Quesnel TSA Timber Supply Analysis Technical Report

Transcription

1 Quesnel TSA Timber Supply Analysis Technical Report Forest Analysis and Inventory Branch Ministry of Forests and Range 727 Fisgard Street Victoria, B.C. V8W 1R8 May 21

2 Table of Contents 1. DIVISION OF THE AREA INTO MANAGEMENT ZONES... 1 ii 1.1 MANAGEMENT ZONES AND TRACKING OF MULTIPLE OBJECTIVES (GROUPING) ANALYSIS UNITS NonTHLB Problem forest types TIMBER HARVESTING LAND BASE DEFINITION DETAILS ON LAND BASE CLASSIFICATION Crown land administration for timber supply Land classified as nonforest Noncommercial cover Environmentally sensitive areas Areas considered physically inoperable Roads, trails and landings Wildlife habitat reductions Cultural heritage/archaeological resource reductions Riparian reserve zones Lower Blackwater LRUP Cariboo River management area Area inclusion factors Low site exclusions CURRENT FOREST MANAGEMENT ASSUMPTIONS HARVESTING Merchantable timber specifications Volume exclusions for mixedspecies stands Minimum harvestable criteria Silviculture systems UNSALVAGED LOSSES Shelflife of MPB impacted timber Condition of MPBimpacted young stands SILVICULTURE Regeneration activities in managed stands Immature plantation history Selection harvesting Not satisfactorily restocked (NSR) areas Nonsalvaged MPB impacted stands Objectives managed using forest cover requirements Reductions to reflect volume retention in cutblocks BASE CASE DIAGNOSTICS BASE CASE HARVEST FORECAST Scenario 1 Continue the salvage harvest of dead pine stands while maintaining the harvest of nonpine leading stands at a sustainable level Scenario 2 Minimize the harvest of nonpine volume while salvaging dead pine and then utilize the reserved nonpine volume to alleviate the harvest level decline. Additionally, alter the minimum harvest criteria to increase midterm timber supply Scenario 3 Stop salvaging dead pine immediately and start harvesting nonpine leading stands at about the 28 harvest level INVENTORY Species and age profile Resource value zonation SITE PRODUCTIVITY... 29

3 4.4 GROWTH AND YIELD Natural stand yields Managed stand yields ACCESS AND ROAD BUILDING MOUNTAIN PINE BEETLE LANDSCAPELEVEL BIODIVERSITY VISUALLY SENSITIVE AREAS iii

4 Tables TABLE 1. MANAGEMENT ZONES... 1 TABLE 2. ANALYSIS UNITS FOR EXISTING NATURAL STANDS... 2 TABLE 3. ANALYSIS UNITS FOR EXISTING MANAGED STANDS... 2 TABLE 4. TSA AREA SUMMARIZED BY OWNERSHIP AND SCHEDULE TABLE 5. TSA AREA SUMMARIZED BY OWNERSHIP AND SCHEDULE... 5 TABLE 6. TSA AREA SUMMARIZED BY FORESTED AND NONFORESTED... 6 TABLE 7. TSA AREA SUMMARIZED BY STABILITY CLASS... 6 TABLE 8. TSA AREA REMOVED BY AREA INCLUSION FACTORS... 7 TABLE 9. EXAMPLE OF SELECTION HARVEST SYSTEM YIELD CURVE TABLE 1. CALCULATION OF CURRENT GENETIC GAINS FOR EXISTING MANAGED STANDS TABLE 11. CALCULATION OF ANTICIPATED GENETIC GAINS FOR FUTURE MANAGED STANDS TABLE 12. SUMMARY OF NONFOREST DESCRIPTION IN PREVIOUS FOREST COVER INVENTORY TABLE 13. DISTURBANCE LIMITS APPLIED TO VISUALLY SENSITIVE AREAS Figures FIGURE 1. ANALYSIS UNIT THLB AREA DISTRIBUTION CLASSIFIED BY MANAGEMENT, PRODUCTIVITY AND LEADING SPECIES FIGURE 2. SENSITIVITY ANALYSIS LOWERING MINIMUM HARVESTABLE CRITERIA TO 13 CUBIC METRES PER HECTARE FIGURE 3. SENSITIVITY ANALYSIS REMOVING GENETIC GAINS FROM MANAGED STANDS FIGURE 4. SCENARIO 1 2YEAR HARVEST FORECAST WITH YEARSSINCEDEATH CLASSES FIGURE 5. SCENARIO 1 25YEAR HARVEST FORECAST FIGURE 6. SCENARIO 1 GROWING STOCK FIGURE 7. SCENARIO 1 AVERAGE HARVEST AREA FIGURE 8. SCENARIO 1 AVERAGE HARVEST AGE FIGURE 9. SCENARIO 1 HARVEST FROM NATURAL, MANAGED AND SELECTION STANDS FIGURE 1. AGE CLASS DISTRIBUTION GRAPHS FOR FIRST 2 YEARS IN FIVEYEAR STEPS FIGURE 11. AGE CLASS DISTRIBUTION GRAPHS OVER 25 YEARS IN 5YEAR STEPS FIGURE 12. SCENARIO 2 HARVEST FORECAST FIGURE 13. SCENARIO 3 HARVEST FORECAST FIGURE 14. LEADING SPECIES CLASS AREA DISTRIBUTION FIGURE 15. THLB AREA AGE CLASS DISTRIBUTION CLASSIFIED BY LEADING SPECIES FIGURE 16. BEC ZONE AREA DISTRIBUTION FIGURE 17. VISUALLY SENSITIVE AREA DISTRIBUTION CLASSIFIED BY VISUAL QUALITY CLASS FIGURE 18. MULE DEER WINTER RANGE AREA DISTRIBUTION CLASSIFIED BY STAND STRUCTURE HABITAT CLASS FIGURE 19. CARIBOU HABITAT AREA DISTRIBUTION FIGURE 2. AVERAGE SITE INDEX FOR NATURAL STAND ANALYSIS UNITS FIGURE 21. AVERAGE INVENTORY AND ADJUSTED SITE INDEX FOR PINELEADING ANALYSIS UNITS FIGURE 22. SENSITIVITY ANALYSIS USING INVENTORY SITE INDEX FOR MANAGED STANDS FIGURE 23. NATURAL STAND YIELD CURVES FOR MAJOR ANALYSIS UNITS FIGURE 24. SENSITIVITY ANALYSIS DECREASING NATURAL STAND YIELDS BY 1% FIGURE 25. MANAGED STAND YIELD CURVES FOR MAJOR ANALYSIS UNITS FIGURE 26. SENSITIVITY ANALYSIS DECREASING MANAGED STAND YIELDS BY 1% FIGURE 27. BASE CASE HARVEST CONTRIBUTION BY REGION WITHIN TSA FIGURE 28. SENSITIVITY ANALYSIS LIMITING HARVEST TO LANDSCAPE UNITS WITHIN A SIXHOUR CYCLE TIME FIGURE 29. SENSITIVITY ANALYSIS ASSUMING PINE FALLS OVER AFTER 15 YEARS FIGURE 3. SENSITIVITY ANALYSIS ABANDONING PINE SALVAGE AFTER FIVE YEARS FIGURE 31. SENSITIVITY ANALYSIS REMOVING SERAL CONSTRAINTS iv

