The May '04 WMPALA Workshop Handbook

The following is the online version of The Second WMPALA Workshop Handbook that was provided in hard copy to participants. This document can be downloaded in its original form as a Microsoft Word document (5.14MB) or as a PDF file (1.93MB). The Workshop was held May 11-13, 2004 on the Northern Arizona University Campus in Flagstaff, Arizona. (Photographic images from the workshop have been added to this online edition.)

Table of Contents

• ForestERA Principal Investigator Dr. Tom Sisk welcomes the participants

  Introduction
• Map of the Western Mogollon Plateau Adaptive Landscape Assessment area
• Workshop agenda
• Goals and objectives for the May WMPALA workshop
• Summary of treatment scenarios developed during the February WMPALA workshop
  • A: Green Group Results
  • B: Yellow Group Results
  • C: Red Group Results
  • D: Blue Group Results
  • E: Synthesis
• Datasets developed or compiled since the February WMPALA workshop
• Description of treatment modeling tools
• ForestERA-generated example management action scenario
• Healthy Forests Restoration Act guidance on determining wildland-urban interface zones

Introduction (Remarks by Dr. Tom Sisk)

My hope is that, over the next three days, we can work together, using the best science and the collective wisdom of all participants and the organizations they represent, to produce a sort of “blueprint” for forest restoration across the WMPALA land base. Such a blueprint could not possibly hope to solve all the key problems, but I think it is reasonable to expect that it might provide very helpful guidance to decision makers by identifying priority areas and providing a suitable “menu” of management directions. As such, our work may provide a bridge between the regional and national objectives of forest planners and the local concerns of citizens and on-the-ground managers.

This notebook, designed to complement the ForestERA Data Dictionary distributed at the February Workshop (copies still available), provides a synopsis of the WMPALA achievements, to date, in text and maps, and it also presents new data sets developed at the request of Workshop participants. It also illustrates the ForestERA treatment modeling and planning tools, which are intended to support your work. We have provided an example of how these tools might work toward the end of this notebook, not to push for any particular use or outcome, but simply to illustrate how you might put the data to work for you, as you help to guide this critical phase in the WMPALA process and, by example, the development of a new and empowering process for engaging a broader public in efforts to restore forest ecosystems across the West.

Tom Sisk
ForestERA Project

II. The Western Mogollon Plateau Adaptive Landscape Assessment Area

The Western Mogollon Plateau spans two million acres of ponderosa-pine dominated forests and includes portions of four National Forests (Kaibab NF in purple; Coconino NF in blue; Apache-Sitgreaves in grey; Tonto NF in yellow), State Trust (white) and private lands (red).

III. Workshop Agenda

May 11 – Day 1

• 8:00 - 8:30 AM Registration
• 8:30 – 9:00 AM Introductions
• 9:00 – 9:15 AM Welcome and Overview
• 9:15 – 10:15 AM Discuss links between WMPALA and other assessment efforts
• 10:30 AM – 12:00 PM Review and refine preliminary scenarios from February workshop
• 1:00 – 3:00 PM Use ForestERA-generated management scenarios as a lead-in to discussion about creating map-based possible management action scenarios
• 3:10 – 4:30 PM 1st small group session. Explore guidelines by topic: Fire, Wildlife, Watersheds, and Communities
• 4:30 – 5:15 PM 1st large group review and 1st day wrap-up discussion.

May 12 – Day 2

• 8:30 – 9:00 AM Review first day’s progress and give 2nd day direction
• 9:00 – 10:20 AM 2nd small group session. Mixed groups develop management guidance for WUI areas.
• 10:30 – 11:00 AM 2nd large group review.
• 11:00 AM – 12:30 PM 3rd small group session. Mixed groups develop management guidance for wildland areas.
• 12:30 – 1:30 PM
• 1:30 – 2:00 PM 3rd large group review
• 2:00 – 2:30 PM Presentation and short discussion about translating guidelines into map-based scenarios
• 2:40 – 4:00 PM 4th small group session. Mixed groups more specifically define map-based scenarios.
• 4:00 – 5:00 PM Large group session reviewing and discussing map-based scenarios to be built.
• 5:00 PM – 8:00 AM ForestERA builds map-based scenarios.

