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Green Diamond Forest HCP Effects Analysis of EIS Alternatives on Habitat for the Northern

Spotted Owl

This section describes the methods used to understand and describe the impacts of each action alternative on Green Diamond’s forest stands in California and on habitat for Covered Species. The building blocks for analysis that are described here are the forest inventory and growth modeling system that Green Diamond uses for its California Timberlands, and Green Diamond’s sustainable yield harvest planning process that relies on the inventory and growth modeling to project the future timing and location of timber harvest. Next, we describe the Habitat Fitness model that Green Diamond developed for the Northern Spotted Owl and the habitat fitness trend on California Timberlands based on Green Diamond’s projected future forest stand and harvest conditions. Then, we explain that changes in silviculture and harvest constraints – the action alternatives -- will affect future forest stand and habitat fitness conditions in ways that have not been fully modeled. It is therefore necessary to make assumptions about how the action alternatives will change forest stand conditions over time and how those changes will affect habitat fitness. Using those assumptions and projections, this section then provides a relative comparison of habitat fitness under each of the alternatives and the different silvicultural methods and harvest constraints used in each alternative. Forest Inventory and Growth Green Diamond has maintained timber inventory records for its California timberlands for more than three decades. Individual forest stand polygons are delineated to define vegetational areas that are relatively homogeneous with respect to species composition, stocking, and age. Individual forested stand polygons range in size from less than 1 acre to slightly over 1,000 acres (mean ≈25 acres), and each stand has an estimate of age, site quality, stocking and volume by tree species. Logging history has generally been used to delineate stand polygons in younger age classes (<30 years). Stand ages for these polygons are based on an assumption that regeneration was achieved in the year following harvest. Older stands have been delineated primarily by aerial photo-typing. In some cases, stand delineations were obtained from prior owners at the time of acquisition of the land by Green Diamond. Inventory estimates typically come either from timber cruising conducted by Green Diamond, or from inventory values obtained from prior owners at the time of land acquisition. Between 1976 and 2011, approximately 174,233 acres (43.6% of the forested ownership) were cruised by Green Diamond, and between 2005 and 2015 Green Diamond cruised 80% (approximately 193,000 acres) of the forest stands 30 years and older. Green Diamond currently uses the Forest Projection and Planning System (FPS), developed by the Forest Biometrics Research Institute (FBRI), for inventory tracking, growth modeling and long-term harvest scheduling. Green Diamond’s California Timberlands Division tracks individual stands using an ESRI ArcGIS platform on an underlying Microsoft SQL-Server database. All stand inventory data is updated annually for growth using FPS. At the end of each year, we compare our inventory estimates for harvest units (depletion values) with actual production figures for each unit that was harvested (actuals). This comparison has been done annually since 1982. Over that time, total conifer depletion and production differ by less than one percent. This rigorous comparison is required under corporate policies governing financial accounting for depletion and forest management planning. A range of strategies have been used to collect timber inventory data and the methods for storing and utilizing the data have changed over time as technology has advanced. The current inventory in general is not stratified. Instead, each stand has an individual estimate of age, site

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quality, stocking and volume by tree species. Individual forested stand polygons range in size from less than 1 acre to slightly over 1,000 acres, with an average size of 24.7 acres. Green Diamond’s current goal is to inventory (cruise) all forest stands > 30 years of age within a 10-year time frame. This currently equates to approximately 20,000 acres per year. Individual forest stand polygons are delineated using aerial photographs and light detection and ranging (LiDAR) data that was acquired for the timberlands in 2009 to define vegetational areas that are relatively homogeneous with respect to species composition, stocking, and age. Plots for sampling forest data are established at a rate of one plot for every two acres. Each plot within forest stands consists of variable and fixed radii. Within the variable radius plots, a prism is used to determine count trees for measuring diameter at breast height (dbh), and measure trees for determining total height and taper. Management, or site trees, are dominant or codominant trees used to determine age of stand, crown ratio and defect (for net volume). Smaller fixed radius plots (1/100 acre) are used to quantify species and height of trees < 4.5 inches dbh. Green Diamond, in consultation with the FBRI, established 30 new permanent growth plots in 2006-7, to provide better local calibration of the growth model. Each plot is 0.75 acre in size, and plots are distributed across the ownership to represent the full range of habitat types, stocking levels, and species compositions. Remeasurement of these plots will be conducted whenever the height growth differential reaches 20 feet. Green Diamond intends to maintain these plots through multiple remeasurement cycles, updating the calibration of the growth model after each set of remeasurements. Beginning in 2007, all five year old stands were surveyed for stocking by species and height class. These were plot-based surveys that can be directly incorporated into FPS. These data constitute the only empirical survey of regeneration on Green Diamond land. Because they effectively integrate the combined effects of planting, natural regeneration, and vegetation management through the first five years after stand establishment, these data are used as the basis for determining the initial species composition and stocking levels for all regenerated stands in a100-year simulation consistent with Green Diamond’s long-term harvest plan. Long-term Harvest Planning for Sustainable Yield Green Diamond manages its California timberlands for Long Term Sustained Yield under a Maximum Sustained Production (MSP) plan prepared and approved in accordance with the California Forest Practice Rules (FPR) under Title 14 CCR 913.11(a). Commonly referred to as an “Option (a)” plan, Green Diamond’s most recent Option (a) plan was completed in 2009. The Option (a) contains confidential proprietary information that is protected from public disclosure under California law. This reference to the Option (a) is explanatory, and the Confidential Option (a) is not intended to be publicly available. Under the Green Diamond Option (a) plan, annual harvest levels are scheduled to balance forest growth and timber harvest over a 100-year period. The Option (a) rule (CCR 913.11 (a)) requires the landowner to demonstrate achievement of MSP by satisfying the following five requirements:

• Producing the yield of timber products ... while accounting for limits on productivity due to

constraints imposed from consideration of other forest values, including but not limited to, recreation, watershed, wildlife, range and forage, fisheries, regional economic vitality, employment and aesthetic enjoyment;

• Balancing growth and harvest over time; • Realizing ... adequate site occupancy; • Maintaining good stand vigor; • Making provisions for adequate regeneration.