5 1. Division of the Area into Management Zones 1.1 Management zones and tracking of multiple objectives (grouping) The land base was split into pineleading and nonpine leading management zones. Harvest targets were set separately for each management zone. The pineleading zone was defined as all stands with VRI species 1 code starting with P within the forest management land base (FMLB). Nonpine leading was defined as all other stands within the FMLB. Table 1. Management zones Management zone THLB (ha) FMLB (ha) Pineleading Nonpine leading Total The pineleading zone is larger than the sum of the pineleading analysis units (79 and 2729) because it also includes pineleading stands that were assigned to mule deer winter range and caribou analysis units. The nonthlb (AU 99) was also assigned to management zones for tracking purposes even though it does not contribute to harvest targets. Other management zones were created for the application of seral distribution, disturbance limits, wildlife habitat and visual constraints. These will be discussed in later sections for each constraint. 1.2 Analysis units Analysis units were assigned using the first letter of the VRI species 1 code. Stands within the FMLB that were missing leading species information were assigned a species based on the dominant species of the BEC zone. There were no cedar, hemlock or maple leading stands within the timber harvesting land base (THLB). Mule deer and caribou habitat mapping was used to assign stands to mule deer and caribou analysis units that were modelled with special silviculture and management regimes. Each species group was divided into productivity classes using site index. The class split points were set by evaluating a frequency distribution of site index values for each species group and roughly splitting the population into evenly distributed classes. The analysis unit series 1 17 represent natural stands and the series represent managed stands (age 47 or younger). When stands are harvested in the model they were regenerated to series as future managed stands. All caribou and mule deer analysis units were modelled as selection harvesting (except for mule deer clearcut) that regenerate as natural stands. 1

6 Table 2. Analysis units for existing natural stands AU Species Site index FMLB (ha) THLB (ha) 1 Fir/Larch <16 7,3 6,537 2 Fir/Larch ,67 8,943 3 Fir/Larch >19 5,222 4,749 4 Spruce/Balsam <11 3,171 27,127 5 Spruce/Balsam ,343 44,885 6 Spruce/Balsam >17 15,41 14,5 7 Pine <12 151,698 14,236 8 Pine , ,473 9 Pine >16 92,586 86,953 1 Deciduous <18 28,84 26, Deciduous >=18 14,62 13, Mule Deer Low All 1,322 1,22 13 Mule Deer Moderate All 2,59 2, Mule Deer High All 7,514 6, Mule Deer Clearcut All 1,725 1, Caribou Northern All 64,781 6,89 17 Caribou Mountain All 2,381 18,937 Table 3. Analysis units for existing managed stands AU Species Site index FMLB (ha) THLB (ha) 21 Fir/Larch <16 3,263 3, Fir/Larch ,795 5, Fir/Larch >19 1,584 1, Spruce/Balsam <11 11,98 11,48 25 Spruce/Balsam ,671 31,9 26 Spruce/Balsam >17 2,576 19, Pine <12 25,2 23, Pine ,415 17, Pine >16 14,766 99,97 3 Deciduous <18 5,438 5, Deciduous >=18 9,23 8, Mule Deer Clearcut All The total THLB area in all analysis units is summarized by management status, productivity grouping and leading species in Figure 1. 2

