Progress 10/01/04 to 10/01/09
Outputs
OUTPUTS: This project has been terminated. This research of this particular problem will continue in RMRS Project 4853-8
Impacts
(N/A)
Publications
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Progress 10/01/06 to 09/30/07
Outputs
Forest managers face many questions where managing for fire as a disturbance process in Northern Rockies forests. What mosaic of treatments is most effective at reducing risk of catastrophic fire while having acceptable resource impacts? What are cost and resource trade-offs over time between treatments and no treatments? A study is testing integration of information from three types of spatial landscape models to address these and other related questions. SIMPPLLE (http://www.fs.fed.us/rm/ecology/publications/simpplle/) is being used to predict the spatial likelihood of fire across the landscape for current conditions and how these conditions will change in the future if there are no management treatments. Simulations include changes due to bark beetles and disease that affect future fuels. Fire behavior models, FARSITE, FLAMMAP, and MTT (http://farsite.org/), are being used to predict fire spread and intensity for the existing landscape conditions for specified fire
scenarios. The Treatment Optimization Model (TOM) component is used to identify treatment locations to reduce fire spread rate and intensity for specific fire scenarios. MAGIS (http://www.fs.fed.us/rm/econ/magis/) is being used to schedule optimal treatment scenarios and calculate resource and economic trade-offs where managing for multiple resource objectives. MAGIS integrates input from the fire behavior and disturbance process and balances treatments to modify fire behavior with the location of valued resources homes, sensitive habitats, and streams while estimating costs and possible revenues over a range of treatment options. Analyses for evaluating current conditions and change without treatment have been completed. The fire behavior models were run for two fire scenarios that assumed burning conditions at the 95 percentile; one assumed ignition from lightning on the western edge of the study area with west winds, the other assumed ignition points in the southern portion of the
area with south winds. The TOM component was used to identify optimal treatment locations for these fire scenarios. Approximately 25% of the suggested treatment locations for the west wind scenario were also selected for the south wind scenario. Runs were made with MAGIS to schedule treatment locations. The information from these runs was combined with information from field reconnaissance to develop a proposed alterative. The treatment alternatives were simulated by the fire behavior models and SIMPPLLE. Comparing simulated results from a treatment alternative with the no-treatment alternative provided a measure of the predicted effectiveness of the treatments. In addition, treatment effects, costs, and revenues computed by MAGIS provide information for evaluating alternatives. A related study is modeling biomass volumes and costs associated with fuel treatments over time and space, and comparing the carbon balance and particulate emissions associated with utilizing the
sub-merchantable of biomass produced by fuel and forest health restoration treatments with on-site disposal by burning.
Impacts
The models involved in this study address different important aspects of fuel and forest health restoration. This project gives researchers and managers an opportunity to work together to investigate how to best integrate the use of these diverse models to effectively address critical questions for designing vegetation treatments. Answers emerge to the questions of how best to use fire and planning modeling tools throughout the development of fuel reduction projects. Modelers continue to guide managers through interpretation of model results while managers integrate the results into the planning process. A similar approach is being applied on the Beaverhead-Deerlodge National Forest as part of a of national effort to test alternative approaches for planning the location for fuel treatments to reduce the likelihood of severe wildland fire in locations with significant values at risk. Results will provide valuable information about the advantages and disadvantages of the
tested approach, and possibly provide a basis for future fuel treatment/forest health restoration analyses. Integrating biomass volume and cost estimates into treatment scheduling models will help identify added value of utilization facilities in terms of reducing the cost and environmental affects of fuels treatments. Concern over global climate change has increased interest in evaluating the use of sub-merchantable material associated with forest health and fuel reduction treatments as an energy source. This material is commonly burned onsite, an activity that imposes costs to the landowner and produces unwanted smoke composed mostly of carbon, methane, and particulates. Knowing the net environmental effects of using this material for energy production compared to burning onsite is important from the standpoint of wise resource use and public attitudes toward biomass utilization. The results of this research indicate there is a distinct possibility of marketable carbon credits for
the net saving in fossil fuels associated with utilization of this woody biomass for energy.
