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- The use of mechanical mastication to treat non-merchantable fuels is becoming increasingly popular, but loadings and other characteristics of masticated fuel beds are unknown. Surveys of eight recently masticated sites in northern California and southwestern Oregon indicate that significant site level differences were detected for 1 hr and 10 hr time-lag classes and total woody fuel loading (P < 0.0001). the majority of the total woody fuel loading occurred in the 10 hr time-lag class (76.9 ± 14.1 percent) at all 10 sites. at one particular site, planar intercept estimates of woody fuel...AuthorsJeffrey M. Kane, Eric E. Knapp, J. Morgan VarnerKeywordsSourceIn: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 341-350Year2006
- Computerized and manual systems for modeling wildland fire behavior have long been available (Rothermel 1983, Andrews 1986). These systems focus on one-dimensional behaviors and assume the fire geometry is a spreading line-fire (in contrast with point or area-source fires). Models included in these systems were developed to calculate fire spread rate (Rothermel 1972, Albini 1976), fire shape (Anderson 1983, Alexander 1985), spot fire distance (Albini 1979, 1983) and crown fire spread rate (Van Wagner 1977, Rothermel 1991). The FlamMap program was developed for extending the utility of...AuthorsMark A. FinneyKeywordsSourceIn: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 213-220Year2006
- This study used a rule-based approach to prioritize locations of fuel treatments in the boreal mixedwood forest of western Canada. The burn probability (BP) in and around Prince Albert National Park in Saskatchewan was mapped using the Burn-P3 (Probability, Prediction, and Planning) model. Fuel treatment locations were determined according to three scenarios and five fuel treatment intensities. Fuel treatments were located according to jurisdictional boundaries and BP; BP only; and nonflammable landscape features, BP, and fuel treatment orientation. First, a baseline BP map was created...AuthorsMarc-André Parisien, Dave R. Junor, Victor G. KafkaKeywordsSourceIn: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 221-236Year2006
- The LANDFIRE project is a collaborative interagency effort designed to provide seamless, nationally consistent, locally relevant geographic information systems (GIS) data layers depicting wildland fuels, vegetation and fire regime characteristics. The LANDFIRE project is the first of its kind and offers new opportunity for fire management and research activities. Here we introduce the LANDFIRE wildland fuels data layers including fire behavior fuel models, canopy bulk density, canopy base height, canopy cover, canopy height and new Fuel Loading Models. Specifically, we focus on the methods...AuthorsMatthew C. Reeves, Jay R. Kost, Kevin C. RyanKeywordsSourceIn: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 239-252Year2006
- Efforts to quantitatively evaluate the effectiveness of fuels treatments are hampered by inconsistencies between the spatial scale at which fuel treatments are implemented and the spatial scale, and detail, with which we model fire and fuel interactions. Central to this scale inconsistency is the resolution at which variability within the fuel bed is considered. Crown fuels are characterized by clumps of fuel separated by gaps between needles, between branches, and between trees. A growing body of evidence suggests that this variability plays an important role in how fire spreads. A new...AuthorsRussell A. ParsonsKeywordsSourceIn: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 253-272Year2006
- This paper describes the FuelCalc computer program. FuelCalc is a tool to compute surface and canopy fuel loads and characteristics from inventory data, to support fuel treatment decisions by simulating effects of a wide range of silvicultural treatments on surface fuels and canopy fuels, and to provide linkages to stand visualization, fire behavior and fire effects programs that rely on estimates of fuel loads and qualities. Canopy fuel characteristics, including available fuel, canopy bulk density, canopy base height and canopy cover are estimated from a list of trees.AuthorsElizabeth Reinhardt, Duncan C. Lutes, Joe ScottKeywordsSourceIn: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 273-282Year2006
- Managers are faced with reducing hazardous fuel, restoring fire regimes, and decreasing the threat of catastrophic wildfire. Often, the comprehensive, scientifically-credible data and applications needed to test alternative fuel treatments across multi-ownership landscapes are lacking. Teams from the USDA Forest Service, Department of the Interior, and The Nature Conservancy are completing the LANDFIRE Project, which produces consistent and comprehensive spatial data describing vegetation composition and structure, wildland fuel, historical fire regimes, and ecosystem status across the...AuthorsKevin C. Ryan, Kristine M. Lee, Matthew G. Rollins, Zhiliang Zhu, James Smith, Darren JohnsonKeywordsSourceIn: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 193-200Year2006
- United States wildland fire policy and program reviews in 1995 and 2000 required reduction of hazardous fuel and recognition of fire as a natural process. Although an existing policy, Wildland Fire Use (WFU), permitted managing natural ignitions to meet resource benefits, most fuel reduction is still achieved through mechanical treatments and prescribed burning. However resource constraints suggest that successful fuel and ecosystem management hinges on expanding WFU. The decision to authorize WFU in the U.S. Forest Service rests with line officers, and the ‘go/no go’ decision constitutes...AuthorsMartha A. WilliamsonKeywordsSourceIn: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 67-77Year2006
- Fire managers are required to evaluate and justify the effectiveness of planned fuel treatments in modifying fire growth, behavior and effects on resources and assets. With the number of models currently available, today’s fire manager can become overwhelmed when deciding which model to use. Each model has a required level of expertise in order to develop the necessary data, run the model(s), and analyze and interpret their associated outputs. In addition, each model has an appropriate temporal and spatial scale for its use, e.g., stand level versus landscape level. Traditional fuel...AuthorsCharles W. McHughKeywordsSourceIn: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 81-105Year2006
- A simulation system was developed to explore how fuel treatments placed in random and optimal spatial patterns affect the growth and behavior of large fires when implemented at different rates over the course of five decades. The system consists of a forest/fuel dynamics simulation module (FVS), logic for deriving fuel model dynamics from FVS output, a spatial fuel treatment optimization program, and spatial fire growth and behavior model to evaluate the performance of the treatments in modifying large fires. Simulations were performed for three study areas: Sanders County in western...AuthorsMark A. Finney, Rob C. Seli, Charles W. McHugh, Alan A. Ager, Berni Bahro, James K. AgeeKeywordsSourceIn: Andrews, Patricia L.; Butler, Bret W., comps. 2006. Fuels Management-How to Measure Success: Conference Proceedings. 28-30 March 2006; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 125-147Year2006