7 THLB Area (ha) 35, 3, 25, 2, 15, 1, 5, Decid Fd / Lw Sx / Ba Pl Natural Poor Natural Medium Natural Good Managed Poor Managed Managed Medium Good Leading Species Class MDWR Caribou Figure 1. Analysis unit THLB area distribution classified by management, productivity and leading species NonTHLB All nonthlb area ( hectares) was assigned to AU 99. It is assumed that growth equals mortality and disturbance in the nonthlb so the model does not age the nonthlb. This maintains the original natural range of variation in age throughout the modelled time horizon. The nonthlb is not harvested but does contribute to seral stage and disturbance objectives. In order to calculate height based disturbance objectives, one height curve was generated for this AU by fitting a transformed linear regression of inventory stand height against inventory stand age Problem forest types Problem forest types were not identified in this analysis. Therefore, no analysis unit was created for these stands as occurred in previous analyses. The data package specifies a definition and a harvest limit on problem forest types. However, data on piece size specified in the definition was not available and the area between the Nazko River and the Fraser River to which the constraint was to be applied was not spatially defined. District staff decided it was no longer necessary to model this constraint. 3

8 2. Timber Harvesting Land Base Definition 2.1 Details on land base classification The Quesnel TSA land base was classified through a netdown process documented in the following table. Each reduction is discussed in detail in the following sections. Table 4. TSA area summarized by ownership and schedule. Crown / FMLB Removed Total TSA Crown Managed TFL Woodlots NonForest FMLB (Productive) Protected Areas Caribou NoHarvest OGMA NonStable Excluded Species Low Site Index Riparian Reserves Riparian Management ESA Existing Roads Current THLB Future Roads Future THLB Crown land administration for timber supply The administrative boundaries were defined by the ownership and schedule attributes in the VRI that were updated in 29 by the MFR VRI data management section. The gross area within the boundaries of the TSA is hectares. It was assumed that parks within the TSA contribute to all management objectives so area outside crown forest management land and miscellaneous reserves (62C and 69C respectively, totalling hectares) is initially included in the netdown. The parks are removed from the THLB at a subsequent netdown step. 4

9 Table 5. TSA area summarized by ownership and schedule Ownership Schedule THLB (ha) FMLB (ha) Crown and Parks (ha) Gross (ha) 6 N N N 81 4 N N C N N C C B N N 61 Total The crown forest management land and park area together, totaling hectares, approximates the total TSA area of hectares reported in the previous analysis. A portion of TFL 52 and some woodlots fell within the area classified as crown forest management land area. Therefore, hectares of TFL 52 (totalling hectares) was removed in the next step of the netdown. This was followed by the removal of 7317 hectares of woodlots (totalling hectares) Land classified as nonforest The data package specifies that nonforested land be identified using the inventory attribute Type Identity Code. This attribute no longer exists in the current VRI. Nonforested land was identified using the BC Land Classification System (BCLCS) attributes within the VRI. Satellite imagery and RESULTS harvest records were used to ensure recently harvested areas classified as nonforest under the BCLCS were not removed from the THLB. In total, hectares of nonforest area was removed. The remaining area of hectares is referred to as the forest management land base. This is the land base modelled in the timber supply analysis. 5

10 Table 6. TSA area summarized by forested and nonforested Classification THLB (ha) FMLB (ha) Crown (ha) Gross (ha) Forested NonForest Logged NonForest Total Once the FMLB was identified, all areas where harvesting is restricted were removed as the first steps of the THLB netdown. Parks and other protected areas that were included in the FMLB to contribute to management objectives were removed (18 66 hectares). Caribou habitat areas where harvesting is restricted were removed next ( hectares). Finally permanent OGMA were removed (7 459 hectares). Transition and rotating OGMA were not removed because they may be harvested at some point in the future. It was assumed that they would be represented in the model as part of the area reserved to meet the aspatial seralstage constraints (discussed in Section ) Noncommercial cover The data package specifies that land covered by noncommercial species be identified using the inventory attribute Type Identity Code. As discussed in the previous section, this attribute no longer exists in the VRI. It was assumed that this netdown step is now redundant with the area inclusion factor netdown that similarly removes area based on species composition Environmentally sensitive areas Environmentally sensitive areas (ESA) were removed as documented in the data package. ESA were the second partial netdown (i.e. percentage reduction removing less than one hectare), following riparian and preceding roads. The total area removed for ESA was hectares Areas considered physically inoperable Physically inoperable areas were removed as documented in the data package. Terrain stability mapping only covered a small portion of the TSA (7.7% of the FMLB). The area within stability classes 4 and 5 was hectares. The area removed, following prior netdowns, was hectares. Table 7. TSA area summarized by stability class Stability class THLB (ha) FMLB (ha) Crown (ha) Gross (ha) Total

11 2.1.6 Roads, trails and landings The reductions for roads, trails and landings were removed as documented in the data package. The partial netdown for existing roads was the last reduction applied removing hectares. The reduction factor for future roads was applied within the timber supply model removing area at the time of first harvest. A total of 9657 hectares was be removed from the current THLB by the model resulting in a future THLB of hectares Wildlife habitat reductions All objectives described in this section of the data package were modelled either through growth and yield inputs or biodiversity constraints. No netdown reductions were made for this section Cultural heritage/archaeological resource reductions The data package did not specify any netdown reductions or modelling inputs for this section Riparian reserve zones Reductions for riparian reserve zones were combined with reductions applied to model riparian management zones. The area of riparian reserve zone and riparian management zone overlapping each hectare was calculated for all lakes, water courses and wetlands within the TSA. The area of overlap in riparian reserve zone was removed through a partial netdown. A total of hectares was removed. Only a portion of the area of overlap in riparian management zones was removed in order to model partial retention management within these zones. The process of calculating the area of overlap summed all riparian management zones regardless of lake, stream, or wetland class. Therefore, it was not possible to model the varying levels of partial retention specified by class under the FRPA. An average of 15% basal area retention was assumed for all riparian management zone classes. Following this assumption, 15% of the area of overlap within riparian management zones was removed through a partial netdown. A total of hectares was removed Lower Blackwater LRUP The data package did not specify any netdown reductions or modelling inputs for this section Cariboo River management area The data package did not specify any netdown reductions or modelling inputs for this section Area inclusion factors The inventory attribute Inventory Type Group no longer exists in the current VRI. In order to remove areas covered by nonmerchantable species, the species groupings previously represented by Inventory Type Group were approximated using the first character of the species 1 attribute in the VRI. For example, all stands with leading species codes starting with H or C were grouped to represent Inventory Type Group 9 17 (Cedar/hemlock leading). The following table shows the approximations used and the area removed. Table 8. TSA area removed by area inclusion factors Leading species codes Inventory type group approximated FMLB (ha) C or H 917 (Cedar/hemlock leading) B (and not 'S' as species 2) 1819 (Balsamleading) 5227 P (and 'A', 'D', 'E' as species 2) 31 (Lodgepole pinedeciduous) D 3739 (Deciduous/coniferous and maple) 54 Total