May 13 – Day 3

• 8:30 – 9:00 AM Review 2nd day’s progress and give 3rd day direction.
• 9:00 – 11:00 AM Review and discuss map-based scenarios in large group.
• 11:10 AM – 12:00 PM Discuss a subset of the predicted effects of map-based scenarios.
• 12:00 – 1:00 PM
• 1:00 – 1:30 PM Distribute survey soliciting feedback on WMPALA process.
• 1:30 – 2:15 PM Formulate questions to be posed to expert reviewers (large group).
• 2:15 - 3:00 Discuss next steps and wrap up.

IV. Goals and Objectives for the May WMPALA Workshop

Goals:

Hold a structured, facilitated adaptive landscape assessment workshop using the ForestERA landscape scenario analysis system to build upon the work completed during the first WMPALA workshop and the subsequent virtual workshop. The primary goal of this workshop will be to begin the process of developing science-driven, collaboratively formulated landscape-scale management action scenarios that can asssist decision-makers in site-specific planning at the project level, and in developing a broader context for planning. Secondary goals of this workshop will be to explore the links between landscape-scale and multiple project-scale (e.g., the Flagstaff Community Fire Protection Plan) assessments, and to continue developing and piloting a model adaptive ecosystem assessment process that identifies forest ecosystem restoration and community protection needs at the landscape scale.

Specific Objectives and Related Activities:

1. Clarify the significance of WMPALA products in ongoing land management planning processes. Activity: Discuss links between WMPALA and other assessment efforts, such as Community Wildfire Protection Plans, Forest Service planning efforts, and other planning efforts as time permits.
2. Review and refine the identification/prioritization scenarios developed during and since the February workshop. Activity: Review, discuss, and refine preliminary identification/prioritization scenarios.
3. Familiarize workshop participants with assessment techniques for exploring management options. Activity: Discuss ForestERA-generated management scenarios as a lead-in to discussions about management options across the WMPALA study area.
4. Develop preliminary guidelines for selecting forest restoration and/or fuel reduction treatments or other management activities within the WMPALA study area. Activity: Discuss and develop set(s) of guidelines for selecting treatments or other management activities.
5. Develop methods for translating guidelines into map-based scenarios. Activity: Discuss and develop scenario building instructions for the ForestERA team based on guidelines developed.
6. Explore map-based potential management scenario(s) based on guidelines developed. Activity: ForestERA generates map-based scenarios, which will then be reviewed and discussed by workshop participants.
7. Characterize the predicted effects of scenario(s) on fire and wildlife habitat characteristics. Activity: Discuss a subset of predicted effects of management scenarios.
8. Evaluate the effectiveness of the WMPALA process as it has occurred thus far. Activity: Distribute a survey that can be completed by workshop participants.
9. Provide collaborative guidance to expert reviewers. Activity: Develop a list of questions/issues that can guide expert reviewers in contributing to WMPALA process.
10. Define next steps in the WMPALA process. Activity: Workshop participants will suggest and discuss next steps in the WMPALA process.

V. Summary of Treatment Scenarios Developed during the February WMPALA Workshop

The February workshop involved four teams of stakeholders, and each worked on the same challenge: identifying areas of forest most in need of management attention. The four teams, each comprised of people from different organizations and often holding different values, first identified features or areas of particularly high importance, and combined that information with an assessment of the risks those areas faced from threat of catastrophic wildfire and its consequences. Priority areas were those where high importance and high risk coincided (see figure below).

Va: Green Group Results

Areas of High Importance

The group chose the following four high-priority categories and indicators for prioritizing focal areas:

1. Biodiversity hotspots: Springs, riparian areas, special soils, endemic species, concentration of listed species, and passerine avian species richness.
2. Human communities and infrastructure: Concentrations of homes and immediate environment, utilities, roads, and developed recreation areas.
3. Surface water: Surface water in the form of springs, wetlands, water bodies, perennial streams (historical), and riparian areas.
4. Old growth: Old growth forest stands.

