Economic Operability Assessment and Priority Classification in MPB Impacted Areas in the Quesnel Timber Supply Area

Transcription

1 Economic Operability Assessment and Priority Classification in MPB Impacted Areas in the Quesnel Timber Supply Area PHASE II FINAL REPORT v1.1 March 31 st, 21 A Report by: Forest Ecosystem Solutions Ltd. # Harbourside Dr. North Vancouver BC V7P 3T2 tel fax: Submitted by: Jonathan Armstrong, R.P.F. jarmstrong@forestecosystem.ca Submitted to: Phil Winkle, Decision Tree Forestry Consulting Ltd Quesnel TSA Mitigation Committee Canadian Forest Products Ltd C&C Wood Products Tolko Industries West Fraser Timber Co. Ltd. British Columbia Timber Sales

2 Acknowledgements Forest Ecosystem Solutions Ltd. would like to acknowledge Phil Winkle (Decision Tree Forestry Consultants) for his guidance and administration of this project and the input and assistance provided by Ian Moss RPF (ForesTree Dynamics Ltd) in the development and understanding of stand structure in the Quesnel TSA. Additionally, the Quesnel TSA Licensee staff (Canfor, C&C Wood Products, Tolko and West Fraser), provided valuable insight into the forest conditions, beetle impacts and operating parameters in the Quesnel TSA. FESL would also like to thank Gyula Gulyas with Timberline Natural Resource Group, for his work in developing the shelf life and grade tables used in this analysis.

3 TABLE OF CONTENTS ACKNOWLEDGEMENTS...1 LIST OF TABLES...3 LIST OF FIGURES...4 LIST OF FIGURES INTRODUCTION PROJECT BACKGROUND OBJECTIVES DATA SOURCES SPATIAL RESULTANT DESCRIPTION OF THE STUDY AREA TIMBER HARVESTING LAND BASE MODEL LAND BASE METHODOLOGY AND INPUT DESCRIPTION DESCRIPTION OF THE MODEL USED...9 Forest Economic Assessment Model (FEAM) OPERABILITY ASSESSMENT OVERVIEW UPDATES TO STAND VALUE MODEL...1 Stand Structure...1 The Reassignment of Stand Structure Classes To Inventory Polygons In The Quesnel TSA:...13 Mountain Pine Beetle Spread / Infestation...16 Shelf life...17 PFT Stand Grade Distribution and Shelf Life ALTERNATIVE PRODUCTS BIOFUEL (BF) AND ORIENTED STRAND BOARD (OSB) SELLING PRICES / LOG VALUE ESTIMATING OPERATING COSTS UPDATED ROAD NETWORK DETERMINING ECONOMIC RETURN (OPERABILITY) ECONOMIC STRATIFICATION RESULTS BASECASE RESULTS COMPARISON WITH PHASE I BASECASE...ERROR! BOOKMARK NOT DEFINED INCLUDING BIOFUEL AND OSB VALUE COSTS MINUS 15 PERCENT COSTS MINUS 25 PERCENT VALUE INCREASE MOUNTAIN PINE BEETLE MOUNTAIN PINE BEETLE MOUNTAIN PINE BEETLE FINAL SCENARIO...52

4 5.11. SCENARIO COMPARISON HARVEST RANKING CONCLUSION...59

5 LIST OF TABLES Table 1 Sources of data used in this project...4 Table 2 Updated to spatial dataset for Phase II...5 Table 3 Final data list used in analysis database...5 Table 4 Quesnel TSA Land base Classification...7 Table 5 Quesnel TSA Timber harvesting land base definition...8 Table 8 Pine Grade Distribution and Shelf Life Small Logs...18 Table 9 Pine Grade Distribution and Shelf Life Medium Logs...18 Table 1 Pine Grade Distribution and Shelf Life Large Logs...19 Table 11 Grade Distribution without URL - Large Logs...19 Table 12 Grade Distribution without URL - Medium Logs...2 Table 13 Grade Distribution without URL - Small Logs...2 Table 14 1 Pine Grade Distribution and Shelf PFT Stands...21 Table 15 Grade Distribution without URL PFT Stands...21 Table 16 Log selling prices ($/m3)...22 Table 17 MOFR Publish Average Cost Estimates...23 Table 18 Average Hauling Distance by LU Code...24 Table 19 Economic stratification - Opportunity land base classes...26 Table 2 Basecase Results - THLB Area and Merch Volume by Return Class...27 Table 21 Scenario Comparison...56

6 LIST OF FIGURES Figure 1 Location of the Quesnel TSA...6 Figure 2 Quesnel TSA Map - Land base classification...8 Figure 3 Descriptive statistics of each stand structure class (Ian Moss RPF)...12 Figure 4 Stand table summary for stand structure classes (Ian Moss RPF)...13 Figure 5 New Stand Structure Class Allocation...14 Figure 6 Old Stand Structure Class Allocation...15 Figure 7 Lumped stand structure classes in the Quesnel TSA Phase I...15 Figure 8 Revised 29 Stand Structure Class Assignments...16 Figure 9 Updated MPB Predictions - Severity...16 Figure 1 Updated MPB Predictions - Status...17 Figure 11 Updated MPB Predictions - Severity and Status...17 Figure 12 Estimated hauling distance zones from Quesnel Phase I...24 Figure 13 Updated Road Network and Major Haul Routes...24 Figure 14 - THLB Area by Return Class and Supply Block - Basecase...28 Figure 15 THLB Area by Return Class and SSC - Basecase...29 Figure 16 THLB Area by Return Class and Distance From Quesnel - Basecase...3 Figure 17 THLB Area by Return Class and Supply Block - Basecase and BF/OSB...31 Figure 18 THLB Area by Return Class and SSC - Basecase and BF/OSB...32 Figure 19 THLB Area by Return Class and Distance From Quesnel - Basecase and BF/OSB...33 Figure 2 THLB Area by Return Class and Supply Block - Basecase Minus 15% Cost...34 Figure 21 THLB Area by Return Class and SSC - Basecase Minus 15% Cost...35 Figure 22 THLB Area by Return Class and Distance From Quesnel - Basecase Minus 15% Cost...36 Figure 23 THLB Area by Return Class and Supply Block - Basecase Minus 25% Cost...37 Figure 24 THLB Area by Return Class and SSC - Basecase Minus 25% Cost...38 Figure 25 THLB Area by Return Class and Distance From Quesnel - Basecase Minus 25% Cost...39 Figure 26 THLB Area by Return Class and Supply Block - Basecase + 15% Value...4 Figure 27 THLB Area by Return Class and SSC - Basecase + 15% Value...41 Figure 28 THLB Area by Return Class and Distance From Quesnel - Basecase + 15% Value...42 Figure 29 THLB Area by Return Class and Supply Block Projection...43 Figure 3 THLB Area by Return Class and SSC Projection...44 Figure 31 THLB Area by Return Class and Distance From Quesnel Projection...45 Figure 32 THLB Area by Return Class and Supply Block - 22 Projection...46 Figure 33 THLB Area by Return Class and SSC - 22 Projection...47 Figure 34 THLB Area by Return Class and Distance From Quesnel - 22 Projection...48 Figure 35 THLB Area by Return Class and Supply Block Projection...49 Figure 36 THLB Area by Return Class and SSC Projection...5 Figure 37 THLB Area by Return Class and Distance From Quesnel Projection...51 Figure 38 THLB Area by Return Class and Supply Block - 21 Final Scenario...53 Figure 39 THLB Area by Return Class and SSC - 21 Final Scenario...54 Figure 4 THLB Area by Return Class and Distance From Quesnel - 21 Final Scenario...55 Figure 41 Scenario Comparison...57