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Green Diamond’s 2009 Option (a) modeling used spatially explicit simulation of harvesting and growth of individual stand components over more than one rotation for 100 years, based on the GIS mapping of the standing inventory for Green Diamond’s California timberlands as of January 1, 2008. The Option (a) modeling used even-aged silvicultural practices (clear-cutting) as the harvest/regeneration method. The MSP modeling resulted in a constant level of harvest for approximately 50 years, followed by an increase to a higher level for the last 50 years, with growth exceeding harvest at all times throughout the period, and with corresponding increase in standing inventory throughout the whole period. Timber stands 45 years and older are available for regeneration harvest. However, the harvest of some stands may be delayed until the 60 or 70 year age class due to the implementation of intermediate treatments such as commercial thinning and FPR that constrain both the size of even-aged management units and the timing of adjacent even-age harvesting operations. The anticipated average age of harvest stands as currently modeled is about 50 years as the property approaches full regulation. Full regulation is a future condition where there is a relatively even distribution of age classes across the ownership that has been created by controlling annual harvest rates over time. For an ownership that starts with an irregular age class distribution, it would take the number of years that are equivalent to the planned average rotation age to create a “fully regulated” forest. (i.e., it would take 50 years to create a fully regulated forest with a 50 year rotation age). Actually achieving a fully regulated forest condition for a large complex ownership is a difficult task given that most large forest ownerships are not static over time; land is bought and sold, market fluctuations occur and environmental constraints may encumber land that was planned for harvest resulting in delayed harvests that extend timeframes to achieve a fully regulated forest condition Because essentially all of Green Diamond's property has been harvested at some time in the past, the progress of timber harvesting across the ownership will reflect the pattern of age classes developed as a result of prior logging activity. Where large areas were initially harvested as continuous logging operations resulting in large tracts of evenage young forest, present day harvesting operations will be more concentrated. California FPR constraints will cause the dispersal of activities over time and space within these blocks during current and future rotation periods. This is a product of the California FPRs adjacency harvesting constraints that are applied to even-aged harvesting units resulting in retention of many stands far past planned rotation age. If harvesting of a tract of mature timber is initiated around age 45, the harvesting of much of that tract will be constrained into the following decades, and the harvest of a few stands will be constrained past 70 years of age. This effect has been demonstrated in Green Diamond’s growth and yield planning. Harvest planning occurs over long and short term timeframes and occurs ownership-wide and at the harvest unit level. The Option (a) discussed above is the longest term harvest planning tool used by Green Diamond and it has a 100 year time horizon and covers all of the California timberlands. The Harvest Stand Availability Forecast (HSAF) model is used to plan for the availability of harvest stands over a 10 year time period and is capable of modeling all of the California lands or sub regions depending on the modeling objectives. The Log Production Projection System (LPPS) models harvest units and log production by logging operator for a 2 year time period. THPs are detailed documents that provide specific information needed for the operation of individual harvest units. The HSAF model is used to plan for the availability of harvest stands over a 10 year planning horizon. This is a GIS based model that uses a harvest polygon layer and supporting inventory data to identify a theoretical harvesting pattern that would support a sustained yield of timber over the 10 year planning period. This planning effort is accomplished using GIS data pertaining to evenage harvest date for harvested areas and stand age for potential future

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harvest areas, as well as timber volume and species composition, watercourse location, road location, wildlife and habitat presence and other site characteristics to identify potential harvest polygons during the 10 year period. The model parameters can be set to account for regulatory constraints governing harvest stand age and adjacency limitations. The chief foresters and GIS staff work closely together to pick potential harvest polygons for each year of the planning period that comply with regulatory constraints and attain Green Diamond’s sustained yield goals. The result is a sequence of hypothetical (modeled) harvest polygons across the California ownership for a 10 year period that complies with regulatory constraints and attains the Option (a) sustained yield goals. The actual harvest units that are harvested in any given year tend to be different than the modeled polygons due to market changes that occur or changes in environmental and on-the-ground conditions. This model is typically updated every three to five years to correct for the variations that develop over time. As a planning tool, THPs provide the site specific operational and environmental details needed to implement harvest operations. Silviculture prescriptions and yarding methods are designated for individual harvest units and sub-units and environmental protection measures are specified. A critical aspect of THPs is that numerous time limits and requirements are put in place upon approval. The earliest possible starting date for evenage harvest units is often specified in the THP and the date for completion of work is also specified. THPs generally have a three year period where operations may occur and may be extended for two additional years under certain circumstances. Replanting and stocking deadlines are tied to the completion of logging operations in a unit. Development of the Habitat Fitness Model for Northern Spotted Owls The 1992 NSO HCP was based largely on rather simple assumptions about NSO habitat in the redwood region. Extensive research on Green Diamond’s lands and elsewhere in the redwood region has enabled Green Diamond to craft the Forest HCP based on detailed analyses of actual NSO habitat uses and needs. Pursuant to the 1992 HCP, Green Diamond conducted a long-term demographic study that enabled it to assess the impacts of timber harvesting on NSO. Green Diamond’s geographically referenced, relatively detailed forest stand information was used to directly relate habitat characteristics to survival and fecundity in order to estimate habitat fitness. Green Diamond used capture-resight data from 1990-2003 to estimate survival and nesting data over the same period to estimate fecundity. Finally, Green Diamond estimated habitat fitness as a function of average survival and fecundity at a location through a site-specific projection matrix. Fitness, the ability to survive and reproduce, has traditionally been considered an individual attribute, but the quality of the habitat occupied by a particular individual also influences its fitness. Therefore, habitat fitness is habitat quality relative to its impact on the fitness of individuals occupying it (Franklin et al. 2000). Combining the influence of habitat on both survival and reproduction provides the ultimate measure of habitat quality such that areas with high habitat fitness are capable of supporting a stable or increasing source population while areas of low habitat fitness are associated with habitat sinks. The habitat fitness model was developed to analyze all of the habitat (including timber harvest, set-asides and take) and non-habitat variables influencing NSO population trends, and as such, was partly a heuristic model to help understand and design conservation measures that promote future stable or increasing populations of NSO. For example, the habitat fitness model integrated model inputs from separate nesting, nighttime activity, survival and fecundity models (see Appendix C, Chapter 4, pp. B-168 to B-172). Included in these models were a variety of

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spatially explicit covariates (e.g., edge density and mean patch density) produced by complex computer intensive GIS analyses using FRAGSTATS. The complex habitat fitness model was very useful to understand how the various habitat elements function to meet the needs of NSO, and how overall forest management strategies influence Plan area-wide habitat quality.

Trend in Habitat Fitness To estimate habitat fitness into the future, Green Diamond used the known 2009 forest landscape with the anticipated harvest plans over the next 10 years. Green Diamond then projected harvests derived through a newly developed harvest schedule model to project spatially explicit stand conditions at 10 year intervals from 2010 to 2060. Assuming important non-habitat variables, e.g., weather and barred owls, remained at some mean value, the spatially explicit estimates of habitat fitness on Green Diamond’s study area were extended at 10 year intervals from 2010 to 2060 (Figure 1). The proportion of the ownership in the highest categories of habitat fitness increase through time, and the category of habitat fitness >1.05 which indicates habitat capable of supporting an increasing population of NSO, increased from 95,899 acres (35% of ownership) in 2010 to 179,959 acres (64% of ownership) in 2060. In 2060, a total of 87% of Green Diamond’s ownership is projected to be in the two highest categories of habitat fitness, which would support stable or increasing populations of NSO if other non-habitat variables (e.g., weather and barred owls) remain within acceptable limits.

