Tahoe Research Supported by the SNPLMA Program, RFP 2012
I.
Title Page
Project Title
Theme and subtheme
Principal
Investigator
Co-Principal
Investigator
Co-Principal
Investigator
Co-Principal
Investigator
Grants contact
person
Total funding
requested
Total value of inkind and financial
contributions
Incorporating project-level analysis and enhanced decision support
into the OptFuels fuel treatment planning system for the Lake Tahoe
Basin
Theme
Forest Health
Sub-theme Informing decisions for multi-objective forest management
Name
Greg Jones
Institution USDA Forest Service, Rocky Mountain Research Station
Address
PO Box 7669, 200 East Broadway
Phone
406-329-3396
Fax
406-329-3487
Email
jgjones@fs.fed.us
Name
Woodam Chung
Institution College of Forestry and Conservation, The University of
Montana
Address
32 Campus Dr. Missoula, MT 59812
Phone
406-243-6606
Fax
406-243-4845
Email
woodam.chung@umontana.edu
Name
Jody Bramel
Institution USDA Forest Service, Rocky Mountain Research Station
Address
PO Box 7669, 200 East Broadway
Phone
406-329-3414
Fax
406-329-3487
Email
Jbramel02@fs.fed.us
Name
William J. Elliot
Institution USDA Forest Service, Rocky Mountain Research Station
Address
1221 S. Main St., Moscow, ID 83843
Phone
(208) 883-2338
Fax
(208) 883-2318
Email
welliot@fs.fed.us
Name
Cindy Gordon
Institution USDA Forest Service, Rocky Mountain Research Station,
Grants & Agreements Staff
Phone
(970) 498-1172
Fax
(970) 498-1396
Email
cdgordon@fs.fed.us
$ 121,890
$ 50,781
II.
Proposal Narrative
Project Abstract
Many communities in the Lake Tahoe Basin are at high risk for damage from wildfire. The USDA Forest
Service Lake Tahoe Basin Management Unit (LTBMU) and other land management agencies in the Basin have
conducted fuel treatments on numerous acres, primarily within the wildland urban interface, and there are plans to
treat over 68,000 acres of forested areas within the Basin over the next 10 to 15 years. Efficient and effective tools
are needed to help these managers develop and evaluate fuel treatment alternatives for reducing fire risk to public
safety, property, and the environment, address other forest management objectives, and generate a shared
understanding of the benefits and costs of alternatives in planning. In recognition of this need, SNPLMA provided
funds to develop a decision support system, OptFuels, for scheduling fuel treatment locations in time and space
across landscapes to maximize treatment effectiveness (P034 “Integrated decision support for cost effective fuel
treatments under multiple resource goals”).
We propose a 1.5-year project to enhance the current version of the OptFuels decision support tool in
response to suggestions from Basin managers made at a May 2011 OptFuels workshop. With these enhancements
managers will be able to quickly and easily build an OptFuels model for any planning area in the Basin by clipping
information from a Basin-wide database. Functionality will be added to allow managers to enter and analyze
treatment unit polygons of any shape and size. Other proposed enhancements will provide more information for
comparing treatment alternatives, including treatment costs, biomass volumes and delivery costs, and the extent to
which values at risk would be impacted with and without fuel treatment if wildfire were to occur, including
predicted sediment loading in stream channels and listings of values at risk within the burn perimeter for various
durations of burn time. We believe this enhanced OptFuels system effectively addresses the needs for a tool to help
resource managers better evaluate alternative strategies for reducing fire risk to public safety, property, and the
environment.
1. Justification
The Lake Tahoe Basin is a national treasure and an area of national concern. Due to environmental damages
caused by past land use practices and development, Lake Tahoe’s water clarity has significantly diminished
(Goldmann 1988), and a large portion of the Lake Tahoe Basin is at high risk of catastrophic wildfires (TRPA 2007).
The USDA Forest Service Lake Tahoe Basin Management Unit (LTBMU) considers catastrophic wildfire a
significant threat to the natural resources, scenic qualities, communities and economic values within the Lake Tahoe
Basin, including lake water quality (LTBMU 2006). Reducing catastrophic wildfire risk is a priority in the LTBMU,
and fuels reduction is recognized as an essential tool for enhancing forest health conditions, habitat, and watershed
quality, as well as reducing fire risks (LTBMU 2006, Murphy et al. 2007).
In response to the elevated threat of high severity wildfire and the need for ecosystem restoration in the Basin,
the Forest Service-LTBMU has treated 21,000 acres of fuels since 1977 through the Environmental Improvement
Program (EIP). In addition, the LTBMU has developed fuels treatment plans for over 68,000 acres of forested areas
within the Basin for next 10 to 15 years (TRPA 2007, LTMBU 2007). Although these efforts have begun to address
excessive fuel loads in Lake Tahoe Basin forests, the existing fuel treatment plans and management strategies have
not been thoroughly examined nor refined in terms of their: 1) effectiveness in changing fire behavior and the
associated potential for loss of values at risk, including structures and water quality, 2) longevity of effects of fuels
treatment and strategies for maintaining desired effects over time, 3) cost effectiveness in fuels treatment and slash
disposal, and 4) options for utilizing biomass removed by treatments. Well-designed decision support tools and
systems can help to improve the planning and evaluation of forest treatment projects with regards to these
characteristics, as well as generate shared understanding regarding risks, costs, and benefits of treatment alternatives.