7 1. Introduction Operability, in the strategic timber supply context, refers to a classification of the land base as either suitable or not suitable for timber extraction. Suitability for timber extraction is influenced by the physical characteristics of the land, social and environmental concerns, and the potential economic return generated contrasted with the costs incurred during all phases of production. Economic operability can be a difficult element to quantify. The report presents the results of Phase II of an economic operability analysis, conducted for the Quesnel TSA. The approach taken with this analysis was to define the factors that are important drivers of the economics in the Quesnel TSA, develop reasonable estimates of those factors at a stand level, evaluate the results, and investigate areas of uncertainty via scenario analysis. Economic operability and the changes in economic return, will be used to assist in developing salvage strategies and harvest priorities in the Quesnel TSA. Phase II of this project incorporated revised estimates for stand structure, mountain pine beetle attack, road locations, shelf life, product yield and value and product pricing. The results of Phase II are presented in this report along with a comparison with the Phase I basecase Project Background Phase 1 of the Quesnel TSA Operability project was completed in March 28 for the Quesnel TSA Mitigation Committee. Project guidance was provided by the committee with analytical work conducted by Forest Ecosystem Solutions Ltd. and ForesTree Dynamics Ltd. Copies of the report were distributed to Quesnel licensees and the MOF (FAIB and Quesnel District). Recommendations in the Phase 1 report stated: As with any modeling based analysis project, the results and interpretations achieved are only as precise and relevant as the data used for the inputs. With this operability model, there are several input parameters that have a large influence over the end result. Some of these parameters currently have a high degree of uncertainty around them. In order to fully utilize the data generated from this operability analysis, the following next steps may be considered for future assessments: 1. Calibrate with actual returns: Review recently harvested blocks and compare value, cost and returns with model estimates. Use the comparison to calibrate the model to provide a more accurate assessment. 2. Phase II VRI Inventory: Once the VRI inventory is complete, rerun the model. It is assumed that the more detailed and accurate inventory will significantly improve the results of any economic analysis. 3. Compare with Volumes: Compare cruise, inventory, sample volumes with those estimated from the model. 4. Calibrate Stand Structure Classes: Adjust the stand structure class assignment process to accurately reflect the stand conditions in the Quesnel TSA. 5. Apply actual / more realistic costs: In lieu of appraisal manual costs, utilize actual costs or relative estimates from licensees. Page 1 of 67

8 6. Scenario analysis (log values, operating costs, shelf life): Analyze the impacts of shifting log markets, operating costs and uncertainty around shelf life. 7. Manufacturing / end product value model: Consider accounting for the entire value of each stand by applying the manufacturing / end use model to the Quensel TSA. It is expected that considering the entire value generated by the stand and the variation in associated manufacturing costs will provide a more detailed and accurate result. 8. Other forest products (biofuel): Consider modeling the impacts that alternative forest products such as biofuels will have on the economics of the Quesnel TSA. Phase 2 of the project focused on implementing recommendations 3, 4, 6 and 8. In addition, Phase 2 incorporated improved Mountain pine beetle attack and spread estimates, and revised cost estimates using the most up to date Appraisal Manual (29). The following background information is taken from the Operability Assessment and Priority Classification in MPB Impacted Areas, Quesnel TSA, tender package. Physical limits on operability in the Quesnel TSA have not been considered a significant issue in previous Timber Supply Reviews as only.2% of the THLB is comprised of slopes greater than 6%. However, operability is now a large issue as the Mountain Pine Beetle (MPB) is impacting traditional views of operability as large areas of timber are declining in volume and value at rapid but varying rates. Some stands that were traditionally considered merchantable will be operable only for certain time periods or may not be operable at all and will require renewal treatment. The whole stand may not be degraded and analysis must impose techniques to apply merchantability reductions based on documented attribute assumptions (moisture regime, non-pine component, class distributions ). Therefore, temporal stand degradation issues and end product estimates must be accounted for in defining operability in MPB areas. This degradation to the operable land base portfolio will be the major driver for harvest strategies and AAC determinations for the next few decades. In the near term, operability over time will also be defined by the timber and site characteristics that determine product viability for saw log, OSB, bio-fuel, etc. Understanding and defining the current and near future (2 year) operable land base is instrumental in evaluating wood supply scenarios and developing mitigation strategies. This issue was recognized in the July 26 letter from R. Coleman, the Minister of Forests and Range, to the Chief Forester outlining the Economic and Social Objectives of the Crown as, in part, to assist the province and affected communities in planning their responses to the beetle infestation, it would be best to have realistic assessments of timber volumes that can be utilized economically. Therefore, in determining the best rate of harvest to capture the economic value from beetle killed timber, I ask that you examine factors that affect the demand for such timber and products manufactured from it, the time period over which it can be utilized, and consider ways to maintain or enhance the mid-term timber supply. In addition to the rate of harvest (AAC), current harvest profiles and harvest sequencing are impacting the future availability of near term operable timber. Stands are currently being sequenced and harvested without sufficient strategic planning and regard for the impact on timber supply and other values. For example, a MPB attacked stand may be harvested today that was economically viable for a longer time period than an adjacent Page 2 of 67