Figure 1. Percentage of Green Diamond Resource Company ownership in different projected Northern Spotted Owl habitat fitness categories. Fitness values <1.0 represent habitats projected to have declining populations while those ≥ 1.0 are projected to support stable or increasing populations of owl. Based on a sensitivity analysis of habitat fitness, the habitat variable that most likely contributed to the projected upward trend in habitat fitness was open edge density. Open edge density measures the amount of edge per acre surrounding a site, where edge is defined as the interface between areas 0-5 years in age (i.e., open areas) with older areas. The proportion of

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older stands (41-60 years-old) adjacent to younger stands (6-20 and 21-40 years-old) also contributed to the trend in site fitness. Both of these variables measure habitat heterogeneity that is projected to increase mostly due to implementation of Green Diamond’s Aquatic HCP (AHCP) and the California Forest Practice Rules (FPR). The implementation of the AHCP results in an extensive network of riparian and geologic buffers that total approximately 25% of the Plan Area and are subject to limited single tree selection harvest or no harvest. These extensive areas result in a forested network aging through time (Figure 2) to produce an increasing amount of nesting and roosting habitat adjacent to younger forest stands that provide habitat for NSO prey species. The riparian and geologic areas with limited or no harvest had an average age of 54 years in 2015 and will have an average age of 104 at the end of the 50 year permit term. The resulting forest landscape provides nesting and roosting habitat with edges adjacent to foraging habitat, a situation that benefits survival of NSO and that is functionally similar to NSO sites adjacent to Set Asides. Percent hardwood and residual structure, (i.e., older trees retained from previous timber harvest) are also important habitat elements that have a quadratic relationship with nesting habitat. This means values above an optimum level are predicted to reduce overall habitat fitness values for NSOs. NSO habitat quality is highly dynamic and active management is critical to regenerate habitat with high fitness values after re-growth of forest stands has reduced habitat heterogeneity. These projections of habitat fitness provided a very positive assessment of future habitat for NSO. Compared to habitat in the past, the modeled habitat on Green Diamond’s ownership is predicted to be able to support a stable or increasing population of NSO assuming other non-habitat variables (e.g., weather and barred owls) remain within acceptable limits.

Figure 2. Distribution of forest age classes within riparian management and geological protection zones within the Plan Area at decadel intervals from 2015 through 2065.

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Evaluating Silviculture and Harvest Constraint Alternatives using FPS modeling: The EIS alternatives analyzed in detail, if applied over the Plan Area, would result in different landscape habitat scenarios over the proposed permit term of 50 years due to application of different forest management practices at the level of the timber harvest plan unit. The reason that different forest landscapes are created is that the EIS Alternatives analyzed in detail have varying silvicultural practices and other constraints that would alter Green Diamond’s forest management in the Plan Area. Green Diamond has been implementing an approved NSO HCP since 1992 and has collected demographic data on NSO that was used to develop and evaluate a unique and complex site-specific habitat fitness model developed during the 10 year review for the 1992 NSO HCP. The habitat fitness model is comprised of four other models (Nesting model, Nighttime Activity Resource Selection Function (aka Foraging Model), NSO Survival model and NSO Fecundity model) with numerous physical and environmental covariates that were developed using complex and computer intensive spatial analyses. This provided a unique look into factors that influence habitat selection and landscape habitat fitness for NSO based on a landscape that was created primarily through evenage management and a range of no regulation to progressively more restrictive forest practice regulations. Green Diamond could not repeat and feasibly evaluate the effects of different EIS alternatives on NSO habitat fitness described previously for several reasons. Green Diamond would first need to create more detailed long-term harvest schedules adapted for each EIS alternative (as described in the Forest Inventory and Growth section) to fit a business model for each of those action alternatives. After development of the additional detailed harvest scenarios, Green Diamond would need to apply each of the independent NSO models to the 50 year harvest scenarios. The final step would be to integrate those models into another habitat fitness model. The most serious limitation for developing a new set of models applies to the Uneven-age Management Alternative. As previously stated, the current landscape was created primarily through clearcut harvesting. The extensive demographic and radio telemetry data collected under the existing landscape scenario would not apply to a future landscape created through an entirely different forest management regime. In other words, Green Diamond would have to collect data and develop models on northern spotted owl response to selection harvest in order to credibly predict site fitness from uneven-age forest management. To evaluate the potential effects of different forest management scenarios on habitat for northern spotted owls under the various EIS alternatives, Green Diamond conducted a series of 50-year harvest modeling scenarios using FPS. It is important to note that these are hypothetical harvesting scenarios based on several general assumptions and do not necessarily represent the actual harvesting schemes that Green Diamond would develop and deploy in a more detailed fashion such as that described above under the 10-year HSAF process. Nor do they replicate any 50 year period under the Option (a) modeling effort. A detailed harvest schedule such as the HSAF is an ongoing iterative process based on past harvesting practices that produced the current spatial arrangement and distribution of forest age classes present within the Plan Area and subsequently a much more detailed view of near term (10 years) future harvesting opportunities identified by an experienced Registered Professional Forester. The EIS alternatives that maintain some evenage silviculture component (No Action, Preferred and Terrestrial Reserve) followed the same basic harvest modeling process with similar assumptions. Green Diamond has not invested in development of a complex harvesting model for uneven-age management because selection is not the chosen forest management strategy or business model within the Plan Area, and it was not used in the past to create the current forested landscape. However, for purposes of this EIS and to generally compare how landscape conditions could change at the Plan Area scale, Green Diamond developed an uneven-age forest management harvest model using FPS. If Green Diamond were to make a business decision to switch to uneven-age forest management or if regulatory changes required Green Diamond to transition away from even-age management, it would require years to develop a