A number of models and tools have been developed and extensively validated for addressing the effects and
effectiveness of fuel treatments from different perspectives and geographic scales. FARSITE (Finney 1998) and
FlamMap (Finney 2006) are able to compute fire behavior characteristics at a landscape scale. However, neither
temporal effects of treatments nor maintenance scheduling are included in either of these models. The Fire and
Fuels Extension to the Forest Vegetation Simulator and the (FVS-FFE, Reinhardt and Crookston 2003) has the
ability to model stand-level fuel and vegetation dynamics, but it does not simulate the spread of fires between stands.
As an economic optimization tool, MAGIS (Multiple-resource Analysis and Geographic Information System;
Zuuring et al. 1995, Chung et al. 2005, Jones et al. 1986) has the ability to optimize forest treatments spatially and
temporally in the presence of multiple objectives and constraints, but no fire spread logic exists in the system. FS
WEPP (Elliot 1999, Elliot and Foltz 2001) is able to compute the amount of soil loss along a hillslope, as well as the
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sediment yield and runoff at the bottom of the hillslope, but it neither simulates fuels treatment options, nor takes
into account vegetation changes by itself.
SNPLMA Project P034 “Integrated decision support for cost effective fuel treatments under multiple resource
goals,” has developed a system, OptFuels, for scheduling fuel treatment locations in time and space across
landscapes to maximize treatment effectiveness while meeting other management objectives
(http://www.fs.fed.us/rm/human-dimensions/optfuels/). OptFuels utilizes FVS-FFE to project stands into the future
both with and without fuel treatments and compute the fuel parameters needed for fire behavior modeling in future
time periods with FlamMap Minimum Travel Time (MTT) fire spread modeling. MTT is used in OptFuels to
evaluate the effectiveness of alternative schedules of fuel treatments for modifying fire behavior across a given
landscape in each planning period. Using this information, the OptFuels solver selects the most effective schedule
and locations of fuel treatments over multiple planning periods to minimize the expected loss from potential future
wildland fire (Figure 1). OptFuels is operational but, like any sophisticated modeling system, improvements are
possible that would enhance the functionality of the system and its metrics of treatment costs and effects, as well as
its ability to predict wildfire risks from future fire scenarios, both with and without fuel treatments.
We propose enhancements to OptFuels that respond to suggestions from Basin managers made at a May 2011
OptFuels workshop. This proposed research addresses Sub-theme 1a “Informing decisions for multi-objective forest
management” under the Forest Health Theme of Lake Tahoe Research 2011 request for proposals. It refines an
existing modeling system, OptFuels, which itself integrates widely used models FVS-FFE, FlamMap, and WEPP.
With the proposed enhancements, OptFuels can be used both at landscape and project planning scales, providing a
tool for improving forest management decision-making at both strategic planning and project levels. Other
proposed enhancements target improved ability to evaluate the economics of alternative strategies for managing
forest vegetation considering such factors as access and transportation. Additional enhancements estimate the
reductions in the effects of wildfire on sediment yields and various values at risk to improve the shared
understanding among managers and stakeholders regarding the risks, costs, and benefits of treatment alternatives.
The first enhancement proposed adds functionality to OptFuels for users to enter treatment unit polygons with
assigned treatments for project alternatives and analyze the effectiveness of those proposed treatments to modify fire
behavior and reduce the risk from future wildland fire. These treatment unit polygons will be entered either as a GIS
coverage (such as coverages available in the Forest Service Activity Tracking System, FACTS) or through a new
OptFuels GIS interface. In the current version of OptFuels, users must assign treatments to pre-existing stand
polygons, which only approximate the location of proposed treatments in a project alternative. The ability to
analyze more spatially-accurate treatment unit polygons enhances the application of OptFuels at the project planning
level. With this change, OptFuels can be used to analyze spatial and temporal fuel treatment strategies at the
landscape scale, then transition to more location-specific placement of treatment units at the project planning scale.
One system for both scales simplifies and streamlines the fuel treatment planning process.
The second enhancement constructs a Lake Tahoe Basin-wide OptFuels database and develops a streamlined
process for clipping information from that database to build planning-area specific OptFuels models within the
Basin. In addition, a process will be developed for basin managers to update this database over time when
treatments are accomplished or fire or other natural disturbances occur. Our current SNPLMA OptFuels project is
delivering an operational system with treatments and associated costs relevant to the Basin, but users must provide
the polygons and polygon attributes for the area to be analyzed and then go through the OptFuels model building
process. This enhancement provides managers with an analysis-ready OptFuels model for any user-specified area in
the Basin, making OptFuels efficient to use. It also provides for updating the vegetation and fuels information for
treatments and disturbances that occur over time in the future.
The third enhancement adds to the treatment information provided by OptFuels. This information includes
estimates of biomass volumes produced by treatments, treatment costs, and future stand structure and other stand
data for all stands across the planning area both with and without treatments. This additional information will help
managers and stakeholders understand the economic and silvicultural trade-offs among alternatives in planning.