Publications
- Chalfoun, A.; Martin, T.E. 2007. Assessments of habitat preferences and quality depend on spatial scale and metrics of fitness. Journal of Applied Ecology 44: 983-992.
- Sullivan, Janet. 2007. Using models to provide a virtual test of forest treatments. In: Bitterroot Ecosystem Management Research Project EcoReport, 2007. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station: p. 4. (http://www.fs.fed.us/rm/ecopartner/ecoreport.shtml)
- Watson, Alan; Matt, Roian; Knotek, Katie; Williams, Dan; Yung, Laurie. [In press] Traditional wisdom, protecting wilderness as a cultural landscape. In, Proceedings: Sharing Indigenous Wisdom International Conference. Green Bay, WI. June 2007.
- Watson, Alan; Kotek, Katie; Matt, Roian; Yung, Laurie. 2007. Understanding landscape meanings, attributes and threats for the planning and application of fuel treatments and fire management on the Flathead Indian Reservation, Montana. Report to the Confederated Salish & Kootenai Tribes. 382 p.
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Progress 10/01/05 to 09/30/06
Outputs
Forest managers face many questions when managing for the role of fire in forests of the Northern Rockies. What mosaic of treatment is most effective at reducing risk of catastrophic fire while having acceptable resource impacts? What are trade-offs in costs and resources over time between treatments and no treatments? A study is testing the integration of information from three types of spatial landscape models to address these and other questions. SIMPPLLE (http://www.fs.fed.us/rm/ecology/publications/simpplle/) predicts the spatial likelihood of fire across the landscape for current conditions and how these conditions will change over time without treatments. Simulations include changes due to bark beetles and disease that affect future fuels. Fire behavior models FARSITE, FLAMMAP, and MTT (http://farsite.org/) predict fire spread and intensity for the existing landscape conditions for specified fire scenarios. The Treatment Optimization Model (TOM) component
identifies treatment locations to reduce fire spread rate and intensity for specific fire scenarios. MAGIS (http://www.fs.fed.us/rm/econ/magis/) schedules optimal treatment scenarios and calculates resource and economic trade-offs where managing for multiple resource objectives. MAGIS integrates input from the fire behavior and disturbance process and balances treatments to modify fire behavior with the location of valued resources such as homes, sensitive habitats, and streams, while estimating costs and possible revenues over a range of treatment options. The analyses for evaluating current conditions and change without treatment have been completed. Fire behavior models were run for two fire scenarios presented by the land managers. The TOM component was used to identify optimal treatment locations for these fire scenarios. Information from MAGIS runs was combined with information from field reconnaissance to develop a proposed alterative. The treatment alternatives have been
simulated by the fire behavior models and SIMPPLLE. Comparing the simulated results from a treatment alternative with the no-treatment alternative will provide a measure of the effectiveness of the treatments. In addition, treatment effects, costs, and revenues computed by MAGIS provide information for evaluating alternatives. A related study is modeling biomass volumes and costs associated with fuel treatments over time and space. The results reflect the importance of haul distance and cost it is more cost effective to deliver the small woody biomass created by fuel and forest health restoration treatments to a hypothetical local market for biomass-utilization for 82 percent of the study area than incur an average cost of $100 per acre to dispose of this biomass on site. It was more cost effective to deliver biomass to a distant user for 16% of the area falling in the northern portion of the study area than onsite disposal. A new study is examining the carbon effect of displacing
fossil fuel use by using forest residues resulting from restoration and/or stewardship projects. It is calculating carbon and other emissions from bio-utilization compared to onsite burning, including the savings in fossil fuels.
Impacts
Models address important aspects of fuel reduction and forest health restoration. Researchers and managers are investigating how best to integrate these models to answer critical questions throughout development of fuel reduction projects. Modelers guide managers in interpreting model results while managers integrate results into the planning process. A similar approach is being applied on another forest as part of a national effort testing alternative approaches for planning fuel treatments to reduce likelihood of severe wildland fire in areas with significant values at risk. Results will provide valuable information about advantages and disadvantages of the tested approach. Integrating biomass volume and cost estimates into treatment scheduling models will help identify added value of bio-utilization facilities in reducing costs and environmental affects of fuels treatments. Fuel treatment cost prediction equations have been implemented in fuel treatment software
and provide the capability to make condition-specific estimates of cost, rather than using broad averages. The biomass study led to implementation of a standardized adjustment that provides a timber purchaser a cost allowance to promote utilization of non-sawlog tree boles. This is highly valued by Northern Region timber appraisal personnel searching for a method to promote small tree utilization and reduce open burning. The carbon emission comparison will reveal the net contribution of greenhouse gases from two different approaches for handling biomass, and examine potential for carbon credits in the future.