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completely new sustained yield plan under the FPRs, and it would take several decades to transition from a landscape created through even-age management to one that is represented by uneven-age forest stands under selection harvest. Green Diamond used the current forest stand inventory information derived from timber cruise data and harvest history and a hypothetical 50 year harvest forecast to model forest growth and harvest from 2015 through 2065 for each EIS alternative. Current year forest stand information is not available until growth and harvest is completed in a calendar year. Therefore, Green Diamond used the most current information available (2015) to describe the forest age class distribution at “time zero” for the Plan Area and to predict future trends in growth and harvest of forest stands. The 50 year harvest schedule is a model that uses current stand information, projected forest growth, and anticipated harvest levels to simulate how forest stands change through time. For example, a 25 acre stand of 50-year old timber that is harvested in 2015 is reset to age zero and will age through time until is harvested again at about 50 years old near the end of the permit term. Similarly, a 100 acre stand of 40 year old timber (originally harvested ~1975) will be harvested about 5-10 years into the permit term (~age 50 in year 2025), but it will be harvested over multiple entries due to current FPR requirements on the spatial extent of harvest units (typically limited to 30 acres for clearcut) and limits on timing of adjacent clearcut harvest that average about 5 years. Another factor that limits the amount of clearcut harvest is the presence of riparian management zones and other protected areas with limited harvest. Green Diamond estimates that approximately 25% of its landscape is composed of riparian and geologic protection zones that require the use of uneven-age silviculture such as single tree selection. Using the above example with a 100 acre stand of 40 year old forest that was created under a different and less restrictive set of environmental regulations, approximately 25 acres would be composed of riparian zone (25%X100 acres) with single tree selection and one harvest entry. The remaining 75 acres could be clearcut, but those acres are constrained by FPRs limiting clearcut size, location and timing of harvest adjacent to other recently clearcut areas. Therefore, the remaining 75 acres would likely be three separate clearcut units of approximately 25 acres. Two clearcuts could occur at the same time (year zero) and the third clearcut could occur 5 years later due to FPR constraints. The resulting 100 acre harvest area would have 25 acres of selection harvest that remains on the landscape and ages, while the other three harvest areas have an age class gap of 5 years. At the end of the permit term, this example of a 100 acre area contains 50 acres of 45 year-old forest (two 25 acre clearcuts at year 5 in 2020), 25 acres of 40 year-old forest (one 25 acre clearcut at year 10 in 2020) and 25 acres of 90 year old forest in RMZs (single tree selection harvest once in year 5 and once in year 10 coincident with adjacent clearcuts). This same type of harvest pattern is repeated over the plan area for the permit term. The above scenario describes harvesting with clearcutting as the primary silvicultural practice and creates the pattern of habitat heterogeneity that produces habitat capable of supporting an increasing population of NSO. The use of selection harvest is governed by a different set of restrictions under the FPRs. Selection harvest is generally less constrained by forest age, but it is determined by an Option (a) or sustained yield plan. A landowner typically chooses the frequency of stand entry based on sustained yield and a desired number of forest age classes (≥3). Typically, selection harvest is conducted every ten to 20 years, and the oldest cohort of trees may be approximately 80 years of age. Small patch cutting in the form of group selection is permitted under the FPRs with no more than 20% of the harvest area in group selection and those areas are limited to no more than 2.5 acres in size where separated by another logical group selection area. In the above example of a 100 acre patch of forest, the entire area could be selectively harvested at 10-20 year intervals with no more than 20% (~18 acres) in group selection at each harvest entry. The entire area could be harvested by a combination of selection and group selection in four entries over a 40-80 year period. If a forest stand does not meet the minimum conifer stocking standards for selection harvest, an alternate silvicultural practice may be required to maintain the land in timber production and transition to an uneven-age management scheme. These are

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simplistic examples of harvesting scenarios and forest management may be constrained by a variety of factors that limit maximization of harvest within any given forest stand in the Plan Area. General assumptions for the FPS based harvest modeling process common to each EIS alternative are as follows:

• Using current forest inventory, grow all forest stands over 50 1-year periods (2015-2065) • Initiate harvest in stands ≥45 years old • Do not harvest encumbered areas (e.g., NSO take avoidance buffers, DCAs, ROCAs,

marbled murrelet habitat)

Analysis of Alternatives Preferred Alternative – response of NSO population As part of the 10-Year Review of the 1992 NSO HCP that was completed in 2010, the amount of the highest quality habitat (highest habitat fitness values that has the potential to support an increasing population of NSO) is projected to increase from 35% of the ownership in 2010 to 64% in 2060. There are multiple other biotic and abiotic factors (e.g., climate change or diseases affecting forest structure, NSO or their prey base) outside Green Diamond’s control that could influence the realized population response to projected increases in high quality habitat. In addition, although home range size should decrease with improving habitat quality, NSO are territorial, and there are limits to how many owl sites can be packed into the highest quality habitat. However, for purposes of evaluating the different alternatives, we assumed the other potential threats will be addressed including the barred owl and the limits of maximum NSO site densities will not be reached, and under the Preferred Alternative, the number of occupied NSO sites will approximately track the trend in the highest quality habitat (Figure 1). Relative to the NSO population in 2010, this graph suggests an approximate 15% increase in the number of NSO sites by 2030 followed by a slight dip during the next decade and then another approximate 15% increase from 2040 to 2060. While this projection is model based, and by its nature increasingly less reliable further into the future, the recent barred owl removal experiment on Green Diamond’s ownership resulted in a mean lambda of 1.029 (2.9% annual increase) in the treated areas. Some of the increase was due to NSO sites being released from the influence of barred owls while some was due to an increase in new NSO sites resulting from in-growth of habitat. This suggests that an overall increase of approximately 30% in the 50-year life of the Plan could easily be realized if the barred owl threat is adequately addressed and other non-habitat factors remain within a normal range.

To do this analysis, it is also critical to understand the drivers of the projected increase in high quality habitat. Relative to habitat variables, the highest habitat quality was associated with a buffer area of stands adjacent (< ½ mile) followed by those within NSO set-asides (reserve areas of mature stands with no timber harvest), and habitat quality increased with increases in open edge density. Furthermore, habitat quality was most influenced by forest attributes that conferred high survival followed by fecundity. Although the various factors that contributed to survival and fecundity were complex, it was notable that just as for the sensitivity analysis of habitat fitness, being in the buffer adjacent followed by being within NSO set-asides was associated with the top statistical models for both survival and fecundity. There were numerous

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other habitat attributes that contributed to survival and fecundity, but the most conspicuous pattern was that a habitat mosaic of young and older stands in juxtaposition (high landscape-level habitat heterogeneity) was beneficial for NSO in the Plan Area.

Exactly why being adjacent to a set-aside conferred the highest habitat quality is not known, but presumably it was a function of having a stable older stand with potentially higher densities of tree voles and flying squirrels in close proximity to areas with high open edge density (i.e., heterogeneous mix of young stands with high densities of dusky-footed woodrats interspersed with older stands). Being within a set-aside somewhat reduced habitat quality for NSO sites, presumably because it reduced open edge density within the owl’s home range. However, under the 1992 NSO HCP the 39 set asides varied in size from 61 to 2002 acres with a mean of 340 acres, and most NSO sites in set-asides still had a portion of their home range with the potential for high habitat heterogeneity. Relative to set-asides, the lowest habitat quality was NSO sites completely unassociated with set-asides that were potentially subjected to timber harvesting including levels that resulted in taking of the NSO site. These sites had high habitat heterogeneity, but they tended to lack the stable core areas for roosting and nesting (i.e., they were forced to relocate nest and roost sites as the older stands were harvested).