9 stand that is not planned for harvesting. This impact is increasing annually as MPB degradation is increasing the harvest areas required to achieve cut block volume targets due to increasing waste levels. It now takes approximately 3 to 5% more area to harvest the same saw log volume. The result is a higher than necessary risk to timber supply, hydrology, wildlife habitat, recreation & other social values. Development of strategic level harvest priority guidelines, from the view of optimizing the near term timber availability and utilization on the land base, is required. An assessment and a hierarchical classification of operability types will provide an indication of fibre to be allocated to its highest value use while making better use of the declining available resource. This will provide direction to the goal of ensuring all harvesting is of value in reducing the effects of the beetle and is not additive. Any assessment must be usable as guidelines for local harvest planners. The assessment will also support development of economic indicators and measures for sustainable forest management and certification. The process will indirectly indicate areas for potential retention, salvage and renewal strategies. This information would be valuable to the Quesnel Enhanced Retention Strategy Committee and the Forests For Tomorrow renewal assessments that are ongoing in Quesnel. The Chief Forester s Rationale for Timber Supply Review (TSR) 3 stated that resolution of how to implement the recommendations contained in the paper "Forest Stewardship in the Context of Large-Scale Salvage Operations" was a priority issue. Operability classifications will assist with continuing refinement and implementation of the recommendations. With the MPB attack level having peaked in mature stands in the Quesnel TSA and the TSR 4 process currently scheduled for completion in 21, it is timely to complete operability assessment. As partitioning of the AAC will likely be considered as part of the TSR 4 process, it will be necessary to have a well defined current and near term operable component of the THLB Objectives The objectives for this project, as stated in the 29/21 Workplan are as follows; Ensure operability model and data are compatible with TSR 4 Data Package (as released April, 29) Integrate information from Quesnel licensee group: current timber availability, accumulating timber constraints and potential saw log utilization Incorporate information on OSB and deciduous opportunities including shelf life for OSB Confirm data and model assumptions, including range of pricing, to be modeled with licensees and MFR Confirm model scenarios to be run Run scenarios and analyze results Produce draft report and maps, meet with stakeholders Produce final report Page 3 of 67

10 2. Data Sources The sources of data used in this project are listed in Table 1. Table 1 Sources of data used in this project Data Element Source Comments Forest Inventory Timberline Natural Resource Group Resultant for this project was based on the STTA resultant, used for several projects in the Quesnel TSA. Old Growth Management Areas (OGMAs) Stand Tables, Log Yield Tables Canfor ForesTree Dynamics Updated OGMAs were incorporated into the resultant Stand estimates were derived from Stand Structure Classification system developed by Ian Moss. Landscape Units Canfor Landscape units were added. Recent Fires Canfor Several large fires were included Updated Depletions Canfor Depletions (up to 27)and planned blocks were incorporated into the resultant Enhanced Retention Canfor Enhanced retention areas were identified in the resultant Supply Blocks LRDW Supply Blocks were added Operating Areas Log Grade Distribution / Shelf life curves VRI Pilot Study Area Mapsheets MPB Infestation Rate PEM LRDW / Canfor Timberline Natural Resource Group ForesTree Dynamics Forest Ecosystem Solutions Quesnel TSA Licensees Timberline Natural Resource Group MOFR West Fraser Licensee operating areas (Post bill 28) were overlaid with the resultant Log Grade Distributions and shelf-life curves were developed in conjunction with this project. While not used for this stage of the project, a relationship was established between the pilot area polygons and the resultant Year of death estimates based on 26 Landsat imagery, and subsequent projections of beetle spread by ForesTree Dynamics. Biogeoclimatic variants and zones were extracted from the recently completed PEM. Cost Estimates MOFR 29 Appraisal Manual Log Value MOFR Log Values were taken from the MOFR published average log market reports. Page 4 of 67

11 Table 2 Updated to spatial dataset for Phase II Data Element Source Comments MPB Year of Death MOFR MPB year of death data for 27 that was intended to be included in the Phase I dataset, but was not available at the time was included in the revised data PEM Site Index Stand Structure Class Updates Timberline Ian Moss Site index was extracted from the PEM. This data was used in the SSC work. Updates to both the makeup of the SSC and the assignment to Resultant polygons were completed by Ian Moss in 29. The revised SSC data is the major update to the data for Phase II 2.1. Spatial Resultant Forest inventory data for this project was supplied in an existing resultant dataset from the STTA analysis. The resultant contained some of the data required for the spatial reference portion of this project. Additional data was added to the resultant to create the final modeling database. Details of the data in the final database are shown in Table 3. Table 3 Final data list used in analysis database Data Included STTA Resultant Forest Cover (in the form of a roll over VRI) Biogeoclimatic Zones Timber harvesting land base classification Environmentally Sensitive Areas Visual Quality Objectives Community Watersheds Caribou-Chilcotin Land use plan zones Mule Deer Winter Range Caribou Habitat Moose Habitat Data Added / Updated by FESL Landscape Units Recent Fires Updated Depletions Enhanced Retention Supply Blocks Operating Areas MPB Infestation Rate PEM Old Growth Management Areas (OGMAs) 3. Description of the Study Area The Quesnel TSA is located at the northern edge of the Southern Interior Forest Region. The TSA covers approximately 2 million hectares, of which approximately 1.3 million hectares is productive Crown forest (CFLB). Of the 1.3 million hectares of CFLB, approximately 975, hectares are classified as available for timber harvesting. The area covered by Quesnel Forest District encompasses the Quesnel TSA, woodlot licence areas, as well as Tree Farm Licences 52. As this operability analysis was limited to Timber Supply Page 5 of 67