To represent the values of human communities and infrastructure spatially, the group selected power lines, cell towers, recreation areas buffered by 1/4 mile, and communities buffered by 1.5 miles.

To represent the value of biodiversity, the group chose known northern goshawk nesting and post-fledging areas (PFAs), Mexican spotted owl protected activity centers (PACs), and springs. For surface water, the group developed their own "critical watersheds" layer based on 6th order Forest Service preliminary watersheds that contained perennial streams and/or received more precipitation than others in the study area. National Hydrography Dataset (NHD) water bodies were also incorporated into the scenario. Critical features relating to human communities and infrastructure and areas of high biodiversity were combined spatially to represent relative stakeholder-identified values across the study area from high to low.

Risk Factors

To represent risks to the critical features, the group selected active crown fire behavior, fire risk, and post-fire soil erosion potential. Concerns about cumulative risk were represented by doubling the weight of the fire hazard and risk layers relative to the soil erosion layer when these layers were combined to create a composite risk layer.

Final Priorities

The group reviewed an overlay in which each of the critical value layers was given equal weighting. They decided to apply increasingly larger weights to the community layer until it stood out significantly from the other value layers. A final overlay was generated in which the values and risks were combined.

Va: Green Group Layers

Vb: Yellow Group Results

Areas of high importance

The yellow team identified resource protection within the WUI as the number one priority. To delineate this focal prioritization area, the group incorporated the 1/4 mile Urban Buffer layer; 2-mile Upwind Urban Buffer layer, Municipal Watershed layer, and 6th Order Watershed layer into a single composite layer. This new “Gradient Buffered” WUI layer was scaled between 0 and 1, with higher values closer to urban areas and lower values towards the perimeter of a watershed.

To characterize areas important for both sensitive wildlife species and large tree retention (i.e., old-growth areas), the group identified the following wildlife layers: Mexican spotted owl protected habitat, predicted northern goshawk nesting and post-fledging habitat, and important turkey habitat (derived from the turkey habitat suitability layer). Because the study area includes wilderness areas and other areas of special concern, the group also identified the importance of the specially designated areas layer. Additionally, the group wanted to account for biodiversity hotspots using various hydrology and vegetation layers: perennial streams, springs, lakes, and riparian areas. These hydrology layers were buffered at 300m (985 feet) and used to create a new layer.

In total, 5 layers (Mexican spotted owl protected habitat, northern goshawk nesting and post-fledging areas, turkey habitat, specially designated areas, and water bodies and riparian corridors) were combined to create a final Ecosystem Priority layer (1 = critical area, 0 = non-critical area) to be used in the prioritization overlay process.

Risk factors

The yellow group identified the Post-fire Erosion Potential, Fire Risk, and Active Crown Fire Behavior layers as key risk factors at the landscape scale. These 3 layers were combined (additively) to create a single Risk Overlay layer (rescaled between 0 and 1 for visual purposes).

Final priority features

Combining the Ecosystem Priority layer with each of the 3 individual risk layers, the yellow group created 2 distinct final prioritization overlay layers: one based on those areas contained within the perimeter of the Gradient Buffered WUI layer (not shown here) and a second encompassing the entire Western Mogollon Plateau Adaptive Landscape Assessment Area. The final overlay layer additively combines the Ecosystem Priority layer with each of the 3 Risk Overlay layers. Within the study area, the group considered the area encompassed by the Gradient Buffered WUI layer to be a focal area for critical resource protection and prioritization.

Vb: Yellow Group Layers

Vc: Red Group Results

Areas of high importance

The red group focused primarily on priorities within wildland areas. The group identified perennial streams, riparian areas, and surface water bodies as critical landscape features. After testing of various thresholds using GIS tools, the high and moderate quality Mexican spotted owl habitat and northern goshawk nesting habitat were also selected as layers for prioritization. In addition the mixed conifer vegetation type was added due to its importance in defining MSO habitat.

Risk factors

The group selected fire hazard as a primary risk factor, identifying three critical thresholds: Low fire hazard (<2000 BTUs/Ft2); medium fire hazard (2000-3500 BTUs/Ft2), and high fire hazard (>3500 BTUs/Ft2).