The importance of habitat heterogeneity and juxtaposition of NSO sites with older forest stands is also consistent with the future increasing trend in high quality habitat and future timber management in the Plan Area under the Preferred Alternative. Relative to past forest management in the Plan Area, future management under the Preferred alternative will result in much smaller clearcuts (average opening size of ~15 acres) and an increase in riparian management and geological protection zones that will encompass 25% (approximately 90,000 acres) of the Plan Area. Given the extensive dendritic network of these riparian and geological zones, and the very limited timber harvest associated with these zones, there will be a high proportion of the Plan Area that will be adjacent (< ½ mile) to the ecological equivalent of the NSO set-asides. These areas continue to age over the permit term and develop trees with structure that provide nesting opportunities for NSO. There are certainly many other habitat attributes that are important to NSO on managed landscapes, and Green Diamond’s NSO studies and other studies in adjacent areas have documented, for example, that maintaining residual large and older wildlife trees and having stands with a substantial component of hardwoods are very important to NSO. However, while these habitat attributes may change under the different alternatives, the extent to which they might change cannot be readily forecasted given that they are individual tree based. This means that the forest attributes that will be subjected to the greatest change and will have the greatest potential impact on future NSO habitat quality will be a function of the amount of dispersed stable protected areas (riparian zones and Dynamic Core Areas) in juxtaposition to a mosaic of different aged stands resulting in overall high landscape-level habitat heterogeneity (Figure 3). Relative to the other alternatives analyzed in detail, the Preferred Alternative results in the greatest amount of habitat heterogeneity as evidenced by the creation of open edge (0-5 years) and young stands (6-40 years) supporting high densities of available prey adjacent to older stable core areas located within riparian management zones and other protected areas. To further evaluate the influence of forest covariates on habitat fitness, Green Diamond’s statistical consultant, Dr. Trent McDonald at West Inc., provided marginal plots of three covariates from NSO habitat fitness modeling. The plots illustrate the direction and magnitude of

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changes in habitat fitness (λ) given changes in the habitat characteristic of interest and assuming all other variables are constant (Figures 4-6). While there are numerous dimensions within the habitat fitness model, these graphs focus on three dimensions affected by forest management. Other covariates involved in habitat fitness are held constant at median values and the range of the habitat covariates of interest cover the median ± 2 standard deviations. One point illustrated by these graphs is that as percent of forest >40 years old increases, site fitness increases, peaks, and then is estimated to decline when >65% of a buffer surrounding the site is comprised of forest in that age class (Figure 4). Moreover, at approximately 45% the incremental increase in fitness associated with additional increases in the proportion of stands aged >40 years begins to diminish. The effect of open edge on habitat fitness is linear, and it continues to increase within the range of values observed in the study area (Figure 5). The effect of age of forest stand on habitat fitness increased in a curvilinear nature within the range of stand ages observed in the study (Figure 6). When these three variables are scaled so that their relative effects can be compared, two basic conclusions are apparent. First, increasing the percentage of >40 year old trees surrounding a site and increasing opening edge density produce approximately equivalent incremental benefit to site fitness provided the percentage of >40 year old stands is less than about 45% (Figures 4, 5, and 7). Second, when the percentage of >40 year old trees surrounding a site increases much beyond 45%, additional fitness can only be gained by increasing opening edge density (Figure 7). These conclusions translate into an “ideal” landscape that has percent >40 year old stands as close to 65% (approximately) as possible while maximizing open edge density. Put another way, a more dispersed arrangement of >40 years old stands has higher site fitness for NSO than a less dispersed arrangement containing the same percentage of >40 year old stands (because the dispersed arrangement has more edge). This illustrates the relative importance of open edge and habitat heterogeneity on habitat fitness for NSO when comparing the EIS alternatives.

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Figure 3. A simulated 50 year harvest schedule under the Preferred Alternative used to produce modeled trends in four age classes of forest representing different functional types of northern spotted owl habitat identified in Green Diamond’s habitat fitness model. The age classes were as follows: 1 = 0-5 years young recently clearcut forests; 2 = 6-20 years prime woodrat habitat; 3 = 21-40 years woodrat habitat, other foraging and roosting habitat and 4 = >40 years foraging, roosting and nesting habitat. The Preferred Alternative assumes application of the CA Forest Practice Rules and the Conservation Strategy proposed under the Forest HCP.

Figure 4. Effects on site (habitat) fitness (λ) when the percentage of forest aged 41+ in surrounding the site changes. Percent of >40 year old stands computed for areas within 820 ft of the site.

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Figure 5. Effects on site (habitat) fitness (λ) when the amount of opening edge (“open” = forest age 0-5 years) changes. Opening edge density computed as feet per acre within 1969 ft of the site.

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Figure 6. Effects on site (habitat) fitness (λ) when age (in years) of the forest stand changes.

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Figure 7. Effects on site (habitat) fitness over changes in landscape values of percent >40 year old forest, age of forest stand, and amount of open edge density (“open” = forest 0-5 years).

No Action

Under the No Action, the static Set-Asides that are no harvest and Special Management Area that is no-take remain until 2022. The Set Asides total approximately 13,200 acres and the Special Management Area is approximately 18,500 acres. After the NSO HCP expires in 2022, timber harvest would be permitted in the Set Asides, but a take avoidance approach would be required around all active NSO sites (occupied by NSO within the past three years) in order to be in compliance with USFWS no take guidelines enforced through the California Forest Practice Rules. Site specific conditions could require that Green Diamond maintain an NSO site as active beyond a three year period (e.g., an NSO site is occupied by barred owls creating uncertainty in NSO occupancy) which could restrict harvest beyond a three year period of NSO absence at the site. However, for the purpose of this analysis, the 104 active NSO sites present on the Plan Area in 2015 were held static for the 50 year plan term and harvest scheduling because there is no way to predict where NSO would colonize new sites and where other NSO sites become extinct. This method is valid because sites are held constant across comparisons of the EIS alternatives.

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For the No Action, the buffer area for NSO sites was increased to be compliant with USFWS take avoidance guidelines (985 acre circle with 0.7 mile radius circular buffer compared to the 502 acre with 0.5 mile radius circular buffer circle used in the 1992 NSO HCP). The USFWS guidelines require approximately 52% of the circle be maintained in nesting, roosting and foraging habitat and 40% of the area must be nesting habitat (USFWS 2011). The NSO HCP requires 46% of the NSO habitat buffer be maintained as NSO habitat of which 38% must be nesting habitat. There are more nuanced requirements regarding the spatial arrangement of habitat for take avoidance (USFWS 2011), but the on-the-ground effect is that more nesting, roosting and foraging habitat is retained under the No Action. When threshold levels of habitat within the NSO buffers would be exceeded by timber harvest, Green Diamond would defer harvest or implement other silvicultural practices such as commercial thinning and selection to maintain habitat within the NSO buffers. Although there will be no additional riparian and geological buffer commitments under the No Action, for purposes of analysis, we assume these protected areas will be created and maintained until 2057 as part of Green Diamond’s AHCP. This indicates the benefits of the dispersed riparian management zones and geologic protection areas will be realized, but relative to the Preferred Alternative, there will be a general erosion of habitat heterogeneity because fewer young seral stages will be created under the No Action as a result of reduced harvest. The reduction in young seral stages (stands aged 0-5 years) is a result of fewer clearcuts being implanted within the larger NSO buffers with greater restrictions on harvest relative to the Preferred Alternative.