12 Area, the information provided is this report is specific to the TSA. The Quesnel TSA is included in the area covered by the Cariboo-Chilcotin Land-Use Plan (CCLUP). Figure 1 Location of the Quesnel TSA 3.1. Timber harvesting land base The timber harvesting land base (THLB) definition for this project was taken directly from the resultant as supplied, with one exception. Updated Old Growth Management Areas (OGMA) were incorporated into the resultant dataset. The new OGMA s represented in increase of approximately 4 ha over those used in the previous analysis. Area within the OGMAs was defined as within the Crown Forested Land base (CFLB) and excluded from the THLB Model Land base The timeframe for this economic operability assessment extends from 21 out over the next 2 years. Currently immature (logged and natural) stands are not expected to be harvested during the time frame of this analysis. While these stands are part of the THLB, in the context of a short term operability / economic analysis they do not factor in to the equation. As such, only currently mature volume was considered during the analysis. In modeling terms, the area of concern was limited to what is referred to as the Modeling land base. The modeling land base was restricted to THLB stands greater than 4 years of age (in 21) and not currently under Category A cutting permit. Page 6 of 67

13 Table 4 Quesnel TSA Land base Classification Land base Classification Area (ha) Total Land base Area 2,77,267 Crown Forested Land base 1,31,324 Non-Contributing Land base Timber Harvesting Land base 33,96 975,667 Model Land base 621,952 Page 7 of 67

14 Table 5 Quesnel TSA Timber harvesting land base definition Land Classification Total Area CFLB (ha) THLB (ha) Total Quesnel Land District 2,77,267 TFL 295,251 - Total Timber Supply Area 1,782,16 Non-Forested 277, Non-Crown 63, Schedule N 126, Parks 5, Crown Forested Land base 1,31,324 Non-Commercial Caribou 65,43 65,43 - Lake Buffers Non-Merchantable 4,37 4,37 - Low Productivity 12,434 12,434 - Residual Non Merchantable 2,653 2,653 - Deciduous 14,423 14,423 - Riparian 17,261 17,261 - OGMAS 12, 12, - New OGMA 4,89 4,89 - Non-Contributing Land base 259,9 Partial Reductions (WTPs, ESA, Roads) 1,5,424 74,758 Timber Harvesting Land base - 975,667 Figure 2 Quesnel TSA Map - Land base classification Page 8 of 67

15 4. Methodology and Input Description The following section defines the methodology used in this economic operability analysis Description of the Model Used Forest Economic Assessment Model (FEAM) FEAM provides a framework to assess and investigate the economics of a forest estate. The concept was initially designed as a model to connect existing knowledge of the forest estate, operational conditions, manufacturing parameters and costs, and historical, current and future market conditions, to generate an economic assessment. The original focus of FEAM was on conditions expected in the interior of British Columbia. The design of the model has subsequently been modified in order to allow for data from any provincial or regional jurisdiction to be used. FEAM can be used to examine economic conditions, scenarios and strategies that range from a strategic to a tactical level. To allow for the wide range of analysis that can be done with FEAM, a variety of data scales, from single forest stand, to a landscape unit, a supply block, a timber supply area or region can be incorporated into a FEAM model. The concept behind FEAM is that connections can be made between existing data to produce a locally relevant value and cost estimate for individual forest stands. The estimates produced are specific to their geographic location, stand attributes, operating conditions, licensee preferences and constraints. FEAM produces stand-specific values and costs that can then be aggregated or analyzed through user defined analysis groupings (e.g. woodsheds, watersheds, landscape units, tracts, development types or cutting permits) to produce an economic assessment. FEAM is an application that allows the user to develop relationships between existing data sources and forest resource inventory information to create an economic model of the entire land base. FEAM has two methods of estimating the value of a forest stand. Both methods begin with forest stand structure classifications to estimate the species, quality, size and amount of fibre available from each stand. Building on the stand or inventory estimates, the level of detail used to assign value can be done in one of two ways, the manufacturing based model or the log market model. The manufacturing based model can utilize actual end product values to determine an economic return. The log market model allows us to capture the unique operating conditions and product grades and log sales markets for coastal forest products. The grade market model is used in this project. The FEAM cost model allows the user to define what costs are to be tracked and how they are to be applied. Analysis tools built into FEAM can be used to compare and evaluate costs as they relate to economic return. FEAM does not tell you how to define economic operability for a given land base. The users define the appropriate economic parameters through a flexible data and assumptions model interface Operability Assessment Overview The FESL approach to economic operability analysis involves combining a range of assumptions about the forested land base including; Page 9 of 67

16 Stand location Stand structure, Species composition, Volume, Geographical location, Grade distribution, and Forest health factors (MPB). These individual elements are grouped together and related spatially to individual forest stands to provide a detailed estimate of the potential value of each stand. Once the stand value estimates have been completed, operating cost estimates are applied to each stand. These operating costs can be based on operational data, as experienced by the companies who operate in the TSA, or the cost can be generated by inputting the value and cost parameters generated by the model in provincial stumpage equations. The latter approach was taken in this analysis. Once the value and cost for each stand have been determined, the estimated economic return can be calculated (by subtracting cost from value). By maintaining the spatial stand level link, the results can be summarized and economic return to be determined for any type of spatial or attribute based grouping. The following sections describe in detail how the value and cost of each stand are determined Updates to Stand Value Model The methodology employed to support this assessment of economic operability for the Quesnel TSA represents a new and innovative approach for determining the economic return for a forest management unit. The process involves a stand value sub-model and a cost-submodel. The stand value sub-model is based on a series of assumptions beginning with defining the forest land base as it relates to economic operability. For this project, stand structure classes were defined as a part of a previous project. Stand Structure Stand structure classes were assigned to each forest cover polygon in a separate project completed in 27 by ForesTree Dynamics Ltd. The distribution of stand structure classes in the Quesnel TSA is shown in Figure 7. Stand structure classes that either; have characteristics that render them similar in relation to economic value, or represent a very small portion of the Quesnel TSA were lumped together to facilitate modeling. The stand structure class data associated with each polygon was compiled in relation to the analysis units described below. Updates to the Stand Structure Classification (SSC) were the key new data element for the 29 Phase II analysis. This work focused on refining both the stand structure classes and their assignment to individual resultant polygons. Ian Moss completed the analysis. More details on the process and results are expected in the near future. Stand structure classification (SSC) refers to a method of classifying stands using a range of stand level attributes. These attributes include; density (stems per hectare), diameter distribution, crown closure, stem height, stocking, and age. The classification system was Page 1 of 67