12 Balsam and spruce mixed stands (ITG 2) are included in the THLB, so only balsam stands where spruce was not the secondary species were removed. Residual type stands (ITG 131 multilayered stands resulting from nonclearcut logging or natural events such as fire) could not be identified using this approximation. Also, there were no Ponderosa pine leading or larch leading stands (ITG 3233) in the VRI to remove. All area inclusion factors listed in the data package were either zero or 1% so no partial reductions were required. On review of the analysis, district staff believe that lodgepole pinedeciduous stands are currently being harvested and should not be removed from the THLB. A sensitivity analysis was run to explore the effect on timber supply of including lodgepole pinedeciduous stands. Without the hectares of lodgepole pinedeciduous stands the area inclusion factor only accounted for hectares of FMLB. The area removed for this factors was therefore reduced from hectares to 5475 hectares which increased the THLB from hectares to hectares (a difference of hectares or eight percent). Including this area resulted in an initial increase of 8.5 million cubic metres in pineleading growing stock of which 5.1 million cubic metres was already killed by the mountain pine beetle. The sensitivity analysis forecast that an additional 4.3 million cubic metres of pineleading stands could be salvaged compared to the base case. However, by the time this volume is salvaged the stands are more than 15 years dead. A consequence of including the lodgepole pinedeciduous stands was that the timber supply contribution from nonpine leading stands decreased by 1 cubic metres per year across the entire forecast. This decrease diminishes the small gain of 6 cubic metres per year provided in the midterm by the lodgepole pinedeciduous stands. However, in the long term, these stands provide an additional 21 cubic metres per year which is directly proportion to the THLB area increase of eight percent. On review of the analysis, district staff believe that lodgepole pinedeciduous stands are currently being harvested and should not be removed from the THLB. A sensitivity analysis was run to explore the effect on timber supply of including lodgepole pinedeciduous stands. Without the hectares of lodgepole pinedeciduous stands the area inclusion factor only accounted for hectares of FMLB. The area removed for this factors was therefore reduced from hectares to 5475 hectares which increased the THLB from hectares to hectares (a difference of hectares or eight percent). Including this area resulted in an initial increase of 8.5 million cubic metres in pineleading growing stock of which 5.1 million cubic metres was already killed by the mountain pine beetle. The sensitivity analysis forecast that an additional 4.3 million cubic metres of pineleading stands could be salvaged compared to the base case. However, by the time this volume is salvaged the stands are more than 15 years dead. A consequence of including the lodgepole pinedeciduous stands was that the timber supply contribution from nonpine leading stands decreased by 1 cubic metres per year across the entire forecast. This decrease diminishes the small gain of 6 cubic metres per year provided in the midterm by the lodgepole pinedeciduous stands. However, in the long term, these stands provide an additional 21 cubic metres per year which is directly proportion to the THLB area increase of eight percent Low site exclusions The reductions for low productivity sites were removed as documented in the data package. A total of hectares had a site index below the minimum limits. However, only hectares were removed as the remainder had been removed by previous netdown reductions. 8

13 3 Current Forest Management Assumptions 3.1 Harvesting Merchantable timber specifications The merchantability criteria for sawlogs were used as specified in the data package when generating yield curves for the analysis. Since PFT were not identified in the analysis, the merchantability criteria listed for PFT could not be applied Volume exclusions for mixedspecies stands Exclusions for mixedstands were applied as specified in the data package when generating natural stand yield curves Minimum harvestable criteria The timber supply model was able to model the minimum volume per hectare criteria specified in the data package directly eliminating the need to convert it to an equivalent age for each analysis unit. Since PFT were not identified, it was not necessary to model minimum harvest volume criteria specifically for these stands. A sensitivity analysis was run to investigate the effect on timber supply of increasing and decreasing the minimum harvestable volume criteria. Recent harvesting records from January 1, 22 to September 22, 29 were queried to look for trends in current harvest practices. The average harvest volume per hectare over this time was 235 cubic metres per hectare. The lower limit at the 1. percentile of the data distribution was 13 cubic metres per hectare. The minimum harvest criteria of 12 cubic metres per hectare assumed in the data package closely approximates the lower limit at the 2.5 percentile of the distribution. Figure 2 shows the results of the first sensitivity analysis that lowered the minimum harvest limit to 13 cubic metres per hectare. 6,, Dead Pine 5,, Live Pine NonPine Harvest Volume (m3/yr) 4,, 3,, 2,, 1,, Year Figure 2. Sensitivity analysis lowering minimum harvestable criteria to 13 cubic metres per hectare. When the minimum harvest criteria was reduced to the lowest limit seen in recent harvesting it was possible to increase the shortterm and midterm harvest level by 1%. However, with the reduced harvest criteria it was not possible to sustain the increased harvest level in the long term. A followup sensitivity found that the base case longterm harvest level could not be sustained under the reduced 9

