IMPLICATIONS OF ALTERNATIVE HERBICIDE-USE POLICIES FOR FOREST MANAGEMENT IN ONTARIO by Gordon J. Whitmore A Graduate Thesis Submitted In Partial Fulfilment of the Requirements for the Degree of Master of Science in Forestry School of Forestry Lakehead University May, 1995 ProQuest Number; 10611919 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. Pro ProQuest 10611919 Published by ProQuest LLC (2017). Copyright of the Dissertation is held by the Author. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code Microform Edition ® ProQuest LLC. ProQuest LLC. 789 East Eisenhower Parkway P.Q. Box 1346 Ann Arbor, Ml 48106 - 1346 .LIBRARY RIGHTS STATEMENT In presenting this thesis in partial fulfilment of the requirements for the M.Sc.F. degree at Lakehead University at Thunder Bay, I agree that the University shall make it freely available for inspection. This University Thesis is made available by my authority solely for the purpose of advancing the practice of professional and scientific forestry and may not be copied or reproduced in whole or in part (except as permitted by the Copyright Laws) without my written authority. Signature: Date: A CAUTION TO THE READER This M.Sc.F. thesis has been through a semi-formal process of review and comment by at least two faculty members. The reader should realize that opinions expressed in this document are opinions and conclusions of the author and do not necessarily reflect the opinions of either the supervisor, the faculty or the University. ABSTRACT Whitmore, G.J. 1994. Implications of alternative herbicide-use policies for forest management in Ontario. School of Forestry, Lakehead University, Thunder Bay, Ontario. 289 pp. Advisor: Dr. P.N. Duinker. Keywords: herbicides, vegetation management, alternatives to herbicides, forest-level analysis, sirhulation, FORMAN, cost analysis, variable harvest cost curves. Public sentiment is against herbicide use on public forests in Ontario. Provincial policies are directing research into alternative vegetation management with only limited interaction or support with forest resource based industries. The initiative of this analysis was to substantiate or dismiss the hypothesis that a forest industry could feasibly regenerate a sound wood supply from a forest in Northwestern Ontario under various herbicide-use limitations. Forest-level simulation was used to produce 100-year forecast data for thirteen management scenarios, which covered current levels, reductions in area treated, restrictions on how and where it could be applied, no use of herbicides, and a shift to a flexible wood supply. Results of the wood-supply analysis revealed that the company's wood-fibre needs from the study forest could be maintained for all scenarios. Due to the age class structure of the forest and the reasonable harvest levels imposed by^ the company, the most important component of the forest model was its present volume. Thus, even under assumptions of decreased coniferous volume production resulting from non-herbicide silvicultural treatments, only slight increases in harvest area were necessary 70+ years into the forecasts. The wood supply, area treated with herbicides and silviculture cost response variables provided the information required for sound decisions to be made for a large array of potential herbicide policy changes. Any strategy derived would need to meet the new policy's requirements while minimizing impacts on wood supply and silviculture costs and maintaining a desirable level of flexibility. For the Seine River forest, a step-wise reduction in herbicide use was determined to be the most appropriate strategy. This timing conforms well with forecasts of low need for herbicide treatments and provides adequate time for research and IV development of environmentally sound, socially acceptable and economically feasible alternatives to herbicides. This strategy meets the 20% herbicide use reduction imposed in 1991 and sets the company in a position to meet further changes. Impacts on both wood supply and silvicultural costs were shown to be minor. TABLE OF CONTENTS Page LIBRARY RIGHTS STATEMENT . . . ii ABSTRACT ... . . iii LIST OF FIGURES . x LIST OF TABLES ., .. xiii ACKNOWLEDGEMENTS . . . . xiv 1.0 INTRODUCTION 1 1.1 PROBLEM STATEMENT 1 1.2 STUDY OBJECTIVE 4 1.3 SCIENTIFIC JUSTIFICATION 4 2.0 LITERATURE REVIEW 6 2.1 ONTARIO HERBICIDE CONFLICT 6 2.2 FOREST VEGETATION MANAGEMENT IN ONTARIO 11 2.2.1 Changing Attitudes to Herbicides in Ontario 15 3.0 METHODS 19 3.1 ANALYTICAL APPROACH 19 3.2 TOOLS CHOSEN FOR ANALYSIS 20 3.2.1 The FORMAN Model 20 3.2.2 The FORMANCP Model 23 3.3 THE CASE-STUDY FOREST 23 3.3.1 Representing Forest State for Modelling 27 3.3.2 Forest Type Aggregates 28 3.3.2.1 Jack Pine Aggregations 29 3.3.2.2 Spruce Aggregations 34 3.3.2.3 Poplar Aggregates 38 3.3.3 Volume Development Patterns 42 3.3.3.1 Assumptions 44 VI 3.3.4 Present Strategy of Management 47 3.3.4.1 Wood Supply 47 3.3.4.2 Herbicide Program 48 3.4 SILVICULTURE PRESCRIPTIONS AND ASSOCIATED COSTS 49 3.5 ALTERNATIVE METHODS OF VEGETATION MANAGEMENT AND THEIR ASSOCIATED COSTS 51 3.5.1 Pre-harvest Girdling Program 51 3.5.2 Mechanical Site-Preparation Techniques 53 3.5.3 Planting of Larger Growing Stock 55 3.5.4 Manual Thinning Treatments 56 3.5;5 Ground Application Techniques for Applying Chemicals 56 3.5.6 Summary of Alternative Silviculture Treatments 57 3.6 DECISION RESPONSE VARIABLES 59 3.6.1 Wood Supply 59 3.6.2 Herbicides 60 3.6.3 Silviculture Costs 61 3.7 ALTERNATIVE MANAGEMENT STRATEGIES 62 3.7.1 Reduced Herbicide Use 62 3.7.1.1 67% Herbicide Program (67HP) Scenario 63 3.7.1.2 50% Herbicide Program Scenario 64 3.7.1.3 40% Herbicide Program Scenario 65 3.7.2 Restricted Herbicide Use 66 3.7.2.1 Aerial-Tending-Only-A Scenario 67 3.7.2.2 Aerial-Tending-Only-B Scenario 67 3.7.2.3 Aerial-Tending-Only-C Scenario 68 3.7.2.4 No-Aerial Application Scenario 68 3.7.3 No Herbicide Use 69 3.7.3.1 Other-Weed-Control-A Scenario 69 3.7.3.2 Other-Weed-Control-B Scenario 70 3.7.3.3 No-Weed-Control Scenario 70 3.7.4 Wood Supply Change 71 3.7.4.1 Flexible-Wood-Supply-N Scenario 72 3.7.4.2 Flexible-Wood-Supply-GW Scenario 73 3.8 SENSITIVITY ANALYSIS 74 4.0 RESULTS AND DISCUSSION 79 4.1 PRESENT MANAGEMENT 79 4.1.1 Wood Supply 79 4.1.2 Herbicide Use 91 4.2.1 Reduced Herbicide Use 92 4.2.2 Restricted Herbicide Use 93 4.2.3 No Herbicide Use 94 4.2.4 Wood Supply Change 95 vii 4.2.6 Summary of Basic Analysis Results 98 4.3 SENSITIVITY ANALYSIS 105 5.0 CONCLUSIONS . .118 6.0 LITERATURE CITED ... . . 123 APPENDICES.. 130 APPENDIX I ORGANIZATIONS CONCERNED WITH THE USE OF HERBICIDES IN FOREST MANAGEMENT 131 APPENDIX II SUMMARY OF THE MAJOR ATTRIBUTES ASSOCIATED WITH A NUMBER OF TYPES OF FOREST VEGETATION MANAGEMENT 135 APPENDIX III A SUMMARY OF THE PRODUCTIVE FOREST OF THE SEINE RIVER FOREST MANAGEMENT UNIT 140 APPENDIX IV A SUMMARY OF FOREST AGE CLASSES WITHIN EACH AGGREGATION NUMBER FOR THE JACK PINE FOREST 143 APPENDIX V A SUMMARY OF FOREST AGE CLASSES WITHIN EACH AGGREGATION NUMBER FOR THE SPRUCE FOREST TYPE 146 APPENDIX VI A SUMMARY OF FOREST AGE CLASSES WITHIN EACH AGGREGATION NUMBER FOR THE POPLAR FOREST TYPE 149 APPENDIX VII NORTH WESTERN ONTARIO FORMAN FOREST CLASS DEFINITIONS AND YIELD CURVES 152 viii APPENDIX VIII JACK PINE AND BLACK SPRUCE YIELD CURVES FROM SPACING TRIALS 162 APPENDIX IX VOLUME DEVELOPMENT PATTERNS USED FOR THE BUSINESS-AS- USUAL MANAGEMENT SCENARIO 167 APPENDIX X SILVICULTURE TREATMENT SPECIFICATIONS AND COSTS . . . 218 APPENDIX XI SAMPLE CALCULATIONS OF TREATMENT AREA, REAL FOREST AREA TREATED AND ACTIVE INGREDIENT 233 APPENDIX XII REPORT ON FOREST MANAGEMENT ACTIVITIES AND AGE-CLASS DISTRIBUTIONS RESULTING FROM FORMANCP RUNS OF THE VARIOUS SCENARIOS 235 APPENDIX XIII SIMULATION OUTPUT OF THE BAU SCENARIO AFTER MODIFICATION OF OPERABLE LIMITS AND INTEGRATION OF THE VARIABLE HARVEST COST CURVES 284 APPENDIX XIV EXAMPLE OF HARVEST COST CURVE CALCULATIONS . 287 IX LIST OF FIGURES Page Figure 1, Harvested, regenerated, chemically tended (aerial) and total silvicultural treatment areas in Ontario from 1981 to 1990 2 Figure 2. Flowchart of the input and processing steps of the FORMAN model . 22 Figure 3. Map of the Seine River Forest Management Unit and the surrounding area of Northwestern Ontario . 25 Figure 4. Age class distribution of the jack pine forest type and the typical present and future volume development patterns used . . 30 Figure 5. Age class distribution of the spruce forest type and the typical present and future volume development patterns used 35 Figure 6. Age class distribution of the poplar forest type and the typical present and future volume development patterns used 89 Figure 7. Representation of changes made to a volume development pattern for sensitivity analysis .77 Figure 8. The Spruce Forest Type's primary growing stock and harvest volumes at five-year intervals in time for the BAU scenario 82 Figure 9. The Spruce Forest Type's harvested and regenerated areas as a function of time for the BAU scenario . 83 X Figure 10. The Jack Pine Forest Type's primary growing stock and harvest volumes at five-year intervals in time for the BAU scenario. . . 84 Figure 11. The Jack Pine Forest Type's harvested, regenerated and spaced areas as a function of time for the BAU scenario . 85 Figure 12. The Poplar Forest Type's primary growing stock and harvest volumes at five-year intervals in time for the BAU scenario 86 Figure 13. The Poplar Forest Type's harvested and regenerated areas as a function of time for the BAU scenario . . 87 Figure 14. Softwood fibre supply and harvest level for the BAU scenario . 88 Figure 15. The average annual treatment activity in the BAU scenario for the 100-year forecast period . . 92 Figure 16. Comparison of the primary growing stock levels of all scenarios in the jack pine forest type .101 Figure 17. Comparison of primary growing stock for all scenarios in the Spruce forest type .102 Figure 18. Comparison of primary growing stock levels for all scenarios for the forest . ld3 Figure 19. Comparison of response variables from alternative management scenarios with the Business-As-Usual Scenario . 104 Figure 20. Percent change in average jack pine harvest volume per hectare due to increases and decreases of all values of the volume development patterns .106 XI Figure 21. Percent change in average spruce harvest volume per hectare due to increases and decreases of all values of the volume development patterns .107 Figure 22. Percent change in average jack pine harvest volume per hectare due to increases and decreases of peak values of the volume development patterns .108 Figure 23. Percent change in average spruce harvest volume per hectare due to increases and decreases of peak values of the volume development patterns .109 Figure 24. Percent change in average jack pine harvest volume per hectare due to increases and decreases of tail values of the volume development patterns .110 Figure 25. Percent change in average spruce harvest volume per hectare due to increases and decreases of tail values of the volume development patterns . Ill Figure 26. Initial age-class distributions of the Pj, Sp, Po and combined forest types . 113 Figure 27. Age class distributions of the Pj and Sp forest types from the BAD scenario simulation runs. . . . 1 f4 Figure 28. Jack pine harvest area distribution and source of volume for the BAU scenario . 116 Figure 29. Spruce harvest area distribution and source of volume for the BAU scenario . 117 LIST OF TABLES Page Table 1. The evolution of vegetation management through time. . .12 Table 2. Summary of the total area of the Seine River Forest Management Unit as of 1991 26 Table 3. Summary of all the productive areas by tree species in the Seine River Forest Management Unit as of 1991 27 Table 4. The area and percent of the total area of forest types being managed in the Seine River Forest Management Unit 29 Table 5. Summary of the rules for and the stratification of the Jack Pine forest type in the Seine River Forest Management Unit 33 Table 6. Summary of the rules for and the stratification of the Spruce/Fir forest type in the Seine River Forest Management Unit 37 Table 7. Summary of the rules for and the stratification of the Poplar forest type in the Seine River Forest Management Unit 41 Table 8. Summary of silvicultural treatments and their assumed costs used in the construction of management scenarios 50 Table 9. Summary of alternative silviculture treatments and changes from the BAU scenario used in alternative management strategies 58 Table 10. Scaling factors used to increase and decrease the three groupings of volume development patterns for use in their sensitivity analysis. ... 78 XIII Table 11. The wood-supply and regeneration for forest level analysis of the Seine River Forest Management Unit under the Business-As-Usual management scenario . . 89 Table 12. Wood-supply harvest levels for the FWS-N alternative management scenario .. 97 XIV ACKNOWLEDGEMENTS I would like to thank Dr. P.N. Duinker for his guidance, encouragement, financial support and inspiration as my principal advisor. This study was made possible by the assistance of a number of individuals. Personnel at the Fort Frances Division of Boise Cascade, including Peter Kirby, Woodlands Manager; Paul Jewiss, Forestry Superintendent; Jim Krag, Superintendent, Seine River Operations; Bob Cox, Superintendent, Manitou Operations; Colin Flewitt, Planning Forester; Jim Parsons, Project Forester; Joan Keene, Silviculture Forester, Seine River Forest; and Nick Blacklock, GIS Specialist, gave their time, experience and insights for the development of the computer model of the forest and the various management scenarios. Bob Wagner, Director, Vegetation Management Alternatives Program, OMNR, was instrumental in the direction of the study and helped to develop the thesis into a format which ensured technological transfer. Laird Van Damme, Director, Ontario Advanced Forestry Program, and a member of my thesis committee, assisted in the development of the stand development patterns and gave professional insights at all stages of the study. Wayne Bell, Vegetation Management Specialist, Northwestern Ontario Forest Technology Development Unit, relayed his opinions and gave ideas for alternative silviculture treatments. I must also thank Kevin Topolniski of Fraser Inc. in New Brunswick for urging me on in the final stages of writing. Last but not least I would like to give special thanks to JoAnn Crichlow, Research Assistant, Chair in Forest Management and Policy and who kept me on the up'n'up through my time with the Chair. 1.0 INTRODUCTION 1.1 PROBLEM STATEMENT While the annual harvest area in Ontario has increased only 8% over the last decade, from 196 377 ha in 1981 (Smyth and Campbell, 1987) to 211 000 ha in 1990 (OMNR, 1991 ^), there has been a 55% increase in areas artificially regenerated. This substantial increase in reforestation is due largely to an increased awareness of Ontarian and Canadian policymakers of the need to invest in forests for the future, and also, an overwhelming public sentiment towards proper care for the forests of Canada (Environics, 1989). A commitment to reclamation of forest sites which did not develop back to their "pre-harvest" species composition (backlog), in addition to more intensive silviculture on annual harvest areas, has meant a considerable increase in the use of silvicultural tools, especially in silvicultural tending with herbicides (Figure 1). Ini 989 alone, over 89 thousand hectares of Crown land in Ontario were treated aerially with herbicides, up over 32 thousand hectares from 1986 figures (OMNR, 199V). Public awareness and concern over the use of herbicides in the forest has been increasing in Canada. Results of this concern include the severe restriction of 2 Figure 1. Harvested, regenerated, chemically tended (aerial) and total silvicultural treatment areas in Ontario from 1981 to 1990 (Source: Smyth and Campbell, 1987; and OMNR, 1991’). herbicide use by some provinces (Saskatchewan and Alberta) and limitations on use of some registered herbicides in others such as Ontario. These policies assume (or fail to consider) that if vegetation management methods other than herbicides were applied to selected and suitable forest sites, and if research created effective and efficient alternative treatments, the amount of herbicide applied could be drastically reduced with little effect on the long-term viability of the forest products industry. The government of Ontario has recently implemented a policy which acknowledges concerns over herbicide use and is intensively seeking the development of environmentally-sound, effective, cost-efficient and socially 3 acceptable alternatives (OMNR, 1991^). The Vegetation Management Alternatives Program (VMAP) is seeking alternatives to herbicides and a better understanding of ecosystem dynamics through research, education and field delivery (Wagner, 1991).'The introduction of the VMAP in 1990 was accompanied by a 20% reduction in forest areas treated with herbicides. To substantiate or dismiss hypotheses on the need for herbicide use to deliver an economical and sustainable supply of quality wood fibre, an investigation of a range of alternative herbicide programs was performed on a forest management unit in Northwestern Ontario using forest-level analysis. The few impact assessments completed on the use of herbicides in forest management in the past, as well as public opinion, have focused on the environmental and human- health implications and risks associated with the use of herbicides, but have neglected to analyze potential consequences of not using herbicides or alternative vegetation management strategies (Dietz, 1985; Duinker, 1991). In this study, forest-level simulation are used to examine how forest management might have to change, and how forests and their wood-fibre yields may be altered under reduced-herbicide-use policies that differ from continuation of the present "business-as-usual" policy of Ontario. 4 1.2 STUDY OBJECTIVE The objective of this study is to develop a framev\/ork for the evaluation of forest management's ability to accommodate changes to Ontario's present herbicide policy and maintain present wood-supply levels to industry at reasonable costs. 1.3 SCIENTIFIC JUSTIFICATION This study focused on the hypothesis that Ontario forest industries could feasibly maintain current wood-supply objectives under a policy of reduced herbicide use but not under a policy of no herbicide use. This hypothesis was tested by analyzing wood-supply and associated costs of treatment scheduling resulting from a variety of alternative management strategies meant to reflect possible management responses to changes to the current herbicide policy in Ontario. The alternative management strategies, developed in cooperation with the study area's forest managers, reflect hypotheses on how the present herbicide policy in Ontario may change in an attempt to address public concerns over herbicide use on public forests. Since no wood-supply studies centred on herbicide use have been performed on an Ontario forest to date, this study provided a framework for future analyses in Ontario and elsewhere. 5 The proved efficacy of herbicides and their low financial cost made them the vegetation management tool of choice in forestry. However, recent concerns over potential health risks due to herbicide use, especially use on public lands, brought about the development of provincial policies involving immediate reductions in herbicide treatment levels and a move to greater dependence on alternatives. Due to the long time span required for trees to grow to operable dimensions (at least 40+ years for most species in Canada), empirical studies of responses to silviculture treatments are only available for the early stages of developrnent. While a complete data set reflecting the development of a forest stand through to rotation age after a silviculture treatment would be ideal for analysis, no such data is yet available. To facilitate potential outcomes from today's actions, the responses of stands to various treatments were estimated using a combination of empirical data and professional judgement based on scientific research. Thus, the volume development patterns which reflect responses of forest productivity are themselves hypotheses. The theory behind them was that different treatments would result in different rates and levels of softwood and hardwood volume development over time. Sensitivity analysis was used to determine how crucial these development patterns were to 100-year wood- supply projections for the study forest. If large changes to the development patterns produced only small changes to the response variable (forest productivity based on harvest volume per hectare) then they would be deemed insensitive, and visa versa. 6 Though the knowledge-base for impact assessments such as this is limited, society cannot afford to wait for a more concrete understanding; information is required now to make decisions on issues likely to affect future events (Baskerville, 1990; Duinker et al., 1992). An iterative approach which starts now, based on what information is available, a series of assumptions, bounded by sound judgement, and periodically calibrated with more accurate representations of the system's dynamics, is a responsible approach to planning under high levels of uncertainty. Proper use of analytic techniques such as sensitivity analysis will ensure that sensible routes are pinpointed and possibly followed. Identifying all assumptions used in the analysis and limitations of the approach will give scientific credibility to the process used and allow for replication and/or application of the technique. 