volume and height for herbaceous (RSE = 0.00911) and woody litter (RSE = 0.0123), while only volume was used for live woody (R2 = 0.44). These were used to estimate consumption based on our volume-mass predictions, linked pre- and post-fire plots by fuel type, and showed similar results for herbaceous and woody litter when compared to paired plots. This study illustrates an important non-destructive alternative to calculating mass and estimating fuel consumption across vertical volume distributions at fine scales.

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Predicting slash depth for fire modeling /

Cited by 7 publications

References 0 publications

Spruce Beetle Biology, Ecology and Management in the Rocky Mountains: An Addendum to Spruce Beetle in the Rockies

Spruce Beetle Biology, Ecology and Management in the Rocky Mountains: An Addendum to Spruce Beetle in the Rockies

BehavePlus fire modeling system, version 5.0: Variables

Non-Destructive Fuel Volume Measurements Can Estimate Fine-Scale Biomass across Surface Fuel Types in a Frequently Burned Ecosystem

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