14 criteria. Allowing the model to harvest stands at 13 cubic metres per hectare resulted in lost growth potential in managed stands as stands were harvested well below culmination Silviculture systems Mule Deer Winter Range The management practices specified for Mule Deer Winter Range (MDWR) in Tables 11a and 11b in the data package provided operation level details that could not be modelled. However, the cutting cycles described in table 11b(i) were used to create yield curves representing unevenaged selection harvesting. Four analysis units were created from the MDWR mapping. Three analysis units represented the low, moderate and high stand structure habitat classes while the fourth analysis unit represented MDWR where clearcutting was permitted. Selection yield curves for low, moderate and high analysis units were built starting with natural stand yield curves generated just as they were for other analysis units. The new selection curve was assigned a volume proportional to the area harvested per pass for each analysis unit (i.e. low: 33%, moderate: 25%, high: 2%) to represent the volume harvested at each pass. All ages below the effective rotation were set to zero yield since the volume at the rotation age (reduced by the proportion taken at each pass) is the minimum volume available at each entry. The data package specifies that selection harvest stands should contribute to biodiversity objectives at all times. The highest age in the seralstage constraints is 12 years and all three analysis units assume a minimum cutting cycle of 4 years. Therefore, the reduced volume at rotation age was shifted to 16 years on all three yield curves and the regeneration delay was set to 12 years (i.e. when stands are harvested they are regenerated as 12 years old). The minimum harvest volume criteria was set for each analysis unit to equal the reduced volume at rotation age. The result was yield curves that allow a harvest proportional to the number of passes every 4 years while always being greater than 12 years age. 1

15 Table 9. Age Example of selection harvest system yield curve. Natural Yield Selection Yield Regenerates to age % 13 harvested each pass * minimum harvest volume = 96 m 3 The data package specified a delay in the first entry to MDWR stands based on the risk that crown closure requirements would not be met. Data on this risk level was not available and a specific delay in first harvest would have been difficult to model. A consequence of the methodology used to model the selection harvesting is that all stands less than 16 years old are not harvestable. Therefore, the delayed first entry is approximated in the modelling as the selection harvesting cycle cannot begin until immature stands reach 16 years of age at which point the risk of not meeting crown closure requirements is minimal Caribou habitat Two analysis units were created for areas within caribou habitat. The first was habitat for Itcha Ilgachuz caribou providing terrestrial lichen. The second was habitat for Itcha Ilgachuz and Eastern caribou providing arboreal lichen. Spatial data was not available to discern terrestrial lichen sites from arboreal lichen sites. Following the 8% / 2% distribution described in the data package, 8% of the Itcha Ilgachuz caribou habitat was randomly assigned to the first analysis unit and the remainder to the second analysis unit. All Eastern caribou habitat was assigned to the second, arboreal lichen, analysis unit. The same methodology used to produce selection harvest yield curves for MDWR was used to produce yield curves for the caribou analysis units. This included the regeneration to age 12 years in order to contribute to biodiversity. As specified in the data package, the Itcha Ilgachuz terrestrial lichen analysis unit was modelled with a 14 year rotation cycle with 7 years between entries. The Itcha Ilgachuz 11

16 arboreal lichen and Eastern analysis unit was modelled with a 24 year rotation cycle with 8 years between entries. The data package also specified that no more than onethird of the caribou habitat can be harvested at each period. This ensures that the partial harvest entries within the caribou habitat are distributed over time. A disturbance constraint of a maximum of 33% below 14 years was set for both caribou analysis units. Since the regeneration age is 12 years, this constraint ensured that no more than 33% of the caribou habitat could be harvested within the first 2 years of the cutting cycle. 3.2 Unsalvaged losses Timber supply reductions to account for unsalvaged losses were applied as documented in the data package. It was necessary to allot a portion of the unsalvaged losses to each management zone in the timber supply model. The total reduction of 48 m³/year was split proportional to the THLB area in each zone. A reduction of m³/year (3%) was applied to the nonpine leading zone and m³/year (7%) was applied to the pineleading zone Shelflife of MPB impacted timber The data package outlines default assumptions about the shelflife of MPB impacted timber for sawlogs to be used in the analysis. However, the analysis was run without assumptions about the potential end use of the dead pine and each product s associated shelflife. Instead, it was assumed that the dead trees will have some commercial use (e.g., sawlogs, chips, bioenergy) as long as the trees are standing. Presenting the information in this way makes it possible to solicit people s opinions and knowledge regarding shelflife for various commercial products at any time in the future and accordingly interpret the timber supply projections without the requirement to rerun the timber supply model. The data package also states that all dead stands that remain unsalvaged after 15 years will be assumed to fall over and regenerate with a fiveyear regeneration delay. During the model preparation, the fall over age was extended to 2 years in order to demonstrate the volume available for other potential biomass products Condition of MPBimpacted young stands Currently, nothing has been modelled relating to the information provided in this section of the data package. The BCMPB model data assumes that stands younger than 6 years will not be killed. The studies cited in this section provide evidence this assumption is not appropriate for the Quesnel TSA. Since the lowest age mortality assumption is built into the data, it was not possible to run sensitivity analysis on this issue. 3.3 Silviculture Regeneration activities in managed stands The managed stand yield curves were generated using the input assumptions as outlined in the data package. Some exceptions were noted during this process. First, the PFT yield curve was not produced since no analysis unit was created for these stands. Second, the mule deer selection analysis unit was modelled using only one natural stand yield curve (see section ). It was assumed that understory regeneration will be shaded by the retained overstory and will therefore grow at approximately natural stand growth rates. Finally, TIPSY would not accept coniferous species as the secondary species in deciduous leading stands. These stands were modelled as pure deciduous Genetic gains Data on recent genetically improved seed use and associated genetic gains between 22 and 29 were provided by Tree Improvement Branch staff for seed zones within the Quesnel TSA. The gains were 12