2.0 LITERATURE REVIEW 2.1 ONTARIO HERBICIDE CONFLICT Chemical herbicides were thrust into the public spotlight principally with the use of three phenoxy herbicides, 2,4,5-T, Silvex and 2,4-D, by the U.S. military in the Vietnam conflict and from the discovery of a dioxin contaminant in 2,4,5-T and Silvex (Newton and Knight, 1981; Van Strum, 1983). Both herbicides were 7 contaminated with a class of chemical known as dioxin. The specific dioxin found in 2,4,5-T and Silvex, that is 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), is not found in 2,4-D (Walstad and Dost, 1984). TCDD is the most toxic chemical substance known to humankind (Anon, 1985). Obviously, with a chemical so toxic being found in 2,4,5-T and Silvex, the most commonly used herbicides of the time (Walstad and Dost, 1984), public concern rang loud. While the low levels of TCDD (routinely less than 5 parts per trillion) likely represented less risk to public and environmental health than the herbicides themselves (Walstad and Dost, 1984), controversy over the use of TCDD led to an immense amount of research on the phenoxy herbicides. Phenoxies are now more understood than any other pesticide or toxicant in the world today (Newton and Knight, 1981). Most research has concluded that the dioxin-contaminated phenoxies pose no threat to human health if used as directed and if proper safety precautions are followed when handling the products (Walstad and Dost, 1984; Sutton, 1985). However, public pressure prevailed as the cost to regain registration through court battles outweighed the foreseeable profits, and the chemical industry (primarily Dow Chemical) did not pursue registration and thus stopped manufacture of 2,4,5-T and Silvex in 1983 for use in the United States (Walstad and Dost, 1984). Public opinion was swayed by books written by environmental activists such as Rachel Carson (1962), author of SILENT SPRING (often said to be a key instigator of the environmental movement). The increased public awareness of 8 potential health hazards from man-made chemicals helped build up zealous anti- chemical groups such as Citizens Against Toxic Herbicides, Citizens Against Toxic Sprays, Northwest Coalition for Alternatives to Pesticides, and the National Veterans Task Force on Agent Orange (Van Strum, 1983). The list of groups against chemical use does not stop there, however. Other organizations which focus on environmental issues also opposed the use of chemical pesticides/herbicides; Friends of the Earth, Southern Coalition for the Environment, National Council of Churches, Interfaith Centre on Corporate Responsibility, Citizen Soldier, National Association of Farmworker Organizations, and the Sierra Club (Van Strum, 1983). Though most of these groups were located/headquartered in the United States, they must have indirectly influenced Canadian thinking on herbicides. While the fight against 2,4,5-T and Silvex was finally settled in the United States (2,4,5-T ceased to be produced in 1984), chemicals in general were still a major public concern. Attention shifted to the banning of other commonly used chemicals, especially the phenoxy herbicide 2,4-D, and pushing for tighter and more stringent controls and screening processes for chemicals. Other countries around the world, including Canada, did not pull registration of 2,4,5-T (Sutton, 1985). In Canada, the use of 2,4,5-T is permitted by the federal government for use as a tool in silvicultural vegetation management. However, a number of provincial governments (e.g. British Columbia, Ontario, Saskatchewan and Quebec (Sutton, 1985)) currently do not have 2,4,5-T registered for forest 9 management. Obviously there was public pressure in Canada (and still is) against herbicides and/or the spraying of herbicides. In Ontario, a major "voice" for environmental issues is the Ontario Environment Network (OEN) which is supported by 87 Ontario citizens groups (Appendix I). In a 1991 action agenda, OEN pushed for a ban on aerial spraying of chemical herbicides in tandem with a move towards "the use of appropriate modified cutting practices and natural regeneration" (Maynes, 1991). The Conservation Council of Ontario (CCO), an organization representing 31 member organizations (combined membership of over a million people) formulated an environmental strategy for Ontario (Appendix I). The CCO's stand on chemical pesticides (in general) was to reduce the dependence upon them by developing and using a greater number of alternatives (CCO, 1990). One of the purposes for the production of "An Environmental Strategy for Ontario" by the CCO was to provide the Ontario Round Table on Environment and Economy (ORTEE) with "concrete recommendations for a provincial sustainable development strategy" (CCO, 1990). A Forestry Sector Task Force was also organized "to examine the forestry sector and to make recommendations on implementing a sustainable development strategy" to the ORTEE (Forestry Sectoral Task Force, 1991). The Task Force members represented universities, government, industry, and non-government organizations (Appendix I). While individual opinions ranged from an immediate ban, to a stepwise reduction with eventual elimination of use of chemicals as a 10 forest management tool, the Task Force did agree that research into the development of "safe, effective and efficient alternatives to the use of chemical herbicides and insecticides" should be encouraged (Forestry Sectoral Task Force, 1991). Ontario's youth have also formed an opinion on the use of herbicides. They desire a change to the use ot alternatives to pesticides (Public Focus, 1990). Health risks perceived by the public regarding the use and presence of chemical herbicides (especially phenoxies) in the environment includes cancer, mortality, organ abnormalities, and birth defects in any organisms coming in contact with them (Walstad and Dost, 1984). While a fear of possible detrimental effects from herbicides exists, the reality in present terms, that the use of herbicides (aerial) "is associated with a lower risk to both site productivity and human health than any alternative" (Walstad and Dost, 1984), is also an important consideration. The debate goes on. However, in recent years, the trend has moved to political judgements being made on the basis of public concern and not on science. Evidence for this includes restriction of the use of 2,4,5-T, promotion of reduced dependence on herbicides, and an increase of research in Ontario towards the development and use of alternatives. Public opinion as documented in a number of surveys completed from 1984 to 1989 showed that seven in ten people of both Ontario and Canada either disapproved or strongly disapproved of "the use of chemical pesticides and herbicides in Canada's forests" (Environics, 1989). 11 2.2 FOREST VEGETATION MANAGEMENT IN ONTARIO The reforestation of harvested forest sites usually requires some form of vegetation management of on-site competing vegetation to be successful. The reduction of competing vegetation improves one or more of the following stand attributes;, survival: height, diameter or basal area growth; tree and stand volume; crown length and width; needle colour and length; tree vigour; and resistance to pests such as insects (Stewart, 1987). In addition to the tree- specific effects, there are other direct and indirect effects such as increased harvests, increased stand value, lower harvest costs, and earlier return on investment resulting from vegetation management (Stewart, 1987). Thus, if commercial forests are to be effectively and economically managed, vegetation management must be practised (Walstad et al., 1987). There are several silvicultural vegetation management practices available to the forest manager including harvest, site preparation, tending (stand release), and stand improvement (Walstad et al., 1987). A summary of the major attributes associated with a number of types of forest vegetation management was compiled by Walstad et al. (1987) and is supplied in Appendix II. Vegetation management has evolved through time to what it is today (Table 1). Primitive hand- and cattle-drawn implement use have slowly progressed to dependence on herbicides, and finally to management based on ecological and environmental principles (including use of herbicides). 12 Table 1. The evolution of vegetation management through time. Period Significant Accomptishments 6000 B.C.-1800 A.D. Magic and superstition gradually discarded. Primitive hand- and cattle-drawn implements used. Early documents written about weeds. 1801-1900 Improved ploughs, cultivators, mowers and disks developed during horse-drawn era. Prototype sprayers invented for applying inorganic pesticides. Weed control “proved" beneficial in crop production. Scientific publications on weeds and weed control appeared. 1901-1940 Transition to mechanized implements occurred. Inorganic herbicides developed. Research and extension programs established. 1941-1968 Plant growth regulators discovered. Organic herbicides synthesized and marketed. Research and extension rapidly expanded. Major increases achieved in crop production, attributable in part to weed control. 1969-1987 Major breakthroughs in plant physiology, biochemistry, and genetics continued to occur. Organic herbicides further developed and refined for operational use. Regulatory activities expanded and strengthened. Concept of vegetation management adopted. Energy efficiency and environmental impacts became important parameters for evaluating techniques. Source: Adapted from Walstad and Kuch (1987)’ 13 The various silvicultural methods available to the forest manager for vegetation management as cited by Sutton (1985) are as follows; (i) Manual (e.g. pre-release and/or release tending treatments with Sandviks, chainsaws and/or brush saws); (ii) Mechanical (e.g. disk trenching or shear blading); (iii) Prescribed burn (e.g. site preparation with light/heavy controlled fire); (iv) Biological (e.g. cattle or sheep); (v) Systems based (e.g. advanced timing and selection of harvest methods); and (vi) Chemical (e.g. herbicide used alone or in combination with other methods for site preparation and/or tending). Traditionally, herbicides have been used in three areas of forest vegetation management: (i) site preparation; (ii) tending; and (iii) reclamation of backlog areas. Site preparation is any form of soil disturbance which is used to precede the establishment of a tree crop by either artificial or natural methods (Brown, 1983). Its purpose is to prepare microsites for seeds, seedlings, vegetative cuttings or root suckers, to eliminate competing vegetation and to control spacing and stocking of the new stand (Brown, 1983). Site preparation is usually accomplished mechanically, chemically, mechanically and chemically, or with a prescribed burn (Sutton, 1985), 14 Tending is the selective control of weeds (undesirable vegetation) in the presence of crop trees (desirable vegetation) (Sutton, 1985). Its purpose is to act as either a pre-release measure, which is a preventative treatment used to control weeds on the site before the vigour of the crop trees is at risk, or as a release treatment, which "rescue[sl established but declining crop trees" (Sutton, 1985). Tending is usually executed chemically or manually within the early development stage of a stand when tree vigour is high and the trees are more able to take advantage of the changed growing conditions (Newton et al., 1987). While both chemical and non-chemical methods for site preparation and tending have been available to the forest manager in Ontario for decades, the trend has been towards the use of chemicals, especially for tending purposes. Most scientists and foresters have observed herbicides to be an extremely effective and economical tool for the control of competing vegetation (Newton, 1975; McCormack, 1981; Day, 1984; Stewart et al., 1984; Sutton, 1985; Malik and ✓ Vanden Born, 1986; Walstad et al., 1987). This support for the use of chemical herbicides was a factor in the promotion of chemical treatment on Forest Management Agreement lands in Ontario by OMNR. Indeed, the following statement appears in the Ontario Timber Management Planning Manual: "...in the event that appropriate herbicides are not or cease to be licensed for forestry use in Ontario, the company's [industry's] obligation to tend if necessary will no longer hold" (OMNR, 1986’). 15 There were five herbicides registered for silvicultural use on the forests of Ontario in 1991: glyphosate; hexazinone; 2,4-D; triclopyr; and simazine. Glyphosate (Vision®) was licensed for aerial and ground application for both site preparation and tending,‘hexazinone (Velpar-L®, Velpar-ULW® and Pronone®) was licensed for ground and aerial application, 2,4-D was licensed for aerial and ground application, and triclopyr (Release®), for ground application (Campbell, 1991). Due to governmental restrictions, constant delays, general controversy over herbicides and that registered herbicides must be well researched for crop tolerances and efficacies, the registration of other herbicides for forestry use is unlikely (Campbell, 1991). Current research addresses environmental and health issues, long-term crop benefits and effective use of herbicides (Campbell, 1991). 2.2.1 Changing Attitudes to Herbicides in Ontario The objective of forest management on Crown Lands in Ontario during the 1980s was to "provide for an optimum continuous contribution to the economy by forest-based industries consistent with sound environmental practices and to provide for other uses of the forest" (OMNR, 1986^). The Ontarian and Canadian governments worked together to meet this goal with the Canada-Ontario Forest Resource Development Agreement (COFRDA). COFRDA was a 50/50 cost-sharing agreement between the two levels of government which had the following three main objectives: 1. To encourage and support forest management activity in order to increase the sustainable supply of wood fibre from the forest resource and ensure the long-term viability and competitiveness of the forest industry in Ontario; 16 2. To improve and increase the utilization of the forest resource to enhance future forest industry development opportunities; and 3. To contribute to the economic development of the Ontario forest sector, including the improvement of employment opportunities in the sector (Smyth and Campbell, 1987). A system of forest tenure known as Forest Management Agreements (FMAs) was introduced as part of Ontario's Crown Timber Act in 1979. Lands managed under FMAs had the responsibility for timber management activities, including regeneration, set primarily on the shoulders of the tenure holder (Roots and Ouinby, 1992). The major advantage for FMA holders was that as regeneration efforts proved successful, an immediate increase in the sustainable harvest level could often be realized. However, these agreements were also dependent on a high level of provincial funding, which in has continued to decrease (Duckert, 1992). Renewal of these 20-year agreements, which are subject to review every five years, has been slow, even when the holder has been shown to meet all of the conditions. Changing times, an increase in the public's awareness of the environment around them, and the expiration of the COFRDA agreement in March 1989, brought about considerable change in forest management in Ontario. Some of those changes were reflected in the Northern forestry Program which was funded ($50 million) under the cost-sharing agreement called the Northern Ontario Development Agreement (NODA) (Rosen and Kuntz, 1992). While the COFRDA pushed for supply and utilization of timber resources, the Northern Forestry Program focused "on providing better tools and management decisions for Ontario's forests with both economic and environmental benefits" (Rosen 17 and Kuntz, 1992). In addition to these changes at the provincial and provincial/federal levels, the federal government acknowledged that the care of the Canadian environment was not only a national obligation, but one which must be considered on an international, global scale as set out in Canada's Green Plan. The Green Plan had over $3 billion in funding available (over five years) of which a major proportion was to be used to find the most environmentally suitable methods to practice sustainable development (Anon, 1990). In May 1991, the Honourable Bud Wildman, then Minister of Natural Resources, announced the beginning of "a new system of forest management in Ontario" based upon a sustainable forestry approach. Sustainable forestry focuses on the long-term health of forest ecosystems as well as social, cultural and economic opportunities and benefits (OMNR, 1991^). In an effort to implement sustainable forestry, the government dedicated additional funding ($10 million) to the following new initiatives: 1. An independent audit of the province's boreal forest to determine the level of artificial and natural regeneration in harvested areas; 2. A four-person working group to co-ordinate the development of a comprehensive forest policy framework, through a broad public consultation process, by the end of 1992; 3. An old-growth ecosystem conservation strategy to be developed in conjunction with the scientific community, interest groups and the public; 4. Community forest projects to be established in four communities to test options for increasing local involvement in forest management; 18 5. Expansion of the province's silvicultural program through an enlarged research program and the field testing of alternatives to current practices, including options to reduce the use of chemical herbicides; and 6. A private woodlands strategy to promote sustainable forestry on private lands, mainly in southern Ontario (OMNR, 1991^). The initiative of interest for this study was of course the fifth one listed above, which would yield alternatives for vegetation management in an effort to reduce the use of chemical herbicides. The public concern over use of chemicals in the forest was acknowledged and the infrastructure to provide "environmentally- sound, effective, cost-efficient and socially acceptable alternatives to chemical herbicides" was funded (OMNR, 1991^). The Vegetation Management Alternatives Program (VMAP) was designed "to gradually reduce the dependence on herbicides in Ontario forest management by developing alternatives and a better understanding of forest ecosystems through research, education and field delivery" (Wagner, 1991). In 1991, Ontario forest managers faced a 20% reduction in aerial application of herbicides. The goal of the Ontario government was to systematically reduce "dependence on herbicides as new alternatives [were] developed" (OMNR, 1991^). The integration of new tools with those available to forest managers would also require more sophisticated and technical methods of decision-making. 19 3.0 METHODS 3.1 ANALYTICAL APPROACH . While a change to the herbicide use policy in Ontario would undoubtedly affect the growth pattern of individual stands, a method was required which would provide an indication of the impact on the forest as a whole. Forest-level analysis using simulation was used to forecast how a forest might evolve in the event of different scenarios of management. To do this, models meant to reflect the forest and activities within it were produced "to compress the forest into a comprehensible format" (Baskerville, 1990). By creating a model which looks, acts, reacts and accurately represents the variability of a forest, emphasis can be placed on the processes which drive change in the forest over time. Model development required the characterization of the present forest conditions and management techniques. Alternative management strategies were then devised to reflect possible reactions to herbicide policy changes. To accommodate the strategic goals set.by each alternative, alternative silvicultural treatments were selected and/or envisioned with changes in vegetation management efficacy and/or cost, dependent on the management scenario. Variables were chosen and later used for comparative analysis and the formation of a logical decision. 20 3.2 TOOLS CHOSEN FOR ANALYSIS Forest simulation was chosen as the method for this analysis primarily for its straightforward, bookkeeping approach which allowed a high level of awareness to how the forest was reacting to various methods of management. A well- tested simulation program (FORest MANagement - FORMAN (Wang et al., 1987)) was readily available for use and the forests of Ontario had recently been characterized for FORMAN. Thus, by using simulation as a tool, a nearly complete mathematical formulation of the case-study forest was available, the techniques were easily understood and useable, and all the steps involved in a simulation could be retraced. The increased level of understanding of the process and cause-effect relationships added to the legitimacy of the results. 3.2.1 The FORMAN Model The FORest MANagement (FORMAN) simulation model is a "sequential inventory projection model used in forest level analysis" (Wang et al., 1987). This model is not statistical, but is a bookkeeping and updating device which allows quantitative representations of the forest dynamics and the management strategies to be tracked overtime (Walker, 1989; Baskerville, 1990; Duinker etal., 1992). 21 The model required extensive data input to describe the present and future states of the forest as a result of time and/or management techniques, and the rules and levels of harvest, silviculture and costs. Walker (1989) captured the methods used in the FORMAN model to describe the forest structure, the management strategies, and the stages followed in the simulation of a forest in Figure 2. The formation of the forest structure data sets used to reflect reality (to the highest level possible) determined the level of validity of the results (Duinker et al., 1992). Only with effective representation of these rules into a consistent model such as FORMAN could worthwhile forecasts of the future be made. 22 Figure 2. Flowchart of the input and processing steps of the FORMAN model. (Source; Walker, 1989) 23 3.2.2 The FORMANCP Model FORMANCP (Williams, 1991), a modified version of FORMAN 2.1, was chosen as the simulation tool for'this study. FORMANCP opens links to CROPLAN (a program developed by Williams (1991) which creates and examines the files for Benefit Cost Analysis (BCA) necessary for running FORMANCP), has run-time graphics, and includes discounted values of harvest and silviculture costs, harvest value and present net worth values for forecasts (Williams, 1991). Otherwise, FORMANCP produces identical results to FORMAN 2.1; however, the addition of run-time graphics and the calculation of discount and present net worth values greatly enhances the usefulness of the model and sharpens the analysis of alternative management scenarios for a forest. 3.3 THE CASE-STUDY FOREST The Seine River Forest Management Unit (SRFMU) was selected as the case- study forest. The SRFMU, managed under a Forest Management Agreement (FMA) by the Fort Frances Division of Boise Cascade Canada Ltd., is located within the Fort Frances District of the Northwest Region of Ontario (Figure 3). The total.area of the SRFMU is 280 273 ha of which 46 373 ha are water and 267 221 ha are Crown land. Of the available Crown lands, 650 ha are non- forested and 25 722 ha are non-productive forest (Table 2). 