17 developed in 24 by Ian Moss RPF for the Williams Lake TSA, under the TOLKO Caribou Innovative Forest Practices Agreement. In 27, Ian adapted the stand structure classification for the Quesnel TSA. Stand Structure classes provide us with an estimate of the stand characteristics that are relevant to an economic operability analysis. Some of these attributes such as those found in stand tables, are not typically found in a forest cover data set. In this economic operability analysis, stand structure classes are used for several functions. First the stand tables associated with each polygon are used in the grouping of stands into development types or Analysis Units. Second, the connected log yield tables (generated for each forest cover stand) are used to create log volume estimates by species and log characteristics (Section 4). Lastly, stand structure class provides a general estimate of piece size (m3 / log) that is a key characteristic used in determining economic operability. Figure 3 and Figure 4 are taken directly from the report titled Seventeen Stand Structure Classes by Ian Moss. These figures describe in detail the composition of each stand structure class. The full report is found in Appendix V. Page 11 of 67

18 Figure 3 Descriptive statistics of each stand structure class (Ian Moss RPF) Page 12 of 67

19 Sta nd Ta ble Di ame te rc la ss Lower Li mi t Sta nd Ta ble Diame te rcla ss Lower Limit Sta nd Table Diame te rclas s Lower Lim it Sta nd Table Diame te rclas s Lower Lim it Stan d T ab le Diam eter Cla ss L o wer Limit Stand Table D ia meter C l ass Lo we rli mi t Stand Table Dia meter Class Lowe rlimit Stand Table Dia meter Class Lowe rlimit Stand Table Dia meter Class Lowe rlimit Stand Table Diameter Class Lower Limit Stand Table Diameter Class Lower Limit Stand Table Diameter Class Lower Limit Stand Table Diameter Class Lower Limit Stand Ta ble Dia meter Class Lower Limit Stand Ta ble Dia meter Class Lower Limit Stand Ta ble Dia meter Class Lower Limit Stand Ta ble Dia meter Class Lower Limit Stand Table Summary Average Numbers of Trees Per Hectare By Diameter Class TPH 9392 TPH 259 TPH 6652 TPH Trees P er H ectare Trees P er H ectare Trees Per H ectare Trees Per H ectare Trees Per H ectare TPH 189 TPH 3472 TPH 6724 TPH Trees Per H ectare Trees Per H ectare Trees Per H ectare Trees Per H ectare TPH 2258 TPH 237 TPH 246 TPH Trees Per H ectare Trees Per H ectare Trees Per H ectare 13 Trees Per H ectare 848 TPH Trees Per H ectare 3346 TPH Trees Per H ectare 717 TPH Trees Per H ectare 5684 TPH 17 Tre es Per Hec tare 5473 TPH Figure 4 Stand table summary for stand structure classes (Ian Moss RPF) The x-axis represents each of the diameter classes, 1 to 16 with the respective maximum diameters as follows (cm): 2.5, 4, 7.5, 12.5, 17.5, 22.5, 27.5, 32.5, 42.5, 52.5, 62.5, 72.5, 82.5, 92.5, 12.5, > The y-axis represents the average stems per hectare by diameter class up to a maximum of 2 with major intervals indicated in increments of 2. The numbers inset into each figure describe the total trees per hectare (on average). The reports below explain the process of assigning stand structure classes and the associated stand and stock tables to inventory polygons in greater detail. Quesnel TSA Forest Cover Inventory Stand and Stock table assignments Project Summary,March 23, 27. ForesTree Dynamics Ltd. Imputation: Predicted versus Actual Inventory Polygon Stand and Stock Table Attributes Landscape and Harvest Block Scales Quesnel Timber Supply Area, April 16, 27, ForesTree Dynamics Ltd The Reassignment of Stand Structure Classes To Inventory Polygons In The Quesnel TSA: The following section was prepared by Ian Moss RPF as a summary of the changes to the Stand structure class assignment process. The figures below provide a comparison of the percentage of area (out of 1.38 million hectares) allocated to each stand structure class using new data. In addition the process for extrapolating from polygons with ground plot data to estimate stand structure classes in polygons without ground plot data was upgraded. Page 13 of 67

20 The process involved relating the following kinds of plots: cruise, PFT plots established by J.S. Thrower and Associates, 28 VRI calibration plots, 27 Pilot VRI plots and plots established in the TOLKO Cariboo (Williams Lake and 1 Mile TSA s) Innovative Forest Practices Area between 1996 and 21. These plots were related to inventory polygons to produce a tree list. The tree list was then input into the stand structure compiler to classify them according to stand structure class. Each polygon stand structure class was then related to the following Forest Cover Attributes: Merchantable Volume (12.5 +), projected age and height, crown class and percent PL. These were input into a neural network to develop a system of classifying the polygons using after partitioning the data into training and test datasets. Once training was complete the algorithm was then used to classify all of the remaining polygons without plots. The new stand structure assignments do not involve stand structure classes 1 and 7, unlike the old. This occurred because the polygons with plots were classified in the stand structure compiler according to a minimum diameter of 12 cm dbh, instead of cm dbh as was done before. While this did not change all of the class assignments associated with each polygon, it did change some of them. Initial indications were that the classes were more closely related to polygon attributes than the + classes. For the purpose of comparison with the new assignments, stand structure classes 1 and 2 were combined in 2, and 6 and 7 were combined in 6 to estimate areas under the old assignments. Figure 5 New Stand Structure Class Allocation Page 14 of 67