17 weighted by the seed use for each species by year. The weighted gains for each year were then averaged to produce a gain for each species. However, since these gains were applied to the existing managed stands, which represent stands harvested over the last 47 years, the eight years of genetic gains were averaged to include 39 years of planting with no genetic gains (i.e. the sum of the genetic gains between 22 and 29 divided by 47 years). Table 1. Calculation of current genetic gains for existing managed stands Year Percent of requested seeding with select seed Estimated genetic worth for SPU in Quesnel Average genetic worth modelled FDI PLI SX FDI PLI SX FDI PLI SX 22.% 58.5% 95.5%.% 3.% 17.%.% 1.8% 16.2% 23.% 78.5% 98.2%.% 3.% 15.%.% 2.4% 14.7% 24.% 53.9% 99.5%.% 3.% 17.%.% 1.6% 16.9% % 49.6% 1.% 11.% 4.% 17.%.6% 2.% 17.% % 31.5% 9.9% 15.% 4.% 2.% 3.3% 1.3% 18.2% % 48.9% 91.9% 2.% 5.% 18.% 4.6% 2.4% 16.5% 28 5.% 46.5% 88.% 14.% 3.% 16.%.7% 1.4% 14.1% % 54.9% 93.5% 14.% 4.% 14.% 4.8% 2.2% 13.1% 47year average.3%.3% 2.7% Forecasts of the increases in future genetic gains were provided by MFR Tree Improvement Branch staff. Information on the anticipated production and demand for improved seed was also provided. The genetic gain 1 years in the future was selected to be applied to future managed stand yield curves. This may overestimate the regeneration yields for stands harvested in the first 1 years of the forecast. However, this is countered by the fact that all additional gains made over the following 24 years are foregone. The production relative to the demand was used to weight the future genetic gains. However, the forecast gains were provided by seed planning unit (SPU) so the gains had to be weighted by the proportion of each SPU within the Quesnel TSA to provide TSA averages. The elevation zones of the SPU were not considered in the weighting. Table 11. Calculation of anticipated genetic gains for future managed stands Seed planning unit Seedling need (millions) Production forecast (millions) Estimated gain Production weighted gain Proportion of SPU in TSA 41 FDI PG % 15.8% 31% 37 FDI QL % 28.% 5% 43 FDI CT % 16.% 64% 12 PLI PG % 9.3% 91% 17 PLI BV % 13.% 7% 14 SX PG % 21.4% 1% 28 SX TO % 15.% % 3 SX TO % 19.% % Applied gain 16.5% 9.4% 21.4% 13

18 A sensitivity analysis explored the impact on timber supply of removing the genetic gains applied to managed stands. Figure 3 shows a growing shortfall in timber supply in the very long term. This shortfall affects both the pine and nonpine contributions equally. 6,, Dead Pine Harvest Volume (m3/yr) 5,, 4,, 3,, 2,, Live Pine NonPine 1,, Year Figure 3. Sensitivity analysis removing genetic gains from managed stands Immature plantation history The data package defines all stands established prior to 1959 as unmanaged natural stands. It also specifies that only 75% of stands aged 41 5 years are managed. To simplify the process of assigning these stands to either managed or unmanaged analysis units, a cut off age of 47 years (approximately 75% of the 41 5 age class) was used to define managed stands Selection harvesting This section of the data package confirms that using natural stands yield curves is appropriate for modelling stands managed using a selection system Not satisfactorily restocked (NSR) areas NSR areas were not directly modelled in the analysis. The data package specifies that all backlog NSR will be restocked or reclassified within five years and current NSR is addressed within the modelled regeneration delay. As specified in the data package, all stands with missing leading species information (regardless if it was identified as NSR or not) were assigned to analysis units based on the BEC zone. The area classified as NSR was identified using the nonforest description attribute carried over from the old forest cover inventory into the VRI. This attribute is no longer updated in the VRI. The table below summarizing the land base by nonforest description is provided for information purposes only. Table 12. Summary of nonforest description in previous forest cover inventory Nonforest description THLB (ha) FMLB (ha) NC 4 4 NSR NCBR

