Using Silviculture to Sustain Wildlife Habitat: Assessing Changes and Trade-offs in Forest Habitats Using a Habitat Evaluation Procedure within the Landscape Management System

Here's a link to the PDF version of this Thesis

By

Kevin R. Ceder

A thesis submitted in partial fulfillment of the requirements for the degree of

Master of Science

University of Washington

2001

Program Authorized to Offer Degree: College of Forest Resources

TABLE OF CONTENTS

List of Figures

Introduction and Objectives

Background

Original Habitat Evaluation Procedure
Other Approaches To Habitat Evaluation
Proposed Pathways
The Landscape Management System

Methods

Study Area
Field Procedures
Lab Procedures
Data Analysis

Results

Validation
Landscape Simulations
Pathway Simulations

Discussion and Management Applications

Habitat Model Responses
Management Applications
Advantages Of Integrating HEP and LMS
Limitations Of Integrating HEP and LMS

Conclusion

Bibliography

Appendix A: Tabular results from Landscape Management Simulations (PDF Here)

Appendix B: Satsophsi.py documentation and computer code (PDF Here)

Satsophsi.py Program File Documentation
Satsophsi.py Computer Code

Appendix C: Hsi.ini Configuration File and Documentation (PDF Here)

Hsi.ini Configuration File Documentation
Hsi.ini Configuration File

List of Figures

List of Tables

Introduction and Objectives

The public has become increasingly concerned over the past three decades about potential negative effects on wildlife caused by development and other modifications of wildlife habitat. Conversion of naturally regenerated mature and old-growth forests to intensively managed plantations for timber production has raised concerns about habitat for species that are associated with these forest structures. As a result of the concerns, regulatory pressures on forest management to provide habitat has resulted in a shift away from harvesting mature and old-growth forests to creating a system of reserves for wildlife habitat. With the reduction of the mature and old-growth forests, concerns have been raised about the ability of species associated with these forests to survive in the remaining mature forests. Consequently, there is much interest in applying alternative silvicultural regimes to produce mature and old-growth forest structures in managed forests, with the hope of providing an increased amount of habitat for species associated with mature forests.

The fields of forest management and wildlife biology often have competing objectives for the use and management of forests and often disagree on the best way to manage the forests. The common area is in forests where both timber products and wildlife habitats are provided. The management perspectives from each field vary, but the results are not necessarily mutually exclusive.

Tools exist in the forest management and wildlife biology fields to model both forest growth and wildlife habitat suitability. The tools that each field has at their disposal have common features, although they are not frequently used together. Habitat models for forest wildlife species often require tree-based measures - such as tree species, sizes, and densities - for calculating habitat values or species abundance. Forest growth and yield models use current forest inventory to predict forest growth and potential outputs in the future by using a set of tree-based measures that include tree species, sizes, and densities. With these commonalities it may be possible to integrate these tools and estimate forest outputs of timber production and wildlife habitats for the same forest. The result would be a new tool that allows both forest managers and wildlife managers to analyze and communicate proposed forest management in new ways.

This project has two dual objectives:

• Integrates these tools by implementing a habitat evaluation procedure (HEP) for Satsop Forest using the Landscape Management System. This LMS procedure parallels the original HEP that was performed on Satsop Forest in the early 1990's:
• Demonstrates how the tool can be used to analyze projected outputs from both proposed landscape management plans and from several, alternative silvicultural pathways that are proposed for creating wildlife habitats.

When assessing the performance of landscape level management plans, only a single ownership will be considered as a landscape. The term "landscape" can be defined at many scales, from an entire region to an individual watershed or a single ownership. For the analyses in this project the landscape will be limited to the Satsop Forest ownership.

Silvicultural pathways are discussed throughout this paper. These pathways are similar to management regimes but are at the stand level. A silvicultural pathway consists of a set of silvicultural treatments that will be performed on a stand during the analysis period. A pathway can include harvesting, thinning, fertilizing, pruning, and planting as well as performing no silvicultural treatments. These pathways will set the stand on a specific development trajectory based on the initial conditions and the types and timings of silvicultural treatments.

Background

Original Habitat Evaluation Procedure

During the early 1990's a habitat evaluation procedure (HEP) was performed on Satsop Forest (at the time the Satsop Nuclear Site) to assess changes in wildlife habitat to be caused by the construction of Washington Public Power Supply System (WPPSS) Nuclear Projects Nos. 3 and 5 (USDI 1980a; USDI 1980b; WSEFSEC 1990; WPPSS 1994a) as part of the Site Certification Agreement (WSEFSEC 1990). The result of the HEP was a 50-year wildlife plan to mitigate the effects of the construction of the Projects (WPPSS 1994e).

Performing the HEP involved several steps. First a vegetation cover type inventory of the area was undertaken using aerial photographs with associated criteria for determining cover types. Next, a set of species for the analysis was selected, followed by habitat suitability index (HSI) model selections and a habitat attribute inventory. Several potential management scenarios were then drafted for the area, with forest changes estimated. Habitat suitability index values were then calculated for each cover type that was expected to be found on Satsop Forest at specific future target years. These target years were 1976 (the pre-project year), 1978 (the beginning of plant construction), 1989 (the end of passive land management period), 2015 (the mid-point of the active land management period), and 2040 (the end of the analysis period). For each target year, cover type acreages and HSI and habitat unit (HU) values for each species were calculated. For the life of each alternative, annual average habitat unit (AAHU) values were calculated to estimate average available habitat quantities. The AAHU values were then compared for selection of the preferred management alternative.