The 50 year model of timber harvesting applied by Green Diamond under the No Action indicates that relative to the Preferred Alternative, timber harvest is reduced on average approximately 450 acres per year due to constraints from NSO site buffers (Figure 8, 0-5 years old trend line) but in some years it could exceed 600 acres per year. This is significant because timber harvest creates the young seral stages that contribute to open edge density, a key habitat covariate of habitat fitness. Regenerating forest stands remain in the open edge category for six years (age zero through age 5). Therefore, the reduced timber harvest under the No Action due to larger NSO site buffers and greater restrictions on harvest results in an estimated average annual “loss” of 2,700 acres of young seral stages contributing to open edge density (450 acres/year X 6 years that stands remain in open edge), and the loss may approach or exceed 3,500 acres in some years. The open edge stands develop into habitat for dusky-footed woodrats (6 - 40 years of age), and they become important to increasing habitat fitness for NSO by increasing habitat heterogeneity. The lack of timber harvest creating young seral stands, or open edge, contributes to an overall erosion of NSO site quality because fewer stands will develop into habitat for dusky-footed woodrats. For example, the highest densities of woodrats occur in stands 6-20 years of age (Hamm 1995, Hamm and Diller 2009). The harvest modeling indicates that in some years, as much as 9,000 acres of the prime woodrat habitat will be lost on an annual basis because timber stands remain in this age class for 15 years (2.5 times as long as forests in open edge). The effect is even greater in the 21-40 age class where habitat heterogeneity may be reduced by almost 12,000 acres in some years (Figure 8).

Green Diamond analyzed in the harvesting model 104 NSO sites with the site center on Green Diamond’s Plan Area and a 0.7 mile radius circular buffer. Each NSO buffer of 0.7 mile radius is 985 acres, so the approximate area affected by non-overlapping buffers is 102,440 acres. The 2015 NSO site buffers overlapped by 15% which resulted in an effective buffer area of approximately 87,000 acres. Approximately 76% (66,000 acres) of the 0.7 mile buffers were on

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Green Diamond ownership Over a 10-year period (2006-2015), Green Diamond conducted timber harvest within 0.7 mile buffers of 155 unique NSO sites and an annual average of 40 NSO site buffers. The total area affected by 155 site centers is approximately 100,500 acres or 28% of the Plan Area. If we assume the annual reduced harvest of 450-600 acres came from 40 NSO buffers, this equates to a 11-15 acre/NSO buffer (1.3-1.8%) reduction in forest stands contributing to open edge density. Green Diamond could not estimate the number of NSO sites within a 0.7 mile radius buffer of the Plan Area as required by USFWS take avoidance guidelines, but we assume that any additional NSO sites within 0.7 miles of the Plan Area would be subject to a similar 1.3-1.8% annual reduction in timber harvest relative to the Preferred Alternative. The net reduction to habitat heterogeneity under the No Action at the Plan Area scale appears relatively minor compared to the Preferred Alternative (Figure 3 trends compared to Figure 8), but a loss in habitat heterogeneity will result in a reduction in habitat fitness values under the No Action. In order to assess the effect on habitat heterogeneity within the 104 NSO site buffers, we evaluated trends in forest age classes within the area constrained by the NSO site buffers (Figure 9). The restrictions on harvest within the 0.7 mile buffers illustrate a much more dramatic effect on habitat heterogeneity relative to the Plan Area scale for the Preferred Alternative. There is a >15% projected reduction in age classes 2 and 3 within NSO buffers under the No Action compared to the Preferred Alternative by the end of the permit term. In addition, when comparing the habitat fitness trend (Figure 1) to the habitat trends under the Preferred Alternative (Figure 3) and the NSO buffers for the No Action (Figure 9), the prediction would be a decline in site fitness for NSO buffers under the No Action.

Site fitness for the No Action outside of the NSO buffers would be similar to the Preferred Alternative because forest management activities would be nearly identical. If the USFWS guidelines for take avoidance are functional, we assume the stands subjected to selection harvest or deferred from harvest will remain suitable habitat, but rather than the high quality habitat with site fitness capable of supporting an increasing NSO population (site fitness values >1.0 as predicted under the Preferred Alternative), this habitat will likely have an approximate habitat fitness value of ≤1.0 meaning it will be capable of supporting a declining or possibly stable NSO population. However, given that the NSO sites are not static, it is likely that the site buffers will shift through time such that NSO may be able to locate their home ranges within the Plan Area landscape to adjust for areas with greater habitat heterogeneity until such time as harvest is restricted and once again habitat fitness begins to decline within the NSO site buffers under the No Action.

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Figure 8. A simulated 50 year harvest schedule under the No Action alternative used to produce modeled trends in four age classes of forest representing different functional types of northern spotted owl habitat identified in Green Diamond’s habitat fitness model. The age classes were as follows: 1 = 0-5 years young recently clearcut forests; 2 = 6-20 years prime woodrat habitat; 3 = 21-40 years woodrat habitat, other NSO foraging and roosting habitat and 4 = >40 years NSO foraging, roosting and nesting habitat. The No Action assumes application of the CA Forest Practice Rules and management of northern spotted owl sites under a take avoidance strategy consistent with USFWS guidelines.

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Figure 9. A simulated 50 year harvest schedule within northern spotted owl site buffers under the No Action used to produce modeled trends in four age classes of forest representing different functional types of northern spotted owl habitat identified in Green Diamond’s habitat fitness model. The age classes were as follows: 1 = 0-5 years young recently clearcut forests; 2 = 6-20 years prime woodrat habitat; 3 = 21-40 years woodrat habitat, other NSO foraging and roosting habitat and 4 = >40 years NSO foraging, roosting and nesting habitat. The No Action assumes application of the CA Forest Practice Rules and management of northern spotted owl sites under a take avoidance strategy consistent with USFWS guidelines. Large Terrestrial Reserves