24 The production forest (194 476 ha) is dominated by jack pine, black spruce and trembling aspen (Table 3). The primary product from the forest was softwood (jack pine and spruce) with only a small amount of hardwood (poplar) used. Thus, all vegetation competing with softwood regeneration, except on hardwood sites, was considered competition; primarily poplar, pincherry, birch, raspberry and grasses. An in-depth account of the respective productive forest and protection forest areas is provided in Appendix III. 25 Northwctt Region Kllom*tr»* Figure 3. Map of the Seine River Forest Management Unit and the surrounding area of Northwestern Ontario. (Source; Boise Cascade Canada Ltd.- Fort Frances Div., 1991) 26 Table 2. Summary of the total area of the Seine River Forest Management Unit as of 1991. LAND CLASS AREA (ha) Water 46 373 Non-forested land 650 Forested land Non-productive 25 722 Productive 194 476 Total 267 221 (Source: Boise Cascade Canada Ltd.- Fort Frances Div., 1991) 27 Table 3. Summary of all the productive areas by tree species in the Seine River Forest Management Unit as of 1991. Working Group Protection Production Total Species Forest Forest (ha) (ha) (ha) White Pine (Pw) 0 969 969 Red Pine (Pr) 0 1304 .1304 Jack Pine (Pj) 214 74572 74786 Spruce-all (S) 0 253 253 Black Spruce (Sb) 946 53705 54651 White Spruce (Sw) 0 253 253 Balsam Fir (Bf) 99 10945 11044 White Cedar (Ce) 129 2402 2531 Tamarack (L) 18 70 88 Ash (A) 0 98 98 Soft Maple (Ms) 0 1636 1636 Trembling Aspen (Po) 426 36755 37181 Black Poplar (Pb) 0 98 98 White Birch (Bw) 398 9 186 407 Total 2230 192246 194476 (Source: Boise Cascade Canada Ltd.- Fort Frances Div., 1991) 3.3.1 Representing Forest State for Modelling As with any simulation model, the present state of the forest must be represented, as well as the rules by which change would occur, in the form of a mathematical model. The present state of the study forest was reflected with the following parameters: 28 1. Forest type (forest areas dominated by one species of tree (working group)); 2. Aggregate group (sub-groupings of forest types separated on the basis of stand composition and stocking); 3. (sub-groupings of aggregate groups based on site class); 4. Age class (sub-grouprngs of aggregate numbers based on five-year age classes); and 5. Volume development patterns (curve sets used to describe the net merchantable volume (NMV) of coniferous and deciduous components per hectare over stand age for each aggregate number). 3.3.2 Forest Type Aggregates Forest type aggregates were compiled and aggregated from 1985 Ontario Forest Resource Inventory (FRI) data updated to the end of 1990 for depletions and free-to-grow status. While FRI data are not the most suitable database for forecasting and forest-level analysis (FRI stand interpretation was done by aerial photo interpretation with photo scales of 1:15 840 and only minimal ground- truthing, and was never intended for use in simulation models), it was the only account of the study forest's resources available in the Seine River Forest. Each of these forest types was simulated separately to add a higher level of control over changes in management made wthin each type. To aid the reader in comprehending the assumptions made in forming the respective aggregate groups and aggregate numbers, the explanations are noted by forest type. 29 Table 4. The area and percent of the total area of forest types being managed in the Seine River Forest Management Unit. FOREST AREA TYPE Hectares Percent Spruce/Fir 66 888 38 Jack Pine 74 983 42 Poplar 35 866 20 Total 177 737 100 3.3.2.1 Jack Pine Aggregations The jack pine forest type occupied 42% of the total area (74 983 ha), of which the majority was mature to overmature (Figure 4). The jack pine (Pj) aggregate groups reflect conditions used by Boise Cascade managers to decide on methods of management for regenerating the sites. These conditions, which - were also used for the aggregation of the spruce and poplar forest types, include: • site class: identified through age-height relationships of a stand's working group species which are compared to species specific site class curves prepared by Plonski (1981). Order of site class in terms of productivity, from highest to lowest, are: X, 1, 2, and 3 with site class 30 Jack Pine Forest Type 20 15 10 5 0 0 20 40 60 80 100 120 140 160 180 200 Age (years) Softwood ©Poplar Operable iBArea Age (years) Post Harvest Futures BNatural i :inoperable XSeed Dperable ASeed/Space Operable Figure 4. Age class distribution of the jack pine forest type and the typical present and future volume development patterns used. 31 representing any poor site (shallow soil) regardless of age-height numbers; coniferous and/nr : determined through summarization of a stand's species composition; and • stocking of stands: values representing the relationship of a stand's actual volume to Plonski's (1981) normal volume. The three aggregate groups formed were Pj-1, Pj-2 and Pj-3 (Table 5; Appendix IV). : Jack pine aggregate group Pj-1 is made up of stands having a Pj Working Group (WG) and an overall stand composition of coniferous trees only (i.e. the stands are all 100% coniferous). While the original intention was to break this aggregate group into stands with stocking greater than or equal to (ge) 70% and stocking less than or equal to (le) 60%, analysis of the Pj stands revealed that there was an insignificant area with stocking le 60%. Consequently, those areas were both incorporated into the Pj-1 aggregate group. This area was separated into site classes X-i-1, 2 and 3 to produce aggregate numbers 1, 2 and 3 respectively. As with the formation of the forest types, the information used for producing all of the detailed aggregate groups and aggregate numbers also came from the 1991 FRI. 32 Pj-2 Aggregate Group. The Pj-2 aggregate group is composed of stands with a coniferous component of le 70%. Aggregate Numbers 4, 5 and 6 relate to site classes X+1, 2 and 3 respectively. Pj-3 Aggregate Group. All Pj stands with an 80 or 90% coniferous component are contained in aggregate group Pj-3. Aggregate Numbers 7, 8 and 9 were formed after the group was divided into site classes X+1,2 and 3 respectively. 33 Table 5. Summary of the rules for and the stratification of the Jack Pine forest type in the Seine River Forest Management Unit. Aggregate Aggregate Stand Component Stocking Site Class Area Group Number (ha) Coniferous Hardwood ±Jll 1 100% 0% ge 70% X & 1 2 496 25 963 2 880 Subtotal 31 339 le 70% ge 30% nc X & 1 1 450 10 937 896 Subtotal 13 283 Pi-3 80 or 90% 10 or 20% nc X & 1 2 985 24 225 3 151 Subtotal 30 361 Total 74 983 nc - not considered ge - greater than or egual to le - less than or egual to 34 3.3.2.2 Spruce Aggregations The Spruce forest type (Sp) was also mature, but on average, was assumed to maintain volume (Figure 5). Spruce was originally envisioned to include only black and white spruce since there were no differences in the management strategies used by Boise Cascade for these two forest types. However, since Bf was used interchangeably with Sp at the mill and all the Bf sites were to be converted to black spruce after harvest, it was assimilated into the Sp forest type as well (Table 6; Appendix V). Spruce Forest Type Aggregations. The spruce aggregate groups were formed based on site class, coniferous and hardwood component, stocking of stands, and presence of balsam fir. The spruce forest type was divided into five aggregate groups: Sp-1, Sp-2, Sp-3, Sp-4 and Sp-5. Sp-1 Aggregate Group. The Sp-1 aggregate group is composed of stands having a 100% coniferous component of which ge 50% is black spruce, and stocking is le 60%. The group was split into site classes X+1, 2 and 3 to yield aggregate numbers 10, 11 and 12 respectively. . The Sp-2 aggregate group is similar to Sp-1 except that stands have stocking values ge 70%. Dividing the group into site classes X-i-1, 2 and 3 yielded aggregate numbers 13, 14 and 15 respectively. 35 Spruce Forest Type Volume (m^3/ha) Area {'000s ha) 20 200 - - 15 10 5 0 Age (years) Softwood Q Poplar Operable EArea Figure 5. Age class distribution of the spruce forest type and the typical present and future volume development patterns used. 36 Sp-3 Aggregate Group. The Sp-3 aggregate group is composed of stands with a coniferous component of le 70%. The group was divided into site classes X+1 and 2 (there was no site class 3) which were then labelled as aggregate numbers 16 and 17 respectively. Sp-4 Aggregate Group. The Sp-4 aggregate group is made up of stands with an 80 or 90% coniferous component. The area was then divided into aggregate numbers 18 and 19 which represent site classes X+1 and 2 respectively. Sp-5 Aggregate Group. The Sp-5 aggregate group is composed of stands with a Bf working group. Division of the area by site classes X+1 and 2 yielded the aggregate numbers 20 and 21 respectively. 37 Table 6. Summary of the rules for and the stratification of the Spruce/Fir forest type in the Seine River Forest Management Unit. Aggregate Aggregate Stand Component Stocking Site Class Area Group Number (ha) Coniferous Hardwood Sp-1 10 100% 0% le 60% X & 1 4 275 (Sb qe 50%) 11 6 175 12 1 848 Subtotal 12 298 Sp-2 13 100% 0% ge 70% X& 1 7 008 (Sb ge 50%) 14 3 056 15 629 Subtotal 10 693 Sp-3 16 le 70% ge 30% nc X & 1 10 975 17 1 593 Subtotal 12 568 Sp-4 18 80 or 90% 10 or 20% nc X & 1 17 079 19 2 391 Subtotal 19 470 Sp-5 20 nc nc nc X& 1 10 870 21 989 Subtotal 11 859 Total 66 888 nc - not considered ge - greater than or equal to le - less than or equal to 38 3.3.2.3 Poplar Aggregates The poplar forest type (Po) is composed of stands having Poplar as their WG. The age class distribution of the Po forest type was on average immature to mature (Figure 6). One aggregate group was initially considered for conversion to black spruce (Po stands with spruce and/or pine making up 50% of the stand component). However after simulating the Po forest type, it was found that this conversion was unnecessary and likely improbable, especially in consideration of planting stock shortages and the more important need to convert BF stands to spruce. Planting of spruce was therefore allocated to the spruce forest type only. The final decision was to manage all Po sites with natural regeneration as the silvicultural prescription (Table 7; Appendix Vi). Poplar Forest Type Aggregations. The poplar aggregates were created from conditions of site class, coniferous and hardwood component, and stocking of stands. The aggregate groups formed from the poplar forest type were: Po-1, Po-2, Po-3 and Po-4. Po-1 Aggregate Group. The Po-1 aggregate group is composed of stands with a hardwood component ge 60% and stocking of le 40%. Division of the area into site classes 2 and 3 yielded the aggregate numbers 22 and 23 respectively. 39 Poplar Forest Type Volume (m^3/ha) Area ('000s ha) 250 -I 20 200 - - 15 10 5 0 0 20 40 60 80 100 120 140 160 180 200 Age (years) ■?*rSoftwood 0 Poplar Operable BBArea Figure 6. Age class distribution of the poplar forest type and the typical present and future volume development patterns used. 40 Po-2 Aggregate Group. The Po-2 aggregate group is composed of stands with a hardwood component ge 60% and stocking ge 50%. The area was divided by site classes 1, 2 and 3 which formed aggregate numbers 24, 25 and 26 respectively. PQ-3 Aggregate Group. The Po:3 aggregate group is composed of stands with a hardwood.component le 50% and the presence of Bf in the stand composition. Division of the area by Site classes 2 and 3 produced aggregate numbers 27 and 28. Po-4 Aggregate Group. The Po-4 aggregate group is composed of stands with a hardwood component of le 50% and the presence of Pj and/or Sp in the stand composition. Site classes 29 and 30 are represented in aggregate numbers 29 and 30 respectively. 41 Table 7. Summary of the rules for and the stratification of the Poplar forest type in the Seine River Forest Management Unit. Aggregate Aggregate Stand Component Stocking Site Class Area Group Number (ha) Coniferous Hardwood Po-1 22 le 40% ge 60% le 40% 2 643 23 1 191 Subtotal 3 834 Po-2 24 le 40% ge 60% ge 50% X& 1 1 220 25 13 799 26 10 450 Subtotal 25 545 Po-3 27 ge 50% le 50% no 2 103 Bf present 28 3 158 Subtotal 5 261 Po-4 29 ge 50% le 50% no 457 Pj/Spruce 30 845 Subtotal 1 302 Total 35 866 Grand Total 177 737 nc - not considered ge - greater than or equal to le - less than or equal to Bf - balsam fir; Pj - jack pine; Spruce - white or black spruce 42 3.3.3 Volume Development Patterns Volume Development Patterns (VDPs) were required to represent the quantity of net merchantable volume in cubic metres (NMm^) which would grow in each aggregation as a function of time. The VDPs used to represent the SRFMU in its present, future, regeneration and spacing (pre-commercial thinning) states were taken wholly, or in part, from the Northwestern Ontario FORMAN Forest Class Definitions (NWOFFCD) developed by Thompson (1990) of the Ontario Ministry of Natural Resources (OMNR). The VDP set produced by Thompson (1990) was based solely on natural stands (i.e. stands not previously harvested). Neither Not Sufficiently Restocked stands (NSR stands) or harvested stands regenerating in the free-to-grow (FTG) state were included in his compilations. Thompson (pers. comm., 1991) noted that the VDPs were based on FRIs completed for the SRFMU from 1981 to 1985. Primary (softwood/coniferous) volumes consisted of combinations of jack pine, spruce-all, white spruce, black spruce, balsam fir, white pine, red pine and larch while secondary (hardwood) volumes were based strictly on poplar. Volume estimates for periods from 120 to 200 years were based almost entirely on professional judgement. The methods used by Thompson (1991) to adjust the stocking levels of stands to a uniform level had some problems, primarily due to the complexity of the procedure used (Appendix VII). In addition to stocking, the aggregation of a variety of combinations of site classes led to very generalized estimates of 43 volume. While the VDPs identified some forest classes (Note; Thompson's forest classes are referred to as aggregate numbers in this study) as having a poor productive capacity, this was likely due to the mixture of high and low productivity sites (e.g. aggregation of site classes X, 1, 2 and 3) into one aggregate. Since the curves must represent the various production potentials, the overall potential was unduly low for some sites and high for others. The aggregations for the SRFMU were the result of finer divisions than those that the NWOFFCD yield curves were based on, so adjustments were required. The changes made were based on the expertise of the Boise Cascade managers, professional judgement and review of literature. Initially, percentage factors were applied to the NWOFFCD yield curve sets. However, a number of the yield curves chosen were modified further. For example, the Pj optimized regeneration and spacing yield curves were based entirely on professional judgement and review of literature. The jack pine aggregations (aggregate numbers 1 to 9) were given optimistic regeneration VDPs. The volume production potential of the sites were adapted from spacing trials studied and projected to sixty years by Bell et al. (1990) (Appendix VIII). Approximately 75% of the volumes found by their projections were used as volumes for the jack pine VDPs. This factor was used to reflect final stand stocking of 80% which exists on most Pj plantations where the plantation stock has grown free of competing vegetation (e.g. poplar) in the crown layer or is Free-To-Grow (FTG) in Ontario (Willcocks et al., 1990) and another 5% to show some conservatism. I believe the result more closely 44 reflected the true productive potential of the individual aggregates while still maintaining the overall forest level productivity. The VDPs used to describe the dynamics of the present management system, along with the present area/age class structure and operability limits for each aggregate, are found in Appendix IX. To aid the reader, the VDPs were grouped by aggregate number to allow for easy scanning from present state to possible future states resulting from the particular management regime. 3.3.3.1 Assumptions Due to limited empirical data for the present forest and especially for the future forest and that the future can never be fully known, many assumptions had to be made regarding the development of the forest aggregates. The assumptions are as follows: 1. Volume development patterns derived from analysis of 1989 FRI data by^ the Ontario Ministry of Natural Resources (the Northwestern Ontario FORMAN Forest Class Definition (NWOFFCD) yield curve set) provided the initial estimates for aggregation productivity; 2. After the aggregate groups were formed, the Boise Cascade managers pointed out which set of curves best fit each aggregate group using 45 expertise and knowledge of the SRFMU and results from management practices. Assumptions developed are as follows; (i) Present and Future Yield Curves All the present and future yield curves were based on the NWOFFCD yield curve set except for the Sp-5 aggregate group. According to specific conditions within aggregates, each of the curves was scaled. Sp-5 (balsam fir) VDPs were created with professional judgement and literature which both supported greater potential productivity than expressed in the NWOFFCD yield curve set. (ii) Artificial Regeneration Yield Curves Pj Forest Type: Artificial regeneration yield curves for the Pj forest type were made by modifying NWOFFCD yield curves, based on curves derived to 60 years by Bell et al. (1990) (Appendix VIII). The assumption used was that 75% of the volumes recorded by Bell et al. (1990) (75% represented an average stocking of 80% less 5% for a conservative estimate for Pj plantations) of the curves presented by Bell et al. (1990) as the maximum volume at 60 years. The curves were then projected to higher values based on Plonski's Normal Yield Tables (Plonski, 1981) and reduced to NMm^ based on Ontario cull tables (Morawski et al., 1958). 46 Sp Forest Type: Regeneration yield curves for the Sp-5 aggregate group (balsam fir) were devised by the author with the aid of supporting literature (Payandeh et al., 1989). Regeneration curves for Sp (other than Sp-5) and Po are modifications of the NWOFFCD yield curve set; percentage factors were used to increase/decrease the volume estimates based on the expertise of Boise cascade managers. (iii) Spacing Volume Development Patterns Spaced Pj and Pr sites have identical development patterns to those they are originating from, except that they become operable 10 to 15 years earlier. (iv) Pr Regeneration Volume Development Patterns Red pine VDPs were formed from the Plonski red pine (Pr) plantation curves (Plonski, 1981). Cull was assumed to be zero for ages younger than 100. Percentage factors were used to reduce the estimates of volume growth to reflect the different growing conditions of the SRFMU (i.e. plantation sites would be on cutovers, not abandoned farmland; the SRFMU has a more northerly location). While the assumptions listed above were a source of concern for the long-range projections made in this study, they also served to point out areas where more 47 research was required. Less dependence on questionable assumptions will ultimately lead to more accurate forecasts. However, Ontario can not afford to move blindly from one forest management system to another. By using assumptions based on professional judgement and available research information, a plausible view of the future can be achieved. 3.3.4 Present Strategy of Management The present strategy of management, from here on referenced as the Business- As-Usual (BAD) scenario, reflects Boise Cascade's system of management used on the SRFMU under normal operating conditions. This management strategy involved wood supply, silviculture, and weed control objectives. 3.3.4.1 Wood Supply Harvest scheduling followed a policy of minimizing softwood volume loss in softwood dominated sites and minimizing hardwood volume loss in hardwood sites. The annual required wood-supply from the SRFMU was 300 000 NMm^ of wood-fibre: 240 000 NMm^ of coniferous wood, (140 000 NMm^ from the jack pine forest type and 100 000 NMm^ from the spruce forest type) and a hardwood (poplar) volume of 60 000 NMm^ obtained both indirectly from softwood sites and directly from hardwood sites. The harvest area necessary to 48 sustain this wood-fibre requirement was approximately 2 200 ha/yr based on past experience. 3.3.4.2 Vegetation Management Vegetation management efforts on the SRFMU were influenced by the FMA, wood-fibre needs (primarily softwood) as previously discussed, and the competition problem the included site preparation, method of regeneration, species planted or seeded, and harvest area (ha/yr). Site preparation (SIP) occurred on 86% of clearcut harvest treatments (1 900 ha/yr), of which 1 600 ha/yr is mechanical and 300 ha/yr is mechanical and chemical SIP. Regeneration of the harvested area included 11 % to natural regeneration (200 ha/yr), 17% was planted (400 ha) which was evenly split between Pj and Sb, 69% of the harvested area (1 500 ha/yr) was seeded to jack pine, and 3% of the harvest area (100 ha/yr) was lost to roads and landings. Herbicide Program: The weed control program consisted of site preparation and tending. Chemical site preparation was allocated to 300 ha/yr; 90% (270 ha/yr) aerially applied and 10% (30 ha/yr) by ground application methods. Tending was performed on 1 200 ha/yr with aerial application of herbicide (Vision®). Funding for the weed control program was considered to be sufficient to implement all needs. A complete account of the silvicultural prescriptions and their associated costs is given in section 3.4. 