Twenty-one cover types were found on Satsop forest including "Developed" and "Barren" ground that are not considered as wildlife habitat. There are three riparian cover types as well as ponds, grass, and brush. Non-riparian forested areas that can be managed fit into thirteen cover type classifications. All of which are classified by tree-based measures (Table 2.1). If a stands meets all the criteria for a cover type, it is given that cover type classification.

Five species and associated HSI models were selected for the HEP analysis: Cooper's hawk (Accipiter cooperii; (USDI 1980c), southern red-backed vole (Clethrionomys gapperi;(Allen 1983), pileated woodpecker (Dryocopus pileatus; (Schroeder 1983), spotted towhee (Pipilo erythrophthalmus; (USDI 1978), and black-tailed deer (Odocoileus hemionus columbianus; (WDFW 1991). Each species was chosen for a specific reason (WPPSS 1994a). Cooper's hawks tend to prefer hardwood and mixed conifer-hardwood forests in both upland and riparian habitats. Southern red-backed voles were chosen to represent small forest rodents. They prefer mature and older forest structures and are a prey species for forest raptors and owls. Pileated woodpeckers were selected to represent cavity nesters. They are the largest of the woodpeckers and require larger snags than other cavity nesters; and they are listed as a Washington State species of concern. If habitat exists for pileated woodpeckers, it is assumed that smaller cavity users such as nuthatches, flying squirrels and bats will have habitat as well. Spotted towhees prefer open structures with dense shrub layers, such as brush lands and young forests. Black-tailed deer use multiple habitats and are of concern to the public and wildlife management agencies as a game species.

Three basic management scenarios were compared: "without project", "with project without mitigation" and "with project with mitigation." "Without project" assumed industrial forest management for wood production would continue on the site without constriction of the power plants. "With project without mitigation" assumed that industrial management for wood production would continue on the buffer lands surrounding the developed site. "With project with mitigation" included four potential mitigation alternatives. These alternatives included varying levels road closures and habitat enhancing measures.

Based on average habitat attribute values measured during the 1991 habitat attribute inventory, HSI values were calculated for each species for each cover type on Satsop Forest. Cover types acreages were calculated for all the target years based on estimated forest changes caused by growth and potential management alternatives. These acreages were used with the HSI values to calculate HU values, which were then used to calculate AAHU values for each species. Changes in AAHU values between alternatives were used as the deciding factor in selecting the preferred mitigation alternative for the mitigation agreement.

Other Approaches To Habitat Evaluation

Several other methods have been used for assess changes in quality and quantity of wildlife habitat caused by forest management and disturbances. These have included HSI models implemented within a GIS, optimization systems, and population density models.

GIS-based approaches integrate HSI models with the spatial analysis power if GIS. In one example, Rempel, et al. (1997) used a GIS-based HSI model to examine the effects of past natural disturbance and timber management on populations of moose (Alses alses) in southern Quebec, Canada. Similarly Kliskey, et al. (1999) used GIS-based HSI models for woodland caribou (Rangifer tarandus) and pine marten (Martes americana) in the North Columbia Mountains of British Columbia, Canada. Kilskey et al. examined changes in habitat quality and quantity for both species as well as harvested volume under four simulated forest management scenarios to assess amounts of habitat generated by each scenario, tradeoffs of habitats among species for each scenario, and tradeoffs between habitat quantity and harvested volume.

A second approach is optimization of habitat or an aspect of habitat. Moore et al. (2000) used a genetic algorithm to optimize harvest scheduling on a simulated landscape based on bird populations derived from population models for hypothetical species. Beavers and Hof (1999) took a different approach by spatially optimizing the amount of edge habitat to maintain populations of both edge and interior habitat species.

A third approach was taken by Hansen, et al. (1995). They constructed population density models for sixteen species of birds in the Central Oregon Cascades by using density of trees in specific diameter classes to estimate population densities. With these models several silvicultural pathways were simulated with the ZELIG growth model (Urban 1992) and the outputs were used to estimate the resulting population densities.

Proposed Pathways

As a response to of the growing concern over the perceived negative effects of forest management on wildlife habitat, several silvicultural pathways have been proposed to create mature and late-successional forest structures in managed landscapes. These typically involve multiple thinnings at different stand ages and at different intensities than typically applied in commercial wood production. In many cases these pathways have been simulated using various growth models with varying degrees of success.

Hansen, et al. (1995) used data from a "typical" old-growth stand in the Central Oregon Cascades and simulated thirty-six pathways. These varied in retention of zero to sixty trees per acre with rotation lengths of 40, 80, 120 and 240 years. Simulations were done using the gap model ZELIG (Urban 1992) and relied on simulated natural seeding to regenerate the stands. Thinnings were simulated on the regenerating stands at 15 and 30 years, leaving 220 trees per acre with no preference toward species.

DeBell and Curtis (1993) highlight the Demonstrating Ecosystem Management Options (DEMO) harvests that have occurred in mature forests, Retention in these harvests ranges from 10% to 100% (control) in clumped and dispersed retentions.