Final priority features

When selected Mexican spotted owl and northern goshawk nesting habitats and the mixed conifer vegetation type were overlaid, a combination habitat map was generated that shows the spatial relationships between the two species’ habitats. Further overlaying the combined habitat map with the selected fire hazard generated a map showing spatial relationships between areas of high and very high fire hazard and imperiled species habitats, which can serve as a preliminary map identifying potential focal areas for management attention.

Because the map generated by overlaying selected habitat maps and the fire hazard map was somewhat fragmented, further processing was required in order to obtain a meaningful and understandable output. The preliminary overlay results were “aggregated” to reduce the importance of isolated high values and increase the importance of clustered high values. The final map was rescaled from zero to one and is a continuous score map containing the combined information and aggregated effect, which identifies potential focal areas for management.

Vc: Red Group Layers

Vd: Blue Group Results

Areas of high importance

1. Communities and Infrastructure: The group used the following data layers to approximate the extent of community and infrastructure: the wildland-urban interface (WUI) around developed areas as defined by the Healthy Forest Restoration Act; as well as highways, power lines, and communication towers with a one-quarter mile buffer. Areas of private property not within the boundaries of urban areas or the WUI were also added.
2. Watersheds: The group defined critical watersheds as being those that were important as water sources for municipal water supplies and those that contained perennial streams. Watersheds not identified as being critical were given zero values, while critical watersheds were given scores of 0.25, 0.5, 0.75, or 1 depending on their post-fire erosion potential.
3. 3. High Biodiversity Areas: The group identified areas with large trees, riparian areas, and areas of pine-oak woodland as indicators of biodiversity. To identify areas with large trees, the group chose to use Mexican spotted owl protected activity centers (PACs) and northern goshawk nesting and post-fledging areas (PFAs) as surrogates. These areas were also recognized as being important in their own right as critical habitat. Riparian areas were identified by placing a one-eighth mile buffers around perennial streams and pine-oak woodland areas were identified from the vegetation layer. The group added TNC eco-regional biodiversity hotspots as an indicator for areas with important communities. The group chose to use these features to create an index of biodiversity within the boundaries of each sixth-order watershed rather than prioritize based on the features alone.

Risk factors

1. Fire Hazard: The group used a modified version of the fire hazard (heat output) layer coupled with the crown fire behavior layer. All areas predicted to have active crown fire were given a weight of 1 while areas without active crown fire were scaled between zero and 1 depending on heat output.
2. Fire Risk: The group used the scaled fire risk layer in unmodified form.
3. 3. Upwind Vector: The group produced a layer of the upwind vector from developed areas out to a distance of 6 miles (10 km) and scaled these areas from a value of zero at the maximum distance away from development to 1 at the development boundary.

Final priority features

The three “areas of high importance” layers were overlaid with the three risk layers to create a final priority value map.

Vd: Blue Group Layers

Ve: Synthesis

The four independent sets of products produced by the four groups are alternative solutions to the basic problem of landscape prioritization. The workshop design used the team format to build a beneficial “redundancy” into the prioritization process. Tasks as complicated and challenging as prioritizing across a variable, 2-million-acre landscape do not have a single best answer – they have multiple possible solutions. The best way to converge on good solutions is to have multiple problem-solvers working on the same challenge simultaneously. By examining the different “solutions” to the prioritization process, we can compare and contrast the work of the different groups, learning from each and, ultimately, combining the strongest elements to produce an even better result.

Examination of the four-team efforts shows differences in detail, but considerable similarity in the definition of areas of high importance and risk factors (see Table below). Communities and infrastructure played heavily into the prioritization of three groups, while the fourth began by assuming community values would be well represented by others, and so decided to focus on wildlife and biodiversity issues. All groups used wildlife habitat maps in prioritization, and all focused on water: municipal watersheds, riparian habitats, and seeps and springs played heavily into final maps. This attention to communities, biodiversity, and surface water reflects a shared sense of the need for increased protection of human life and property while safeguarding the natural values that influence quality of life and responsibility to future generations.