49 3.4 SILVICULTURE PRESCRIPTIONS AND ASSOCIATED COSTS Silviculture prescriptions are working hypotheses of what treatnnent or treatments are necessary to produce a desirable outcome (Tappeiner and Wagner, 1987). For the BAU scenario, the silvicultural prescriptions were based on the procedures used by Boise Cascade, while for the alternative scenarios, the prescriptions included alternative silviculture treatments not currently used. Silvicultural prescriptions used included one or a combination of: (i) site preparation (mechanical, chemical or mechanical and chemical); (ii) regeneration (natural, seeding or planting); (iii) tending (chemical treatment two years after establishment, two and five years after establishment, or three years after establishment); and (iv) pre-commercial thinning (on virgin, natural, or seeded sites 10-20 years after establishment). The intensity of silvicultural prescriptions was dependent on the potential for hardwood competition on the sites. Thus, poplar stands received no silvicultural treatments while sites with high poplar components (e.g. aggregate groups Pj-2 and Sp-3) received the most intensive silvicultural prescriptions (Table 9). 50 Table 8. Summary of silvicultural treatments and their assumed costs used in the construction of management scenarios. Category Type Specifics Acronym Cost ($/ha) Regeneration Natural N $0.00 Seeding S $7.00 Planting P $630.00 Planting P-L $700.00 Large Stock Site Mechanical Light M $170.00 Preparation Heavy HM $400.00 Heavy HSSM $500.00 Site- Specific Mechanical/ Light MC $310.00 Chemical Heavy HMC $400.00 Tending Chemical C# $140.00 Ground Brush BS# $400.00 Saw Planning Girdling G-# $100.00 to $250.00 Spacing Pre- PCT $400.00 Commercial Thinning 51 3.5 ALTERNATIVE METHODS OF VEGETATION MANAGEMENT AND THEIR ASSOCIATED COSTS In most of the scenarios, it was necessary to maintain a level of vegetation management while either reducing or eliminating the use of herbicides. A variety of alternatives for vegetation management were available as mentioned previously. Alternatives included a pre-harvest girdling program, more effective mechanical site preparation techniques (heavy-mechanical and heavy-site- specific-mechanical), the planting of large, vigorous growing stock, pre- cohnmercial thinning with either brush saw or leader snipping, and ground application techniques for herbicides including stem injection, back-pack sprayers and mechanical methods (e.g. Bracke herbicider). For each of the scenarios, alternatives were selected based on their strategic direction; reduction of herbicides, restriction on how herbicides are applied, elimination of herbicide use, or change in wood supply. 3.5.1 Pre-harvest Girdling Program For a pre-harvest girdling program, the poplar component in treated stands would be girdled two to three years before the scheduled harvest time. Over the time till harvest, the shade-intolerant poplar trees exhaust carbohydrates stored in their root systems since they continually sucker as a reaction to the 52 girdling, but are unsuccessful due to shade from the standing forest around them (Whitfield, 1989). Risks to the wood supply due to this time factor stem from events which could occur to the yet-to-be-harvested stands including fires, windthrow, pests, or deterioration of the poplar component into an unusable state. It was assumed that the necessary work force required for a girdling program on the SRFMU would be available, primarily since girdling can be done in any season and thus timed with labour availability (Bell pers. comm, in Sept., 1991). Another assumption was the unrestricted availability of the necessary girdling tools. Several girdling tools are often needed for any one stand, and some tools such as the L'il Beaver Power Girdler® have restrictions on their use (Whitfield, 1989). Pre-harvest girdling treatments were scheduled for mature and overmature stands. The costs Involved with a girdling program for a mature forest are dependent on the tools used (e.g. L'il Beaver mechanical girdler), operator experience and expertise, terrain, stand density, and debris. In determining the costs, because the forecasts are long term, it was assumed that the tools would be available, experienced labourers would be available, and that the entire area of the two aggregate groups with a 10 to 20% poplar component (Sp-3 and Pj-3) would be treatable. 53 Costs of girdling programs could vary considerably, dependent on the factors listed above. The most optimistic figures available, which were adapted to the cost figures in this study, were with the L'il Beaver, with costs of $0.75 to $1.25 per tree on average (Whitfield, 1991). Stem counts were obtained from Plonski's Normal Yield Tables (Plonski, 1981) at representative ages (when harvesting was expected to occur) and then multiplied by a factor of 15% to derive rough estimates of the number of stems to be girdled and thus the girdling costs per hectare. This percentage represents the average poplar component of stands which would be considered for a pre-harvest girdling treatment. The costs derived were as follows: Site Class Cost ($/hectare) P]:3 Sp-4 X+1 100 200 2 150 250 3 200 3.5.2 Mechanical Site-Preparation Techniques The aim of mechanical site-preparation is to create conditions which will allow for planting, sowing, and/or natural regeneration (Sutton, 1985, 1990, Stewart, 1987; Orlander et al., 1990) to secure the survival and growth of the growing 54 stock for the following tree crop (Nutter and Douglas, 1978). Recently, the trend has been towards more effective, site-specific systems (Hunt and McMinn, 1988; Hunt, 1989; Orlander et al., 1990). The use of more site-specific prescriptions could improve control of adverse factors which affect seedling survival and growth (McMinn, 1982). In consideration of the advantages of SIP listed above. Heavy Mechanical (HM) and Heavy-Site-Specific"-Mechanical (HSSM) site preparation were designated for use on areas where chemical treatments were either reduced or omitted. Planting of high-quality planting stock on areas given a good treatment of site preparation has been shown both empirically and through experimentation to reduce or eliminate the need for later tending treatments (Stewart, 1987). involved the use of more severe methods than the light site preparation (i.e. TTS disk trenching, barrels and chains, and Bracke mounding) used in BAU management. The methods envisioned involved root rakes, ploughs or large mounds to reduce competition from undesirable vegetation. The cost of HM site preparation was set at $400/ha (OMNR, 1986^; Bell, 1991) which relates to a 235% increase over normal BAU site-preparation costs ($170 per ha). would use a variety of tools for site preparation, when necessary, on individual harvest blocks. The use of a single site-preparation treatment over large blocks with diverse landscapes and conditions was 55 deemed inappropriate for the affected aggregates of this study. Because of increased costs for management (i.e. in planning specific SIP treatments for the treatment sites), capital investment for various SIP tools, transportation and supervision costs, the costs for HSSM treatment were set at $500/ha (294% increase over BAU SIP costs). 3.5.3 Planting of Larger Growing Stock The first few years in the development of planted conifers is well known to be the major determining factor of their future survival and productivity (Simith, 1986; Stewart, 1987; Walstad and Kuch, 1987^; Bell, 1991; Day, 1991 and Towill et al., 1992). Large growing stock has the capacity for larger height increments in the establishment phase than small stock; thus, it can better match the height growth of competing vegetation (Towill et al., 1992). Larger stock is also less susceptible to frost heaving and rodent damage than smaller stock (Towill et al., 1992). Less restricted growth due to the use of large planting stock would allow for faster establishment on very productive sites, especially when used in combination with effective methods of site preparation (Stewart, 1987). The cost for planting larger growing stock was set at $700/ha for both pine and spruce species (a 10% increase over that for norma! sized stock). 56 3.5.4 Manual Thinning Treatments Manual thinning/weeding treatments are used to remove competing vegetation (usually hardwoods but sometimes conifers also) and to space the desired vegetation (usually conifer species) to give remaining trees more growing space, sunlight, nutrients and water (Day, 1991). Manual methods used for these programs include sandviks, chain saws, brush saws and just recently, leader snipping/clipping (Anon;, 1991). The cost for a manual thinning treatment was set at $400/ha. While leader clipping was demonstrated to be both faster and safer than using brush saws, and thus less expensive (40%), this technique was still in the experimental stage (Anon., 1991). 3.5.5 Ground Application Techniques for Applying Chemicals Like aerial chemical application, ground application of herbicides was used to control competing hardwood vegetation. The advantage of using ground application techniques is that a higher level of control is possible during application which can reduce the risk of unexpected drift. Disadvantages include higher insurance costs, higher level of exposure to chemicals for the on- ground personnel, and more difficult supervision of the work (Bell, pers. comm., 1991). Ground application of herbicides would include both site-preparation and tending treatments. 57 For site preparation, a method of ground application which was being experimented with by Boise Cascade was the Bracke herbicider. This machine is capable of scarifying and applying herbicide (liquid or granular) at the same time. For tending, mist blowers carried by either machines or personnel could be used. The cost for ground site preparation was set at $310/ha (based on $140/ha for glyphosate and $170/ha for Bracke SIP) and tending costs with mist blowers was set at $300 per hectare (based on $200/ha for glyphosate and $100/ha as the rate for personnel). 3.5.6 Summary of Alternative Silviculture Treatments The alternative treatments described above all serve to meet the demands of management strategies devised to change the amount of or the way in which herbicides were used. Thus, it is the change in the decision variables (cost, area treated and forest level wood supply) from the current levels which is important to understand. As shown in Table 9, there are 16 silvicultural prescriptions used as alternatives. Each prescription has associated responses and was used in one or more management strategies. 58 Table 9. Summary of alternative silviculture treatments and changes from the BAU scenario used in alternative management strategies. A Delta (change) 59 3.6 DECISION RESPONSE VARIABLES To simply the reporting and decision making process, key response variables were chosen. Since the effect of a change in herbicide use policy on forest management was the question to be answered, herbicide use and wood supply were two obvious variables. A third variable, silvicultural cost, was also selected due to the increasing reliance on industry by the provincial government, to fund their own silvicultural programs. 3.6.1 Wood Supply Wood supply response variables were used to gauge changes that occurred as a result of modifications in management. Since the volume levels harvested from each forest type were not fixed for all the scenarios (the two FWS scenarios had flexible levels), a variable which could be compared independently of the sustainable harvest levels was needed. Thus, the response variable chosen to represent wood supply was Average Harvest Volume per Hectare (AHVH). Average annual harvest area was calculated by averaging the periodic (5-year) totals from the FORMANCP short reports and then dividing by five. Average harvest volume per hectare was calculated by dividing the sustained harvest volume by the average annual harvest area. 60 3.6.2 Herbicides Treatment activity, or the number of hectares treated with herbicides in any one year, was selected as the response variable for herbicide use. Determination of treatment area was a simple bookkeeping task completed under FORMANCP. As noted previously, FORMANCP allows harvest costs to be specified when making simulation runs. This cost file was used to yield TA values in the following manner: Reviewed the silviculture prescriptions for each aggregation (e.g. Pj-2, site class X&1; aggregate number 4) and determined the number of times herbicides were applied to particular forest areas (e.g. one hectare of aggregate number 4 treated with silviculture received herbicides three times: once from mechanical-chemical SIP and two more from tendings 2 and 5 years after planting and thus its treatment area was three) 2. Determined what forest classes received "x" number of herbicide treatments. For example, for the jack pine forest type under the BAD scenario, three aggregates (Pj-4, Pj-5, and Pj-6) could receive three herbicide treatments when treated with silviculture, while three other Pj aggregates (Pj-7, Pj-8 and Pj-9) could receive only one herbicide treatment); 3, Produced a treatment area file (a modified cost file) which described all possible development pattern transfer routes which would result in herbicide treatments being scheduled. Instead of using a cost, a value of "1000" was used (since FORMANCP summarizes this field in thousands); 61 Treatment area file for jack pine aggregations that receive 3 treatment of herbicide for every silviculture treatment scheduled. -9 45 35 25 0.040 11 46 1000 12 46 1000 13 47 1000 14 471000 46 46 1000 47 47 1000 4. Produced runs with each treatment area file for the forest types which received silvicultural treatments (Pj and Sp); 5. Summarized results from the short reports for every time period and multiplied by their corresponding number of treatments to yield treatment area responses. A complete example of TA derivation is supplied in Appendix XI. 3.6.3 Silviculture Costs The cost of the silvicultural treatments for each management strategy was an important indicator since the cost of alternative treatments was so variable and because cost is something which is easy to relate to for most people. To include changes in time of investment as well as level, discounted values were used. These values were direct outputs from the FORMANCP simulation program. 62 3.7 ALTERNATIVE MANAGEMENT STRATEGIES Management strategies define goals and objectives and express a plan for how they are expected to be achieved, and the rules and limitations which guide their actions. Thirteen strategies were devised for this study by myself, my supervisor, and the forest managers of Boise Cascade. The twelve alternative scenarios are explained based on how they differ from the BAU scenario (Table 9). 3.7.1 Reduced Herbicide Use There were two paths which could be followed in a reduced herbicide program scenario. One strategy would have been to reduce herbicide application rates for the forest by specific amounts and therefore leave the program unchanged except for the amount of active ingredient applied to the forest. The second strategy involved the removal of areas to be treated from the herbicide program. This choice of the second herbicide reduction strategy was based on the following assumptions: 1). Decrease of the application rate of herbicides applied could decrease the efficacy of the herbicide for control of competing vegetation, thereby increasing the chance of retreatment and increasing total herbicide use; 63 2) A reduction in area treated not only maintains the efficacy of the herbicides, but also leaves larger areas untreated and increase the need for alternative vegetation management practices; and 3) With the advent of new ultra-low-volume herbicides able to effectively control vegetation at very low levels of active ingredient (e.g. <0.25 kg/ha a.i.), the kilograms of herbicide use becomes a misleading statistic (Wagner pers. comm., 1991), Three levels of herbicide reduction were selected for this study; 33, 50 and 60%. 3.7.1.1 67% Herbicide Program (67HP) Scenario To achieve the 33% reduction in the treatment area of the BAU herbicide program, a pre-harvest girdling program was planned for stands with a 10 or 20% poplar component, which normally would be tended once, three years following planting. The two aggregate groups in the SRFMU fitting this description are Pj-3 and Sp-4, which together make up 28% of the total area (30 361 ha and 19 470 ha respectively). The yields from these two aggregate groups were assumed to be the same as if treated with herbicides, since if properly orchestrated, pre- harvest girdling effectively removes the threat of poplar sprouting and suckering after harvest. 64 The wood-supply results for this scenario remained constant with the BAU scenario since yield was assumed to be maintained. However, the area treated with herbicides, the amount of herbicides applied in the forest and the costs changed. Due to restrictions in FORMANCP, the numbers reported represent averages over five-year periods. For example, when a stand in aggregate number 4 (Pj-2; Scl X-i-1) was harvested and then scheduled for regeneration, it was assumed to receive a mechanical/chemical site preparation and two chemical tendings. The chemical tendings were given at two and five years after planting; however, the treatment activity was tabulated immediately (i.e. three hectares treated for every hectare regenerated) even if the treatments did not occur till the next 5-year time period. It was assumed that the numbers will average out over time. A complete account of the silvicultural prescriptions and their associated costs is supplied in Appendix X. 3.7.1.2 50% Herbicide Program Scenario The 50% Herbicide Program (50HP) scenario was used to explore the effects of a 50% reduction in treatment activity. The 50% reduction was achieved by using the assumptions of the 67HP scenario and also removing the Sp-5 aggregate group from the herbicide program. Of the five aggregate groups in the Spruce forest type, the Sp-5 aggregate group had the highest planting priority (it received treatment before all others) and thus was expected to produce the additional 17% reduction. This aggregate group would normally have been planted to black spruce, mechanically site prepared and chemically tended two and five years 65 after planting. To replace the use of chemicals in the silvicultural treatment of these sites, a pre-harvest girdling treatment was employed on sites containing poplar, in addition to heavy mechanical site preparation and the planting of large black spruce stock. Heavy mechanical site preparation was expected to remove advanced balsam fir regeneration and larger planting stock was assumed to give crop trees an edge over competition on the site. A complete account of the silvicultural prescriptions and their associated costs is supplied in Appendix X. 3.7.1.3 40% Herbicide Program Scenario The 40% Herbicide Program (40HP) scenario was devised to reduce herbicide treatment activity by 60%. Again, the assumptions of the 67HP scenario applied here. However, to reduce the treatment activity to 40% of BAD levels, changes were made to the silviculture treatments of three additional aggregate groups: Pj-2, Sp-3, and Sp-5. The silvicultural prescription for the Pj-2 aggregate group was changed to heavy mechanical plus chemical site preparation (HMC), planting of large jack pine stock (SCL X+1 and 2) and seeding of jack pine (SCL 3) and only one chemical tending (rather than two). Aggregate group Sp-3 had a silvicultural prescription of mechanical plus chemical site preparation, planting to black spruce and two chemical tendings in the BAU scenario. For this aggregate tendings were reduced to one and HMC site preparation was used in combination with the planting of large black spruce stock to maintain control over competing 66 vegetation. The Sp-5 aggregate group's BAU silvicultural prescription of mechanical site preparation, planting of black spruce and two chemical tendings was changed to conform to one chemical tending. To accomplish this, heavy mechanical site preparation (HM) and planting of large black spruce stock was used. These prescriptions and their associated costs are tabulated in Appendix X. 3.7.2 Restricted Herbicide Use Restrictions are often imposed on forest management and they are likely to occur in the future in one form or another. Two types of restricted use were investigated in this study; aerial tending as the only type of herbicide treatment (i.e. site preparation with herbicides was not allowed) and no aerial application of herbicides (i.e. herbicides could be used but only when applied from the ground). The Aerial-Tending-Only (ATO) scenarios were developed to investigate the implications of using only aerially-applied chemicals for tending. Alternatives were used in place of the chemical site-preparation used in the BAU scenario. The two alternatives implemented were HM and HSSM site preparation. The first two scenarios, ATO-A and ATO-B employed HM site preparation, while in the ATOrC scenario, HSSM site preparation was used. Changes to the volume development patterns and treatment costs were also made for each scenario as follows: 67 (i) ATO with reduced/delayed conifer volumes but with BAU site preparation costs (ATO-A); (ii) ATO with reduced/delayed conifer volumes and higher site preparation costs (ATO-B); and (iii) ATO with conifer volumes maintained and considerable increases in site preparation costs (ATO-C); 3.7.2.1 Aerial-Tending-Only-A Scenario The ATO-A scenario used HM site preparation rather than mechanical-chemical (MC) site preparation. The two aggregate groups affected are Pj-2 and Sp-3. For this scenario, these aggregate groups were assumed to lose 15% of their primary volume which reappeared as poplar (secondary) volume. There was no cost increase associated with this change since the cost of HM SIP was assumed to be the same as the cost of normal mechanical site preparation ($170/ha) for this scenario. All assumptions are tabulated in Appendix X. 3.7.2.2 Aerial-Tending-Only-B Scenario The Aerial-Tending-Only-B (ATO-B) scenario was developed to shed light on the implications of higher costs in addition to the reduced yields specified in scenario ATO-A. The cost of HM SIP was increased by $230 to $400 per hectare. These changes as well as the changes in volume development patterns are tabled in Appendix X. 68 37.2.3 Aerial-Tending-Only-C Scenario The ATO-C scenario was developed under the assumption that with HSSM used to replace chemical site preparation, the yield expectations of the BAD scenario could be maintained. Thus, there were no differences in the associated yields, however, silvicultural costs increased by $330 per hectare (since HSSM SIP costs $500/ha while normal SIP costs only $170/ha). These changes and all other assumptions are tabled in Appendix X. 3.7.2.4 No-Aerial Application Scenario The No-Aerial-Application (NAA) scenario was devised to accommodate public concerns for aerial spraying of herbicides. In this management scenario, aerial application of herbicide was not allowed; instead herbicides were applied exclusively with ground application techniques for both SIP and tending. Thus, the changes made involved a switch to ground application systems for chemicals. While the mode of application and the respective costs were changed from the those of the BAU scenario, volume development patterns are assumed to remain the same. Specific changes of treatments and their associated costs are listed in Appendix X. 69 3.7.3 No Herbicide Use These scenarios were developed to investigate the possibility of not using herbicides at all but still maintaining a high level of competition control. The Other-Weed-Control (OWC) scenarios were used to investigate the effects of using alternatives to herbicides for ail vegetation management practices. Vegetation management treatments used included pre-harvest girdling, PCT, and HSSM site preparation.