19 3.3.5 Nonsalvaged MPB impacted stands No information regarding secondary stand structure in the Quesnel TSA was included in the analysis. A pine understory sampling study was completed by MFR Southern Interior Region in 29. The study investigated how implementation of the new secondary structure amendments under the Forest Planning and Practices Regulation (FPPR) affects forest management. The study drafted new understory sampling procedures and provided an estimate of the area that qualifies for retention under the secondary structure amendments. This information is useful at the operational level but could not incorporated in the strategic level timber supply analysis. As noted in the Section, a five year regeneration delay was applied to unsalvaged stands that fall over after 2 years (a total loss of 25 years) Objectives managed using forest cover requirements Greenup The timber supply model used for the analysis was run in a spatial simulation mode. However, spatial greenup adjacency limits were not modelled in the spatial mode because under current practice salvage harvesting is not restricted by cutblock adjacency. After 3 years when salvage is completed, a disturbance constraint (a maximum of 35% of the THLB less than 3m in height) was applied as a surrogate for spatial greenup adjacency (also known as a multipleuse or IRM constraint) for the remainder of the harvest forecast. This constraint was not applied to scenic areas which had more stringent disturbance constraints. As stated in the data package, conservation legacy areas (CLA) were modelled to compensate for the removal of this constraint during salvage (see section ). After 3 years when salvage is complete the CLA were no longer modelled Visuals The data package did not specify the exact disturbance limit for scenic areas so these limits had to be calculated using the 23 Bulletin Modelling Visuals in TSR III. In this guide, the disturbance limit for each visual quality class (VQC) varies by visual absorption capacity (VAC). To assign a disturbance limit for each VQC, the VAC area within each VQC was used to calculate an area weighted average limit. Table 13. Disturbance limits applied to visually sensitive areas VQC Range of disturbance limits Area weighted average limit P 1..5 R PR M Initially, the model was set up to meet the disturbance limits across all visual polygons having the same visual quality objective (VQO) within each landscape unit. After discussions with district and analysis staff, it was decided that the limits should be met within each visual polygon as this best reflects how visual areas are managed operationally. Since many of the visual polygons were missing a VAC classification, the areaweighted average limit was still applied to individual visual polygons by VQO Caribou The disturbance limits for caribou were modelled as discussed in the caribou habitat section (). The greenup height was set to use an age threshold instead of height in metres. The maximum was set at 14 15

20 years to reflect that selection caribou stands regenerate to 12 years so they always contribute to biodiversity. This constraint ensures that no more than 33% of the caribou habitat can be harvested every 2 years Landscapelevel biodiversity Seralstage distribution constraints were modelled as specified in the CCLUP. As mentioned in the netdown section, it was assumed that transition and rotating OGMA would be represented within the area reserved for seralstage constraints. The data package discusses the provision made by the land use plan allowing the salvage of beetlekilled wood that violates the seralstage constraint in trade for recruitment of younger nonpine stands. This tradeoff was assumed to be an operational level issue beyond the scope of the analysis. An investigation carried out for ILMB found that seralstage constraints never limit the salvage of beetlekilled pine. The dead pine falls over well before enough pine can be salvaged to violate the seralstage constraints. After the pine has fallen over, timber supply is simply limited by the severe growing stock shortage. Removing seralstage constraints minutely increased the midterm timber supply. When the vast area of regenerating beetlekilled pine stands reach maturity the seralstage constraints are immediately met again Reductions to reflect volume retention in cutblocks Reductions for wildlife tree patches (WTP) were modelled as specified in the data package. It was assumed that half of the 7% reduction would be met by adjacent areas reserved for other management objectives. Therefore, a 3.5% yield reduction was applied within the model at the time of harvest to represent WTP. The data package also discusses the Quesnel Forest District Conservation Strategy (26) that specifies enhanced retention through CLA during salvage of beetlekilled pine. An update note (#12) to the CCLUP notes that all of the CLA must be located within the harvest block. Therefore, it was not possible to attribute a portion of this reduction to adjacent reserve areas. The CLA were modelled by temporarily removing 13% of the THLB from every hectare of the pineleading management zone for 3 years. After 3 years when salvage is completed, the THLB area is increased to the original area for the remainder of the forecast. 16

21 4 Base case diagnostics Three scenarios were run and provided as the base case. This approach was used because of the large amount of uncertainty in future harvest performance. All three scenarios are based on the exact same set of management assumptions, with one exception, as documented in the data package and this document. The input variable adjusted between scenarios was the harvest targets. Scenario1 provides a middleground reasonable forecast where pine salvage continues while nonpine stands are harvested at a sustainable nondeclining level. Scenario 2 provides an upper bound representing an idealized situation where nonpine stands are initially avoided, salvage continues for another 1 years, and future economics support a lower minimum volume limit for regenerated pine stands (deviating from the base case management assumptions). Scenario 3 provides a lower bound representing the consequences if pine salvage is abandoned and harvesting continues at the current harvest rate entirely in nonpine leading stands. The base case diagnostics will focus on scenario 1 since the other two scenarios represent extremes and their diagnostics will provide little insight into the growth dynamics of the Quesnel TSA. 4.1 Base case harvest forecast Scenario 1 Continue the salvage harvest of dead pine stands while maintaining the harvest of nonpine leading stands at a sustainable level In scenario 1, the initial harvest level is set at 5.28 million cubic metres per year, which is the same as the current AAC. The contribution from nonpine leading stands is 6 cubic metres per year and remains constant over the entire forecast. After the first 14 years of this harvest scenario, almost all of the pineleading stands were assumed to have either been salvaged or have fallen over and no longer be merchantable. For the next 46 years, a harvest level of 72 cubic metres per year can be maintained, comprised of 6 cubic metres per year from the nonpine leading stands and 12 cubic metres per year from pineleading stands that survived the mountain pine beetle attack. 6,, Harvest Volume (m3/yr) 5,, 4,, 3,, 2,, 15+ YSD 1115 YSD 61 YSD 35 YSD 2 YSD Live Pine NonPine 1,, Year Figure 4. Scenario 1 2year harvest forecast with yearssincedeath classes. In the Public Discussion Paper, the volume of pine classified as live by the BCMPB model was not reported as in Figure 4 for two reasons. First, district staff felt that this live pine does not exist and is an overestimation made by the BCMPB model. Second, the majority of the live pine is a residual component of partially attacked stands that can only be harvested if the entire dead stand is also 17