**As a first step in exploring spatial overlap in map-based scenarios, the ForestERA team produced a “synthesis map” (shown below) combining priorities from all groups. The map was derived from the four final prioritization maps (one from each team) by first ranking priorities identified by each team simply as “high”, “medium”, and “low”, and then assigning values of 3, 2, or 1, respectively. These maps were combined, producing prioritization values ranging from 4 to 12. Where all four groups had identified a particular area as a high priority, the synthesis map shows a value of 12; where all groups had identified an area as low it received a value of 4; and so on. As such, the synthesis map identifies those areas that “rose to the top” in the overall prioritization effort.

The final prioritization maps from the four groups show striking overlaps near communities, municipal watersheds, and key habitat areas. They also show a wide range of different high-priority sites that derive from novel and creative uses of available data, local knowledge, and analytical approaches. For example, one group incorporated pine-oak forest into their map, knowing that these areas are particularly valuable for wildlife, while two others used habitat maps for species that require large trees to identify possible old growth forest, since spatial data are currently lacking for this important resource.

VI. New Datasets

During the February workshop, participants identified a number of layers that were of high importance and needed to be obtained, developed or updated. We were able to meet many of these requests. The following is a list of the layers that we have obtained, developed or updated since the February workshop, and which are available for use during this workshop.

Perennial Streams

Perennial streams are important water sources for communities, provide habitat for many important organisms, and support riparian communities. We worked with Shaula Hedwall of the US Fish and Wildlife Service to create a more comprehensive perennial streams layer. The new layer includes not only perennially flowing streams, but also streams that contain perennial pools, and other perennial water bodies, such as reservoirs.

Watershed Attributes

We are working with Brad Peihl of JW Associates, Inc. to produced layers predicting the potential for post-fire soil erosion, flooding, and sedimentation in watersheds across the assessment area. Severe crown fires in forested areas often result in ecosystem degradation, including immediate soil damage in burned areas, increased surface runoff, erosion, and sedimentation. Often, these are initiated during the first significant rainfall event after fire. These layers classify watersheds across the study area into hazard ratings for each attribute. They are intended to be relative measures of erosion, flooding, and sedimentation potential across the watersheds in the assessment area. Management attention in or around "fire-sensitive" watersheds could assist in strategies to mitigate ecosystem degradation.

Communities

Participants noted a number of communities that were missing from our urban areas layer, such as Stoneman Lake, Blue Ridge, and Lake Mary Estates. We have updated this layer by adding these additional communities. In addition, we have updated our wildland-urban interface layers and downwind vector layers using these new data.

Wildlife Corridors

We have obtained a layer that identifies potential wildlife corridors and important habitat areas for a number of wildlife taxa across the study area. This layer was developed for Coconino County by a wildlife council consisting of local wildlife experts. A total of 16 species are covered by the layer, including Mountain Lion (Puma concolor), Wild Turkeys (Meleagris gallipavo), Black Bear (Ursus americanus), Elk (Cervus elaphus), White-tailed Deer (Odocolius virginianus), and Pronghorn (Antelocapra Americana). These data are not comprehensive, having only been completed for 7 planning areas within Coconino County.

Potential Old Growth Stands

We are working with the Coconino National Forest to develop a layer that identifies areas that are potential old growth stands. The Forest Service provided data on stands identified as being dominated by large trees (VSS class 5 or VSS class 6), and we combined this information with forested areas inside wilderness or on high slopes (> 40%) from the ForestERA data layers. These areas would be those that are most likely to have conditions representative of old growth.

Aquatic Organisms

We are working with the Shaula Hedwall of the US Fish and Wildlife Service to provide a data layer that includes information about rare, threatened, and endangered aquatic organisms in perennial water bodies across the study area. Due to limitations in the available data, information in this layer is primarily limited to fish. Data on other aquatic organisms, such as mollusks, amphibians, and aquatic invertebrates is mostly lacking.