- Sites which were not treated with herbicides in the BAU scenario were not changed. Two OWC scenarios were developed to test the sensitivity of silviculture treatment response (i.e, wood-fibre production): (i) OWC with BAU conifer volumes and increased silviculture costs (OWC-A); and (ii) OWC with decreased BAU conifer volumes and increased silviculture costs (OWC-B); 3.7.3.1 Other-Weed-Control-A Scenario For the Other-Weed-Control-A (OWC-A) scenario, the assumption that the alternative vegetation management practices would yield the same output as the BAU scenario was made. However, costs of ^he alternative treatments were higher than the treatments used in the BAU scenario. All the assumptions made for the OWC-A scenario are tabled in Appendix X. 70 3.7.3.2 Other-Weed-Control-B Scenario The Other-Weed-Control-B (OWC-B) scenario was identical to the OWC-A scenario in its assumptions of alternatives to herbicides and costs; however, it was assumed that there were volume losses due to the exclusion of herbicide use in some of the aggregate groups. Aggregate groups Pj-2, Sp-3 and Sp-5 lost 15% of their BAU volumes and aggregate group $p-1 lost 10% of its BAU volume. The Sp aggregate was assumed to lose 5% volume less than the Pj aggregate since spruce is a more tolerant species and slightly less effected by poplar competition. The two aggregate groups which were treated with pre- harvest girdling (Pj-3 and Sp-4) were assumed to retain their volumes as were Pj- 1 and Sp-2 which were unchanged. Assumptions made for this scenario are listed in Appendix X. 3.7.3.3 No-Weed-Control Scenario The No-Weed-Control (NWC) scenario explored the consequences of not using tending treatments at all, either chemically or manually, for silvicultural prescriptions. Instead, emphasis was placed on site preparation techniques and use of larger, healthier planting stock. The HSSM SIP treatment was employed on all sites which were site prepared in the BAU scenario. Large planting stock was used for all sites normally planted (both Pj and Sb) and reductions in the coniferous component of volume 71 development patterns were made. Aggregate groups Pj-1, Sp-1 and Sp-2 (except for Aggregate number 12) lost 10% of their primary (coniferous) volume and gained 10% in their secondary (hardwood) volumes. Aggregate groups Pj-3, Sp-4 and Sp-5 all lost 15% of their primary volumes and gained 15% in their secondary volumes, while aggregate groups Pj-2 and Sp-3 both lost 20% of their primary volumes, which was gained in their secondary volumes. The assumptions made in discerning what percentage decrease should be placed on what sites were based primarily on common sense. The more drastic the change from BAU silvicultural specifications, the larger the decrease in primary volume. The limits of volume decreases from 10 to 20% were judgement calls made on the basis of experience with sites which were treated with HSSM in the past and some speculation on the advantage of using larger planting stock. These assumptions are all tabled in Appendix X. 3,7.4 Wood Supply Change The wood supply change scenarios were devised to examine some of the implications of new pulping facilities which would be capable of using all types of wood fibre in any proportion. Two Flexible-Wood-Supply (FWS) scenarios were formulated to investigate the implications to herbicide use: FWS where management took advantage of the natural regenerative nature of the forest. Decreased conifer 72 volumes, increased hardwood volumes and zero artificial regeneration levels and costs were assumed; and (ii) FWS where management took advantage of the most productive coniferous tree.species (jack pine and red pine) by use of intensive silviculture (a combination of site preparation, seeding or planting, chemical tending, and PCT where necessary) and the natural regenerative ability of poplar. Spruce was omitted from harvest scheduling altogether due to its low productivity in relation to pines and poplar. Increased conifer volumes, decreased hardwood volumes and increased silviculture costs were assumed. Silviculture levels were increased for the jack pine aggregations to ensure the necessary amount of wood-fibre is produced. 3.7.4.1 Flexible-Wood-Supply-N Scenario The Flexible-Wood-Supply-Natural scenario (FWS-N) was perhaps an abstract concept since pulping facilities are dependent on particular mixes of wood fibre to produce their desired products (e.g. newsprint). However, in the event of technological advancement to the point that this restriction no longer holds, and chemicals are prohibited for use in forest management, how would the structure of the forest be affected over time? The FWS-N scenario reviewed possible 73 effects of using any type of wood fibre and natural regeneration. Since only natural regeneration is used, there are no post-harvest silvicultural prescriptions or associated costs (Appendix X). 3.7.4.2 Flexible-Wood-Supply-GW Scenario The Flexible-Wood-Supply-GW (FWS-GW) scenario was the most presumptuous of the scenarios created in this study. Wood fibre was harvested only from the Pj forest type (211 000 NMm^/yr), the Po forest type (59 000 NMm^/yr) and their fallout volumes (30 000 NMm^/yr). While the Po forest type was managed as in the BAU scenario (i.e. with natural regeneration), the Pj forest type received considerable change to its silvicultural program including an increase in the maximum annual PCT treatment area which was increased to 1 100 ha/yr. The most significant additional treatment was the planting of red pine (Pr) on the most productive Pj forest types (i.e. site class X+1; aggregate numbers 1,4 and 7). Other differences in the silvicultural prescription included a pre-harvest girdling treatment for the Pj-3 aggregate group (replaced two chemical tendings for aggregate numbers 7, 8 and 9) and one chemical tending (rather than two) for aggregate number 4 (assumed that the planted Pr will keep up to or exceed the growth of competing vegetation on this site). All of these assumptions can be found tabled in Appendix X. 74 3.8 SENSITIVITY ANALYSIS Sensitivity analysis is an important procedure used to discover relationships which exist between data and a dependent response variable. When dealing with questionable data, forecasts/estimates produced from it are always suspect. While sensitivity analysis can not improve the accuracy of the estimates, it can provide additional insight to critical data-response relationships. It is for this reason that sensitivity analysis has been used so widely in forest-related studies. Some examples of the use of sensitivity analysis in forestry include: habitat supply analysis (McCallum, 1993), economic analysis (Williams, 1991; Willcocks etal., 1990), and wood-supply analysis (Hauer, 1989; Willcocks etal., 1990). Data were deemed sensitive if minor changes to them resulted in major changes in the response variable. An example of such a situation would be a 30% increase in the value of "y" response variable due to an increase of 10% in the value of "x" data. If this relationship also holds true for other positive and/or negative modifications of x values, then the relationship may be described as a ratio; in this case, a 1:3 ratio which would indicate that for every 1 % change in x, there will be a 3% change in y. 75 In this study, the x-data in question were the Volume Development Patterns (VDPs). A considerable amount of professional judgement was used to describe the volume development patterns since there was little empirical evidence to support their creation, especially those which represented responses to artificial regeneration treatments. Steps in the sensitivity analysis included: (i) Identification of a response variable; (ii) Determination of the response variable elements to be tested; (iii) Setting of levels of change in the data to provide for adequate interpretation of the data-response relationships; (iv) Altering the data and running the model to produce the responses; and (v) Analysis and interpretation of the data-response relationships. Average Harvest Volume per Hectare (AHVH) was chosen as the response variable because of its inherent links to both wood-fibre productivity and harvest scheduling. The relationship tested was the change in AHVH resulting from changes to the VDPs of the BAD scenario. Analysis of only the BAU VDPs was assumed adequate for this sensitivity analysis .since the minor changes which did occur in the VDPs of the other scenarios affected only the values of the patterns - their general shape was maintained. 76 The VDPs were analyzed in groups based on their function in the wood supply of the management scenario. Groupings of VDPs were chosen to enable an effective and efficient analysis of what would have been an infeasible task {i.e. testing the VDPs individually and in their numerous combinations with each other). These groups were as follows: (1) All VDPs used to describe the forest; (2) VDPs for future (natural) and regeneration (seeding, planting and PCT) forest; and (3) VDPs for the regeneration forest. Interpretation of the results from the three groups provided insight into effects of other groupings of VDPs; (1) Response due to present forest VDPs = Group 1 response - Group 2 response; and (2) Re.spnn.se due to future forest VDPs = Group 2 response - Group 3 response. In addition, each forest type (Pj and Sp) was run separately under FORMANCP, which pinpointed sensitivity further. Adjustments to the VDPs (Figure 4) included: (1) scaling (multiplication of the data by a factor which increased or decreased its value by a specified percentage) of the entire pattern; (2) scaling of the peak (maximum) values in the pattern; and (3) scaling of the tail values 77 Scaling of Development Patterns for Sensitivity Analysis Initial Curve — All Values Scaled Peak Values Scaled Tail Values Scaled Figure 7. Representation of changes made to a volume development pattern for sensitivity analysis. (values representing over-maturity and volume loss). The specific scaling factors used are shown in Table 10. 78 Table 10. Scaling factors used to increase and decrease the three groupings of volume development patterns for use in their sensitivity analysis. Changes Scaling of Volume Development Patterns (%) Entire VDP Peak Values Tail Values 1 + 15 30 30 2 + 10 -h 20 20 3 + 5 + 10 + '10 4 - 10 - 10 - 10 5 -20 -20 -20 6 -30 -30 -30 The response variable, average harvest volume per hectare, was calculated by dividing the average periodic (5-year total) harvest volume by the average periodic harvest area. Due to the low utilization of the poplar forest type, as demonstrated in the basic analysis, sensitivity analysis was not performed on it (i.e. less than 5% of annual harvest area for the BAU scenario occurs in the Po forest type). Responses to adjustments of the VDPs of the Pj and Sp forest types were then summarized to give insights into their effects at the forest lev✓e l. An additional level of interpretation was made on the forest types individually. 79 4.0 RESULTS AND DISCUSSION 4.1 PRESENT MANAGEMENT The BAU scenario for the SRFMU was feasible; however, there were some areas of concern. The spruce forest type could not produce the volume desired by the company, the jack pine forest type had untapped potential, the poplar forest type was not fully utilized, and there were large fluctuations in the chemical treatment activity over the 100-year forecast period. 4.1.1 Wood Supply Potential problem areas revealed from the wood-supply analysis were as follows: (i) The spruce.forest type was able to provide only 91 000 NMm^/yr with a planting program of 200 ha/yr. (ii) The balsam fir forest type had the potential to produce an annual harvest of 21 000 NMm^ after seventy years if all harvested areas in 80 the first 30 years were planted to spruce. At this point it was decided that the balsam fir forest type would be run with the spruce forest type, since the sites were being converted to black spruce; (iii) Conversion of poplar to black spruce was found to be impractical in consideration of the poor availability of Sb planting stock for the SRFMU. (vi) Poplar harvest areas were determined by first considering the poplar yields from harvests in the Pj and Sp forest types. After deciphering the nature of these problem areas in managing the Seine River forest, the simulation process was initiated for the BAD scenario. The forest types were simulated in the following order: 1. Spruce Forest Type; 2. Jack Pine Forest Type; and 3. Poplar Forest Type. The spruce forest type was run with a harvest level of 91 000 NMm^/yr and a planting level of 200 ha/yr (Appendix XII); as shown in Figure 8, this was its maximum sustainable harvest level. Regeneration efforts remain constant at the -81 maximum of 200 ha/yr but harveatfe>^s fluctuate dramatically during the 65- to 100-year time period, which relates to the harvest of regenerating areas in their early stages of operability (Figure 9). At a harvest level of 149 000 NMm^ the primary growing stock decreases dramatically from approximately 6.2 million NMm^ to 1.5 million NMm^ at 45 and 65 years (Figure 10) and from 70 to 100 years, it increases to 3.5 million NMm^. (Appendix XII). The areas harvested and regenerated remain identical at around 1 020 ha/yr and the areas spaced remain steady at the maximum of 100 ha/yr (Figure 11). The spruce and jack pine forest types yielded an average of 32 000 NMm^/yr and 12 500 NMm^/yr of poplar wood-fibre respectively which meant that only 16 000 NMm^yr was required directly from the poplar forest type (Appendix XII). Figure 12 shows the effect that the low Po harvest level has on its operable volume: areas aging are larger than the harvest level which results in a decrease in net merchantable volume levels of poplar growing stock. Figure 13 illustrates the low harvest levels (an average of 152 ha/yr) which are partially responsible for the above shifts in growing stock. The final volumes achieved in the BAU scenario were 149 000 N,Mm^/yr of Pj, 91 000 NMm^/yr of Sp, 6 000 NMm^/yr of miscellaneous conifer and 60 000 NMm^/yr of Po for a total wood-supply of 306 000 NMmVyr (Table 11 and Figure 14). 82 Spruce Forest Type | iPrImory Growing Stock and Harvest % : Growing Stock VoL >»M««S4iKWi»SSSa!5S:< I 2000 - 2- I 1500 •••- mimiiiiiiiiiiiii Time (y«arv. Figure 8. The Spruce Forest Type's primary growing stock and harvest volumes at five-year intervals in time for the BALI scenario. 83 Figure 9. The Spruce Forest Type's harvested and regenerated areas as a function of time for the BAD scenario. 84 Figure 10. The Jack Pine Forest Type's primary growing stock and harvest volumes at five-year intervals in time for the BAD scenario. 85 Figure 11. The Jack Pine Forest Type's harvested, regenerated and spaced areas as a function of time for the BAU scenario. 86 4000 I Growing Stock VoL g 3500 3000 2500 2000 1500 1000 500 ft . • 0 20 40 «0 80 100 10 30 50 70 90 Firne Figure 12. The Poplar Forest Type's primary growing stock and harvest volumes at five-year intervals in time for the BAD scenario. 87 Figure 13. The Poplar Forest Type's harvested and regenerated areas as a function of time for the BAU scenario. 88 Forest-level Harvest Softwood ^ SW Growing Stock ^S\N Harvest Figure 14. Softwood fibre supply and harvest level for the BAU scenario. 89 Table 11. The wood-supply and regeneration for forest level analysis of the Seine River Forest Managennent Unit under the Business-As-Usua( management scenario. Forest Type Wood-Supply Regeneration Softwood Flardwood Planted Seeded Spaced (NMmVyr) (NMm^yr) (ha/yr) (ha/yr) (ha/yr) Spruce 91 000 32 000 200 Jack Pine 149 000 12 000 151 869 100 Poplar 6 000 16 000 Total 246 000 60 000 351 869 100 90 To supply 100 000 mVyr of softwood fibre from the Sp forest type, the planting program would need to be increased to at least 600 ha/yr; a.level 200% higher than could be supplied in 1991. However, the jack pine forest type easily provided its wood-supply requirement. If a large spacing program, say 1 600 ha/yr, was implemented (a level exceeding the area seeded per year) in addition to the present regeneration specifications, a maximum sustainable yield of 204 000 NMm^/yr could be achieved. Since seeding was the predominant method of regenerating-jack pine sites in the Seine River Forest, a larger PCT program should be considered for the management of those sites to decrease operational rotation periods and thus its maximum sustainable yield. The poplar forest type could have provided much more volume. The stands lost volume due to aging and a slow conversion to coniferous stands. While this was desirable due to the market area's low demand for poplar wood fibre, the sites could have been much more productive if managed as poplar-producing stands. For more intensive poplar management to occur, a market would be necessary such as if the Boise Cascade mill could use a higher proportion of poplar. 91 4.1.2 Herbicide Use Herbicide use occurred primarily within the jack pine forest type, as a result of its large regeneration program. The periods where high levels of TA occurred (40 to 55 years into the forecast), which were a result of sudden rises in the areas required to be planted rather than seeded (i.e. sites which were given three treatments of herbicides), would likely be difficult to implement at an operational level (Figure 15). However, Kirby (pers. comm., 1991) stated that the company was seriously thinking about a jack pine forest type regeneration program comprised of 100% seeding. If, in addition to this change, mechanical and chemical SIP were performed on most if not all the sites, there could be a reduction in yearly herbicide use due to a reduced need for chemical tending of these sites. This option would be even more effective with the inclusion of PCT treatments after 10 to 20 years of stand development. Pre-commercial thinning treatments would serve not only to space the jack pine stems, but also to weed 92 Treatment Activity j BAD Scenario | 3000 ; * 2500 i \ 2000 •• o £ 0 20 40 60 60 100 10 30 50 70 90 lime (yrs) Figure 15. The average annual treatment activity in the BAU scenario for the 100-year forecast period. out unwanted competing vegetation such as poplar, paper birch and pincherry. 4.2 ALTERNATIVE MANAGEMENT 4.2.1 Reduced Herbicide Use The scenarios used to investigate a policy of reduced herbicide use (67HP, 50HP and 40HP) were revealed in this study to be very promising alternatives (Note: simulation reports of the basic analysis for all scenarios are supplied in 93 Appendix XII). Volume output remained consistent with the BAU scenario and annual average silviculture costs increased by less than 3%.for the three herbicide reduction scenarios. In addition to the desired reduction in treatment area, there are several other advantages which occur from these scenarios. With a herbicide reduction policy, herbicides were retained as a silvicultural tool. With the impetus put on the reduction of treatment areas rather than a reduction in the total amount of herbicide used, forest management was directed toward use of alternative methods of vegetation management as well as more-site- specific use of the tools. With a wider variety of silvicultural tools available and a large, trained workforce, the costs of vegetation management alternatives perhaps could decrease and possibly deliver more socially acceptable forest management program. 4.2.2 Restricted Herbicide Use The Aerial-Tending-Only scenarios (ATO-A, ATO-B and ATO-C) were also shown to be economically feasible alternatives. While Boise Cascade relied heavily on mechanical site-preparation, chemical SIP was only starting to be used (300 ha/yr), so changes in the wood supply, treatment area and cost response variables, due to the elimination of chemical SIP, were minor. 94 While restriction of herbicide application to ground methods (NAA scenario) did not change either wood supply or treatment area, silvicultural costs for were increased by 28%. 4.2.3 No Herbicide Use Although the Other-Weed-Control scenarios (OWC-A and OWC-B) were still viable options with regard to wood supply, harvest area increased over time due to the less effective alternative silviculture treatments and costs were substantially higher (a 37% increase in annual silviculture costs for both). The substantial increases in silvicultural costs occurred because of the assumption that non-herbicide treatments were more expensive. However, if the costs of these treatments were to decrease to levels more comparable to herbicide treatment costs, rather than remain fixed, the differences would likely be much lower. The No-Weed-Control scenario was an extreme approach to vegetation management in that only non-chemical SIP was allowed. The increase in silvicultural costs for this scenario was the second highest of the scenarios tested. Softwood volume output per hectare was substantially decreased due to lower future yield expectations, which resulted in a higher average annual harvest area. However, the volume requirements for the mill were still maintained and the forest received no herbicides. 