21 Figure 6 Old Stand Structure Class Allocation Figure 7 Lumped stand structure classes in the Quesnel TSA Phase I Page 15 of 67

22 Figure 8 Revised 29 Stand Structure Class Assignments Mountain Pine Beetle Spread / Infestation One of the main objectives of this project is to quantify the economic impact of the MPB on the forest industry in Quesnel. To accomplish this assessment, the rate at which pine in the TSA is degrading needed to be estimated in more detail than had previously been done. The level of decay and loss of merchantable volume is a function of the spread of the epidemic (rate of attack), as well as how quickly the trees degrade following attack. In order to provide a realistic estimate of the rate of attack, the progression of the pine beetle has to be modeled not only at the landscape level (between stands) but also at the stand level (between trees in a stand). In Phase I of this project a combination of provincial estimates, modeling and local knowledge was used. The results were acceptable, but improvements were possible. To update the MPB assumptions, new data available from the FFT program were used. Inputs to this project included, orthophotos, remote sensing change detection, forest health flights and other inventory updates. The results are a significant improvement in terms of data quality over what was used in Phase I. Spatial representations of the MPB attack are presented in Figure 9, Figure 1 and Figure 1. Figure 9 Updated MPB Predictions - Severity Page 16 of 67

23 Figure 1 Updated MPB Predictions - Status Figure 11 Updated MPB Predictions - Severity and Status Shelf life Initial Shelf-life estimates used in this analysis were developed in the separate shelf life project, Developing Shelf-life tables for the Quesnel TSA Economic Operability Analysis. TNRG, 28. The shelf life curves produced from this project, reflect both the total loss of marketable volume in the stand and the degrading of the pine (or the shift from a higher grade to lower grade). The shelf life curves were separated by log diameter and two stand classes (regular and PFT stands in Supply block A, B and C). For Phase II, updates were made to the shelf-life and grade distribution estimates following meeting with the Quesnel TSA Licensees. In general, assumptions were made more pessimistic, with more volume lost and being allocated to pulp and in the year previous. Biofuel and OSB were added to the grade distribution tables as well. These alternative products are discussed further in the following section. Page 17 of 67

24 Table 6 Pine Grade Distribution and Shelf Life Small Logs Years Interior Log Grades / Suitable Product Since 1 2 4S 4P 6 BF OSB U/R Attack % of volume 77% % 7% 3% 12% % 1% 1 64% 5% 1% 3% 16% % 2% 2 45% 1% 19% 3% 21% % 2% 3 41% 13% 17% 3% 23% % 3% 4 39% 15% 16% 3% 24% % 3% 5 37% 17% 14% 3% 26% % 3% 6 35% 18% 14% 3% 25% % 5% 7 3% 18% 18% 3% 23% % 8% 8 28% 18% 19% 3% 22% % 1% 9 24% 18% 22% 3% 21% % 12% 1 21% 18% 24% 2% 21% % 14% 11 17% 17% 24% 2% 24% % 16% 12 14% 16% 24% 2% 26% % 18% 13 1% 15% 22% 2% 31% % 2% 14 6% 14% 19% 2% 37% % 22% 15 3% 13% 17% 2% 39% 2% 24% 16 % 11% 14% 2% 4% 7% 26% 17 % 1% 12% 2% 35% 13% 28% 18 % 9% 9% 2% 3% 2% 3% 19 % 8% 9% 1% 28% 22% 32% 2 % 7% 9% 1% 25% 24% 34% Table 7 Pine Grade Distribution and Shelf Life Medium Logs Years Interior Log Grades / Suitable Product Since 1 2 4S 4P 6 BF OSB U/R Attack % of volume 5% 72% % 1% 12% % 1% 1 3% 66% 3% 12% 14% % 2% 2 2% 52% 9% 19% 16% % 2% 3 1% 46% 13% 2% 18% % 2% 4 1% 43% 13% 21% 2% % 2% 5 1% 4% 14% 22% 21% % 2% 6 % 36% 15% 23% 21% % 5% 7 % 31% 15% 22% 24% % 8% 8 % 26% 15% 21% 28% % 1% 9 % 23% 15% 21% 29% % 12% 1 % 19% 15% 21% 31% % 14% 11 % 15% 15% 22% 32% % 16% 12 % 11% 15% 23% 33% % 18% 13 % 7% 15% 24% 34% % 2% 14 % 3% 15% 25% 35% % 22% 15 % % 15% 25% 36% % 24% 16 % % 1% 25% 37% 2% 26% 17 % % 8% 23% 37% 4% 28% Page 18 of 67

25 18 % % 3% 23% 37% 7% 3% 19 % % 1% 23% 35% 9% 32% 2 % % 1% 18% 35% 12% 34% Table 8 Pine Grade Distribution and Shelf Life Large Logs Years Interior Log Grades / Suitable Product Since 1 2 4S 4P BF OSB U/R Attack % of volume 45% 3% % 5% 18% % 2% 1 32% 32% 3% 4% 26% % 3% 2 15% 35% 6% 7% 33% % 4% 3 1% 35% 9% 7% 35% % 4% 4 5% 34% 12% 7% 38% % 4% 5 2% 28% 12% 12% 41% % 5% 6 1% 24% 12% 16% 42% % 5% 7 % 19% 12% 18% 43% % 8% 8 % 13% 12% 18% 47% % 1% 9 % 9% 12% 18% 49% % 12% 1 % 5% 1% 2% 51% % 14% 11 % 2% 1% 18% 54% % 16% 12 % % 9% 16% 57% % 18% 13 % % 7% 13% 6% % 2% 14 % % 4% 11% 63% % 22% 15 % % 2% 8% 66% % 24% 16 % % % 5% 66% 3% 26% 17 % % % 4% 61% 7% 28% 18 % % % 3% 57% 1% 3% 19 % % % 2% 53% 13% 32% 2 % % % 1% 49% 16% 34% Table 9 Grade Distribution without URL - Large Logs Interior Log Grades / Suitable Product YEAR BF OSB 78% 7% 3% 12% % 1 65% 15% 3% 16% % 2 46% 3% 3% 21% % 3 42% 31% 3% 24% % 4 4% 32% 3% 25% % 5 38% 32% 3% 27% % 6 37% 34% 3% 26% % 7 33% 39% 3% 25% % 8 31% 41% 3% 24% % 9 27% 45% 3% 24% % 1 24% 49% 2% 24% % 11 2% 49% 2% 29% % 12 17% 49% 2% 32% % 13 13% 46% 3% 39% % 14 8% 43% 3% 47% % Page 19 of 67