The fourth enhancement expands the capability of OptFuels to predict wildfire effects both with and without
fuel treatments across user-specified fire scenarios. Results from MTT fire spread modeling incorporated in the
OptFuels treatment scheduler will be combined with sediment loading predictions from WEPP to predict sediment
loading in stream channels for various amounts of wildfire burn time. In addition this enhancement would produce
listings of values of risk (such as residences, other structures or improvements, and categories of forest vegetation)
that are within the burn perimeter for various durations of wildfire burn time. This information will help managers
and stakeholders better understand how specific fuel treatment alternatives change the risk exposure from future
wildland fire over time.
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The OptFuels team is working with the Integrated Fuels Treatment Decision Support System (IFT-DSS)
developers to integrate aspects of OptFuels into that system. The IFT-DSS team is currently working to incorporate
the use of FVS to project forest vegetation and fuels into the future for multi-period fuels treatment planning. The
components and approach envisioned is consistent with the components and approach employed in OptFuels. Based
on this information, we believe that the data and components used in OptFuels will be compatible with those used
by IFT-DSS for multiple period fuel treatment planning, allowing seamless integration of the systems.
2. Background and Problem Statement
Fire was undoubtedly the most pervasive agent of ecological disturbance in the Lake Tahoe Basin prior to its
settlement by Euro-Americans in the latter half of the 1800s. Forests that developed under fire suppression after
extensive logging in the Tahoe Basin during the middle and later 1800s are now very different than those historical
forests. Tree densities, particularly in smaller size classes, are now much higher, and species composition has
shifted to favor firs over pines (Barbour et al. 2002, Taylor 2004). The abundance of trees and increased fire return
intervals have led to unnaturally high amounts of surface fuels (Barbour et al. 2002) and greater fuel continuity,
contributing to high fire hazard and greater probability of stand replacement upon burning (Manley et al. 2000,
McKelvey et al. 1996, Skinner and Chang 1996).
Reducing surface and ladder fuels using prescribed fire or mechanical treatments has been shown to
substantially improve the resilience of forest stands to wildfire (Agee and Skinner 2005, Pollet and Omi 2002).
However, fuel management in the Lake Tahoe basin presents unique challenges because of the importance of
tourism, forest proximity to populated areas, and concerns about protection of water quality and other natural
resources. Legal liability and public concern limit the use of prescribed burning in many areas. Even in areas
where prescribed burning is a viable management option, smoke management and the narrow window available for
prescribed burns in many years severely limit the number of acres that can be treated. As a result, fuels in these
areas are often treated mechanically or by hand, rather than through burning. However, mechanical removal may
not be cost-effective because much of the excess forest biomass in the Basin is in the form of small trees of low
value. In addition, the intensity and extent of fuels treatments can greatly differ among agencies and projects. In
the near term, treatments designed with fuel reduction as the primary objective tend to simplify and homogenize
forest structure and composition, and may intensify impacts associated with urbanization farther into the forest by
functionally extending edge effects. Simplified forest structure as observed in urban forest remnants (Heckmann et
al. 2008) exhibited reduced biological diversity and ecosystem resilience (Manley et al. 2006; Sanford et al. 2009;
Schlesinger et al. 2008). Decision makers and the public in the Tahoe Basin are engaged in important debates
regarding the tradeoffs between reducing the risk of severe wildfire, protecting and restoring ecological values, and
wisely using financial resources. Efforts to reduce fuel hazards and restore natural ecological processes involve
risks to resource values, but inaction carries the risk of severe wildfire in highly altered forest stands.
The Tahoe Fire Commission Report (2008) identified a need for tools that help managers to better evaluate
alternative strategies for reducing fire risk to public safety, property, and the environment. A number of models
exist that can address various planning aspects independently, but there is a need to create linkages among existing
decision support tools to provide integrated products that will aid in planning and evaluating forest management
projects or programs to best achieve multiple relevant management objectives while meeting applicable constraints.
Tools are needed to help managers and stakeholders better understand how specific fuel treatment alternatives
change fire behavior and the level of risk exposure from potential future wildland fire to various values at risk.
Well-designed decision support tools and systems can help to improve the planning and evaluation of forest
treatment projects across diverse landscapes, as well as generate shared understanding among managers and
stakeholders regarding risks, costs, and benefits of treatment alternatives.
3. Project Objectives
3.1 Add functionality to OptFuels for users to enter treatment unit polygons with assigned treatments for project
alternatives and analyze the effectiveness of those proposed treatments to modify fire behavior and reduce the
risk from future wildland fire. These treatment unit polygons will be entered either as a GIS coverage or
through use of a new OptFuels GIS interface. Once treatment polygons with specified treatments are entered,
OptFuels will update the landscape fuel parameters for those treatments and then model fire spread and
behavior across the planning area, both with and without the proposed treatments to quantify treatment
effectiveness at modifying fire behavior and changing risk from future fire. Hypothesis: This integrated
decision support system can provide information needed for planning and evaluating project alternatives and
communicating the expected benefits to stakeholders.
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3.2 Construct a Lake Tahoe Basin-wide OptFuels database and develop a streamlined process for clipping and
building planning-area specific OptFuels models. In addition, a process will be developed for basin managers
to update this database over time when treatments are accomplished or fire or other natural disturbances occur.