95 4.2.4 Wood Supply Change The FWS scenarios assumed changes in the wood supply requirements and the silvicultural prescriptions; Thus, a more thorough review of their results is given for each scenario individually. Flexible-Wood-Supply-GW: The wood supply requirements were taken from the Pj and Po forest types only in this scenario. The Pj forest type was able to sustain an average harvest of 213 000 NMm^/yr of softwood volume and an average of 20 200 NMmVyr of hardwood volume with an average harvest area of 1 531 ha/yr. The remainder of the wood-supply requirement was obtained from the Po forest type with 59 000 NMm^/yr of hardwood volume and 9 600 NMm^/yr of softwood volume from an average of 503 ha/yr. The Sp forest type was not directly managed for wood supply which essentially meant a 38% decrease in the wood-supply landbase. Treatment activity decreased by 40%, but average annual silviculture costs increased by 57%, due primary to the large increase in the pre-commercial thinning program. The major advantages of this scenario were that the landbase required to fulfil the wood supply and TA were decreased, and the productive potential of the forest was used. Of course, this required a substantial silvicultural investment on the lands which were intensively managed and it assumed that the industry would invest capital to develop pulping facilities capable of using any type of wood fibre. It is difficult to measure many of the possible advantages of such a 96 scenario. Perhaps the annual area cost charged by the government could be decreased since the Sp forest type was not being harvested or maybe the Sp forest type area could be developed for some other profitable purpose. In any case, use of a scenario such as this would broaden the scope of management. Flexible-Wood-Supply-N: The FWS-N scenario also differed considerably from the BAU scenario. These differences included changes in the source of the wood supply, the silvicultural treatments, the economic figures and the final structure of the forest. The wood-supply requirements were taken first from the Po forest type, then the Pj forest type and finally from the Sp forest type. This order followed a decreasing capability for natural regeneration and productivity of the three forest types. When the maximum sustainable yield was attained from the Po forest type, wood fibre was extracted from the Pj forest type with the Sp forest type used to top it off. The wood supply was obtained from the Po forest-type (27%), the Pj forest type (50%), and the Sp forest-type (23%) as shown in Table 12. 97 Table 12. Wood-supply harvest levels for the FWS-N alternative management scenario. Forest Type Wood-supply Volumes Total ('000s NMm^) Conifer Poplar Volume % ('000s NMm^) Po 10 72 82 27 Pj 130 19 149 50 Sp 50 19 69 2^ Total 190- 110 300 100 The harvest area averages for the Po, Pj and Sp forest types were 697, 1 085 and 480 ha/yr respectively for an total average yearly harvest of 2 262 ha/yr, which was 313 ha/yr more than in the BAD scenario. In addition, fluctuations in yearly harvest levels in each forest type were greater in the FWS-N scenario. While there were no silvicultural costs for this scenario, in practice, there would likely be increased costs for harvesting techniques used to promote natural regeneration. The Po and Pj forest types would likely still be clearcut. Flowever, on Pj sites, methods which would allow for self-seeding such as delimbing at the stump, and skidding methods which would expose more mineral soil to act as a seedbed, would possibly be used. In the Sp forest type, methods such as strip cutting, leaving advanced regeneration, and other innovative methods of uneven- aged management would be used. An analysis of how harvest costs could change due to harvest method was beyond the scope of this study, however. 98 this is a necessary step if this scenario were to be considered as the managennent strategy. Volume output from the forest per unit area decreased, but there were no artificial regeneration costs. Advantages which could arise from the implementation of this scenario include: not using any herbicides could give the company credibility in the eyes of the public and the environmental movement at large which may open new markets; a decrease in silvicultural investments would be possible; and an incentive to develop new mill technology and/or open new markets to allow this scenario to work. Disadvantages of this scenario include: larger annual harvest areas to maintain current wood supply requirements; likely higher per-unit-costs for wood-fibre extraction due to a younger forest and thus smaller piece size; a reduction in the age of the forest if present harvest levels were maintained; and possible socio-economic repercussions in the form of reduced employment and thus the local economy due to the elimination of silviculture. 4.2.6 Summary of Basic Analysis Results The large amount of numbers produced in such an analysis makes it difficult to determine the best course of action. However, by reviewing the variations in growing stock conditions compared to that for the BAU scenario, as well variables which represent herbicide use (treatment activity), silvicultural costs 99 (difference in cost between BAD and alternatives) and average annual harvest area together, an idea of the practicality of the scenarios under the different strategic directions can be seen. The Pj growing stock was more effected by the use of less effective silvicultural treatments (Figure 16) than the.Sp growing stock levels (Figure 17) due primarily to the larger Pj silviculture program. The FWS scenarios appear to be quite different than the other scenarios since both softwood and hardwood were considered equally as wood-fibre (i.e. neither is secondary). For this reason there was a considerable increase in operable volume per hectare for the wood supply scenarios. Growing stock levels for the forest were declining for the first sixty years, but levelled out for all but the no use scenarios (Figure 18). The wood supply scenario which used a large intensive silviculture program with a reduced landbase (FWS-GW) had a more stable growing stock, earlier on, than all other scenarios investigated. Review of the decision variables together reveaied that the best strategy to follow in order to get the greatest reduction in treatment area with the least amount of change, would be the reduced use scenarios (Figure 19). If herbicides were highly restricted or banned completely, a change to the FWS-N scenario should seriously be considered, since the condition on herbicides is met and 100% savings on herbicides are realized with only a minor increase in AHVFI. Not having herbicides as a tool while still trying to maintain the same level of 100 control over competition would require large increases in expenditures, but would have only minor decreases in harvest volume per hectare. A progressional approach would likely be the most sensible long-term strategy since it is unclear what policy will be adopted in the future. One possibility might be to adopt first the 67HP scenario, then the 50HP or 40HP scenario, and then either consider a change to an FWS-N or an OWC scenario. Suppose a policy requiring a stepwise reduction in use of herbicides were implemented (such as that advocated by the Forestry Sectoral Task Force of the Ontario Round Table on Environment and Economy in 1992 (Forestry Sectoral Task Force, 1992)). As the need for alternatives increased with each reduction in herbicide-use, the supply of alternative vegetation management tools and contractors to do the work would also increase and costs may come down to more attractive levels due to competition. 101 Comparison of Growing Stock Jack Pine Forest Type Volume (million m^3) Years from Present +BAU,67HP,50HP,40HP.ATO-C,OWC-A,NAA -^-OWC-B □ NWC ♦ ATO-A, ATO-B ©FWS-GW -^FWS-N Figure 16, Comparison of the primary growing stock levels of all scenarios in the jack pine forest type. 102 Comparison of Growing Stock spruce Forest Type Volume (million m ^3) Years from Present -fBAU,67HP,50HP,40HP,ATO-C,OWC-A,NAA -kO\NC-B BNWC 4ATO-A, ATO-B 0FWS-GW PFWS-N Figure 17. Comparison of primary growing stock for all scenarios in the Spruce forest type. 103 Comparison of Growing Stock All Forest Types Volume (million m ''3) Years from Present +BAU,67HP.50HP,40HP,ATO-C.OWC-A,NAA -jicOWC-B E NWC ♦ ATO-A, ATO-B ePWS-GW -^-FWS-N <®^arvest Figure 18. Comparison of primary growing stock levels for all scenarios for the forest. 104 Harvavt Volume (m 3Av) 80 I 40 - - - - C0) ^ O SiMculture Costs (S^yeaO (/) 80 I ^^ CD Treatment Area fiw/yeai) O 80 I CD CL 40 - - - I 67HP 5QHP 4QHP I ATQ-A ATO-6 ATOC NAA | WWC OWC-A OWC-B j FWS-GW FWS-N Reduced Use Restricted Use No Use Wood Supply Change Figure 19. Comparison of response variables from alternative management scenarios with the Business-As-Usual Scenario. 105 4.3 SENSITIVITY ANALYSIS Results presented here are from the sensitivity analysis performed on the VDPs of the BAU scenario. Interpretation of the results indicated that average harvest volume per hectare was primarily dependent on the volume development patterns that describe the present forest. Positive and negative scaling factors applied to all values in the VDPs produced strong responses from both the Pj forest type (Figure 20) and the Sp forest type (Figure 21). Interpretation of these results showed that it was the present VDPs that contributed most to the responses. A similar result occurred when the peak values of the VDPs were altered. As illustrated in Figures 22 and 23, it was again the present VDPs which were responsible for the majority of change in the Average Harvest Volume per Hectare (AHVH).' Average harvest volume per hectare was insensitive to adjustments made to the tail values of VDPs. The Pj forest type showed virtually no response (Figure 24) and the Sp forest type showed only slight response to the changes (Figure 25). Thus, effects on the response variable were primarily due to VDPs of the present forest. 106 Sensitivity Analysis Effects of Scaling on PJ Forest Type 50 40 O ■10 - o -20 0) -30 -40 -50 up 15% up 5% down 10% down 30% up 10% no change down 20% Scaling Factor All Curves Reg. & Fut. Curves Reg. Curves Figure 20. Percent change in average jack pine harvest volume per hectare due to increases and decreases of all values of the volume development patterns. 107 Sensitivity Analysis Effects of Scaling on SP Forest Type 50 40 X 30 > <5 20 c 10 CD D) C CO 0 O -10 c. CD o -20 CD 0- -30 -40 -50 up 15% up 5% down 10% down 30% up 10% no change down 20% Scaling Factor All Curves Reg. & Fut. Curves Reg. Curves Figure 21. Percent change in average spruce harvest volume per hectare due to increases and decreases of all values of the volume development patterns. 108 Sensitivity Analysis Effects of Peaking on PJ Forest Type 50 T- 40 -50 up 30% up 10% down 10% down 30% up 20% no change down 20% Peaking Factor All Curves Reg. & Fut. Curves Reg. Curves Figure 22. Percent change in average jack pine harvest volume per hectare due to increases and decreases of peak values of the volume development patterns. 109 Sensitivity Anaiysis Effects of Peaking on SP Forest Type 50 40 1 X 30 f >5 20tf 0-) 10- 05 T ^ 0- 1 t -10 i-20f 05 O- -30 i -40 -50 up 30% up 10% down 10% down 30% up 20% no change down 20% Peaking Factor All Curves Reg. & Fut. Curves Reg. Curves Figure 23. Percent change in average spruce harvest volunne per hectare due to increases and decreases of peak values of the volume development patterns. 110 Sensitivity Analysis Effects of Tails on PJ Forest Type 50 40 X 30 -r > X < 20 -r -- 10 - < 20 - 10 Q> O) S 0 H -10 ^ o -20 - ■£-3oi -40 -- -50 1 up 30% up 10% down 10% down 30% up 20% no change down 20% Tailing Factor All Curves Reg. & Fut. Curves Reg. Curves Figure 25. Percent change in average spruce harvest volume per hectare due to increases and decreases of tail values of the volume development patterns. The sensitivity or insensitivity of AHVH to changes in the VDPs, which essentially controlled both the potential average volume per hectare of the forest and harvest area, were also affected by several other factors including: • Age-class distribution; * Harvest scheduling rule; 112 • Silviculture levels; • Harvest levels; and • Simulation period. The area of the SRFMU was reasonably well distributed over age classes except for large areas in the 5- and 10-year age classes of the Pj and Sp forest types (Figure 26). As can be seen from the BAU's simulation age-class patterns shown in Figure 27, the harvest levels resulted in younger forests for both Pj and Sp forest types over the 100-year simulation period. The Pj forest type had dramatic changes occur to its age-class structure (i.e. Pj: 6 age classes to 4 age classes; Sp; 7 to 6) over a shorter time (i.e. 60 years for the Pj forest type as compared to 100 years for the Sp forest type). These differences between Pj and Sp forest- type age-class dynamics resulted from differences in harvest levels, silviculture levels, and the VDPs which expressed Sp as slower growing and better able to maintain merchantable volume on the stump. 113 Jack Pine SpfUo» 25000 —— ■■llllllllllfli ■ ■ 5 1S 25 5S 45 55 «6 75 as 95 10S ns 125 155 145 156 ifisi Popiar Total 2S000 25000 I I ioooo — - - *■15000 — - - IJ I! 4 10000 -p - - kg* i>»«' Figure 26. Initial age-class distributions of the Pj, Sp, Po and combined forest types. 114 Pine - Age Class Distribution BAU Scenario 10 20 30 40 50 60 70 80 90 100 Age (years) Spruce - Age Class Distribution BAU Scenario 70 65 60 55 ~ . 50 tn 2 ^ 45 s c 40 O (0 ® « 35 ^^30 £ t25 20 15 10 5 0 5 15 25 35 45 55 65 75 85 95 10 20 30 40 50 60 70 80 90 100 Age (years) 0-20 21-40 ■■ 41-60 ■■ 61-80 ■■ 81-100 101-120 121-140 E3 141-160 161-180 181-200 Figure 27. Age class distributions of the Pj and Sp forest types from the BAU scenario simulation runs. The effects from these factors culminated in the harvest scheduling of areas. The harvest areas of the Pj forest type were almost entirely dependent on the present forest for wood-fibre for the first 70 years, after which they were entirely dependent on volume from artificial regeneration and pre-commercial thinning 115 treatments (Figure 28). The Sp forest type did not have volume harvested from anything but the present and naturally regenerating forest for the first 90 years of the simulation, after which only about 50% of its volume was harvested from the artificially regenerated forest (Figure 29). Obviously, the simulation time-period would need to be longer, in the magnitude of 200 years, for the Sp or the Pj forest types' wood supplies to show any significant responses from changes to the regeneration yield curves. This insensitivity of volume output per hectare to assumptions of decreases in coniferous volume in response to reduced herbicide use (for the 100-year forecast) means that VDPs representing future responses could have been changed by any factor within reason (e.g. up 30% decrease) and it would not have substantially altered any of the results of this study. While changes to the VDPs which describe the present forest would have produced drastic differences, the present forest is the most understood when comparing it to forests originating from artificial regeneration, pre-commercial thinning, or natural regeneration after harvesting. Since the present VDPs affect the wood supply the most, the forecasts can be assumed to be representative of the future wood supply on the SRFMU. However, efforts to ensure the present VDPs are representative of their aggregations would be a wise investment for the management of this forest. The second most important set of VDPs describe the treated Pj forest type (artificial regeneration and PCT); refinement of these curves with empirical data would enhance long-term volume output results. 116 Pj Harvest Area Distribution and Source of Volume 8000 6000 «, 4000 — a> 2000 - 35 45 55 65 Simulation Time (years) Natural Regen [ | Thin Figure 28. Jack pine harvest area distribution and source of volume for the BAU scenario. 117 Sp Harvest Area Distribution and Source of Volume Simulation Time (years) Figure 29. Spruce harvest area distribution and source of volume for the BAU scenario. 118 5.0 CONCLUSIONS Comparison of the current system of management with alternative strategies calling for reductions of up to 60% in herbicide use revealed that only minor increases in silvicultural costs (<3%) would be required, with no change in the wood supply. Indiscriminant restriction of herbicide use would require large increases in silvicultural expenditures (over 25%). Similarly, substitution of all herbicide treatments with non-herbicide ground-based alternatives required an increase in the silviculture budget of approximately 37% with noticeable decreases in harvest volume per hectare. A change to a flexible wood supply was feasible if natural regeneration was used, but was a very expensive alternative when the land-base was decreased and intensive management was used. These results support the hypothesis of this study, that Ontario's forest industries could maintain, an economically feasible wood supply under a policy of reduced herbicide use but not under a policy of no herbicide use. Stepwise reductions of up to 60% of the current levels of herbicide-treated areas, when replaced with non-herbicide alternatives, resulted in only modest increases in costs and slight reductions in the softwood growing-stock levels. 119 Sensitivity analysis of the volume development patterns revealed that the volume dynamics of the present forest were the critical element in the harvest scheduling of the forest, and heavily influenced the level of herbicide treatment as well as the harvest costs for the management of the forest. Effects of management interventions today, while influencing the present sustainable harvest volume, will not be directly encountered for seventy to eighty years, when the last of the present forest is harvested. The logical route to follow in managing the Seine River forest, under the assumptions and limitations of the day, should be to implement a stepwise reduction of the herbicide program; first by 30% and then by 50% of 1991 levels. Due to a low need for herbicides in the first three decades of this forest's development, there should be ample time for either the acceptance by the public that herbicides are an environmentally sound method of vegetation management, or the development of more economical, non-herbicide vegetation management techniques. From this point, the company would be well-poised to commit completely to alternatives to herbicides if necessary. Another logical long-term strategy is a move to a flexible wood supply where natural reproduction and thus advanced harvesting techniques to promote it are used. However, this scenario would require change on a grand scale, from the development of advanced harvesting techniques to the re-fitting of pulping facilities, preparation for planned fluctuations in product production, employment levels, overall production costs and possibly even a changed market strategy. 120 The structure of this analysis provides a systennatic method for quantifying notions of how management and the forest would be effected by a change in the provincial herbicide policy of Ontario. For instance, it can be demonstrated that if herbicide use was not alfowed, silvicultural costs could increase from 37 to 50%, average harvest area would likely increase, wood supply demands would be met. The ability of this framework to.provide the necessary information to make sound, defendable management decisions and anticipate the possible implications from herbicide reduction/elimination policies indicate its strength. While the procedures developed for this study can be easily and legitimately applied to analyze potential effects of policies on wood supplies of other forests, the results are particular to the Seine River Forest. Forest models are characterizations of the landbase being studied; their age-class distribution, species composition, productivity, management, costs, investments, history, etc. Differences in one or more of these parameters change the model and thus the basis on which decisions can be made. Use of this study's results to diagnose potential implications to other forests would most likely result in an inappropriate strategy being chosen, to the detriment of the forest and/or the wood supply. Forest-level analyses such as this provide decision-makers with the necessary insight to make more informed decisions about the effects of their actions or inactions made today. They also serve to highlight areas requiring more research. Three candidates for future research arising from this study are: (i) characterization of advanced harvesting techniques; (ii) spatial analysis; and (iii) benefit-cost analysis. 121 The promotion of silvicultural systems where advanced harvesting techniques are used to either promote or retain regeneration on sites being harvested was investigated in this study with the no-weed-control scenario. However, the full impacts of the scenario could not be uncovered due to the lack of suitable data to describe effects on growth and yield, their costs, and other unforseen effects. Harvesting techniques used to promote natural regeneration such as a two-pass shelterwood system, harvesting with advanced regeneration protection and controlled skidding, processing at the stump and strip cutting should be researched and the information integrated into a model such as this. A spatial model could provide the decision-maker(s) with the necessary information to make estimates on: (i) harvest feasibility (regarding locations of scheduled harvests); (ii) road costs; (iii) harvest block restrictions (adjacency rules, maximum size, green-up periods, etc.); and (iv) hauling distances and costs, to name only a few. Much of the information derived from a spatial model would also contribute to an economic analysis (e.g. haul distance). While basic costs of forest management such as silviculture and harvesting were analyzed in this study, the “economic picture" of this forest remains incomplete. Effort should be made to integrate as many of the costs and benefits involved from management strategies as possible into the forest model. With this information, benefit-cost analysis could be used to evaluate the economic worth of one strategy versus another. An initial summarization of well known costs and benefits could eventually be expanded to include multiple-use values including 122 wildlife, biodiversity, and aesthetics. A forest-level model which incorporated the above research with this study would provide for much more informed decisions being made and would broaden the views of forest management. 