Municipal Watersheds

We developed this layer in consultation with USGS and Salt River Project (SRP) hydrologists who identified municipal water supplies inside and outside of the study area. Municipal water supplies were defined as reservoirs that provide municipal water to communities. This layer is not intended to capture other important water uses, such as irrigation, recreation, or fisheries. We evaluated the watersheds in the study area that drain into municipal water supplies for their risk to impact those water supplies. Watersheds containing reservoirs were given a value of one, whereas watersheds feeding more distant reservoirs were given values of one or less based on an assessment of the relative probability that sediment transport would reach those reservoirs following a wildfire. This analysis is based on preliminary 6th order watershed boundaries supplied by the US Forest Service.

VII. Treatment Modeling Tools

There are a variety of management actions that will be discussed and defined as appropriate by participants within this workshop.  Working with experts in forest management and fire ecology, the ForestERA project has described five management actions that are representative of typical treatments within ponderosa pine forest ecosystems in this region. If participants choose to use these management actions, the ForestERA project team can describe the potential short-term effects of those actions in a spatially explicit and quantitative manner.  For example, we can assess the effects of these management actions on forest structural attributes, fire hazard and behavior characteristics, and wildlife habitat characteristics. Figure 1 below visually represents the change in basal area after "applying" two different management actions to portions of the landscape.

Figure 1. Modeled change in basal area (m2/ha) before (left) and after (right) intermediate-level treatments (black perimeter) and high-level thinning treatments (white perimeter).

In developing these five management actions, we assembled empirical data from published studies to quantify post-treatment changes in forest structure. The assumptions of our high, intermediate, and low intensity treatment alternatives rely on data from experimental studies conducted in ponderosa pine-dominated stands in Arizona, Montana, and California. The effects of our burn-only treatments were described using data from experiments that used prescribed fire to manipulate ponderosa pine forest structure. In addition to these data, we integrated the knowledge of well-known experts in forest management and fire ecology to refine predictions of the effects of treatments on forest structure. Please see our web page for literature citations and a list of collaborators on this part of the project.

Descriptions of the management actions are as follows:

High Intensity - High intensity thinning, followed by a prescribed burn. Representative of a “full” restoration, heavy fuels reduction, multi-age group selection, or WUI-based treatment.

Intermediate Intensity - Intermediate intensity thinning, followed by a prescribed burn. Representative of a “moderate” or “full” restoration, moderate fuels reduction, or WUI-based treatment.

Low Intensity - Intermediate intensity thinning, followed by a prescribed burn. Representative of a “light” restoration or fuels “maintenance” treatment.

Heavy Burn - Typically, treatments used to “thin with fire” or reduce heavy fuel accumulations in a controlled space.

Light Burn - Representative of a light “broadcast” burn or fuels maintenance treatment.

Table 1 below describes the predicted effects of these management actions on a number of forest structural attributes, including stem density, basal area, and canopy closure. For each of these attributes, we assigned a mean and range of values for percent change in that attribute following treatment. Challenges involved in this effort have included: (1) the relative scarcity of empirical data derived from forest treatment experiments; (2) the need to consider multiple structural variables simultaneously; dependence of post-treatment structure on initial conditions: and (3) bridging the gap between plot-level and landscape-scale analyses. However, we attempted to reconcile these challenges by describing the effects of treatments on forest structure through a rigorous review of the literature and collaborative efforts with many scientists and stakeholders.

Table 1. Values for the mean and range of percent reduction in basal area, canopy cover, and tree density, following each of the five ForestERA management action alternatives.

VIII. An Example Management Action Scenario

Step one:

Create a map reflecting general rules for possible management actions within wildland-urban interface (WUI) areas

Rules:

1. Apply high intensity thinning treatments in all WUI areas that are predicted to have active crown fire.
2. Apply intermediate intensity thinning treatments in all other areas of the WUI.

Reasoning:

The primary goal of treatments within the WUI will be to reduce the threat of fire to communities and human infrastructure. Therefore it seems appropriate to use higher intensity thinning treatments to greatly reduce fire hazard. Areas that would not carry active crown fire are unlikely to need such intense thinning, but intermediate intensity thinning treatments would still be used to thin wooded areas so that fire suppression techniques would be most effective.