Publications
- Hyde, Kevin; Jones, J. Greg; Silverstein, Robin; Stockmann, Keith; Loeffler, Dan. 2006. Integrating fuel treatments into comprehensive ecosystem Management. In: Andrews, P.L., Butler, B.W. Comps. Fuels management how to measure success: Conference proceedings. 2006 28-30 March; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 549-561.
- Jones, Greg. 2005. Visualizing a forest landscape today and tomorrow. ECO Report. Missoula, MT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Forestry Sciences Laboratory; Fall: p. 3, 8.
- Loeffler, Dan; Calkin, David E.; Silverstein, Robin P. 2006. Estimating volumes and costs of forest biomass in Western Montana using forest inventory and geospatial data. Forest Products Journal. 56(6): 31-37.
- Calkin, Dave. 2005. Economics research unit explores biomass utilization opportunities on the Bitterroot National Forest. ECO Report. Missoula, MT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Forestry Sciences Laboratory; Fall: p. 5.
- Canton-Thompson, Janie. 2005. Scale matters some thoughts on landscape sustainability. ECO Report. Missoula, MT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Forestry Sciences Laboratory; Fall: p. 1-2.
- Gunderson, Kari; Watson, Alan E.; Nelson, R.D.; Titre, J. 2004. Mapping place meanings on the Bitterroot National Forest a landscape-level assessment of social value input to fuel hazard reduction treatments. Final Report. In-house-0310. Aldo Leopold Wilderness Research Institute, Missoula, MT. 39 p.
- Silverstein, Robin P.; Loeffler, Dan; Jones, J. Greg; Calkin, Dave E.; Zuuring, Hans R.; Twer, Martin. 2006. Biomass utilization modeling on the Bitterroot National Forest. In: Andrews, P.L., Butler, B.W. Comps. Fuels management how to measure success: Conference proceedings. 2006 28-30 March; Portland, OR. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. 673-688.
- Twer, Martin. 2005. Design and comparison of quantitative alternative future landscape scenarios for the Bitterroot Area. Final Report 03-JV-11222052-096. The University of Montana, Missoula, MT. 162 p.
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Progress 10/01/04 to 09/30/05
Outputs
Forest managers face many questions where managing for the role of fire in forests of the Northern Rockies. What mosaic of treatments is most effective at reducing risk of catastrophic fire while having acceptable resource impacts? What are the cost and resource trade-offs over time between treatments and no treatments? A study is testing the integration of information from three types of spatial landscape models to address these and other related questions. SIMPPLLE (http://www.fs.fed.us/rm/ecology/publications/simpplle/) is being used in this process to predict the spatial likelihood of fire across the landscape for the current conditions and how these conditions will change in the future if there are no management treatments. Changes due to bark beetles and disease that affect future fuels are included in these simulations. Fire behavior models, FARSITE, FLAMMAP, and MTT (http://farsite.org/), are being used to predict fire spread and intensity for the existing
landscape conditions for specified fire scenarios. The Treatment Optimization Model (TOM) component is used to identify treatment locations to reduce fire spread rate and intensity for specific fire scenarios. MAGIS (http://www.fs.fed.us/rm/econ/magis/) is being used to schedule optimal treatment scenarios and calculate resource and economic trade-offs where managing for multiple resource objectives. MAGIS integrates input from the fire behavior and disturbance process and balances treatments to modify fire behavior with the location of valued resources - homes, sensitive habitats, and streams while estimating costs and possible revenues over a range of treatment options. The analyses for evaluating current conditions and change without treatment have been completed. The fire behavior models were run for two fire scenarios, both scenarios assumed burning conditions at the 95 percentile, one assumed ignition from lightning on the western edge of the study area with wind from the west,
the other assumed ignition points in the southern portion of the area with wind from the south. The TOM component was used to identify optimal treatment locations for these specific fire scenarios. Approximately 25% of the suggested treatment locations suggested for the west wind scenario were also selected for the south wind scenario. Runs were made with MAGIS to schedule treatment locations. The information from these runs was combined with information field reconnaissance to develop a proposed alterative. The treatment alternatives will be simulated by the fire behavior models and SIMPPLLE. Comparing the simulated results from a treatment alternative with the no-treatment alternative will provide a measure of the effectiveness of the treatments. In addition, the treatment effects, costs, and revenues computed by MAGIS provide information for evaluating alternatives. A related study is modeling biomass volumes and costs associated with fuel treatments over time and space. Another
study estimated statistical models for predicting fuel treatment costs on National Forest Lands.