Barbour, et al. (1997) simulated several pathways on young stands in central Oregon to examine the effects on wood quality and production under alternative silvicultural regimes. Beginning with stands stocked at 300 trees per acre at 15 years total age, stands were thinned to 30 or 60 trees per acre from below at 15 years, to 30 trees per acre from below at 30 years, to 60 trees per acre at 30 years leaving the 30 largest and 30 smallest trees per acre, and to 100 trees per acre from below at 30 years and the control stand was left at 300 trees per acre. These were all projected using the ORGANON (Hann, Olsen et al. 1994) growth model with output analyzed using a spreadsheet bucking algorithm and product grading simulation software.

McComb, et al. (1993) simulated four pathways using data from a 115-year old naturally regenerated stand in central Oregon using the ORGANON growth model. A clearcut pathway, leaving no remnants form the original cohort, was planted and then thinning at 35 and 60 years, with clearcutting at 70 years. This pathway was used to simulate industrial forestry silviculture. To simulate the potential of managing for both wood products and wildlife habitat, single-storied, few-storied, and multiple-storied pathways were simulated. The single-storied approach left two remnant trees over 30" DBH per acre and six snags per acre with DBH >25" followed by planting. At 45 years 30% of the trees in the 8-20" DBH class were removed and 2 mbf/ac were designated for creation of snags and downed wood. The few-storied approach left six remnant trees over 30" DBH per acre and four snags with DBH >25" per acre followed by planting. At 35-years, three more snags per acre were created. At 45 years, the regenerated stand was thinned to 50 tpa and underplanted with dominantly shade tolerant species. At 55 years, one more snag per acre was created; at 70 years, the understory was thinned to 70 % of the trees remaining. With the multiple-storied approach, a 25-year cutting cycle was simulated. The initial harvest removed 76% of the standing volume and was followed by planting dominantly shade tolerant species and allotting 4% of the volume to snag and log creation with the remaining 20% for growing stock. Entries at 25 and 50 years removed 17% and 16% of the volume, respectively, followed by thinning the understory to 50-60% and underplanting dominantly shade tolerant species.

Along with these pathways a plantation restoration pathway was simulated, also using ORGANON. This pathway began with a 40-year old plantation in central Oregon stocked at 319 trees per acre. The initial harvest was thinned to 81 trees per acre at 40 years, followed by creating 2 mbf/ac of snags and planting dominantly shade tolerant species. Snags were then created at 45, 75 and 110 years at 1, 2, and 2 mbf/ac, respectively. At 90 years, trees <30" DBH were thinned to 60%.

Carey, et al. (1996) simulated biodiversity pathways on using the SNAP II harvest scheduling program and data from the Washington State Department of Natural Resources Clallam Block. Beginning with young managed stands the biodiversity pathways thinned the stands to 300 trees per acre from below at 15 years, favoring multiple species. At 30 years the stands were commercially thinned to 100 dominant trees per acre with three trees per acre inoculated with top rot fungi. A second commercial thinning was performed between 50 and 60 years with 75 dominants, hardwood and non-merchantable trees, and sufficient downed wood >20" diameter left to assure 15% ground cover and one snag per acre. Between 70 and 90 years, a third commercial thinning was performed, leaving 36 dominant and co-dominant trees per acre while leaving sufficient downed wood to assure 15 - 20% cover and creating one snag per acre.

The Cascade Center for Ecosystem Management (1993) began a study in the early 1990's to examine the effect of thinning on the development of young stands. Proposed thinning for 30 - 50 year old stands stocked at approximately 250 trees per acre are a light thinning leaving 100 - 120 tpa, a heavy thinning leaving 50 tpa, with underplanting, and thinning to 100 - 120 tpa with gaps where all trees are removed.

The Landscape Management System

The Landscape Management System (LMS) is an integrated forest management simulation and decision analysis software package developed as a cooperative effort between the Silviculture Laboratory, College of Forest Resources, University of Washington, and the USDA Forest Service (McCarter, Wilson et al. 1998). LMS is an evolving application designed to assist in stand and landscape ecosystem analyses by coordinating the processes of forest growth and management simulations, tabular data summarization, and stand and landscape visualization. Implemented as a Microsoft Windows™ application, many separate programs integrate these tasks. These programs include forest growth models, harvest simulation programs, and data summary programs, as well as stand and landscape level visualization software.

Underlying data for LMS are consolidated into a landscape portfolio. These data include forest inventory data; stand level data (e.g. site index and age), and topographic data (slope aspect and elevation), as well as geographic information system (GIS) data in the form of a digital terrain model (DTM), ESRI (Environmental Systems Research Institute, Inc., Redlands, CA) shapefiles of stand boundaries, and other features such as streams and roads. This assemblage of data is then used by LMS to simulate, analyze, and communicate the effects of forest management on the landscape.

Summary output tables from LMS range from standard inventory tables, to stand structural stages, to harvested and standing volumes. All tables are summaries of current and projected inventories for analyses of predicted future conditions and forest outputs. The large array of tables allows analyses of proposed forest management from many perspectives.

Methods

Study Area

The Satsop Forest consists of approximately 1,281 acres just south of the Chehalis River in southwest Washington in Sections 7, 8, 17 and 18 of Township 17 North Range 6 East (Figure 3.1). The area has been divided into 163 polygons in ten cover types: Timbered, palustrine forest, palustrine shrub, palustrine emergent, grass, brush, developed, roads (including rights-of-way), barren, and ponds (Table 3.1, Figures 3.2 & 3.3).