Step two:

Create a map reflecting general rules for possible management actions within wildland areas

Rules:

1. Apply high intensity thinning treatments in areas with both active crown fire and higher post-fire erosion potential.
2. Apply intermediate intensity thinning treatments in areas with both active crown fire and lower post-fire erosion potential.
3. Use low intensity thinning treatments in areas without active crown fire and with higher post-fire erosion potential.
4. Use burn only (burn for thinning) treatments in areas without active crown fire and with lower post-fire erosion potential.

Reasoning:

The primary goal of management actions within wildland areas is to return low intensity surface fire to the landscape as a dominant ecological process. In doing so so, fire hazard levels in many areas will need to be reduced using a variety of techniques. Areas predicted to have active crown fire are likely to need higher intensity thinning than areas without active crown fire. However, higher intensity treatments may not be ecologically necessary or appropriate in many places, and may be more costly and time consuming than lower intensity treatments. Therefore, areas of lower concern could receive lower intensity treatments while still effectively meeting ecological objectives. Where post-fire erosion potential is lower, and the damage caused by post-fire erosion is likely to be lessened, less intense treatments will be used. The result is a set of 4 rules that base treatment intensity on crown fire behavior and post-fire erosion potential.

Map of baseline potential management actions for WUI areas

Map of baseline potential management actions for wildland areas

Step three: Make exceptions to the general rules based on additional considerations.

Rules:

1. In municipal watersheds, where a fire would threaten community water supplies, apply high intensity thinning in areas predicted to have active crown fire and intermediate intensity thinning in other areas, except as outlined in rules 2 and 3.
2. In Mexican spotted owl (MSO) restricted habitat, where management guidelines constrain the types of treatments that may be used, only apply low intensity thinning, except as outlined in rule 3.
3. In specially designated areas such as wilderness areas, where mechanical thinning is not allowed, apply burn only (burn for thin) treatments.

Reasoning:

Municipal water supplies are critically important to communities and may be damaged in the event of high-intensity crown fires. Therefore, more intense thinning may be necessary in municipal watersheds even though post-fire erosion potential may not be high. Within MSO restricted habitat, management guidelines strongly encourage thinning from below treatments and restrict thinning to trees less than 24” DBH, both of which suggest a low-intensity thinning should be used. In many specially designated areas, mechanical thinning is not allowed and may not be appropriate, so burn only treatments may be the only management option in these areas.

Step four: Identify constraints that may eliminate areas from consideration for treatment.

Rules:

1. No treatments in vegetation types not dominated by ponderosa pine.
2. No treatments in urban areas.
3. No treatments in MSO protected habitat or northern goshawk nesting and postfledging areas (PFA’s).
4. No treatments in high slope areas.

Reasoning:

Our management action models were based on data from ponderosa pine-dominated areas, and treatments in other vegetation types may look very different. In urban areas, treatments will likely be under the jurisdiction of community planners and private property owners. Specific legal guidelines apply to treatments in MSO protected habitat and Northern Goshawk PFAs. Steep slope areas are difficult to treat. Thus, designating treatments for any of these areas may be less effective or inappropriate.

Baseline map of potential management actions with exceptions added

Map of potential management actions with constraints added

IX. Healthy Forests Restoration Act guidance on determining wildland-urban interface zones

Many discussions during this workshop will relate back to definitions of the wildland-urban interface (WUI). For the purposes of clarifying and demonstrating the implications of one existing WUI definition, we provide here the Healthy Forest Restoration Act (HFRA) WUI definition. HFRA stipulates that in the absence of a community fire protection plan the following areas are considered part of the WUI:

• Any area within 1/2 mile of an “at risk” community AND
• All areas within 1.5 miles of an “at risk” community which have any of the following conditions;
  • characterized by a sustained steep slope that created the potential for wildfire behavior endangering the ‘at risk” community.
  • contains a geographic feature (either natural or human made) that aids in creating an effective fire break (e.g., a ridge or major road).
  • Characterized by the fire regime condition class (FRCC) 3 (note that the only FRCC data existing for this area are course scale (1 km resolution) data which have been heavily criticized, and not the finer resolution data that should be used for identification of FRCC at the planning level).
• Any area adjacent to an evacuation route for an “at risk” community that requires hazardous fuel reduction to provide safer evacuation from the community