Impacts
The models involved in this study address different important aspects of fuel and forest health restoration. This project gives researchers and managers an opportunity to work together to investigate how to best integrate the use of these diverse models to effectively address critical questions for designing vegetation treatments. Answers emerge to the questions of how best to use fire and planning modeling tools throughout the development of fuel reduction projects. Modelers continue to guide managers through interpretation of model results while managers integrate the results into the planning process. A similar approach is being applied on the Beaverhead-Deerlodge National Forest as part of a of national effort to test alternative approaches for planning the location for fuel treatments to reduce the likelihood of severe wildland fire in locations with significant values at risk. Results will provide valuable information about the advantages and disadvantages of
the tested approach, and possibly provide a basis for future fuel treatment/forest health restoration analyses. Integrating biomass volume and cost estimates into treatment scheduling models will help identify added value of utilization facilities in terms of reducing the cost and environmental affects of fuels treatments. The fuel treatment cost prediction equations have been implemented in fuel treatment software and provide the capability to make condition-specific estimates of cost, rather than using broad averages.
Publications
- Piao, Limei; Troutwine, Judy, M.; Zuuring, Hans. 2004. Programming MAGIS GIS interfaces and recoding WATSED. 04-CS-11222052-081. RJVA Final Report. 15 p.
- Loeffler, Dan. 2005. An analysis of small diameter forest biomass availability and removal costs in Ravalli County, Montana. Thesis. The University of Montana. 112 p.
- Sullivan, J.; Jones, G.J.; Troutwine, J.; Krueger, K.; Zuuring, H.R.; Meneghin, B. 2004. MAGIS eXpress: Spatial Modeling for Timber and Access Planning. In: Bevers, Michael; Barrett, Tara M., comps. 2004. Systems Analysis in Forest Resources: Proceedings of the 2003 Symposium; October 7-9, Stevenson, WA. Proceedings RMRS-P-000. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station.
- Zuuring, Hans; Troutwine, J.M.; Jones, J.G.; Sullivan, J. 2005. Decision support models for economically efficient integrated forest management. Proceedings: 2005 ESRI International User Conference, July 25-29, 2005, San Diego, CA. 22 p.
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Progress 10/01/03 to 09/30/04
Outputs
A number of models and analytical approaches have been developed for addressing different aspects of scheduling fuel treatments spatially on a landscape. These models, however, operate on a variety of geographic scales, and over timeframes varying from current conditions only, to multiple decades. In addition, data underlying these modeling approaches vary greatly in detail relative to aspects of current vegetation, potential vegetation, fuels condition, and weather. While these models emphasize diverse aspects of the fuel treatment-planning problem, no one model adequately addresses the variety of associated issues facing land managers. A study was initiated this year to develop and test approaches for integrating diverse fuel treatment, fire behavior, and landscape analysis models for planning and evaluating spatial and temporal fuel treatment alternatives for a landscape. This study is employing SIMPPLLE (a spatial vegetation disturbance simulation model), MAGIS (a
spatial optimization model for scheduling treatments), and several models from the FARSITE fire behavior suite of models including Minimum Travel Time (MTT) and Treatment Optimization Model (TOM) to analyze alternative spatial fuel treatment and forest health restoration strategies for the 470,000-acre Bitterroot Front landscape on the Bitterroot National Forest. The current conditions and temporal no action alternative have been modeled thus far. A related study is mapping place meanings for the same landscape to investigate how social values of local residents can be measured and integrated into fuel treatment programs. Bitterroot valley residents were interviewed this year and the results placed in GIS for further analysis. Another study is estimating statistical models for predicting fuel treatment costs on National Forest lands. A survey was conducted in the spring of 2004 in which activity-specific information was obtained directly from Forest Service Ranger District fire
management officers and fuel specialists. 138 surveys were collected including 318 activities (190 prescribed burns and 128 mechanical treatments). Regression analysis has been completed to develop equations for predicting costs for alternative fuel treatment activities under various site conditions. Other research is developing the concept of a diversity framework to integrate and display basic ecological information. The Framework consists of five independent classification components that are used individually and in combination to describe existing vegetation and vegetation habitat types for stand and landscape analyses.