This enhancement provides managers with an analysis-ready OptFuels model for any user-specified area in the
Basin, making OptFuels faster and easier to use, and provides a mechanism for updating the vegetation and
fuels information for treatments and disturbances that occur over time in the future.
3.3 Enhance the fuel treatment information provided by OptFuels that can be used in designing projects to meet
various forest management objectives including reducing wildfire risk, improving forest health, protecting water
quality, etc. This information includes: 1) estimation of biomass volumes produced by treatment type, 2)
estimation of the costs for removing, processing, and delivering biomass or other forest products to specified
locations, 3) estimation of the costs for treatment options that do not remove biomass (hand thinning, prescribed
burning, mastication, etc.), and 4) estimation of future stand structure and other stand data for all stands across
the planning area both with and without treatments.
3.4 Enhance the capability of OptFuels to predict wildfire effects on erosion and water quality and on various
values at risk both with and without fuel treatments across user-specified fire scenarios. This objective will
provide estimates of how key values at risk would be impacted with and without fuel treatment if wildfire were
to occur, including: a) sediment delivery to stream channels for various amounts of burn time, and b) listings of
values at risk (such as residences, other structures or improvements, and categories of forest vegetation) that are
within the burn perimeter for various amounts of burn time.
3.5 Deliver the enhanced OptFuels system to end users. Provide software, default data, documentation, and tutorial
for the enhancement Tahoe Basin OptFuels system on the OptFuels website. Provide user training on the
enhanced system.
4. Approach, Methodology, and Geographic Location of Research
4.1 Add functionality to OptFuels for users to enter treatment unit polygons with assigned treatments.
The OptFuels vegetation and fuels modeling process occurs at the stand level. The current landscape is
represented by a stand polygon layer that has been associated with forest inventory data through a statistical
imputation procedure. For each stand, FVS is used to model a range of appropriate alternatives through a userspecified timeframe. These alternatives include no action and a wide range of silvicultural options that can be
assigned via the FVS Suppose interface. The current version of OptFuels utilizes the CalVeg existing vegetation
polygons that have associated inventory data provided by the Region 5 (R5) Remote Sensing Lab (Warbington et al.
2000). These CalVeg-based polygons serve as the treatment units in the original version of OptFuels, which was
developed to analyze spatial and temporal fuel treatment strategies for modifying potential fire behavior and
reducing associated expected loss through time at landscape scales. However, in order to make OptFuels more
useful as a project-level planning tool, we will provide custom GIS functionality that will allow users to override the
default stand and inventory data. This GIS functionality will allow users to input polygon data for treatment units
from sources such as the Forest Service Activity Tracking System (FACTS) and incorporate field data specifically
collected for project-level planning and implementation purposes (Figure 2). These functions will be based on
existing polygon overlay functionality within the ArcGIS system (e.g. Update, and Identity tools) and will be
automated using an ArcObjects programming procedure. OptFuels outputs related to potential fire behavior,
expected loss to values at risk, sediment, etc. will be reported at the custom polygon unit, allowing managers to
efficiently analyze the potential impacts and benefits for a range of different treatment alternatives.
We also propose additional GIS functionality that will allow users to easily specify treatment options for
individual stands within a planning area. This will be accomplished via a custom add-on to ArcMap that will allow
users spatial point-and-click access to treatment options for individual stands. Once a stand has been selected, a
dropdown will allow users to choose from a list of treatments modeled with FVS-FFE using the default OptFuels
vegetation database. These options will include common fuel treatment activities such as mechanical and hand
thinning, mastication, and prescribed fire. The treatment effects on canopy and surface fuels characteristics will be
modeled using FVS-FFE. Each stand’s post-treatment surface fire behavior fuel model and canopy fuel parameters
will be used to create a series of FlamMap landscape files representing the post-treatment landscape at userspecified time steps across the planning horizon. The OptFuels heuristic solver uses these landscape files and the
MTT algorithm to produce maps of potential flame length, fire arrival time, and expected loss for the specified
treatment schedule.
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These additional functions will be incorporated into a custom ArcMap toolbar that will allow managers to
efficiently develop project planning scenarios and analyze a range of alternatives (Figure 3). In addition to functions
related to project-level modeling, the toolbar will provide the ability to 1) define an analysis area within the Tahoe
basin by clicking and dragging an extent box or by providing a spatial extent for the project area of interest, 2)
manage OptFuels scenarios and their associated outputs, 3) input parameters related to the modeled fire scenario
(ignition point, fuel moistures, wind speed and direction, etc.), and 4) display output data in ArcMap and in Google
Earth.
4.2 Construct a Basin-wide OptFuels database and develop a streamlined process for clipping to build planningarea specific OptFuels models.
We will deliver a fully functional OptFuels database that is based on pre-run FVS outcomes for the default
FIA and FSVEG data that have been associated with the CalVeg existing vegetation polygons for the Lake Tahoe
basin. Fuel treatments will be simulated with FVS for the silvicultural prescriptions typically utilized for hand and
mechanical thinning operations. These prescriptions will be determined through consultation with Lake Tahoe
Basin managers. A fuelbed pathway system has been developed to overcome shortcomings found in the default
fuel models selected by FVS-FFE, a limitation that has been observed in other studies in the Sierra Nevada (Collins
et al. 2011). This fuelbed pathway system was developed by using the R5 vegetation strata-level fuel loading
database to model a variety of surface fuel treatments, including prescribed fire and mastication, with the FCCS
software package (Ottmar et al. 2007). In addition, we will incorporate a custom regeneration establishment module
for FVS that was developed using post-Angora fire field data (Carlson et al. 2010). This custom regeneration
module is necessary due to the lack of a tree establishment model in the Western Sierra Variant of FVS.