Topographically, Satsop Forest has an average stand elevation range from 130 - 512 feet above sea level, with forested lands well distributed through all aspects and flats. "Flat" areas have an average slope of less than 8% and comprise approximately 200-ac of the Forest. Satsop Forest contains approximately 40% of the acreage on slopes less then 30%. These areas are acceptable for harvesting with ground-based systems (i.e. harvester/forwarder, skidder, bulldozer, shovel). The remaining 60% is on slopes greater than 30% and requires cable systems.

Site productivity can be classified in many ways. One standard method is based on tree growth on the particular site. Based on tree height and age, a base site productivity value is generated known as Site Index. A common standard for Douglas-fir is the 50-year base age Site Index curves developed by King (1966). Using this method, tree height at any age can be adjusted to a Site Index at 50 years of age so that productivity of sites can be compared equally. Site Index values classified into Site Classes are shown in table 3.2.

The majority (92%) of the Satsop Forest consists of highly productive soils, Site Classes 1 and 2, with the remaining 8% in Site Class 3 and 4. Geographically these sites are evenly distributed throughout Satsop Forest (figure 3.4).

Satsop Forest has stands ranging in age from 2 to 190 years. Many of the stands are in the 15-yr and younger classes and the 65-yr and older age classes. The <20-year age classes are a result of development and logging on the Satsop Forest since its acquisition in the mid-1970's. Much of this area is in the southern portion of the area (figure 3.5). Poor regeneration in this area has resulted in some extremely variable species compositions in the stands. The 60 - 100-yr age classes are the result of the first round of logging in this area. Many of these stands are in the northern portion of the Site and contain many large trees of high timber value.

Satsop Forest contains seven primary tree species: red alder (Alnus rubra Bong.), Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), western hemlock (Tsuga heterophylla (Rafn.) Sarg.), bigleaf maple (Acer macrophyllum Pursh), black cottonwood (Populus tricocarpa Torr. & Gray), and western redcedar (Thuja plicata Donn). Approximately one half of the Satsop Forest is dominated by "pure" stands of red alder, Douglas-fir, bigleaf maple, or western hemlock. These stands have at least 75% of their basal area in that species. The remainder of the area is in one of a variety of conifer or hardwood dominated mixes (figure 3.6).

Field Procedures

Habitat Parameter Measurement

Field sampling was undertaken during the winter (February 20-26, 1991) and spring (May 3-15, 1991) to measure habitat parameters for each of the evaluation species for input into the HSI models. The following information comes from the original HEP documentation (WPPSS 1994a).

Winter Sampling
Winter sampling was done on the largest six blocks in each cover type. If there were fewer than six blocks in a cover type, all blocks were sampled. In each chosen block, transects of subplots were run beginning 50 feet from the edge of the cover type in the direction of the center of the cover type.

Habitat characteristics measured during the winter sampling were:

• Percent tree canopy cover
  
• Number of forest canopy layers
  
• Percent palatable (to deer) shrub cover
  
• Percent canopy cover of all herbaceous cover
  
• Percent canopy cover of all grasses
  
• Percent cover of all dead woody material on the forest floor >3 inches in diameter
  
• Depth of slash

Subplots were clustered at 100-foot intervals. Each subplot consisted of a tree plot, two shrub plots, and three herbaceous plots. Tree plots had a 37.2-foot radius with ocular estimates of tree canopy cover (for trees taller than 20 feet) and percent ground cover of dead and downed woody material greater than 3 inches. Shrub plots were 4-foot in radius at the outer edge of the tree plots with shrub canopy less than 6.6 feet tall ocularly estimated. Herbaceous plots were 2-feet in radius at the center and outer edges of the tree plot with the green grass and palatable green forb cover ocularly estimated. A total of 59 transects resulted in 177 tree plots, 354 shrub plots, and 531 herbaceous plots.

Spring Sampling
Spring sampling was done on a grid running on a north-south and east-west orientation throughout the project area. Plots were located at the intersections of the grid, every 435 feet.

Habitat characteristics measured in the spring sampling were:

• Overstory canopy - The DBH was taken of all overstory trees in the dominant, codominant, and intermediate layers. This layer was indicated by a break between the highest layer and lowest layers. If >30 percent of the intermediate or suppressed tree crowns were within the highest dominant/codominant tree layer, then those were considered part of the overstory layer.
• Shrub distribution - Shrubs included all woody vegetation less than 6.6 feet in height. Tree boles were not included in this assessment; however, tree branches were included.
• Herbaceous ground cover - Ground cover included all grasses, forbs, ferns, and moss. Grass cover was recorded as a separate characteristic.
• Snags -The DBH's of all snags >4 inches DBH were recorded. The approximate height (within 5 feet) of these was measured to a 4-inch top.
• Stumps - The number of stumps between 1 and 4.5 feet in height and >7 inches diameter were recorded.

Each plot actually consisted of "plot clusters." A 37.2-foot radius tree plot was centered at each grid intersection. The diameter, number and type, either conifer or deciduous, of live overstory trees were recorded as well as an estimate of the shrub distribution. Three herbaceous plots of 2-foot radius were centered at the plot center and at the points where the tree plot met the north-south or east-west transect line. Snags were inventoried in strip transects 33 feet wide that extended for 200 feet, typically 100 feet on either side of the plot center along north-south or east-west transects.

Data Summary
Data for each habitat characteristic were averaged and reported for each cover type. Only means were reported with no accompanying descriptive statistics. Consequently, the variability of each attribute within the cover types cannot be determined. The exception was the shrub cover class, which was converted to an average suitability index for each cover type.