26 15 4% 39% 3% 51% 3% 16 % 34% 3% 54% 9% 17 % 3% 3% 49% 18% 18 % 26% 3% 43% 29% 19 % 25% 1% 41% 32% 2 % 24% 2% 38% 36% Table 1 Grade Distribution without URL - Medium Logs MEDIUM LOGS BF OSB 5% 73% 1% 12% % 3% 67% 15% 14% % 2% 53% 29% 16% % 1% 47% 34% 18% % 1% 44% 35% 2% % 1% 41% 37% 21% % % 38% 4% 22% % % 34% 4% 26% % % 29% 4% 31% % % 26% 41% 33% % % 22% 42% 36% % % 18% 44% 38% % % 13% 46% 4% % % 9% 49% 43% % % 4% 51% 45% % % % 53% 47% % % % 47% 5% 3% % % 43% 51% 6% % % 37% 53% 1% % % 35% 51% 13% % % 29% 53% 18% Table 11 Grade Distribution without URL - Small Logs LARGE LOGS BF OSB 46% 31% 5% 18% % 33% 33% 7% 27% % 16% 36% 14% 34% % 1% 36% 17% 36% % 5% 35% 2% 4% % 2% 29% 25% 43% % 1% 25% 29% 44% % % 21% 33% 47% % % 14% 33% 52% % % 1% 34% 56% % % 6% 35% 59% % % 2% 33% 64% % % % 3% 7% % Page 2 of 67

27 % % 25% 75% % % % 19% 81% % % % 13% 87% % % % 7% 89% 4% % % 6% 85% 1% % % 4% 81% 14% % % 3% 78% 19% % % 2% 74% 24% PFT Stand Grade Distribution and Shelf Life For PFT stands separate grade distributions and shelf life estimates were generated. These separate curves represent the different decay and grade characteristics of the smaller profile stems found in PFT stands. Table 12 1 Pine Grade Distribution and Shelf PFT Stands Years Interior Log Grades / Suitable Product Since 1 2 4S 4P 6 BF OSB U/R All Attack % of volume 92% % 2% 3% 3% % % 1% 1 85% 3% 3% 3% 5% % 1% 1% 2 68% 13% 6% 3% 9% % 1% 1% 3 66% 12% 7% 3% 11% % 1% 1% 4 54% 11% 8% 3% 23% % 1% 1% 5 45% 1% 1% 3% 31% % 2% 1% 6 35% 13% 1% 3% 34% % 5% 1% 7 26% 16% 13% 3% 35% % 8% 1% 8 16% 19% 18% 2% 35% % 1% 1% 9 6% 22% 2% 2% 38% % 12% 1% 1 % 25% 2% 2% 39% % 14% 1% 11 % 3% 13% 2% 39% % 16% 1% 12 % 27% 15% 2% 38% % 18% 1% 13 % 23% 17% 2% 38% % 2% 1% 14 % 2% 19% 2% 37% % 22% 1% 15 % 16% 19% 2% 39% % 24% 1% 16 % 13% 21% 1% 38% 1% 26% 1% 17 % 9% 22% 1% 38% 2% 28% 1% 18 % 6% 22% 1% 38% 3% 3% 1% 19 % 2% 22% 1% 38% 5% 32% 1% 2 % % 22% 1% 36% 7% 34% 1% Table 13 Grade Distribution without URL PFT Stands Interior Log Grades / Suitable Product YEAR BF OSB 92% % 2% 3% 3% % 1 86% 3% 3% 3% 5% % 2 69% 13% 6% 3% 9% % 3 67% 12% 7% 3% 11% % 4 55% 11% 8% 3% 23% % Page 21 of 67

28 5 45% 1% 1% 3% 31% % 6 37% 14% 11% 3% 36% % 7 28% 17% 14% 3% 38% % 8 18% 21% 2% 2% 39% % 9 7% 25% 23% 2% 43% % 1 % 29% 23% 2% 45% % 11 % 36% 15% 2% 46% % 12 % 33% 18% 2% 46% % 13 % 29% 21% 3% 48% % 14 % 25% 24% 3% 48% % 15 % 21% 25% 3% 51% % 16 % 17% 28% 1% 52% 1% 17 % 13% 31% 1% 53% 3% 18 % 8% 31% 1% 55% 4% 19 % 3% 32% 1% 56% 7% 2 % % 33% 2% 55% 11% 4.4. Alternative Products Biofuel (BF) and Oriented Strand Board (OSB) One of the key issues to be evaluated in Phase II of this project was the economic viability and the impact of the additional value gained by alternative forest products (BF and OSB). To accomplish this, value assumptions for biofuel and OSB were added to the model. Interviews with OSB and biofuel producers were conducted in Prince George and 1 Mile House to verify and calibrate the assumptions. Once a detailed set of assumptions was generated, they were loaded into the model, adjusting the previous model to account for the additional products. Biofuel and OSB yields were included in the grade tables (shown above) by regular/pft stands and log size. BF/OSB were treated as alternative grades, generally available for harvest after the sawlog and pulp volume had decayed beyond use Selling Prices / Log Value Selling prices were assigned by end use product and species. The log selling prices were sourced from the MOFR Revenue Branch, monthly log market reports. The date range selected for this basecase was one month ending Jan 31 st, 28. These are selling prices that directly relate to those used in Phase I of this project and are representative of prices as experienced over the last several years. A scenarios testing the impacts of higher selling prices was conducted. Table 14 Log selling prices ($/m3) Species Grade Grade 4 (Sawlog) Pine Only Grade 4 (Pulp) Balsam $47.23 $47.23 $31.93 n/a n/a Cedar $137.1 $137.1 $26. n/a n/a Deciduous n/a n/a n/a n/a n/a Page 22 of 67