Regeneration is a critical input in modeling temporal changes in canopy fuel characteristics such as canopy base
height, canopy bulk density, and canopy cover. Omitting regeneration leads to overly optimistic estimates of fuel
treatment effectiveness over time.
Functionality will be built into the custom OptFuels GIS toolbar that will allow users to select an analysis
area of interest by clicking and dragging an extent box or by selecting a polygon file to define a spatial extent. This
‘click and drag’ option will allow users to quickly queue up an analysis for a project area of interest. Users can
perform analyses using the default FVS databases described above. In addition, we will provide functionality that
will enable users to update the default database to reflect past disturbances such as fuel treatments and wildfire.
This disturbance update will occur via a user-supplied polygon layer that includes either an override tree list
identification code or an activity code and year that defines the type and timing of treatment. FVS provides
modeling keywords that allow users to keep track of the trees that are left in a stand following treatment. We will
use this functionality to create a database of post-activity tree lists that can be stubbed in to update data in areas that
have been identified. This process will be designed to accept data in the FACTS database format.
4.3 Enhance the fuel treatment information provided by OptFuels.
The current OptFuels system provides potential fire behavior outputs for each scenario that include flame
length, arrival time, and an estimate of the overall expected loss to values at risk given the specified arrangement of
fuel treatments. We will include additional outputs to the system that can be used to assess alternative projects for
other relevant forest management objectives, such as timber and biomass production, cost efficiency, changes in
forest and stand structures, etc. Additional outputs include estimates of the biomass and merchantable timber
volumes produced by mechanical treatments and estimates of the costs and revenues associated with the removal,
processing, and delivery of biomass and merchantable timber to specified locations. These tasks will be
accomplished using methods outlined in Loeffler et al. (2006) which involve a combination of outputs from FVS
and the Fuel Reduction Cost Simulator (FRCS) software package (Fight et al. 2006), which is a spreadsheet-based
model used to estimate costs for fuel reduction activities for a variety of harvest systems. FVS produces a list of
marketable cut trees and non-marketable biomass resulting from a modeled silvicultural prescription which will be
used to derive the necessary inputs for FRCS. Haul costs will be estimated by the Forest Residue Trucking Model
(FoRTs: http://www.srs.fs.usda.gov/forestops/), calibrated to reflect local wages and conditions. Costs for surface
fuel treatment activities such as mastication and prescribed burning will be estimated based on inputs from LTBMU
staff. These estimates of volumes and costs will be incorporated in OptFuels and used to provide a volume and cost
estimates for modeled fuel treatment alternatives.
The FVS structural statistics module (Crookston and Stage 1999) will be used to report stand structural
characteristics resulting from an OptFuels scenario treatment schedule. These characteristics include estimates of
canopy cover, dominant species, mean DBH and height, and structural class for different stand strata. These outputs
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will assist basin managers in assessing the long term ecological effects of fuel treatment schedules both at the
project and landscape scales.
4.4 Enhance the capability of OptFuels to predict wildfire effects on erosion and water quality and on various
values at risk both with and without fuel treatments.
OptFuels utilizes the MTT algorithm to model fire spread. Outputs include estimates of flame length and
arrival time for each pixel based on user-specified fire scenarios. Arrival time is reported in active spread minutes
and represents a potential fire progression based on the user specified fuel moisture, wind parameters, ignition
location, and fuels characteristics. We will enhance the OptFuels reporting capabilities by including estimates of
fire effects that will occur within specified spread minute breakpoints that have been calibrated using historic
weather and fire occurrence data within the Basin. These fire effects will include the number of strategic values at
risk (structures, powerlines, etc.) potentially affected within different spread minute breaks of the modeled fire
progression and quantities of post-fire sediment produced for the same spread minute breaks. The WEPP model will
be used to simulate erosion based on a range of fire severity impacts (low, moderate, and high) based on specified
flame length breaks. These WEPP and values at risk outputs will be generated as raster GIS layers that can be
combined with MTT outputs via an automated ArcObjects programming procedure. Reports and graphs will be
generated in MS Excel format summarizing erosion production and impacts to values at risk by spread minute
intervals representing days of fire progression for both the untreated and treated landscape(Figure 4). These outputs
will enable managers to evaluate a range of project-level fuel treatment alternatives based on their potential benefits
in reducing the risk of catastrophic wildfire in the Basin.