1998 Forest Inventory

To develop a Satsop Forest portfolio for use in LMS, timber inventory and landscape attribute data were needed. Neither of these existed in a form usable by LMS when the project was begun in 1998. A timber inventory conducted in the summer of 1998 obtained the necessary data.

Forest Inventory
A forest inventory was conducted on Satsop Forest during the summer of 1998 to collect stand level data on trees, snags, and downed wood. The first step of the inventory was to delineate the cover type polygons. Using a combination of the 1994 HEP cover type map and aerial photographs taken in August 1997. All cover type polygons were the same except for five polygons that contained a distinct cover type break. These were split into two polygons, resulting in five new polygons. Since this inventory intended to take tree data, only forested polygons were inventoried. The result was an inventory of 101 polygons totaling 796.7 acres with polygons ranging in size from 0.5 acres to 42.1 acres. A total of 248 plots were measured with an average of 2.46 plots per polygon and an over all intensity of one plot per 3.2 acres. The number of plots per polygon ranged from one for the smallest polygons to 12 for the largest.
The Satsop Forest inventory followed USFS inventory protocol for plot layout. Initially a 100-meter grid was overlaid on Satsop Forest; however, because of the number of small polygons, some polygons were missed using the grid. Consequently, a "representative" inventory was done requiring at least one plot per polygon.

Plots consisted of two nested plots: a variable radius plot and a fixed radius plot. In the variable radius plot a basal area factor (BAF) of 20 or 40 was used depending on tree size. The goal was to have approximately eight trees per plot. The fixed radius plot was 1/300^th acre where all trees with a DBH of 5 inches or less were measured. For all trees, species and DBH were recorded and height, age, crown ratio and crown class were taken for the tallest dominant tree, (a.k.a. site tree), in each plot. Site tree information was used for site index and stand age. Snags were measured in the variable radius plot if the were counted as "in" using the appropriate BAF. Downed wood was measured if it was all or partially within the fixed radius plot.

Lab Procedures

LMS Portfolio Creation

To apply LMS to a forest, a landscape portfolio must be created. This requires forest inventory data, topographic and site data, as well as Geographic Information System (GIS) data.

Two types of GIS data are needed to create a fully functioning portfolio:

• ESRI shapefiles of stand boundaries and another features that may be of interest
• A digital terrain model (DTM).

Habitat Evaluation Procedure (HEP) Implementation

Implementation of a HEP with LMS required the creation of two files: satsophsi.py and hsi.ini. Together these two files are the Satsop Forest HSI and HEP Cover Type analysis modules in Landscape Management System. These modules allow the user to create all tables necessary to assess changes in available wildlife habitat for Cooper's hawk, southern red-backed vole, pileated woodpecker, and spotted towhee, as well as forest cover types. Output is available in several tabular forms. Included in these are tables are output tables that can be imported into ArcView for mapping of forest cover types and available habitat qualities. These can then be summarized to calculate quantities of habitats of different qualities.

Program File
The program that performs all the calculations is satophsi.py. Full satsophsi.py code and associated documentation are available in Appendix B. It was developed using the Python programming language to become an integral module in LMS. With the Satsop HSI and HEP modules installed in LMS, either module can be run from the Analysis / Tables menu in the LMS cockpit.

Satsophsi.py contains four HSI models that were originally used for the Satsop HEP (WPPSS 1994a). Their habitats were defined as follows:

• Pileated woodpecker (Schroeder 1983): forests with: >75% canopy closure, >30 tpa with >30 inch dbh, >10 stumps per acre >one foot tall and 7 inches in diameter or logs > 7 inches in diameter, >0.17 snags >20 inches in dbh per acre, and snag average dbh of >30 inches.
• Cooper's hawk (USDI 1980c): forests with: >60% canopy cover, >20 inches average dbh,, and 10-30% conifer canopy closure.
• Southern red-backed vole (Allen 1983): sites containing >12 inches average dbh, >20% ground cover of downfall > 3 inches in diameter, <80% grass cover, and >50% evergreen canopy closure.
• Spotted towhee (USDI 1978): 60-90% total ground cover, scattered groups of shrubs and 60-75% canopy closure.

The HSI model for black-tailed deer was not implemented in this analysis.

Each model contains variables that are both tree-based measures (i.e. canopy closure, canopy layers, and dbh) and non tree-based measures (i.e. grass cover, downed wood, and snags). Tree based measures are calculated by several algorithms within LMS. These include an algorithm that calculated the number of canopy layers (Baker and Wilson 2000) as well as an implementation of a canopy closure equation published by Crookston and Stage (1999).

Non-tree-based measures are related to stands by their cover type classification. Cover type classifications are calculated using an algorithm based on the thresholds from the original HEP cover type classification system (Table 2.1) with one change to the classification thresholds: the maximum height imposed on the C1 classification was removed. This was removed because several stands failed to be classified because the average heights were over 15 feet while the average dbh was less than the four inches required by the C2 classification. Once the stand has been given a cover type classification, that classification is used to look up the non-tree-based data in the configuration file. When all the necessary values have been calculated and retrieved the values are used to calculate HSI values for all species designated in the configuration file.