Impacts
The co-operative work between the Bitterroot NF management team and the Research Station modeling groups has substantially advanced practical manager-researcher relationships as well as our general understandings of this collaborative process. Answers emerge to the questions of how best to use fire and planning modeling tools throughout the development of fuel reduction projects. Modelers continue to guide managers through interpretation of model results while managers integrate the results into the planning process. The first phase of the mapping meanings project provided baseline data on meanings Bitterroot Valley residents place on areas within the Bitterroot National Forest identified for fuel hazard reduction treatments. The second phase of the project constructed a social database incorporating human values about places to assist modelers and planners in constructing models for fuel hazard reduction treatment alternatives. The fuel treatment cost prediction
equations provide the capability to make condition-specific estimates of cost, rather than using broad averages. The diversity framework study has provided input into four major concurrent efforts to develop vegetation classification standards: 1) Ecological Society of America Vegetation Classification Panel, 2) FGDC Vegetation Classification Committee, 3) USDA Forest Service draft standards for vegetation classification and mapping, and 4) Northern Region Vegetation Council.
Publications
- Gunderson, K.; Watson, A.E.; Nelson, R.D.; Titre, J. 2004. Mapping place meanings on the Bitterroot National Forest - a landscape-level assessment of social value input to fuel hazard reduction treatments. Final Report. Aldo Leopold Wilderness Research Institute, Missoula, MT. 39.
- Jones, Greg. 2004. Fire and forest health - landscape model fuel and treatment options. Bitterroot Ecosystem Management Research Project Eco Report. USDA Forest Service, Rocky Mountain Research Station, Missoula, MT. Summer 2004.
- Pfister, R.; Sweet, M. 2003. Standards and applications of an ecosystem diversity framework. 00-JV-11222022-580. RJVA Final Report. 18 p.
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Progress 10/01/02 to 09/30/03
Outputs
Collaborative development of two complementary spatial landscape computer models continued. SIMPPLLE is a model for simulating vegetative change in the presence of insects, diseases, and wildfire. MAGIS is a model for scheduling activities and measuring trade-offs among treatment alternatives. Research has demonstrated the combination of SIMPPLLE and MAGIS which provides a powerful analytical methodology for: 1) analyzing the extent and likely location of insects, disease, and fire both in the presence or absence of treatments, 2) developing spatial and temporal treatment alternatives for addressing fuels treatment along with other resource objectives, and 3) evaluating those alternatives in a manner that captures the combined effects of treatments and disturbances processes. A study completed this year tested the possibility of applying these spatial models on sampled 5th code watersheds, then extrapolating the results to other 5th code watersheds having similar
characteristics. Conducting spatial analyses on a small number of watersheds and projecting the results to others would reduce the amount of modeling needed to develop plans for large areas. Statistical techniques were used to classify 43 watersheds into four strata. Representative areas were selected within each strata, SIMPPLLE simulations were run, and the simulation results were extrapolated to other watersheds in the strata. Then simulations for the same watersheds were run and statistically compared to the extrapolated results. The trajectories of vegetative change over ten decades differed greatly between the actual and extrapolated results, indicating that modeling vegetation in the presence of disturbance needs to be conducted separately for each watershed. Similar tests were performed using MAGIS to schedule treatments for four management alternatives over five decades. The treatments scheduled and the effects of those treatments generally varied greatly between the
extrapolated and actual modeling results, particularly in the first decade. However, extrapolated and actual results showed a tendency to converge in later decades, but only for some variables. We conclude that areas the size of 5th code watersheds vary in so many different dimensions that it is not practical to group them into sufficiently similar categories to reliably extrapolate modeling results from one area to another. Other research is developing the concept of a diversity framework to integrate and display basic ecological information. The Framework consists of five independent classification components that are used individually and in combination to describe existing vegetation and vegetation habitat types for stand and landscape analyses. As a result of this work, input has been provided to four major concurrent efforts to develop vegetation classification standards: 1) Ecological Society of America Vegetation Classification Panel, 2) FGDC Vegetation Classification
Committee, 3) USDA Forest Service draft standards for vegetation classification and mapping, and 4) Northern Region Vegetation Council.