4.5 Deliver enhanced OptFuels system to end users.
We will deliver the enhanced OptFuels system to managers and potential users in the Lake Tahoe Basin
through a variety of methods including on-site visits and web-based systems. End products include the enhanced
OptFuels software system that will be accessible via an install package targeting ArcGIS versions 9.3 and 10.0. The
install package and accompanying user guide documentation will be available on the OptFuels website:
http://www.fs.fed.us/rm/human-dimensions/optfuels. We will publish manuscripts and a technical report for
managers in the basin describing the system methodology and results from an analysis that uses the enhanced
OptFuels system to examine tradeoffs related to a range of fuel treatment strategies and their resulting potential fire
behavior, costs and revenues from fuel treatment activities, and ecological outcomes. Training and outreach will
occur via on-site workshops, conference presentations, and meetings with project stakeholders.
5. Relationship of the research to previous relevant research, monitoring, and/or environmental
improvement efforts
This proposed work builds off of the base OptFuels decision support system originally funded by the JFSP
and SNPLMA Round 8 (Project # P034, PI’s Chung and Jones) to build an integrated decision support tool
consisting of FVS, FlamMap, and MAGIS and will use the system to analyze landscape-level fuel treatment
strategies in the Lake Tahoe Basin. We propose enhancements to the base OptFuels system that will improve
system utility for project-level analysis. These enhancements include the delivery of a complete FVS-based
vegetation and fuels database for the basin, GIS tools that make OptFuels more user-friendly, and additional outputs
that characterize potential biomass production, sediment delivery, and stand structure. This work will also leverage
research conducted in SNPLMA Round 8 to characterize the FCCS fuelbeds in the Tahoe Basin (Project # P018,
PI’s Ottmar and Safford). In addition, the OptFuels vegetation modeling effort will utilize research conducted to
characterize post-Angora fire conditions related to tree regeneration and vegetation cover (Carlson et al. 2010).
Finally, we will incorporate a database developed from SNPLMA-funded research related to the WEPP system
(Project #2A11, PI’s Brooks and Elliot) to model potential sediment delivery to streams as a result of fuel treatment
activities and wildfire.
6. Strategy for Engaging with Managers
During the process of working on SNPLMA Project P034 “Integrated decision support for cost effective fuel
treatments under multiple resource goals,” we have developed relationships with Basin managers from the LTBMU,
Nevada Dept. of Forestry, the TRPA, California State Parks, the Tahoe Conservancy, and the Lahontan Water Board,
through meetings (South Lake Tahoe, CA, June 21-22, 2010) and a workshop (South Lake Tahoe, CA, May 17-18,
2011). We will leverage these relationships and work with Basin managers to develop modeling strategies that
realistically mimic project-level fuel treatment activities and their outcomes related to sediment delivery, biomass
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yield, and future stand structure. In addition, we will conduct a hands-on workshop in the Basin to present the final
version of the enhanced OptFuels system and instruct potential users on its use.
7. Deliverables/Products
Five product deliverables will result from this project:
1) The enhanced OptFuels GIS Toolbar installation package will be posted on the OptFuels website
(http://www.fs.fed.us/rm/human-dimensions/optfuels/main.php) for distribution to end users. Enhancements to
the OptFuels system include:
a. Functionality that allows users to input project-level polygon data and build a fuel treatment schedule
based on the selection of fuel treatment activities for individual stand polygons.
b. Integration of a complete vegetation and fuels database for the Tahoe Basin that allows managers to
define an analysis area of interest via ‘click and drag’ functionality. We will also provide utilities that
allow managers to update the default database to reflect changes due to disturbances.
c. Additional output information for each fuel treatment scenario. These include estimates of biomass
produced by fuels treatments, costs and revenues associated with forest product delivery, and estimates
of stand structural characteristics.
d. Estimates of impacts to key values at risk for each treatment schedule. These include potential
sediment delivery to stream channels based on fire intensity and listings of key values at risk including
structures and powerlines.
2) A default vegetation and fuels database for the Basin based on R5 stand polygons with associated plot data.
3) User documentation including a ‘quick-start tutorial’ describing how to analyze tradeoffs between different
project-level alternatives and fire scenarios.
4) Quarterly and yearly reports that describe the progress and expenditure of the project.
5) At least one manuscript suitable for publication in a peer-reviewed journal that describes the system and
applications.
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III. Schedule of Milestones/Deliverables
This project will require 1.5 years starting in June 2012 and ending December 2013.
Table 1. Schedules of deliverables/products
Milestones/Deliverable
Quarterly report
Description
Progress report describing the initiation of this project
Schedules
Sept. 2012
Default database for the
Lake Tahoe Basin
MS Access database that includes pre-run outcomes using FIA data
and incorporates biomass estimates, FRCS-derived costs, and stand
structural outputs (Objectives 2 and 3)
Progress report describing default database
ArcMap toolbar that includes the default database for the basin and an
automated process for choosing an analysis area (Objective 2)
Progress report describing initial version of OptFuels GIS toolbar
Toolbar with functionality that allows users to provide spatial data
identifying project-level polygons and identify areas to be updated to
reflect previous disturbance (Objective 1)
Progress report describing intermediate version of the system
Toolbar that includes automated output display, export to Google
Earth, and reporting features (Objectives 1 and 4)
Progress report describing the final version of the system
Progress report describing activities in FY 2013
Peer-reviewed journal manuscript describing the support system and
its applications
Present results at professional conferences
Installation package and software delivery system (posted on OptFuels
website) (Objective 5)
Updated document describing how to use the support system
(Objective 5)
We will hold a workshop for demonstrating and teaching the updated
modeling system to potential users (Objective 5)
Submission of the final report to the PSW Research Station
Oct. 2012
Quarterly report
Initial version of Enhanced
OptFuels
Quarterly report
Intermediate version of
Enhanced OptFuels
Quarterly report
Final version of Enhanced
OptFuels
Quarterly report
Yearly report
Publication
Presentations
DSS Distribution System
System documentation
Workshop
Final Report
8
Dec. 2012
Jan. 2013
Mar. 2013
April 2013
June 2013
Aug. 2013
Sept. 2013
Sept. 2013
Oct. 2013
Oct. 2013
Nov. 2013
Nov. 2013
Nov. 2013
Dec. 2013
IV. Literature Cited
Agee, J. K., and C. N. Skinner. 2005. Basic principles of forest fuel reduction treatments. Forest Ecology and
Management 211:83-96.