Configuration File
Hsi.ini contains all values needed to control the functionality of satophsi.py. The full configuration file and associated documentation are available in Appendix B. Application of models, calculation methods, cover type thresholds, static habitat attribute data, and output table type can be set in the configuration file. Eleven sections are available to be set by the user to configure HEP calculations, input data types and values, and output types. His.ini is a text file that can be edited using any text editor.

Data Analysis

To ensure the outputs from the coded HSI models, as implemented as an LMS extension, would be comparable with the original calculations from the Satsop HEP (model validation) and to test the silvicultural pathways, several LMS runs using the Satsop Forest portfolio were made. These ranged from a projection with no silvicultural manipulations, to pathways published in the literature that were proposed for creating mature forest structure, to pathways for managing mature and old stands for timber production and wildlife habitat simultaneously (CCEM 1993; DeBell and Curtis 1993; McComb, Spies et al. 1993; Hansen, Garman et al. 1995; Carey, Elliot et al. 1996; Barbour, Johnston et al. 1997).

LMS Simulations
All simulations were done for 80 years using LMS with the Pacific Northwest variant of the Forest Vegetation Simulator (FVS). A keyword file (Van Dyck 2001) is used to simulated natural regeneration and in-growth during all simulations. The keyword file first instructed FVS to calculate Reineke's Stand Density Index (SDI; (Reineke 1933). If the SDI is less than 150, 47 western hemlocks, 22 Douglas-firs, and 25 western redcedars are planted per acre. If the SDI is less than 50, 60 Douglas-firs, 30 red alders, 15 western hemlocks, and 15 western redcedars are planted per acre. The resulting inventory data was then processed using the satsophsi.py program inside LMS to estimate habitat quality and quantity.

Validation
For validation purposes, an LMS projection with no harvesting or silvicultural manipulation was performed. This was to assure that at least one stand of each cover type was examined at some point during the projection. HSI calculations were then done using the original cover type data used for the original HSI calculations (WPPSS 1994d). Using these data, instead of the LMS inventory data allowed the same results from the HSI models for each species and cover type. If LMS inventory data had been used, it would introduce deviations caused by variations in HSI variable values within each cover type.

Calculating the HSI value for each species and comparing it to the value published in the original HEP (WPPSS 1994d) produced good results. Two equations needed to be modified: Variable 1 and Variable 3 of the spotted towhee model. These curves are complex and difficult to interpret into a piecewise function with any accuracy. Equations were then solved again and the proper values placed in the HSI equation code. The models then predicted with quite consistently for each cover type using the original HEP data.

Landscape Simulations
Forest and wildlife management activities occur on large spatial and temporal scales. Often these are "broad-brush" approaches where the same management activities are applied over large areas. Simulating this type of management using an assemblage of individual stands, that will be collectively called a "landscape", changes in overall wildlife habitat quality quantity as well as changes in harvested volume can be assessed.

No Action
All stands were allowed to grow without silvicultural treatments for 80 years.

• Group 1: conifer stands < 40 years old ["young"];
• Group 2: conifer stands >40 years old ["old"];
• Group 3: young deciduous stands;
• Group 4: old deciduous stands;
• Group 5: young mixed conifer/deciduous stands; and
• Group 6: old mixed conifer/deciduous stands.

Stands in Group 1 were pre-commercially thinned to 250 tpa between 1998 and 2008, and then allowed to grow for twenty years. Between 2018 and 2038 the stands were commercially thinned, leaving the 750 largest diameter trees per acre followed by underplanting with 100 tpa each of Douglas-fir, western hemlock, and western redcedar. A third entry was made in each stand from 2058 to 2078, thinning the older cohort to 25 tpa and the younger cohort to 25 tpa followed by underplanting with 300 tpa of Douglas-fir, western hemlock, and western redcedar. These multiple thinnings and plantings were intended to develop a multi-layer canopy on these young planted stands sooner than would occur by letting the stands develop without any treatment.

Stands in Group 2 were commercially thinned between 1998 and 2018 to maintain the existing canopy layers, promote the release of advanced regeneration, and establish regeneration of shade tolerant species. Since two canopy layers already existed in these stands, the thinning prescription was designed to retain trees from each layer and to underplant to create a stands with three or more layers. Between 1998 and 2013 the stands were commercially thinned to 50 tpa. In the >20 inches size class the 62 tallest trees were left, and the largest 25 tpa with diameters <20 inches were also left, followed by underplanting with 300 tpa of Douglas-fir, western hemlock and western redcedar. Between 2038 and 2053, stands were commercially thinned to a diameter limit prescription by leaving 25 tpa in the 8 - 20 inches dbh range and retaining all trees above and below these limits, followed by underplanting with 300 tpa of Douglas-fir, western hemlock and, western redcedar.

Group 3 contained many dense hardwood stands that established through natural seeding. This scenario was designed to convert these stands into conifer stands that would be thinned and underplanted several times to promote the development of multiple canopy layers. Between 1998 and 2038 the stands were clearcut and planted with 450 tpa of Douglas-fir. At age 20 these stands were precommercially thinned to 250 tpa from below. At age 40 these stands were then thinned to 25 tpa, followed by underplanting with 300 tpa of Douglas-fir, western hemlock and western redcedar.