Impacts
Collaborative development of two complementary spatial landscape computer models, SIMPPLLE and MAGIS, has continued. Research has demonstrated the combination of SIMPPLLE and MAGIS provides a powerful analytical methodology for: 1) analyzing the extent and likely location of insects, disease, and fire both in the presence or absence of treatments, 2) developing spatial and temporal treatment alternatives for addressing fuels treatment along with other resource objectives, and 3) evaluating those alternatives in a manner that captures the combined effects of treatments and disturbances processes. A study was completed that tested whether modeling results obtained for a 5th order watershed could be extrapolated to other similar 5th order watersheds. Comparisons of actual modeling results with extrapolated results showed significant differences indicating that results cannot be reliably extrapolated to other areas. Research in classifying existing vegetation has provided
input to four national concurrent efforts to develop vegetation classification standards.
Publications
- Zuuring, Hans. 2003. Extrapolating modeling results from SIMPPLLE and MAGIS to like areas. School of Forestry, University of Montana, Missoula, MT; Final Report. RJVA 01-JV-11222052-227. 38 p.
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Progress 10/01/01 to 09/30/02
Outputs
Collaborative development is continuing two complimentary spatial landscape computer models. SIMPPLLE is a model for simulating vegetation change in the presence of insects, diseases, and wildfire. MAGIS is a decision support system for planning activities and measuring trade-offs among treatment alternatives. Research has demonstrated the combination of SIMPPLLE and MAGIS provides a powerful analytical methodology for: 1) analyzing the extent and likely location of insects, disease, and fire both in the presence or absence of treatments, 2) developing spatial and temporal treatments alternatives for addressing fuels treatment along with other resource objectives, and 3) evaluating those alternatives in a manner that captures the combined effects of treatments and disturbances processes. SIMPPLLE has been validated using recent fire events and processing time has been reduced significantly allowing analyses of much larger landscapes. Work is underway to improve the
graphic interfaces in MAGIS to conduct modeling tasks in a GIS environment. A study is testing the possibility applying these spatial models on sampled 5th code HUCs, then extrapolating the results to other 5th code HUCs having similar characteristics. Conducting spatial analyses on a small number of HUCs and projecting the results to others would help determine if the desired future conditions in a non-spatial forest plan can be achieved. Statistical techniques have classified forty-three HUCs into four strata and simulations for these areas have been run. When the trajectories of vegetative change over ten decades were compared on 5th code HUCs within the same state, it was found that they differed greatly, indicating that modeling vegetation in the presence of disturbance needs to be conduced for each HUC. Similar tests are now being performed on the allocation of treatments to accomplish land management objectives. Other research is developing the concept of a diversity framwork
to integrate and display basic ecological information. Studies have investigated the use of satellite data and found it to be acceptable in modeling landscapes. This is important because other sources of existing vegetation data are incomplete or out of date, particularly for designated wilderness and roadless areas.
Impacts
(N/A)
Publications
- Twer, Martin. 2001. A landscape assessment as foundation for a multiple use planning process for the Bandy Ranch, Ovando, Montana, USA. University of Montana, Missoula, Montana. Thesis. 116 p.
- Zuuring, Hans. 2002. Extrapolating modeling results from SIMPPLLE and MAGIS to like areas, Phase I. Final Report. Agreement No. RMRS-00-JV-11222052-527: 13p.
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