Barbour, M., E. Kelley, P. Maloney, D. Rizzo, E. Royce and J. Fites-Kaufmann. 2002, Present and past old-growth
forests of the Lake Tahoe Basin, Sierra Nevada, US. Journal of Vegetation Science, 13: 461–472.
Carlson, C.H., S. Dobrowski, and H. Safford, 2010. Angora Fire Vegetation Monitoring Annual Progress Report
2010.
Collins, B M, S L Stephens, G B Roller, and J J Battles. 2011. Simulating fire and forest dynamics for a landscape
fuel treatment project in the Sierra Nevada. Forest Science in press, no. 2: 18-31.
Chung, W., G. Jones, J. Sullivan, and J. Sessions. 2005. Developing a heuristic solver for MAGIS: a planning tool to
integrate resource management and transportation planning on large forest lands. In 2005 Proceedings of the
Council of Forest Engineering, July 11-14, Fortuna, CA. 13pp.
Crookston, N.L., and A.R. Stage. 1999. Percent canopy cover and stand structure statistics from the Forest
Vegetation Simulator. Gen. Tech. Rep. RMRS-GTR-24. Ogden, UT: U.S. Department of Agriculture, Forest
Service, Rocky Mountain Research Station. 11 p.
Elliot, W. 2004. Overview of WEPP For Forest Conditions. USFS Region 1 Training Academy, Missoula, MT, U.S.
Department of Agriculture, Forest Service.
Elliot, W. and M. Foltz. 2001. Validation of the FS WEPP Interfaces for Forest Roads and Disturbances. ASAE
Meeting Paper No. 01-8009. St. Joseph, Mich. ASAE.
Fight, R.D., B.R. Hartsough, and P. Noordijk. 2006. Users guide for FRCS: Fuel reduction cost simulator software.
Gen. Tech. Rept. PNW-GTR-668. USDA Forest Serv., Pacific Northwest Res. Sta., Portland, OR. 23 p.
Finney, M.A. 1998. FARSITE: Fire Area Simulator--model development and evaluation. USDA Forest Service Res.
Pap. RMRS-RP-4.
Finney, M.A. 2006. An overview of FlamMap fire modeling capabilities. In: 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.
Goldman, C.R. 1988. Primary productivity, nutrients, and transparency during the early onset of eutrophication in
ultra-oligotrophic Lake Tahoe,California-Nevada.Limnol. Oceanogr. 33(6, Part 1):1321–1333.
Heckmann, K.E., P.N. Manley, and M.D. Schlesinger. 2008. Ecological integrity of remnant montane forests along
an urban gradient in the Sierra Nevada. Forest Ecology and Management 255:2453–2466.
Jones J. G., J.F.C. Hyde III, and M. Meacham. 1986. Four analytical approaches for integrating land management
and transportation planning on forest lands. Research paper INT-361. Ogden, UT: U.S. Department of
Agriculture, Forest Service, Intermountain Research Station. 33 p.
Lake Tahoe Basin Management Unit (LTBMU). 2006. Fact Sheet: Fuels Treatments and Wildlife Risk Reduction in
the Lake Tahoe Basin Management Unit. 2p.
Lake Tahoe Basin Management Unit (LTBMU). 2007. Lake Tahoe Basin Multi-Jurisdictional Fuel Reduction and
Wildfire Prevention Strategy. USDA Forest Service. 62p.
Loeffler, D., D.E. Calkin and R.P. Silverstein, Estimating volumes and costs of forest biomass in Western Montana
using forest inventory and geospatial data. Forest Products Journal. 56 6 (2006), pp. 31–37.
Manley, P.N., J.A. Fites-Kaufman, M.G. Barbour, M.D. Schlesinger and D.M. Rizzo. 2000. Biological integrity.
Lake Tahoe watershed assessment (ed. by D.D. Murphy and C.M. Knopp), pp. 401–598. USDA Forest Service
General Technical Report PSW-GTR-175, Albany, CA, USA
Manley, P.N., D.D. Murphy, L.A. Campbell, K.E. Heckmann, S.E. Merideth, S.A. Parks, M.P. Sanford, and M.D.
Schlesinger. 2006. Biotic diversity interfaces with urbanization in the Lake Tahoe basin. California
Agriculture. 60(2):59-64.