Under the large terrestrial reserve alternative, approximately 68,000 acres (~ 19% of the Plan Area) will be placed in essentially no harvest reserves. These large reserves will have a high proportion of interior habitat meaning they will not function to provide habitat similar to the relatively small set-asides under the 1992 NSO HCP. Without doing a detailed GIS analysis, we assumed the proposed reserve areas currently have similar mean proportions of different quality NSO habitat as the entire Plan Area. Initially, the reserved areas and the surrounding remainder of the Plan Area could support a 15% increase in the NSO population for several decades, but over time, the habitat heterogeneity and beneficial effects of the young seral habitat adjacent to riparian reserves will be lost (Figure 10). The rate at which NSO habitat would be degraded will be approximately a function of how rapidly young stands lose the ability to support populations of dusky-footed woodrats. Similar to the No Action Alternative with approximately 18% of the Plan Area in NSO site buffers, the Reserve Alternative encompassed 48 NSO sites over 19% of the Plan Area. The reduction in open edge density and accordingly, habitat heterogeneity, was more dramatic under the Terrestrial Reserve Alternative because

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there was no clearcut harvest creating the open edge within the reserve areas. The absence of harvest within the reserves results in an average annual reduction of approximately 8,200 acres in open edge (0-5 year old forest) within the Plan Area (Figure 10). For the same reasons explained under the No Action, this loss in open edge translates to much greater reductions in forest age classes 6-20 years and 21-40 years with annual estimates reaching 22,000 to 28,000 acres respectively (Figure 10). The net reduction to habitat heterogeneity under the Terrestrial Reserve Alternative at the Plan Area scale still appears relatively minor compared to the Preferred Alternative (Figure 3 trends compared to Figure 10), but the substantial loss in habitat heterogeneity will result in a reduction in habitat fitness values under the Terrestrial Reserves alternative. In order to assess the effect on habitat heterogeneity within the boundaries of the Terrestrial Reserves, we evaluated trends in forest age classes within the reserves (Figure 11). The lack of harvest within the reserves illustrates a much more dramatic effect on habitat heterogeneity relative to the Plan Area scale for the Preferred Alternative. In approximately 40 years, all stands in the large terrestrial reserves will be homogeneous mature stands with no beneficial buffer areas adjacent to riparian reserves and no open edge density that promotes habitat heterogeneity. At this point, the reserve areas will be in the lowest habitat quality for NSO as projected by Green Diamond’s (2010) and the Franklin et al. (2000) habitat fitness analyses.

NSO site fitness outside of the reserves would be similar between the Preferred Alternative and the Reserve Alternative because forest management activities would be nearly identical. Habitat quality in the remainder of the Plan Area outside the large reserves should continue on an increasing trend, but much of the potential gains will be offset by the loss of almost 19% of the Plan Area transitioning into low quality habitat that would support a declining NSO population. The NSOs at sites outside of the reserves would be able to take advantage of high quality habitat produced by application of the FPRs and implementation of the riparian buffers, but the additional benefits to NSO sites under the Preferred Alternative such as Dynamic Core Areas would not be realized. The habitat quality outside of the reserves might be capable of supporting a stable population of NSO, but the net effect is that 50% of the NSO sites would be located within habitat not capable of supporting a stable or increasing NSO population.

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Figure 10. A simulated 50 year harvest schedule for managed areas and large terrestrial reserves was used to produce modeled trends in four age classes of forest representing different functional types of northern spotted owl habitat used in Green Diamond’s habitat fitness model. The age classes were as follows: 1 = 0-5 years young recently clearcut forests; 2 = 6-20 years prime woodrat habitat; 3 = 21-40 years woodrat habitat, other foraging and roosting habitat and 4 = >40 years foraging, roosting and nesting habitat. The managed areas under the terrestrial reserves alternative assumes application of the CA Forest Practice Rules and incidental take of northern spotted owls outside of the reserves at a rate similar to the Preferred Alternative.

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Figure 11. A simulated 50 year harvest schedule for areas within the terrestrial reserves used to produce modeled trends in four age classes of forest representing different functional types of northern spotted owl habitat used in Green Diamond’s habitat fitness model. The age classes were as follows: 1 = 0-5 years young recently clearcut forests; 2 = 6-20 years prime woodrat habitat; 3 = 21-40 years woodrat habitat, NSO foraging and roosting habitat and 4 = >40 years NSO foraging, roosting and nesting habitat. The terrestrial reserves alternative assumes no or very minimal harvest as a measure to protect northern spotted owl sites and recruit mature forest habitat over the permit term.

Uneven-aged Management Alternative (single tree selection and group selection)

Under the uneven-aged management alternative, Green Diamond would transition away from even-aged management in forest stands capable of supporting selection harvesting, but some stands would continue to be clearcut either because they are currently under stocked with conifers or lack sufficient forest site class growth potential to support stands of conifers capable of being selectively harvested. Green Diamond would use a combination of single tree selection and group selection as allowed under the FPRs. The spatial arrangement and exact amount of group selection harvest is unknown, so Green Diamond conducted 50 year harvest forecasts with single tree and another with single tree and group selection harvest set to 15% because the maximum allowable amount of group selection at each entry is 20% under the FPRs. Some areas may receive less or more than the 15% rate set in the analysis. Since allowable size of group selection harvests range from 0.25 acres to 2.5 acres, it is virtually impossible to predict where these diminutive clearcuts would occur. Green Diamond would begin selectively harvesting at about 45 years of age and would remove basal area to meet

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retention requirements under FPRs and sustained yield. In practice over time, selection harvest could commence before 45 years of age as long as the forest stand could support selection harvest, but the age was held constant in this analysis. In the modeling exercise, stands that would not support selection harvest were deferred until conifer growth supported selection harvest. Other understocked stands would be clearcut using rehabilitation harvest. Rehabilitation harvest is sporadic and driven by economic conditions supporting a hardwood chip market. It is not known how this portion of harvest would be spatially arranged, but in general, the poorer site classes are associated with ridges and south-facing slopes, while the higher site classes are in the lower slopes and valley bottoms. This would indicate that the forest areas managed through even-aged through rehabilitation harvest would be dispersed throughout the Plan Area and would be limited through time based on amounts of understocked stands and the economic limitations at converting these stands to adequately stocked stands of conifer. The results of the harvest forecast for single tree with group selection indicate that nearly 75% of the Plan Area transitions to age class 4 by 2045 (Figure 12). During the same period, habitat heterogeneity declines due to reductions in age classes 1 – 3 (Figure 12). Based on a study of the impacts of partial harvest of mature forest stands on dusky-footed woodrat populations in the Little River Drainage (Hamm and Diller 2009), the uneven-aged stands did not support populations of woodrats because of a lack of the early seral sunlight-dependent plant forage species. Under this alternative, we project that the approximately 75% of the ownership in uneven-aged management would not support the abundant prey base associated with young forest stands, but forest stands with good foraging potential would still be regenerated on the lower site classes in the rehabilitation harvest areas over the short term. In addition, the small patch cuts under group selection are unlikely to provide the same beneficial effects to dusky-footed woodrats compared to the average opening size (~15 acres) under the Preferred Alternative. The reason is that the group selection harvests will be more dispersed across the landscape, and the small islands of group selection within a much larger landscape of older uneven-age stands are unlikely to provide the same quality habitat as the young seral stands under the Preferred Alternative. The small group selection harvests will not provide the same growing conditions as clearcuts under the Preferred Alternative due to shading effects of the surrounding older stands (regeneration of trees and heliophilic shrubs is retarded). In addition these stands will provide less overall prey biomass at the NSO home range and landscape scales. Under a selection/group selection harvest scenario, habitat heterogeneity is dramatically reduced at the landscape scale (Figure 12). Essentially, this is an inverse relationship with habitat fitness projected through time under the Preferred Alternative (Figure 1). The predictions of the potential functional attributes of group selection harvest areas to NSO prey species such as dusky-footed woodrats are unknown at this time because no empirical evidence is available to suggest that these areas would support similar densities of woodrats observed in prior studies (Sakai and Noon 1990, Hamm 1995, Hamm and Diller 2009), The forest stands subjected to selection timber harvesting would also become more open and lose quality as roosting and nesting stands so that the juxtaposition of older selectively harvested and young even-aged stands would not carry the benefit of habitat heterogeneity observed on landscapes with even-aged management. The only exception where high quality nesting and roosting habitat would be retained on the shorter term is in the Reserved Owl Core Areas (ROCA) around existing NSO sites. But given that most NSO sites occur on the lower