Group 4 contained hardwood stands with mature forest structures. This scenario was designed to maintain the mature forest structures while increasing the conifer component in the stands. Between 2018 and 2033 the stands were thinned removing all trees less than 20 inches dbh and leaving all trees greater than 20 inches dbh, followed by planting 300 tpa of Douglas-fir, western hemlock, and western redcedar. A second thinning was performed between 2058 and 2073 that retained 25 tpa >20 inches dbh and 35 tpa between 15 and 20 inches dbh, while the remaining trees were retained. Following the thinning the stands were underplanted with 300 tpa of Douglas-fir, western hemlock, and western redcedar.

Individual Pathway Simulations
"Broad-brush" approaches may not provide habitat for all desired species. Since a landscape is an assemblage of stands "gaming", individual representative stands can be used to test several alternative management regimes and assess the potential of providing habitat for individual species. When the pathways have been simulated and habitat values assessed an assemblage of pathways, which can then be applied to stands in a landscape, can then be created to provide habitat for multiple species across a landscape.

LMS scenarios were created based on the publications mentioned in the Proposed Pathways section earlier in this paper. These pathways were simulated for 80 years using both young and old stands. Pathways that required clumped retention or gap or strip harvesting were not simulated, since LMS cannot perform spatially explicit harvesting methods. To supplement these pathways and to assess trade-offs with industrial wood production pathways, rotations of 40, 60 and 80 years were simulated, with thinning to 300 tpa at 15 years. At 40 years the 60 and 80-year rotation stands were thinned to 140ft2 of basal area. At 60 years the 80-year rotation stand was thinned to 75 tpa. At rotation ages, the stands were clearcut (leaving 5 tpa to comply with Washington State forest practice regulations), and planted with 400 tpa of Douglas-fir.

The stands used for pathway simulations are actual stands on Satsop Forest. The young stands are both approximately 10 years old, Douglas-fir dominated, and stocked at approximately 435 and 1300 tpa, respectively. The old stands are both approximately 90 years old, one with a relatively open single-storied canopy and the second with a multiple layered canopy. The young stands were chosen to simulate young plantations while the older stands were chosen to examine potentials for managing older stands for habitat development and wood products production.

Young Stand Pathways
Separating out the pathways that preliminarily appeared best suited for young stand management resulted in 21 individual pathways that were simulated using LMS:

1. 0_NA: No silvicultural manipulation

2. Barbour15-150: Thinned at 15 years to 60 tpa

3. Barbour15-75: Thinned at 15 years to 30 tpa

4. Barbour30-150: Thinned at 30 yeas to 60 tpa

5. Barbour30-150HL: Thinned at 30 years to 60 tpa leaving smallest and largest

6. Barbour30-250: Thinning at 30 years to 100 tpa

7. Barbour30-75: Thinning at 30 years to 30 tpa

8. BarbourNT: Thin to 300 tpa at 10 years

9. CareyBDPF: PCT at 15 to 300 tpa, CT at 30 to 100 tpa, CT at 50 to 75 tpa, CT at 70 to 36 tpa

10. CareyBDPS: PCT at 15 to 300 tpa, CT at 30 to 100 tpa, CT at 60 to 75 tpa, CT at 90 to 36 tpa

11. CC40_PCT: PCT at 15 to 300 tpa, clearcut at 40 leaving 5 tpa, plant 400 Douglas-fir

12. CC60_PCT_CT: PCT at 15 to 300 tpa, commercial thin at 30 to 140ft2 of basal area, clearcut at 60 leaving 5 tpa, plant 400 Douglas-fir.

13. CC80_PCT_CT: PCT at 15 to 300 tpa, commercial thin at 30 to 140ft2 of basal area, commercial thin at 60 to 75 tpa, clearcut at 80 leaving 5 tpa, plant 400 Douglas-fir

14. Hansen0-40: Thin to 220 tpa at 15 and 30, clearcut at 40 leaving 5 tpa, plant 400 Douglas-fir

15. Hansen0-80: Thin to 220 tpa at 15 and 30, clearcut at 80 leaving 5 tpa, plant 400 Douglas-fir

16. Hansen0-120: Thin to 220 tpa at 15 and 30

17. McCombCC: PCT at 15 to 300 tpa, commercial thin at 35 to 140ft2 of basal area, commercial thin at 60 to 75 tpa, , clearcut at 80 leaving 5 tpa, plant 400 Douglas-fir

18. McCombPR: Thin to 81 tpa at 40 years, planting 75 tpa of Douglas-fir and 190 tpa of western hemlock, thin trees <30" to 60% at 90 years

19. Mit_SOP: Thin to 150 tpa from below at 50 years, plant 50 tpa of western hemlock and western redcedar

20. YSTD-Heavy: Thin to 50 tpa at 40 years, plant 16 tpa Douglas-fir and 104 tpa western hemlock

21. YSTD-Light: Thin to 110 tpa at 40 years.

Old Stand Pathways
Several remaining pathways were used for old stands. This resulted in a set of 30 pathways simulated using LMS:

1. 0_NA: No silvicultural manipulation

2. CC40_PCT: Clearcut, leaving 5 tpa, in the initial year followed by planting 400 Douglas-fir per acre. Thin to 300 tpa at 15 years. Clearcut and plant again at 40 years.

3. CC60_PCT_CT: Clearcut, leaving 5 tpa, in the initial year followed by planting 400 Douglas-fir per acre, commercial thin at 30 to 140ft2 of basal area, clearcut and plant again at 60 years leaving 5 tpa, plant 400 Douglas-fir.