123 6.0 LITERATURE CITED Alig, R.J., B.J. Lewis and P.A. Morris. 1984. Aggregate timber supply analysis. USDA Forest Service, Fort Collins Colorado: General Technical Report, RM- 106. 49 pp. Anon. 1985. Deadly dioxin. Provincial News. International Wildlife. Vol. 15, No. 4. 27 pp. Anon. 1990. Canada's green plan: Canada's green plan for a healthy environment. En21-94/1990E, Government of Canada, Minister of Supply and Services,Ottawa, Ontario. 174 pp. Anon. 1991. To clip or not to clip: that is the question. On Line to Northwestern Forestry Developments. Ontario Ministry of Natural Resources, Thunder Bay, Ontario. Vol 4, No. 1.10 pp. Baskerville, G.L. 1990. Forest analysis: linking the stand and forest levels. Paper presented at the Symposium on The Ecology and Silviculture of Mixed Species Forests, New Haven, Connecticut. 27 pp. Bell, F.W. 1991. Critical silvics of conifer crop species and selected competitive vegetation in Northwestern Ontario. Technical Report #19, Forestry Canada, Ontario Region, Sault Ste. Marie, COFRDA Report 3310/ Ontario.Ministry of. Natural Resources, Northwestern Ontario Forest Technology Development Unit, Thunder Bay, Ontario. 177 pp. Bell, F.W., A.J. Willcocks and J. Kavanagh. 1990. Preliminary variable density yield tables for four Ontario conifers. Technical Report No. 50, Ontario Ministry of Natural Resources, Northwestern Ontario Forest Technology Development Unit, . Thunder Bay, Ontario. 80 pp. Boise Cascade Canada Ltd., 1991. Map of Seine River Forest Management Unit's location in Northwestern Ontario. Fort Frances Division, Boise Cascade Canada Ltd., Fort Frances, Ontario. 1 pp. 124 Brown, G. 1983. Site preparation: policy statement. Policy No. FR-08-01-01, Ontario Ministry of Natural Resources. Forest Resources. Toronto, Ontario. 1 pp. Campbell, R.A. 1991. Silvicultural herbicides in Canada: registration status and research trends. Forestry Chronicle 67(5): 520-527. Carson, R. 1962. Silent spring. Houghton Mifflin, Boston. 368 pp. CCO. 1990. An environmental strategy for Ontario - draft for public review. Conservation Council of Ontario. Toronto. Day, R.J. 1991. Forestry 4060 lecture notes. School of Forestry, Lakehead University, Thunder Bay, Ontario. 321 pp. Day, R.J. 1984. Herbicides in forestry: a growing concern, in 16'^ Annual Forestry Symposium; Herbicides in Forestry; A Growing Concern. Lakehead University, School of Forestry, Thunder Bay, Ontario. 82 pp. Dietz, D.H. 1985. The politics of pesticides, pp. 11-16 in J.R. Carrow (Editor) Proceedings of Public Affairs and Forest Management: Pesticides in Forestry. Canadian Pulp and Paper Association, Montreal. Duinker, P., O. Salinas and S Nilsson. 1992. Role of stand simulation in modelling forest response to environmental change and management interventions, pp. 446-465 in H.H. Shugart, R. Leemans and G.B. Bonan (Eds.) A Systems Analysis of the Global Boreal Forest, Cambridge University Press, Cambridge. Duinker, P.N. 1991. Notes to guide a study on: forest-management implications of alternative herbicide-use policies in Ontario. (Unpubl.) School of Forestry,' Lakehead University, Thunder Bay, Ontario. 2 pp. Environics, 1989. 1989 national survey of Canadian public opinion on forestry issues final report. Forestry Canada, prepared by Environics Research Group Ltd. Toronto. 69 pp. Hauer, G. 1989. Modeling regional timber supply in Ontario's northern region, pp. 81-95 in B. Payandeh, M.F. Squires and R. Calvert, (Cochairs). Forest Investments: a Critical Look. OFRC Symp. Proc. O-P-17, Forestry Canada, Sault Ste. Mane, Ontario. Hunt, J.A. 1989. Mechanical site preparation in Sweden and Finland, pp. 46-47 in Learning from the Past, Looking to the Future. B.A. Scrivner and J.A. 125 MacKinnon (Eds.), Canada-B.C. Forest Resource Development Agreement Report No.030, British Columbia Ministry of Forests, Victoria. Hunt, J.A. and R.G. McMinn. 1988. Mechanical site preparation and forest regeneration in Sweden and Finland: implications for technology transfer. Canada-B.C. Forest Resource Development Agreement Report 031, B.C. Ministry of Forests, Victoria. 59 pp. Kent, B.M. 1988. Forest service land management planners'introduction to linear programming. U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station. Fort Collins, CO. General Technical Report RM-173. 36 pp. Malik, N. and W.H. Vanden Born. 1986. Use of herbicides in forest management. Information Report NOR-X-282. Canadian Forest Service, Northern Forest Centre, Edmonton, Alberta. 18 pp. Maynes, C. 1991. Sustainability as if we mean it: an action agenda prepared by Ontario's citizens groups and environmental organizations. Ontario Environment Network, Guelph, Ontario. 60 pp. + appendices. McCallum, I.R. 1993. Long-term effects of timber management on marten habitat potential in an Ontario boreal forest. MScF Thesis, Lakehead University, Thunder Bay, Ontario. 215 pp. McCormack, M.L. 1981. Chemical weed control in northeastern forests. Pg. 108- 115 in Proceedings: Weed Control In Forest Management, ed. H.A. Holt and B.C. Fischer, Purdue Research Foundation, West Lafayette, Indiana. 305 pp. McMinn, R.G. 1982. Ecology of site preparation to improve performance of planted white spruce in northern latitudes, pp. 25-32 in Murray M. (Editor),Forest Regeneration at High Latitudes: Experiences from British Columbia. Proceedings of the Third International Workshop, Prince George, B.C., Aug./Sept. 1981. Univ. Alaska, School of Agriculture and Land Resource Management, and USDA, Forest Service, Pacific Northwest Forest Range Experimental Station, Miscellaneous Report, 82-1. Meadows, D. 1984. On modeling, limits and understanding pp. 161-166 in J. Richardson (Ed.). Models of Reality; Shaping Thought and Action. Lomond Publishers, Mt. Airy, Maryland. Morawski, Z.J.R., J.T. Basham and K.B, Turner. 1958. A survey of a pathological condition in the forests of Ontario. Forest Resources Inventory Report No. 25 - 126 Cull Studies. Ontario Department of Lands and Forests, Queen's Printer, Toronto, Ontario. 93 pp. Newton, M. 1975. Constructive use of herbicides in forest resource management. Journal of Forestry, 73 (6): 43-49. Newton, M. and F.B. Knight. 1981. Handbook of weed and insect control chemicals for forest resource managers. Timber Press, Beaverton, Oregon. 213 pp. Newton, M., M.L. McCormack (JR.), R.L. Sajdak, and J.D. Walstad . 1987. Forest vegetation problems in the northeast and lake states/provinces, pp. 77-103 in J.D. Walstad and P.J. Kuch (Eds.). Forest Vegetation Management For Conifer Production. John Wiley & Sons, New York. Nutter, W.L. and J.E. Douglass. 1978. Consequences of harvesting and site preparation in the Piedmont, pp. 65-72 in T. Tiepin (Ed.). Proceedings: A Symposium on Principles of Maintaining Productivity on Prepared Sites. Mississippi State University, Starkville, Mississippi. OMNR. 1986V Timber management planning manual for crown lands in Ontario. Ontario Ministry of Natural Resources. Queen's Printer, Toronto, Ontario. 217 pp. OMNR. 1986V Statistics 1986. Queen's Printer, Toronto, Ontario. 153 pp. OMNR. 1991V Statistics: 1989-1990. Ontario Ministry of Natural Resources. Queen's Printer, Toronto, Ontario. 106 pp. OMNR. 1991^. Silviculture strategies for sustainable forestry. Ontario Ministry of Natural Resources. Queen's Printer, Toronto, Ontario. Fact Sheet. 4 pp. Orlander, G., P. Gemmel and J. Hunt. 1990. Site preparation: a Swedish overview. Forestry Canada, Pacific Forestry Centre, Victoria, British Columbia. Canada-B.C. Forest Resource Development Agreement Report. 105. 61 pp. Forestry Sectoral Task Force. 1991. Forestry sectoral task force. Ontario Round Table on Environment and Economy. Queen's Printer, Toronto, Ontario. 36 pp. Payandeh, B., M.F. Squires and R. Calvert (Cochairs). 1989. Forest investments: a critical look. Forestry Canada, Ontario Region, Great Lakes Forestry Centre, Sault Ste. Marie, Ontario. OFRC Symposium Proceedings O-P-17. 216 pp. 127 Plonski, W.L. 1981. Normal yield tables (metric) for major forest species of Ontario (Revised edition). Ontario Ministry of Natural Resources, Forest Resources Group, Toronto. 40 pp. Public Focus. 1990. Visions 2020: Ontario's youth, Ontario's future. Public Focus. Toronto, Ontario. 133 pp. Rosen, M. and P. Kuntz. 1992. $50 million for forestry available through NODA. The Professional Forester. No. 131.8 pp. Simon, H.A. 1988. Prediction and prescription in system modelling. Carneqie- Mellon University, New York. 13 pp. Smith, D. M. 1986. The practice of silviculture (8'^ Edition). John Wiley & Sons, New York. 527 pp. Smyth, J.H. and K.L. Campbell. 1987. Selected forestry statistics, Ontario: 1987. Great Lakes Forestry Centre, Canadian Forestry Service, Sault Ste. Marie, Ontario. Information Report No. O-X-387. 106 pp. Stewart, R.E. 1987. Seeing the forest for the weeds: a synthesis of forest vegetation management, pp. 431-480 in J.D. Walstad and P.J. Kuch (Eds.). Forest Vegetation Management For Conifer Production. John Wiley & Sons, New York. Stewart, R.E., L.L. Gross, and B.H. Honkala. 1984. Effects of competing vegetation on forest trees: a bibliography with abstracts. USDA Forest Service, Washington, DC. General Technical Report WO-43. 260 pp. Sutton, R.F. 1990. Mounding site preparation: a preview. Forestry Canada, Ontario Region, Great Lakes Forestry Centre, Sault Ste. Marie, Ontario. (Unpublished report). 41 pp. Sutton, R.F. 1985. Vegetation management in Canadian Forestry. Forestry Canada, Ontario Region, Great Lakes Forestry Centre, Sault Ste. Marie, Ontario. Information Report No. O-X-369, 35 pp. Sutton, R.F. 1984. Plantation establishment in the boreal forest: giyphosate, hexazinone, and manual weed control. Forestry Chronicle. 60(5): 283-287. 128 Tappeiner, J.C. and R.G. Wagner. 1987. Principles of silvicultural prescriptions for vegetation management, pp. 399-430 in J.D. Walstad and P.J. Kuch (Eds.). Forest Vegetation Management For Conifer Production. John Wiley & Sons, New York. Thompson, J. 1990. Northwestern Ontario FORMAN forest class definitions: Seine River Forest Management Unit. Ontario Ministry of Natural Resources, Souix Lookout, Ontario. (Unpublished report). 4 pp. Thompson, J. 1991. Example of the breakdown of a forest using the Northwestern Ontario FORMAN forest class definitions. Ontario Ministry of Natural Resources, Souix Lookout, Ontario. 31 pp. Towill, B., F.W. Bell and A. Wienscyzk. 1992. Planning a vegetation management strategy. Field Workshop - July 8, 9, and 10, 1992. Dryden, Ontario. Ontario Ministry of Natural Resources, Vegetation Management Alternatives Program, Northwestern Ontario Forest Technical Development Unit, Thunder Bay, Ontario. Unpublished. Van Strum, C. 1983. A bitter fog. Sierra Club Books, San Francisco. 288 pp. Wagner, R.G. 1991. VMAP: towards improving forest vegetation management in Ontario. On Line to Northwestern Forestry Developments. Ontario Ministry of Natural Resources, Sault Ste. Marie. Vol. 4, No. 3, 12 pp. Walker, H.D. 1989. Modeling needs and inputs for forest investments, pp. 23-30 in B. Payandeh, M.F. Squires and R. Calvert, (Cochairs). Forest Investments: a Critical Look. Forestry Canada, Sault Ste. Marie, Ontario. OFRC Symp. Proc. O- P-17. Walker, H.D. 1990. Wood supply analysis at Weldwood-Hinton. pp. 72-84 in Boughton B.J. and J.K. Samoil (Eds.) Forest Modelling Symposium, Forestry Canada, Northwest Region, Northern Forestry Centre, Edmonton, Alberta. Information Report NOR-X-308. Walstad, J.D. and F.N. Dost. 1984. The health risks of herbicides in forestry: a review of the scientific record. Forest Research Lab, Oregon State University, Corvallis. Special Publication 10. 60 pp. Walstad, J.D. and F.N. Dost. 1986. All the king's horses and all the king's men: the lessons of 2,4,5-T. Journal of Forestry. 84(9): 28-33. 129 Walstad, J.D. and PJ. Kuch. 1987'. Forest vegetation management for conifer production. John Wiley & Sons, New York, New York. 523 pp. Walstad, J.D. and P.J. Kuch. 1987^. Introduction to forest vegetation management, pp. 3-14 m J.D. Walstad and P.J. Kuch (Eds.). Forest Vegetation Management For Conifer Production. John Wiley & Sons, New York. Walstad, J.D., M. Newton and D.H. Gjerstad. 1987. Overview of vegetation management alternatives, pp. 152-200 in J.D. Walstad and P.J. Kuch (Eds.). Forest Vegetation Management For Conifer Production. John Wiley & Sons, New York. Wang, E., T. Erdle and T. Roussell. 1987. FORMAN wood supply model user manual. New Brunsvvick Executive Forest Research Advisory Committee Inc. and New Brunswick Department of Natural Resources and Energy. Fredericton, New Brunswick. 61 pp. Whitfield, T. 1989. Preharvest aspen girdling. On Line to Northwestern Forestry Developments. Vol. 3, No. 3: 10. Willcocks, A.J., F.W. Bell, J. Williams and P.N. Duinker. 1990. A crop-planning process for Northern Ontario forests. Ontario Ministry of Natural Resources, Northwestern Ontario Forest Technology Development Unit, Thunder Bay, Ontario. Technical Report 30. 1 59 pp. Williams, J. 1991. CROPLAN user's manual and FORMANCP: a version of FORMAN 2.1 that links to CROPLAN. Ontario Ministry of Natural Resources, Thunder Bay, Ontario 19 pp. + appendices. APPENDICES 131 APPENDIX I ORGANIZATIONS CONCERNED WITH THE USE OF HERBICIDES IN FOREST MANAGEMENT SUPPORTING GROUPS OF THE ONTARIO ENVIRONMENTAL NETWORK APPENDIX 2; SUPPORTING GROUPS THE UNDERSIGNED organizations support this 4 Interfaith Development Education Association of agenda as a statement by Ontario environmental Burlington groups of the principles and priorities for achieving 4 Keep the Escairpment Environment Protected environmental sustainability. 4 Lakefield Environmental Action Forum 4 Maidstone Against Dumping 4 Minto Environmental Group ♦ Algoma Manitoulin Nuclear Awareness 4 Mitchell and Area Environmental Group ♦ Artists Alliance for the Environment 4 Niagara Ecosystems Taskforce (NET Force) ♦ Association of Peel People Evaluating 4 Niagara Citizens for Modern Waste Management Agricultural Land (APPEAL) 4 Nipissing Environmental Watch ♦ Assuring Protection for Tomorrow’s Environment 4 Nipissing Naturalists (Elmira) 4 Norfolk Field Naturalists 4 Avon Hiking Trail 4 North Bay Peace Alliance 4 Botany Conservation Group, University of Toronto 4 Northwatch 4 Bruce Nuctear Awareness 4 Nuclear Awareness Project 4 Canadian Institute for Environmental Law and 4 Ontario Public Health Association Policy 4 Ontario Public Interest Research Group 4 Canadian Environmental Law Association (OPIRG)-Provincial 4 Canadian Organic Growers 4 OPIRG-Brock 4 Canadian Physicians for Aid and Relief 4 OPIRG-Carleton 4 Citizens for a Safe Environment 4 OPIRG-Guelph 4 Citizens' Clearinghouse on Waste Management 4 OPIRG-Ottawa 4 Citizens' Network on Waste Management 4 OPIRG-Peterborough 4 Clean North (Sault Ste. Marie) 4 OPIRG-Toronto 4 Clean Water Alliance; Environment Group 4 Owen Sound Field Naturalists 4 Coalition Advocating Responsible Development - 4 Parkdale Environmental Action Haldimand-Norfolk 4 Pembroke and Area Bird Club 4 Corridor Area Ratepayers Association 4 Pesticides Action Group-Guelph 4 County of Lanark Environmental Action Network 4 Pickering Rural Association 4 Dummer Environment Watch 4 Pollution Probe 4 Durham Nuclear Awareness 4 Preservation of Agricultural Lands Society 4 Earth First-Ottawa 4 Sault Naturalists Club 4 East Coast Ecosystems 4 Save the Rouge Valley System 4 Eco-Action 4 Sierra Club of Eastern Canada 4 Elora Environmental Action Group 4 Solar Energy Society of Canada 4 Energy Action Council of Toronto 4 St. Clair River International Citizens’ Network 4 Environmental Action Ontario 4 Storrington Citizens Against Trash 4 Environmental Minds of Grey-Bruce 4 Sudbury Citizens’ Movement 4 Environmentalists Plan Toronto 4 Temagami Wilderness Society 4 Families Against a Toxic Environment 4 Temiskaming Environmental Action Committee 4 Friends of the Earth 4 Tiny Ratepayers Against Pollution 4 Friends of the Rainforest 4 Toronto Environmental Alliance 4 Friends of the Spit 4 Tottenham Environment Committee 4 Food Chain 4 Toxic Waste Research Coalition 4 Grassroots Humewood 4 Waterloo Public Interest Research Group 4 Great Lakes United 4 West Burlington Citizens’ Group 4 Wildlands League 4 Guelph Field Naturalists 4 Windsor Occupational Safety and Health Group 4 Guideposts for a Sustainable Future 4 Haldimand-Norfolk Organization for a Pure Environment 4 Hike Ontario 4 Hockley Valley Community Association Inc. Actkui Agtnd*; SUPPORTING GROUPS/1 MEMBER ORGANIZATIONS OF THE CONSERVATION COUNCIL OF ONTARIO AN ENVmONMENTAL STRATEGY FOR ONTARIO: DRAPT FOR PUBLIC REVIEW -g- THE CONSERVATION COUNCIL MEMBERSHIP The Council currently has 31 Member Organizations with a combined membership of over 1 million people. Our current member organizations are: THE BRUCE TRAIL ASSOCIATION CANADIAN INSTITUTE OF FORESTRY (Southern Ontario Section) CANADIAN LAND RECLAMATION ASSOCIATION (Ontario Chapter) CANADIAN SCXriETY OF ENVIRONMENTAL BIOLOGISTS (Ontario Chapter) CANOE ONTARIO. ENVIRONMENTAL CONCERNS COMMITTEE COUNCIL OF OUTDOOR EDUCATORS OF ONTARIO FEDERATION OF ONTARIO COTTAGERS' ASSOCIATIONS INC. FEDERATION OF ONTARIO NATURALISTS THE GARDEN CLUBS OF ONTARIO HIKE ONTARIO JUNIOR FARMERS' ASSOCIATTON OF ONTARIO THE METROPOLITAN TORONTO ZOO NATIONAL CAMPERS & HIKERS ASSOCIATION OF OST.ARIO NORTHERN ONTARIO TOURIST OUTFITTERS ASSOCIATION ONTARIO ASSOCIATION OF LANDSCAPE ARCHITECTS ONTARIO CAMPING ASSOCIATTON ONTARIO FEDERATION OF AGRICULTURE ONTARIO FEDERATION OF LABOUR ONTARIO FORESTRY ASSOCIATION ONTARIO INSTITUTE OF AGROLOGISTS ONTARIO MEDICAL ASSOCIATION ONTARIO PROFESSIONAL FORESTERS ASSOCIATION ONTARIO PROFESSIONAL PLANNERS INSTITUTE ONTARIO SOCIETY FOR ENVIRONMENTAL EDUCATION ONTARIO SOCIETY FOR ENVIRONMENTAL MANAGEMENT ONTARIO SOIL AND CROP IMPROVEMENT ASSOCIA'HON ONTARIO WORKERS' OCCUPATIONAL SAFETY .AND HE.ALTH CENTRE POLLUTION CONTROL ASSOCIATION OF ONTARIO THE SIERRA CLUB OF ONTARIO SOIL AND WATER CONSERV.ATION SOCIETY (Ontano Chapter) W1LDL.ANDS LEAGUE (Chapter of Canadian Parks and Wilderness Society) MEMBERS OF THE ONTARIO FORESTRY SECTOR TASK FORCE November 1991 To the Reader; The Forestry Sector Task Force was set up to examine the forestry sector and to make recommendations on implementing a sustainable development strategy to the Ontario Round Table on Environment and Economy. The members of the Task Force are: Chair; John Naysmith, Director, School of Forestry, Lakehead University David Balsillie, Assistant Deputy Minister, Policy, Ministry of Natural Resources Ted Boswell, President, E.B. Eddy Forest Products Robert Cormier, Native Entrepreneur Brennain Lloyd, North watch Terry Quinney, Ontario Federation of Anglers and Hunters Michelle Swenarchuk, Canadian Environmental Law Association Wally Vrooman, Vice-President, Environmental Affairs, Canadian Pacific Forest Products Jerry Woods, Canadian Paperworkers Union In this report, the members of the Task Force present their views on ways that government, non- government organizations, and private industry can best promote a healthy environment and economic development in the forestry sector. The final report will be released for general public comment in January. The Round Table will consider the recommendations contained in the final report in preparing its overall strategy for sustainable development for the Province of Ontario. Individuals, groups, or organizations who wish to comment on this draft report may do so in writing or in person. For more information please contact the Round Table at (416) 327-2032. ^ For long distance call collect. Please send written comments to: Forestry Task Force The Ontario Round Table on Environment and Economy Suite 1003, 790 Bay Street Toronto, Ontario M7A 1Y7 Tel; (416) 327-2032 Fax; (416) 327-2197 135 APPENDIX II SUMMARY OF THE MAJOR ATTRIBUTES ASSOCIATED WITH A NUMBER OF TYPES OF FOREST VEGETATION MANAGEMENT General Specific Applicable Principal Advantages Principal Disadvantages Practice Method Technique Region Harvesting Clearcutting Conventional All Facilitates eSicient even-aged Seedling stock may not be management adapted to the site Removes overstory competition Aids pioneering vegetation Disturbs residual shrubs and Promotes sprouung hardwoods May cause errosion and associ- Most economical method of log- ated adverse impacts ging Most reliable method of refores- Habitat changes may alter com- tation if planting is done position of wildlife species Beneficial to many wildlife spe- Asthetically less pleasing cies Minimum Northwest Same as preceding-plus: Same as preceding except: disturbance 1. Hinders pioneering vegetation 1. Aids residual rather than pi- 2. Helps protect site quality oneering vegetation 2. Logging more costly than con- ventional clearcutting Seed-tree and South and Ameliorates harsh environmental DifUcult and costly to perform on sheitenwood North- conditions for seedlings Steep terrain systems west Less expensive natural regenera- Dil&cuit to control number and tion possible distribution of seedlings Ensures seedling adaptation to Aids understory shrubs and site (unless planted) hardwoods Aesthetically more pleasing (at Multiple entries can damage ad- least temporarily) than clear- vanced regeneration and re- cutting maining trees Unsuitable for thin-barked spe- cies susceptible to stem decay from logging damage Increases incidence of root rot and dwarf mistletoe diseases Damage possible to high value residuals from lightning, windthrow, and insects Logging more costly than clear- cutting Selection South. Facilitates all-aged or uneven- Succession can lead to gradual harvesting North- aged management dominance by low-value hard- east. and Provides a relatively continuous woods Iniand stream of revenue Generally less profitable and North- inexpensive natural regeneration more complicated than even- west possible aged management Ensures seedling adaptation to Multiple entries can damage ad- sue vanced regeneration and dis- Helps protect site quality and turb soils maintain stable environmental increases incidence of root rot conditions diseases .Aesthetically more pleasing than Logging more costly than clear- clearcutting cutting Perpetuates stable habitat for Precludes opportunities to use some wildlife 3pe ;?5 genetically improved stock or Reduces the chances of cata- change species strophic losses from fire and j natural agents Site prepara- Prescribed Broadcast Ail Reduces risk of subsequent wild- Requires precise weather and