The Fire and Fuels Extension to the Forest Vegetation Simulator

Reinhardt, Elizabeth D.; Crookston, Nicholas L.

doi:10.2737/rmrs-gtr-116

Cited by 219 publications

(217 citation statements)

References 51 publications

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“…Elliptical fire size and shape, area, perimeter, lengthto-width ratio (Anderson 1983) double ellipse (Andrews 1986) simplified to simple ellipse CONTAIN Fire containment (Albini and others 1978) in the old BEHAVE (Fried and Fried 1996) in BehavePlus SPOT Spotting distance from torching trees (Albini 1979, Chase 1981 Spotting distance from a burning pile (Albini 1981) Spotting distance from a wind-driven surface fire (Albini 1983a, Albini 1983b, Chase 1984 SCORCH Crown scorch height (Van Wagner 1973) MORTALITY Tree mortality Reinhardt 1988, Reinhardt andCrookston 2003) (Hood and others 2008) updates for version 5.0…”

Section: Sizementioning

confidence: 99%

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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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Section: Sizementioning

confidence: 99%

“…Bark thickness Reinhardt 1988, Reinhardt andCrookston 2003) IGNITE Probability of ignition from firebrand (Schroeder 1969) Probability of ignition from lightning (Latham and Schlieter 1989) Fine dead fuel moisture Tool…”

Section: Sizementioning

confidence: 99%

BehavePlus fire modeling system, version 5.0: Variables

Andrews¹

2009

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“…We simulated the structural development of each unit over three 10-year periods by using the east Cascades FVS variant (Johnson, 1990), the WRDM (Frankel, 1998), and the FVS fuels and fire extension (FFE) (Reinhardt and Crookston, 2003). Conditions in each unit were compared against the definitions for LSF structure and FT in each decade, values assigned as described above, and output for each unit saved in a '7 Fig.…”

Section: Simulating Forest Developmentmentioning

confidence: 99%

Costs of landscape silviculture for fire and habitat management

Hummel

Calkin

2005

Forest Ecology and Management

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In forest reserves of the U.S. Pacific Northwest, management objectives include protecting late-semi habitat structure by reducing the threat of large-scale disturbances like wildfire. We simulated how altering within-and among-stand structure with silvicultural treatments of differing intensity affected late-seral forest (LSF) structure and fire threat (FT) reduction over 30 years in a 6070-ha reserve. We then evaluated how different financia! requirements influenced the treatment mix selected for each decade, the associated effects on FT reduction and LSF structure in the reserve, and treatment costs. Requirements for treatments to earn money (NPV+), break even (NPV0), or to not meet any financial goal at the scale of the entire reserve (landscape) affected the predicted reduction of FT and the total area of LSF structure in different ways. With or without a requirement to break even, treatments accomplished about the same landscape level of FT reduction and LSF structure. Although treatment effects were similar, their associated net revenues ranged from negative $1 million to positive $3000 over 30 years. In contrast, a requirement for landscape treatments to earn money ($0.5 to $1.5 million NPV) over the same period had a negative effect on FT reduction and carded a cost in terms of both FT reduction and LSF structure. Results suggest that the spatial scale at which silvicultural treatments were evaluated was influential because the lowest cost to the reserve objectives was accomplished l~y a mix of treatments that earned or lost money at the stand level but that collectively broke even at the landscape scale. Results also indicate that the timeframe over which treatments were evaluated was important because if breaking even was required within each decade instead of cumulatively over all three, the cost in terms of FT reduction and LSF structure was similar to requiring landscape treatments to earn $0.5 million NPV.

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“…Fire behavior is strongly influenced by fire weather conditions and fuel moisture (Reinhardt and Crookston 2003). We were interested in simulated fire behavior under the most extreme fire weather conditions.…”

Section: Spatial Model Of Forest Reference Conditionsmentioning

confidence: 99%

Landscape‐scale modeling of reference period forest conditions and fire behavior on heavily logged lands

et al. 2014

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Landscape-scale modeling of reference period forest conditions and fire behavior on heavily logged lands. Ecosphere 5(3):32. http://dx.doi.org/10.1890/ES13-00294.1Abstract. Forest conditions prior to extensive land clearing are often used as a point-of-reference by ecologists and resource managers for characterizing the historical range of variability in forest conditions shaped by intact disturbance regimes. Quantitative data on forest reference conditions can be developed from forest surveys and reconstructions using dendroecology; however, these methods lack the spatial resolution needed for landscape management. In this paper, we combine predictive vegetation mapping methods with reference forest conditions inferred from early forest surveys, dendroecology, and fire simulation models to develop landscape-scale reference conditions for forest structure, forest fuels, fire frequency, and fire behavior using the Lake Tahoe Basin, California as an example.The dendroecological reconstruction method used for the Lake Tahoe Basin forests was not sensitive to variation in decomposition rates suggesting that our method provided robust estimates of reference period forest characteristics. The cluster analysis procedure identified five forest structure types (white fir, Jeffrey pine, red fir, lodgepole pine, and subalpine) and 15 subtypes. Each forest type had a characteristic composition, density, and basal area. Our random forests approach to classifying and mapping the spatial distribution of the five dominant reference forest structure types resulted in 51.5% classification accuracy using 14 physiographic and climatic variables. The random forests model to identify subtypes within each forest group had an average percent correct classification of 47.8%. The random forests model for fire intervals explained 67% of the variance in the point fire return interval estimates from fire-scarred trees. Estimates of reference period fuels modeled from stand structure suggested moderate fuel loads for reference forests. The predicted potential fire type for forest subtypes under extreme weather was surface fire except for red fir and the lodgepole pine subtypes with potential for crown fire. By characterizing the reference forest composition, structure, and disturbance frequency with a range of variability, managers can develop a forested landscape more resilient to changes in disturbance regime and climate. Although our approach was developed for the Lake Tahoe Basin, California, it could be applied to a wide range of forest landscapes to identify forest reference conditions.

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The Fire and Fuels Extension to the Forest Vegetation Simulator

Cited by 219 publications

References 51 publications

BehavePlus fire modeling system, version 5.0: Variables

BehavePlus fire modeling system, version 5.0: Variables

Costs of landscape silviculture for fire and habitat management

Landscape‐scale modeling of reference period forest conditions and fire behavior on heavily logged lands

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