4. CC80_PCT_2CT: Clearcut, leaving 5 tpa, in the initial year followed by planting 400 Douglas-fir per acre, commercial thin at 30 to 140ft2 of basal area, commercial thin at 80 years to 75 tpa, clearcut and plant again at 80 years leaving 5 tpa, plant 400 Douglas-fir.

5. DEMO20: Thin from below in the initial year leaving 20% of the trees.

6. DEMO40: Thin from below in the initial year leaving 40% of the trees.

7. Hansen5-40: Clearcut in the initial year leaving 2 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 40 years leaving 2 tpa and planting 400 Douglas-fir per acre. Repeat this for a second rotation.

8. Hansen5-80: Clearcut in the initial year leaving 2 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 80 years leaving 2 tpa and planting 400 Douglas-fir per acre.

9. Hansen5-120: Clearcut in the initial year leaving 2 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years.

10. Hansen10-40: Clearcut in the initial year leaving 4 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 40 years leaving 4 tpa and planting 400 Douglas-fir per acre. Repeat this for a second rotation.

11. Hansen10-80: Clearcut in the initial year leaving 4 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 80 years leaving 4 tpa and planting 400 Douglas-fir per acre.

12. Hansen10-120: Clearcut in the initial year leaving 4 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years

13. Hansen15-40: Clearcut in the initial year leaving 6 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 40 years leaving 6 tpa and planting 400 Douglas-fir per acre. Repeat this for a second rotation.

14. Hansen15-80: Clearcut in the initial year leaving 6 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 80 years leaving 6 tpa and planting 400 Douglas-fir per acre.

15. Hansen15-120: Clearcut in the initial year leaving 6 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years

16. Hansen20-40: Clearcut in the initial year leaving 8 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 40 years leaving 8 tpa and planting 400 Douglas-fir per acre. Repeat this for a second rotation.

17. Hansen20-80: Clearcut in the initial year leaving 8 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 80 years leaving 8 tpa and planting 400 Douglas-fir per acre.

18. Hansen20-120: Clearcut in the initial year leaving 8 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years

19. Hansen30-40: Clearcut in the initial year leaving 12 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 40 years leaving 12 tpa and planting 400 Douglas-fir per acre. Repeat this for a second rotation.

20. Hansen30-80: Clearcut in the initial year leaving 12 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 80 years leaving 12 tpa and planting 400 Douglas-fir per acre.

21. Hansen30-120: Clearcut in the initial year leaving 12 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years

22. Hansen50-40: Clearcut in the initial year leaving 20 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 40 years leaving 20 tpa and planting 400 Douglas-fir per acre. Repeat this for a second rotation.

23. Hansen50-80: Clearcut in the initial year leaving 20 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 80 years leaving 20 tpa and planting 400 Douglas-fir per acre.

24. Hansen50-120: Clearcut in the initial year leaving 20 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years

25. Hansen150-40: Clearcut in the initial year leaving 60 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 40 years leaving 60 tpa and planting 400 Douglas-fir per acre. Repeat this for a second rotation.

26. Hansen150-80: Clearcut in the initial year leaving 60 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years, clearcut at 80 years leaving 60 tpa and planting 400 Douglas-fir per acre.

27. Hansen150-120: Clearcut in the initial year leaving 60 tpa followed by planting 400 tpa of Douglas-fir, thin understory to 220 tpa at 15 and 30 years

28. McCombSS: Clearcut in the initial years leaving 2 tpa, at 45 years thin the understory to 70%, at 70 years clearcut leaving 2 tpa

29. McComdFS: Clearcut in the initial year leaving 6 tpa, at 45 years thin the understory from below to 50 tpa followed by planting 60 tpa of Douglas-fir and 205 tpa of western hemlock, at 70 years thin understory from below to 70%

30. McCombMS: Thin from below to 24% in the initial year followed by planting 16 tpa of Douglas-fir and 140 tpa of western hemlock, at 25, 50 and 75 years remove 16% of the overstory from below, remove 45% of the understory from below, and plant 16 tpa of Douglas-fir and 140 tpa of western hemlock

For all projections, tables and charts were created to compare habitat quality and quantity, standing volume, and cut volume. Habitat values are reported as average HSI, habitat units (HU) and average annual habitat units (AAHU). LMS reports both standing timber volume and harvested timber volume through time. Standing volume is calculated as the total standing volume at the end of each growth period. Cut volume is the amount of timber harvest that occurred during each 5-year growth period. Volumes are calculated by FVS based on Scribner 32-foot log rule with a minimum top diameter outside bark of 4.5 inches. These values are reported for each five-year interval separately for three size classes:

• "Poles": tree <12 inch dbh that are used for low-grade lumber or pulp.
• "Small sawlogs": tree 12 - 24 inch dbh trees that produce average quality lumber.
• "Large sawlogs": trees >24 inch dbh that provide high quality wood for lumber including specialty, clear, tight-grained woods used in boat planking, siding, molding, and ladders.
  

Figure 3.1: Location map of Satsop Forest in Southwest Washington

Figure 3.2: Orthophotograph of Satsop Forest with stand boundaries
(For a larger image, click here.)

Figure 3.3: Map of Satsop Forest cover types.
(For a larger image, click here)

Figure 3.4: Map of Site Classes on Satsop Forest
(For a larger image, click here)

Figure 3.5: Map of age classes on Satsop Forest
(For a larger image, click here)

Figure 3.6: map of species distribution on Satsop Forest
(For a larger image, click here)