29 Fir $57.77 $57.77 $27.61 n/a n/a Hemlock $38.21 $38.21 $- n/a n/a Pine $47.23 $47.23 n/a $47.23 $31.93 Spruce $47.23 $47.23 $31.93 n/a n/a 4.6. Estimating Operating Costs Operating Costs were estimated using the same methodology as in Phase I. Refer to Phase I report for detailed description of methodology. Updates were made to reflect the 29 Appraisal Manual. In addition, stand level costs were compared with the Quesnel TSA average delivered wood cost by district (Table 15). For most stands, the modeled costs were found to significantly exceed the average costs calculated by the MOFR. The discrepancy is largely due to the stand level cost estimating done in this project. To address the difference, two cost reduction scenarios were completed (-15% and -25%) along with the final scenario which reflected an average cost inline with the MOFR numbers. The Final scenario, for submission to TSR IV reflects average costs that coincide with those shown in Table 15 and the costs as described by the licensees. Table 15 MOFR Publish Average Cost Estimates 4.7. Updated Road Network Haul distances and cycle times are a critical component of timber supply economic modeling. The model was originally structured to utilize a concentric circle approach (see Figure 12). However, National Choice BioFuels Industries Ltd. had completed a road network update for the TSA at their expense as part of an evaluation of biofuel opportunities in Quesnel. Page 23 of 67

30 Figure 12 Estimated hauling distance zones from Quesnel Phase I National Choice offered to provide the road coverage at no cost to the Quesnel Mitigation Committee for the operability project. A spatial network is more realistic than using a concentric circle approach. Therefore, the road network was processed, cleaned and incorporated into the data set in December 29. Hauling distances, road construction and maintenance requirements were revised and input into the model. Figure 13 Updated Road Network and Major Haul Routes Table 16 Average Hauling Distance by LU Code Landscape Unit Average Haul (km) Code abha antl baez bake bett bigv 96.5 bowo chin clis Page 24 of 67

31 cogl cunn down drag elig euch geri 57.3 hawk indi jack 78.7 klus ligh marm matt narc pann pant peli rams sand snak swif tibb toil twan 8.6 umit 23.3 vict 73.7 went whit will Determining Economic Return (Operability) Once the stand value and cost have been established, the final equation to determine economic return (or operability) is simple; (Stand Value Operating Cost = Economic Return) Economic Stratification The THLB area in the Quesnel TSA was categorized into economic return stratum. These stratum represent areas that are expected to generate an economic return. Stands in an individual stratum will react in generally the same way to a change in market conditions. Considering this, these stratum can be used to define the opportunity land base. The term, opportunity land base, refers to the group of stands that under certain economic conditions will be able to generate a positive economic return. The classification groups and a description of each are provided in Table 17. These classes Page 25 of 67

32 define the land base in terms of the market conditions under which they will generate a positive economic return. When creating harvest priority decisions, the opportunity land base can be used, in connection with expected market conditions to identify priority areas for harvest. For example, the largest percentage of the THLB occurs in the marginal loss class (4). Stands in this class will generate a positive return when market conditions improve. By targeting stands in this class when the market conditions are favorable will not only maintain sufficient harvesting opportunities in the higher return stands when market conditions are poor, but will also help to ensure that stands in this class do not degrade to the point where they are not economical under any condition. Table 17 Economic stratification - Opportunity land base classes Opportunity Land Base Class Range in per hectare return ($/ha) 1 < - 6, $ /ha Description Stands that are not expected to generate a positive return under any market condition 2-4, to - 6, $/ha Stands that may generate a marginal return under good market conditions 3-2, to -4, $ /ha 4 to - 2, $ /ha 5 to 2, $ / ha 6 2, to 4, $ / ha 7 > 4, $ /ha Stand that will generate a marginal return under good market conditions Stands that generate a marginal loss under poor market conditions. Stands that generate a marginal return under poor market conditions Stands that generate a positive return under poor market conditions Stands that will generate a positive return under all market conditions Page 26 of 67

33 5. Results The following section presents the results of this analysis. Initially a Basecase case scenario was completed that best describes current conditions within the TSA. Following that a series of scenarios were conducted, and finally a selected scenario that includes the estimates of both stand value and cost most applicable to TSR. While every attempt was made to produce accurate input estimates, the results of this model should be viewed as such, modeling results. The results are built on a series of estimates, some more accurate than others. Considering the absolute values presented will provide some insight into the economics of the Quesnel TSA, however, the most information is to be gained by comparing scenarios. Through scenario comparison the relative impact of changing variables can be tested. The main variables to be tested in this project are operating costs, stand value and the varying decay rates of MPB impacted pine stands over time, and the influence that the associated loss of merchantable pine growing stock will have on the available harvest volume. Large scale maps for each Scenario run are also included with this report as an attachment Basecase Results The Basecase (21) results indicate that the majority of the stands from Supply Blocks A, B and C in the Quesnel TSA generate a negative economic return (when applying the value at a log level). Supply Blocks D, E, F and H generate varying levels of positive and marginal return stands. As the average costs generated by the model in the basecase scenario were 44.2$ (which is approximately 25% higher than averages described by the MOFR and Licensees) the basecase will not be used as the final scenario to be submitted to the MOFR. Regardless, the basecase is a good starting point when comparing scenario results, and is the scenario most comparable to the results from Phase I. Table 18 Basecase Results - THLB Area and Merch Volume by Return Class Per Hectare Return Class THLB Area (ha) Percent of THLB Volume (m3) Percent of total volume -1, 385,11 62% 58,213,95 59% -8, 28,773 5% 4,162,438 4% -6, 33,288 5% 4,771,754 5% -4, 36,385 6% 5,138,121 5% -2, 41,93 7% 6,183,274 6% 4,489 7% 5,963,416 6% 2, 11,63 2% 2,33,923 2% 4, 7,177 1% 1,64,885 2% 6, 5,194 1% 1,268,646 1% 8, 3,792 1% 944,1 1% 1, 28,762 5% 7,993,265 8% Page 27 of 67