22 harvested. To avoid the possible misinterpretation that approximately 2. million cubic metres of live volume could be harvested while leaving 3. million cubic metres of dead pine unsalvaged, the live pine volume was proportionately allotted into the yearssincedeath classes with the dead pine volume. Starting in 29 the nonpine harvest is approximately 1.47 million cubic metres per year or 28 percent of the total harvest. This proportion of nonpine volume contribution is much higher than the actual nonpine volume contribution harvested between 24 and 28, which has averaged 55 cubic metres per year. For the first three years of the forecast, approximately 9 cubic metres of nonpine volume is incidental harvest from within salvaged pineleading stands. This incidental harvest volume then decreases over time because in the modelling, a harvest rule was applied that selects highest volume stands first. Since mature stands with mixed species generally have higher yields than mature pure pine stands, the model prioritizes the harvest of the pineleading stands that contain a subcomponent of nonpine species, then directs harvest to the mature pure pine stands. Figure 5 shows that the regenerating pineleading stands are forecast to become harvestable 6 years from now and are projected to contribute 1.92 million cubic metres per year to the total harvest level of 2.52 million cubic metres per year for the remainder of the forecasted time period. 6,, Dead Pine 5,, Live Pine NonPine Harvest Volume (m3/yr) 4,, 3,, 2,, 1,, Year Figure 5. Scenario 1 25year harvest forecast. At 269, a much higher harvest level could be supported because of the large volume of pine that has regenerated from the beetlekilled salvaged stands. This is seen as a large peak in the merchantable growing stock in Figure 6. However, increasing the harvest level for 1 years starting in 269 resulted in a lower longterm harvest level and caused another peak in the growing stock in the very long term. Due to the great uncertainty in the long term, one flatline harvest level was used. The result of this decision is seen in Figure 6 as a large volume of standing growing stock that decreases slowly over time. 18

23 Growing Stock (millions m3) Dead Merchantable Merchantable NonMerchantable 2. Figure 6. Scenario 1 growing stock. Year At the start of the timber supply forecast there are 7.5 million cubic metres of beetlekilled pine to be salvaged. There are also 32.6 million cubic metres of live volume from species other than pine and pine that is forecast to survive according to the BCMPB model. The live merchantable growing stock reaches its lowest point at 13.9 million cubic metres in 219. At this point 27.4 million cubic metres of dead pine salvage remains. For the next 3 years, the merchantable growing stock maintains between 2 and 25 million cubic metres. Throughout this time, the volume of regenerating pine from beetlekilled stands is growing and can be seen as the nonmerchantable growing stock in Figure 6. By 269, the regenerating pine reaches maturity resulting in a spike in merchantable growing stock. In order to support the continuing salvage of beetlekilled pine, the model forecasts that between 2 and 3 hectares must be cut each year. Figure 7 shows that when salvage is complete the annual harvest area decreases to between 3 and 4 hectares per year. When the regenerated pine becomes available again in 269, the longterm annual harvest area averages 12 hectares per year. 19

24 35, 3, 25, Area (ha) 2, 15, 1, 5, Years Figure 7. Scenario 1 average harvest area. As previously discussed, the harvest priority rule was set to harvest highest volume stands first. Therefore, the average harvest area increases during the first 14 years as it requires a larger area of lower volume stands to achieve the same salvage harvest level each year. The average harvest age fluctuates widely as salvage of dead pine progresses. Figure 8 shows that the average harvest age initially fluctuates between 12 and 14 years. When salvage is completed after 14 years the average harvest age jumps to 175 years as harvesting is almost entirely in older nonpine stands Harvest Age (yrs) Year Figure 8. Scenario 1 average harvest age. The average harvest age decreases rapidly after 2 years as the older natural stands are depleted and harvesting transitions to managed stands. The average harvest age starts to increase again from 6 to 12 years in the future as the regenerated beetlekilled pine is harvested. Since such a large cohort of 2

25 regenerated pine becomes available all at once it requires several decades to harvest the entire cohort. The remainder of the cohort that is not harvested each decade continues to age resulting in a higher average harvest age in the following decade. The transition from the harvest of natural stands to managed stands is shown is Figure 9. 6,, Harvest Volume (m3) 5,, 4,, 3,, 2,, Selection Natural Existing Managed Future Managed 1,, Figure 9. Scenario 1 harvest from natural, managed and selection stands. Year Stands modelled as managed under a selection harvest system contribute an average of 11 cubic metres per year. Since these stands yield a small volume at each pass, they are effectively given a low harvest priority under the highest volume first harvest priority rule. However, in 219, cubic metres are harvested from selection stands in one year as the model reaches the very lowest priority stands while attempting to salvage the last of the dead pine. The effect of the dead pine salvage on the age class distribution over the first 2 years is shown in Figure 1. There is a dramatic accumulation of THLB area in the youngest age class. By 219, the area of THLB in age classes older than 6 is less than the nonthlb area. As discussed previously, the nonthlb is not aged within the timber supply model so the original natural range of age variation is maintained. In 229 half of the accumulated beetlekilled regenerating pine moves into the next age class. 21