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third of a watershed where the higher site classes tend to occur (and more selection harvest), the ROCAs will generally be surrounded by uneven-aged stands lacking in an abundant prey base. Green Diamond’s 10-Year Review of the 1992 NSO HCP indicated the probability of a successful nest site increased with increasing amounts of open edge density within 600m of the nest site. Therefore, we conclude that landscape-level habitat heterogeneity will be lost at approximately the rate at which even-aged stands mature and are converted to uneven-aged stands or approximately 4% per decade as indicated by the age class 3 trend line (Figure 12). . Under this alternative, virtually all of the NSO habitat in the Plan Area would be degraded at 3% per decade, and the NSO population would be projected to decline at approximately the same rate that stands are converted to an uneven-aged stand condition. Green Diamond also evaluated the effects of conversion to a single tree selection management scenario within the Plan Area by eliminating group selection harvest. This harvest scenario accelerates the decline in habitat heterogeneity because virtually all young seral stands (<21 years) will disappear from the landscape by plan year 2045 (Figure 13). Implementation of a single tree harvest practice within the Plan Area can be expected to accelerate the decline in the NSO population commensurate with the reduction in landscape habitat heterogeneity (approximately 9% per decade). The prediction for either scenario of uneven-aged management is that habitat quality as measured through site fitness, would be expected to decline over the permit term due to loss in habitat heterogeneity and therefore the Plan Area would provide habitat not capable of supporting a stable or increasing population of NSO.

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Figure 12. A simulated 50 year harvest schedule single tree selection and group selection (GS) at 15% of the harvest area was used to produce modeled trends in four age classes of forest representing different functional types of northern spotted owl habitat used in Green Diamond’s habitat fitness model. The age classes were as follows: 1 = 0-5 years young recently clearcut forests; 2 = 6-20 years prime woodrat habitat; 3 = 21-40 years woodrat habitat, other foraging and roosting habitat and 4 = >40 years foraging, roosting and nesting habitat. The single tree selection/group selection alternative assumes application of the CA Forest Practice Rules and static management of 44 reserved northern spotted owl core areas with permitted incidental take of northern spotted owls outside of the reserved owl core areas at a rate similar to the Preferred Alternative.

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Figure 13. A simulated 50 year harvest schedule for single tree selection harvest was used to produce modeled trends in four age classes of forest representing different functional types of northern spotted owl habitat used in Green Diamond’s habitat fitness model. The age classes were as follows: 1 = 0-5 years young recently clearcut forests; 2 = 6-20 years prime woodrat habitat; 3 = 21-40 years woodrat habitat, other foraging and roosting habitat and 4 = >40 years foraging, roosting and nesting habitat. The Selection Alternative assumes application of the CA Forest Practice Rules for unevenage management and static management of 44 reserved owl core areas.

Conclusions: Green Diamond invested decades of effort into research of NSO demographics and habitat use to develop a habitat fitness model for predicting future habitat quality for NSO under the Preferred Alternative. The outcome of that research and modeling effort predicts that forest management under the Preferred Alternative provides for a very positive outcome for NSO within the Plan Area that is also more cost-effective than the other alternatives. Future habitat quality is predicted to increase by nearly 30% over the permit term due to creation of landscape scale habitat heterogeneity capable of supporting an increasing population of NSO. The lack of available research data on NSO demographics and habitat use for the other landscape habitat scenarios that would be produced under the other EIS Alternatives analyzed in detail required Green Diamond to use the best available information to compare potential effects of those alternatives on habitat for the NSO. The 50-year harvest scheduling and forest management scenarios described above provide comparative evidence of the likely effects on habitat and the population of NSO within the Plan Area. When compared to the Preferred Alternative on the basis of predicted habitat quality alone, the other alternatives do not produce similar levels of habitat quality within the Plan Area landscape capable of supporting an increasing population of NSO. In fact, the prediction is that within No Action NSO take avoidance buffers, Terrestrial

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Reserves and the Uneven-aged Management landscape, habitat would not be capable of supporting a stable or increasing NSO population. This prediction is based on science conducted by Green Diamond (2010) and supported by other regional studies of NSO habitat fitness (Franklin et al. 2000, Olsen et al. 2004). Information Sources: Green Diamond Forest Management Plan Green Diamond Draft Forest HCP Green Diamond Draft Forest HCP Appendix C References Franklin, A. B., D. R. Anderson, R. J. Gutierrez, and K. P. Burnham. 2000. Climate,

habitat quality, and fitness in northern Spotted Owl populations in northwestern California. Ecological Monographs 70:539-590.

Hamm, K. A. 1995. Abundance of dusky-footed woodrats in managed forests of north coastal

California. M.S. Thesis, Humboldt State University, Arcata, CA. 46 p. Hamm, K. A. and L. V. Diller. 2009. Forest management effects on abundance of woodrats in

northern California. Northwestern Naturalist 90:97-106. Olson, G. S., E. M. Glenn, R. G. Anthony, E. D. Forsman, J. A. Reid, P. J. Loschl, and W. J.

Ripple. 2004. Modeling demographic performance of northern spotted owls relative to forest habitat in Oregon. Journal of Wildlife Management 68:1039-1053.

Sakai, H. F. and B. R. Noon. 1993. Dusky-footed woodrat abundance in different-aged forests

in northwestern California. Journal of Wildlife Management 57(2):373-382. United States Fish and Wildlife Service. 2011. Northern spotted owl take avoidance analysis and guidance for California coast forest district (“Attachment A”). Arcata Fish and Wildlife Office. AFWO-11B0075-11TA0069. 12pp.