McKelvey, K. S., and K. K. Busse. 1996. Twentieth-century fire patterns on Forest Service lands. In Sierra Nevada
Ecosystem Project: Final report to Congress, vol. II, chap. 41. Davis: University of California, Centers for
Water and Wildland Resources.
9
Murphy, Dennis D. and C.M. Knopp, technical editors. 2000. Lake Tahoe watershed assessment: volume I. Gen.
Tech. Rep. PSW-GTR-175. Albany, CA: Pacific Southwest Research Station, Forest Service, US Department of
Agriculture; 753 p.
Ottmar, R.D., D.V. Sandberg,C.L. Riccardi, and S.J. Prichard. 2007. An overview of the Fuel Characteristic
Classification System – quantifying, classifying, and creating fuelbeds for resource planning. Canadian Journal
of Forest Research. 37(12):2283-2393.
Pollet, J., and P.N. Omi. 2002. Effect of thinning and prescribed burning on wildfire severity in ponderosa pine
forests. International Journal of Wildland Fire 11: 1-10.
Reinhardt, E.D., and N.L Crookston. (Tech. Ed.) 2003. The Fire and Fuels Extension to the Forest Vegetation
Simulator. USDA Forest Service Gen. Tech. Rep. RMRS-GTR-116.
Sanford, M.P., P.N. Manley, and D.D. Murphy. 2009. Effects of urban development on ant communities:
implications for ecosystem services and management. Conserv. Biol. 23(1):131-141.
Schlesinger, M.D., P.N. Manley, and M. Holyoak. 2008. Distinguishing stressors acting on land bird communities in
an urbanizing environment. Ecology. 89(8):2302-2314.
Skinner, C. N., and C. Chang. 1996. Fire regimes, past and present. In Sierra Nevada Ecosystem Project: Final
report to Congress, vol. II, chap. 38. Davis: University of California, Centers for Water and Wildland
Resources.
Tahoe Regional Planning Agency (TRPA). 2007. Restoration in Progress: Environmental Improvement Program
(EIP) Progress Report. 76p. Available at www.trpa.org.
Taylor, A.H. 2004. Identifying forest reference conditions on early cut-over lands Lake Tahoe Basin, USA.
Ecological Applications, 14. Tahoe Regional Planning Agency (TRPA). 2007. Restoration in Progress:
Environmental Improvement Program (EIP) Progress Report. 76p. Available at www.trpa.org.
Warbington, R., L. Levien, and M. Rosenberg. 2000. Monitoring Wildland Vegetation in California on a 5-Year
Coordinated Schedule Using Remote Sensing, GIS and Ground-Based Sampling. USDA Forest Service and
California Department of Forestry.
Zuuring, H.R., W.L. Wood, and J.G. Jones. 1995. Overview of MAGIS: a multi-resource analysis and geographic
information system. USDA Forest Service Res. Note INT-427.
10
V. Figures
Figure 1. Overview of the OptFuels system showing data linkages between FVS-FFE, the heuristic
optimizer and FlamMap.
11
b. Proposed Treatment Polygon
a. CalVeg Polygon Layer
FFE-FVS
Canopy Cover
Canopy Base Height
Canopy Bulk Density
Canopy Height
OptFuels
Flame Length
Arrival Time
Expected Loss
Treatment Schedule
Sediment Yield
c. OptFuels Analysis Layer
Figure 2. Illustration of spatial update operation for (a.) the base OptFuels fuels and vegetation GIS
database using (b.) user-supplied project-level stand polygons. The resulting layer (c.) will leverage
attributes from the default CalVeg-based database while including project-level treelist data for the
updated area. These project-level treelists will be used to model vegetation and fuel dynamics with FVSFFE. Estimates from FVS-FFE are used to analyze potential pre- and post-treatment fire behavior with
FlamMap.
12
Command to define an
analysis area of interest
within the Lake Tahoe
Basin and override
default data with
project-level polygons
Tool that allows users
to create ignition points
to be used in FlamMap
fire behavior model
Write OptFuels
Scenario outputs
to Google Earth
.KML file
Launch OptFuels
Scenario Manager
screen
Add OptFuels
outputs to
ArcMap Project
Command used to
assign specific fuel
treatment options to
stands for Hazardous
Risk Assessment Run
Figure 3. Mock-up of OptFuels ArcGIS Toolbar. Workflow includes the ability to define an area of
interest using the default OptFuels Tahoe vegetation and fuels database, override default data with
project-level polygons and corresponding inventory data, manage FlamMap fire scenarios, and manage
data output to ArcMap and Google Earth.
13
Sediment Tahoe Basin Example
(Result From Cover Loss Alone)
All Stands in LTBMU
Yield to Stream from
50yr Erosion Event
All Stands in LTBMU
Yield to Stream from
10yr Erosion Event
25
25
15
Mean Rate Fine Sediment
10
20
Tons per acre
Tons per acre
20
Mean Rate Coarse Sediment
15
10
5
5
0
Background
No Action
0
Treated with HS Ground
BMP
Fire, No Treat
Adherence (9-mos Post)
Background Treated with HS Ground
No Action
BMP
Fire, No Treat
Adherence (9-mos Post)
Figure 4. Estimates of sediment delivery resulting from fuel treatment and high-severity ground
fire for a 50-year (left) and 10-year erosion (right) event.
14