tion burning burning fire site conditions to ensure: Provides suitable environment 1. Adequate disposal of slash for seeding and planting 2. Minimum risk of escape Facihuus access for planting 3. Compliance with smoke and other silvicultural activi- management regulations ties Occupational hazards are inher- Provides some control of residual ent in any technique utilizing shrubs and hardwoods fire * Extracted from Table 6-1 from Walstad et al. (1987) General Specific Applicable Principal Advantages Principal Disadvantages Practice Method Technique Region Successional pauems similar to Can be detrimental to soils and that caused by natural wild- site .quality fires Aggravates sprouting and germi- Reasonably inexpensive when nation problems with fire- done under suitable conditions adapted species Improves forage for wildlife and Generally requires pretreaimen: livestock (Note: This may lead via mechanical or chemical to seedling damage in some sit- means uations) Exposed environment for new seedlings can be too harsh Burning of All Same as preceding plus: Same as preceding plus; piles and 1. Minimizes risk of escape 1. Requires costly mechanical windrows during burning or manual methods to pile 2. Weather and fuel conditions or windrow the material do not have to be quite so 2. Piling or windrowing opera- Stringent tions must be carefiilly 3. Makes entire area suitable done to ensure that mate- for planting or seeding rial is burnable and that soils are not adversely im- pacted 3. Terrain must be suitable for operation of mechanical equipment Mechanical Various types All Reduces risk of subsequent wild- Expensive, energy-intensive ap- method? of heavy fire proach equipment Residual vegetation fi'equently Not applicable on steep slopes or uprooted or damaged excessively wet soils Provides suitable environment Can cause serious soil damage for seeding or planting and loss of site productivity Facilitates access for planting Follow-up burning generally re- and other silvicultural activi- quired to dispose of material ties Does not control sprouting vege- Occupational safety is reasonable tation unless it is uprooted if work IS done carefully Creates ideal conditions for inva- Sensitive areas can be treated sion of pioneering vegetation with little controversy or risk Can aggravate problems with of oiT-site damage pest animals E.xposed environment for new seedlings can be too harsh Chemical Broadcast ap- All Provides effective control of Adequate training and precau- methods plication many residual species tions are required for proper (usually Applicable to steep slopes and application aerial ap- diiTicult sites Follow-up burning or mechanical plication Ger.erally the safest, most efTi- treatment generally required cient. and most cost-effective Treatments are confined to spe- mode cf apoiication. especially cific seasons of the year and for large, remote areas; indi- vegetation conditions rect costs can be substantial, Efficacy often depe.ndent upon however weather conditions Legal impediments and regula- tory’ restnenons can be limit- ing Can be a controversial form of treatment Ground ap- All Same as preceding plus. Same as preceding plus: plication 1. EfTicacy tends :n be greater 1. Frequency of occupational (usually 2. Treatments can often be ap- injuries associated with spot. band, plied yearround labor-intensive methods is or individ- 3. Can be taiiored'to small .inherently greater ual stem areas, boundar'es. and 2. Occupational exposure to treatm.cnU’ buffer strips chemicals is greater A. Environmental precautions 3. Not feasible on adverse ter- required tend to be less re- rain or in brushy condi- strictive tions General Specific Applicable Principal Advantages Principal Disadvantages Practice Method Technique Region 4. "Costs tend to be higher 5. Production rates are lower Manual Slashing Northwest Can be used when or where ma- Primarily restncted to brush- methods chines are inoperable and field reclamation and stand chemicals are unsuitable conversion projects Relacively small areas can be Hazardous occupational practice treated even after extensive safety High-value trees or plants can be training Unvolves power saws saved and machetes) Expensive, labor-intensive ap- proach Does not control sprouting spe- cies Adjunct treatment with fire, me- chanicals or chemical treat- ment usually required Mulching and Northwest Same as preceding plus: Only effective on forbs and scalping 1. Done in conjunction with grasses plaatiog Careful installation of mulching 2. Can improve soil moisture material (paper or plastic) re- conditions and seedling quired survival Not stable on excessively steep ground Scalping less effective than mulching Expensive, labor-intensive ap- proach Release Chemical Broadcast ap- All Same as for broadcast chemical Same as for broadcast chemical methods plication site preparation plus; site preparation except: (usually 1. Use of broad-spectrum, selec- 1. Follow-up burning or me- aenal ap- tive herbicides can provide chanical treatments are plication! adequate control of com- inappropriate peting vegetation without 2. Correct timing is critical to damaging conifers avoid damage to conifers 2. Most widely tested and used method of release Ground ap- All Same a? for ground chemical site Same as for ground chemical sue pUcaticni preparation plus' preparation except; tusually di- 1. Generally the most effective 1. Follow-up burning or me- rected xnd selective treatment, chanical treatments are lar or ba^l provided the conditions inappropriate sprays are practical and economi- 2. Conifers can be damaged cal unless care is taken dur- ing application Manual Various t>*pes All Highly selective treatment Highly hazardous occupational methods of hand Minimizes potential for adverse practice tools and envirorunentai impacts Expensive, labor-intensive prac- po^ver Saws Reasonably efficient means of tice treating small, sensitive areas Difficult to perform on adverse where other methods are inap- sites and under brushy condi- propr.ate tions Can be done m conjunction with Multiple treatments may be re- precomir.ercial thinning quired to control resprouting vegetation Conifers can be accidentally cut or set back b)- “thinning sheck" Silvicultural benefits largely un- documented, except when done in conjunction with precom- mercial thinning General Speciiic Applicable Principal Advantages Principal Disadvantages Practice Method Technique Re^oa Biological Livestock South and Can be an effective, eflicient. and Livestock must be adapted to methods grazing North- inexpensive means of control- forest conditions ling herbs and shrubs Conifer seedlings can be dam- Can generate supplemental reve- aged. killed, or eaten nue Careful herd management re- Promotes muUiple-use manage- quired ment Stream pollution, disease trans- mission. and displacement of wildlife are possible Implementation of effective graz- ing programs can be complex Silvicultural benefits largely un- documented Timber stand Chemical Broadcast ap- South Same as for broadcast chemical Same as for broadcast chemical improvement methods plication release release except: (aerial and 1. Aerial application.restricted mist bloNver to treatment of intermedi- application) ate to codominant-sized hardwoods 2. Ground treatment with mist blowers restneted to treatment of understory species on gentle topogra- phy 3. Some herbicide applications may affect desirable hard- woods Individual South and Provides both ma.ximum degree Same as for ground chemical re- treatments Northeast of control and selectivity lease except conifer damage is (usually Treatments can be applied year- likely if *T>ackflash" (transloca- tree injec- round tion of herbicide from hard- lioni Can be tailored to small areas, woods to conifers via the root boundaries, and buffer strips svstems) occurs Reduces need for vegetation con- trol measures in subsequent ro- tations Tree spacing con be adjusted at the same time Manual Power saw» Same as for manual site prep and Same as for manual release plus. methods release plus: I. Stumps capable of sprouting 1. Merchantable material can may become serious com- be har-ested petitors m the subsequent 2- Tree spacing can be adjusted rotation at the same time 3 Conifer damage can gener- ally be avoided Prescribed Broadca-*. South and Same as for site prep broadcast Same as for site prep broadcast burning uncerstcry Ncnh burnine except burning e.xcspt; burning west 1. Provisions for regeneration 1. Neither mechanical nor are not an important con- chemical treatment is re- sideration e.xcept for shel- quired as adjunct meas- terwood feforestation in ures the Northwest 2. V'aluable hardwood stems 2. Normal plant successional may be adversely affected sequence is delayed 3. Danger of crown scorch or 3 Need for vegetation control bole damage to conifers if measures in subsequent fire becomes too hot rotations is reduced 4. Restricted in Northwest to 4 An inexpensive silvicultural sheltervvood system of re- practice, particularly m forestation, where even the S>uth here it is a risky proposi- tion due to the chance of fire escape 140 APPENDIX III A SUMMARY OF THE PRODUCTIVE FOREST OF THE SEINE RIVER FOREST MANAGEMENT UNIT TABLE 4.8.1 AREA SUMMARY OF ALL LAND OWNERSHIPS* for the five year term from April 1, 1992 to March 31, 1997 SEINE RIVER FOREST SUMMARY OF TOTAL AREA (HA) Water 46373 Non-Forested Land 822 Forested Land • Non-Productive Forest 27672 - Productive Forest 205406 233078 Unsurveyed 0 Total Area 280273 suscAUtY or FRODuenve FOREST (HA) rRODUmON FOREST TROTECnON FOREST FTCUadRaM SC4 A BAS lad/or 1SLAM3S NSR 1-6 m BjfsUr SuOtsul SobtoUl TOTAL *0 177 110 917 1077 1077 so }40 ICOJ 1171 1421 1421 ITOU IISM 41741 60119 77351 77603 0 S7 211 241 261 261 7440 lOCSt 17946 41024 53464 56619 U II 169 230 273 275 tOJ7 sill 7441 10129 11156 12012 111 470 2004 2474 592 2721 0 11 ** I 73 73 93 0 0 109 I 109 109 109 0 404 1216 I 1642 1642 1642 S23» U117 21941 1702 40011 40995 0 0 111 112 112 111 SI 2S13 7023 9931 yyoo 1Q3I7 2113 29021 47631 123131 173502 202523 203406 * This summary is not required to be completed for FMA forests. TABLE 4.8.2 AREA SUMMARY OF ALL CROWN LAND* for the five year term from AprU 1, 1992 to March 31,1997 SEINE RIVER FOREST 143 APPENDIX IV A SUMMARY OF FOREST AGE CLASSES WITHIN EACH AGGREGATION NUMBER FOR THE JACK PINE FOREST Forest Type Jack Pine (Pj) Aggregation Pi-1 Pi-2 Pi-3 Total Stocking qe 70% all all % Coniferous Component 100% 70% 80% or 90% Site Class X + 1 X + 1 X + 1 Aggregate No.s 6 8 Age Class Area (hectares) s 128 4377 1080 0 0 0 0 0 0 56^ « 1020 9572 340 143 985 0 0 480 0 ts 14 46 22 54 439 8 65 991 0 na 24 129 0 186 260 0 41 409 0 ' ^ 5 53 0 0 145 21 63 518 0 30 0 109 111 0 0 46 0 389 175 asoi 0 23 0 0 360 0 0 55 114 iSSSt 40 54 27 0 0 0 0 44 142 0 iii 0 53 5 0 0 0 0 78 0 Mm 0 24 0 22 0 0 48 57 0 m 3 44 0 24 158 0 221 521 11 moi 30 114 544 17 110 750 145 357 642 335 8014 246 1303 0 100 1215 39 103 1875 64 W 306 1472 49 393 1384 57 590 3359 319 wm 30 865 275 49 1443 191 68 2563 585 m 163 1566 196 87 934 160 565 3242 349 Mm 54 2228 296 7 884 0 93 4417 165 8144 m 35 1526 299 0 677 154 180 1995 426 9S 0 1593 121 0 371 25 84 683 480 8£»7 Mm 232 258 22 119 471 0 0 804 128 10S 0 151 47 144 46 13 245 311 0 m 110 28 0 0 0 31 0 50 320 0 408 IIS 40 0 0 0 41 0 89 165 0 130 0 0 0 0 318 37 0 206 0 mm m 0 0 0 0 0 0 0 3 0 0 0 0 0 25 0 18 0 0 48 wm 0 0 0 0 0 0 61 0 0 S) iiiio 0 0 0 12 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 mm e 0 0 0 0 0 0 0 0 0 e 1^ 0 0 0 0 0 0 0 0 0 8 ISO 0 0 0 0 0 0 0 0 0 8 J;^ 0 0 0 0 0 0 0 0 0 tow 248S 1450 189?7 m sm zms- 8181 The initial age class distribution of the Jack Pine Forest Type of the Seine River Forest Management Unit as of 1991. 146 APPENDIX V A SUMMARY OF FOREST AGE CLASSES WITHIN EACH AGGREGATION NUMBER FOR THE SPRUCE FOREST TYPE Forest Type Spruce (Sp) Aggregation Sp-1 Sp-2 Sp-3 Sp~4 Sp-5 Total Stocking Ie60% ge 70% all % Coniferous Component 100%. 100% Ie70% 80 % or 90% (ge 50% Sb) (ge 50% Sb) Site Class X-r 1 X* 1 X*1 X-i-1 Aggregate No.s 10 11 12 13 14 15 16 17 18 19 20 21 Age Class Area (hectares) S 239 380 117 0 0 0 0 122 0 0 0 776 1434 4070 861 0 0 0 0 193 0 51 241 16 * Tfi 29 0 0 0 0 0 11 69 14 148 0 13 284 SO 0 0 0 0 0 0 0 0 0 19 0 0 * ^ 0 0 0 14 0 0 0 0 10 0 0 0 t* SO 27 9 0 70 0 0 81 0 517 0 3 0 7 0 0 8 39 0 0 37 0 104 42 0 4U 32 ■ 0 0 59 0 0 109 0 67 0 268 0 6 9 0 27 131 0 195 18 84 11 870 54 161 15 0 121 60 0 162 0 538 10 1340 0 tmr S$ 116 21 0 99 21 0 467 25 617 0 3073 0 m 62 35 0 359 7 0 657 39 888 91 2925 0 213 60 0 249 12 0 1008 0 571 18 1130 78 248 116 0 514 259 9 1706 49 1877 150 427 33 235 70 9 566 95 0 496 16 1287 89 495 0 90 165 109 23 699 258 64 1663 219 1617 164 37 0 m 218 120 46 1209 140 28 1687 76 2775 64 0 0 90 244 192 107 642 204 24 798 173 2341 342 19 0 m 332 57 0 660 93 62 768 0 1260 59 0 0 TOO 118 378 130 833 459 145 491 378 1198 448 0 0 4&m tm 181 238 48 439 211 27 361 72 609 148 0 19 no 101 96 36 103 279 178 286 0 339 181 0 0 5 0 31 0 25 0 0 0 16 0 0 0 m tao 52 95 136 29 382 25 0 45 119 198 0 0 14 0 0 0 0 23 0 0 0 0 0 0 ■87 10 91 215 62 292 6 29 62 328 51 0 0 1148 4 0 31 42 10 0 0 0 0 0 0 0 87 pm 17 0 34 0 21 0 0 0 0 45 0 0 117 T4$ 0 0 24 0 38 0 0 0 0 0 0 0 rm 5 9 0 0 0 0 0 0 0 0 0 0 u Its 0 0 0 0 20 0 0 0 0 0 0 0 26 .....100 0 6 0 4 0 38 0 0 7 0 0 0 84 0 0 0 0 0 0 0 0 0 0 0 0 T<4» 'V-42re .»17S. 1848 Ttm . 30S8 1$93t 17878 2361 18876 Ckm (y«art) The initial age class distribution of the Spruce Forest Type of the Seine River Forest Mcinagement Unit as of 1991. 149 APPENDIX VI A SUMMARY OF FOREST AGE CLASSES WITHIN EACH AGGREGATION NUMBER FOR THE POPLAR FOREST TYPE Forest Type: Poplar (Po) Management Unit as of 1991. 152 APPENDIX VII NORTH WESTERN ONTARIO FORMAN FOREST CLASS DEFINITIONS AND YIELD CURVES FORES'. CLASS D E F I N T I O N pg 1 of 3 CLASS PRESENT FUTURE REGENERATED PO-LEAVE High Competition PO and BW Stands PO & BW SI X,1,2 PO Class 1 (SJ 2) REG & PER Primary vol 10‘ nil planned WG stocking >= 70% Secondary vol 90% 0 yr delay Stand stocking use Present 1 ave * 0.9 PO-CONVERT - Moderate Competition PO and BW Conversion Candidates! PO & BW SI X,l,2 PO Class 2 (SI 3) Heavy SIP REG & PFR Primary vol 10' Plant B/R sb,sw WG stocking <= 60% Secondary vol 90' Tend twice vision AND 0 yr delay SB Class 7 (SI 1) PO & BW SI 3 Stand stocking use Primary vol 70” REG St PFR Present 2 average. Secondary vol 30” WG stocking >= 10% ^ Stocking -use Pres 7 adjust voi to 100' * Pres2 average PJ SB SHALLOW - Low Competition PJ and SB Sfi^low .Sites' PJ SI X,1,2 PFR PJ Class 3 (SI 3 ) Light SIP SI 3 PRF & REG Primary vol 80' D/S (9 30MM/ha WG stocking >= 10% Secondary vol 20' Tend No AND 0 yr delay PJ Class 3 (SI 3) SB & S SI X, 1,2 PFR Stand stocking use Primary vol 90” SI 3 PFR & REG Present 3 weighted Secondary vol 10' WG stocking <- 80% average * 0.5 10 yr advance AND Stand stocking use SW SI 3 ALL Present 3 weighted WG stocking >« 10% average * 0,5 ^ PJ SANDY SITES - Low Competition PJ PJ SI X,1,2 PJ Class 4 (SI 2) Light SIP REG Primary vol 70*^ A/S 0 50MM/ha WG stocking >- 80%' Secondary vol 30' Tend No 6 yr delay PJ Class 4 (SI 2) Stand stocking use Primary vol 90' Present 4 average Secondary vol 10' * 0.6 10 yr advance Stand stock Ing use Pres 4 average *0.9 Fdf^ M.U. : Standard N.W.R. Updated MAY 29 Regional Forest Classes For T.P.P. By John Thomson CLASS PRESENT FUTURE REGENERATED PJ HIGH COMPETITION - PJ and SB Conversion Candidates PJ SI X,1,2 PO Class 2 fSI 1) Light SIP REG Primary vol 40' Plant C/S pj sb WG stocking <= 80^ Secondary vol 60' Tend 2-4-D 0 yr delay PJ Class 5 (Sill Stand stocking use Primary vol 90' Present 2 adjust Secondary vol 10' vol to 100% * Pres 10 year advance 5 average Stand Stocking use Pres 5 average SB MODERATE COMPETITION - Moderate Competition SB Sites SB SI 2 PO Class 2 (SI 3) Light SIP REG Primary vol 40% Plant C/S sb, :w WG stocking >= 10% Secondary vol 60^ Tend vision 0 yr delay SB Class 6 (SI 2) Stand stocking use Primary vol 90“^ Pres 2 adjust vol Secondary vol 10' to 100% * Present 20 year advance 6 average stocking Stand stocking use Present 6 average SB HIGH COMPETITION - High Competition SB Sites SB SI X,1 POCONVERT2 fSI 2) HEAVY SIP REG Primary vol 30^ Plant B/R sb,sw WG stocking >= 10% Secondary vol 70' Tend Vision 5 yr delay SB Class 7 (SI 1) Stand stocking use Primary vol 90% Present 2 adjust Secondary vol 10° vol to 100% and * 20 yr advance by Present 7 Stand stocking use average. Present 7 average. 8 SB WET — Lowland Wet SB sites SB SI 3 SB Class 8 (SI 3) REG & PFR Primarv vol 100^ Leave for natural WG stocking >= 80- Secondary vol 0% 20yr delay Stand stocking use Pres 8 average *0.8 BF LIGHT COMPETITION - Sites for Conversion Light SIP -No Tend Plant C/S sb,pj BF SI X, 1,2 SB Class 9 (SI 3) SB Class 6 (SI 2) PFR Primarv vol 70^ Primary vol 8^ WG stocking >= 10% Secondary vol 30' Secondary vol 20' AND 0 yr delay 20 yr advance BF SI 3 Stand stocking use Stand stocking use REG St PFR Present 9 average. Pres 6 adjust vol WG stocking >=10% to 100% * Present 6 average stocking N W R Forman Class dati lAY 29/90 pg 3 o f 3 CLASS PRESENT FUTURE REGENERATED 10 BF HIGH COMPETITION BF Sites Conversion Candidates BF SI X,l,2 BF Class 10 fSI 11 Heavy SIP & Chem REtl Primary vol 3Q‘ Plant B/R sb WG stockinq >= 10% Secondary vol 70% Tend 2-4-D 20 yr advance SB Class 1 (SI TT Stand stocking use Primary vol 60” Present 10 average Secondary vol 40^ 20 year advance Stocking -use Class 7 adjust vol to 100% * Pres 10 ave 11 PW PR SHALLOW SITES - for Conversion to PJ Modify cut-shelter PW PR SI 2 & 3 PO-Convert2 (SI 3) Light SIP REG Primary vol 30^ Tend No WG stocking >= 10% Secondary vol 70% PR Class 11 (SI 3) AND 0 yr delay Primary vol 90% PW6.PR SIX,1,2,3 Stand stocking use Secondary vol 10% PFR Present 2 adjust 10 yr delay WG stocking >= 10% vol to 100% * Stand stocking use Present 11 average Present 11 average stocking. * 0.9 12 PW PR DEEP SITES - to be maintained in present WG PW PR SI X,1 Present 2 (SI 3) Light SIP REG Primary vol 30% Plant B/R Pr WG stocking >= 10% Secondary vol 70% Tend No 5 yr delay PR Class 12 (SI 1) Stand stocking use Primary vol 90% Present 2 adjust Secondary vol 10% vol to 100% * 10 yr delay Present 11 average Stand stocking use stocking. Present 12 average stocking * l.1 Percentage of Classes Moving To “O*' Curves. These represent areas to be harvested once; thereafter they are lost to production. Class % of class Reason Assign to new class taken out # called 1 2^ Rds St Landing: IRDS&LAN 2 2^ 2RDS&LAN 3 10‘ 3 •• 4 12' 4 ’• 5 11' 5 " 6 4' 6 ’• 7 4' 7 8 0' 8 NONE 9 4' 9 10 4% lORDS&LA 11 0% 11 NONE 12 o% 12 NONE SEINE RIVER FOREST GROWTH CURVES For CLASS F1 — PoLeove Present Curve Future Curve Voium« (Hfn3/ha) VoluTi* (Nff\3/h«) Age Class Regenerated Curve 200 I i, —•— Pflmary —j— Secondary — Total M.U. i540 Updaied Nov. 22, 1990 SEINE RIVER FOREST GROWTH CURVES For CLASS =2-PoConv: Present Curve Future Curve Veium* (NmJ/r>o) Vonjr«« (Nmi/rto) Regenerated Curve Primary Sacondary Total M.U. ffS-iO Updated Nov. 22, ! 990 SEINE RIVER FOREST GROWTH CURVES For CLASS PiSbSh Present Curve Fuiure Curve Vo‘wm« (Nm3/t>«) UO Regenerated Curve liO I ■■« Primary —\— Secondary Total 30 *o •0 lAO .U.a. =540 Updaied Nov. 22, 7590 SEINE RIVER FOREST GROWTH CURVES For CLASS ^5 — PjHiCom Present Curve . Future Curve (HmJ/ho) Vola^r^e (NmJ/ho) Regenerated Curve —■— Primary —I— Secondary Total M.U. Updafsd Nov. 22, J 990 SEINE RIVER FOREST GROWTH CURVES For CLASS ^6-SbMoCom Present Curve Future Curve 20 -AO »0 80 too 130 140 tftO ISO 300 Age Gloss Regenerated Curve —•— Primary —i— Secondary Total M.U. ^540 Updaied Nov. 22, 1990 SEINE RIVER FOREST GROWTH CURVES For CLASS 4^7—SbHiCom Present Curve Future Curve Velum* (m3/he) Veium* (HmJ/»*o) Regenerated Curve —^ Primary —I— Secondary — Total Kf.U. ^540 Updated Nov. 22, 1990 SEINE RIVER FOREST GROWTH CURVES For CLASS A8-SbWei Present Curve Future Curve Velum* (HmJ/he) Velome {HmJ/fio) Regenerated Curve fO Velum* (»m3/ne) iO *0 Non* Plonnva —— Primary 20 —j— Secondary —— Total O 0 30 40 10 90 too 130 UO l»0 110 300 M.U. ^540 Ago Class Updated Nov. 22, 1990 SEINE RIVER FOREST GROWTH CURVES For CLASS A W — BfHCom Present Curve. Future Curve Volume (NmJ/rto) Voiumo {Hml / Regenerated Curve —— Primary —I— Secondary —— Total M.U. ^340 Updated Nov. 25, tP90 162 APPENDIX VIII JACK PINE AND BLACK SPRUCE YIELD CURVES FROM SPACING TRIALS Figure 1. The results from regression analysis of jack pine spacing trials on site class X +1 (Bell et. al., 1990). Figure 2. The results from regression analysis of jack pine spacing trials on site class 2 sites (Bell ct. al., 1990). Figure 3. The results from regression analysis of jack pine spacing trials on site class 3 sites (Bell et. al., 1990). Figure 4. The results from regression analysis of black spruce spacing trials on site class X +1 (Bell et. al., 1990). Figure 5. The results from regression analysis of black spruce spacing trials on site class 2 sites (BeU et. al., 1990). Figure 6. The results from regression analysis of black spruce spacing trials on site class 3 sites (BeU et. al„ 1990). 167 APPENDIX IX VOLUME DEVELOPMENT PATTERNS USED FOR THE BUSINESS-AS-USUAL MANAGEMENT SCENARIO PRESENT YIELD CURVE AND OPERABILITY LIMIT SUMMARY FOR THE BAU SCENARIO Aggregate Site Yield Oper. Limits Group Ro"! Class Curve First Last (NMM^3/YRS) (NMM^3/YRS) Pj-1 1 X+1 5 140/55 99/140 2 2 7 135/55 90/140 3 3 9 120/60 75/140 Pj-2 4 X+1 11 150/90 140/145 5 2 13 120/80 80/190 6 3 15 90/80 80/150 Pj-3 7 X+1 5 140/55 99/140 8 2 7 135/55 90/140 9 3 17 50/90 45/145 Sp-1 10 X+1 19 100/105 99/-- 11 2 21 100/110 99/-- 12 3 17 50/90 45/145 Sp-2 13 X+1 19 100/105 99/-- 14 2 21 100/110 99/-- 15 3 23 60/125 59/- Sp-3 16 X+1 25 120/80 119/-- 17 2 27 120/85 119/-- Sp-4 18 X+1 25 120/80 119/-- 19 2 27 120/85 119/-- Sp-Bf 20 X+1 1 80/55 40/105 21 2 3 80/60 40/100 Po-1 22 2 29 52/40 51/160 23 3 29 52/40 51/160 Po-2 24 X+1 31 103/40 102/155 25 2 33 93/40 92/150 26 3 35 77/40 76/160 Po-3 27 2 33 93/40 92/150 28 3 35 77/40 76/160 Po-4 29 2 37 52/40 51/-- 30 3 39 47/40 46/-- FUTURE YIELD CURVE AND OPERABILITY LIMIT SUMMARY FOR THE BAU SCENARIO Aggregate Site Yield Oper. Limits Group Ro"^ Class Curve First Last (NMM^3/YRS) (NMM^3/YRS) Pj-1 1 X+1 6 70/55 60/110 2 2 8 60/55 50/110 3 3 10 50/45 40/115 Pj-2 4 X+1 12 40/55 30/-- 5 2 14 40/60 30/200 6 3 16 40/45 35/-- Pj-3 7 X+1 6 70/55 60/110 8 2 8 60/55 50/110 9 3 18 25/90 20/160 Sp-1 10 X+1 20 35/70 30/-- 11 2 22 30/70 20/-- 12 3 18 25/90 20/160 Sp-2 13 X+1 20 35/70 30/-- 14 2 22 30/70 20/-- 15 3 24 50/145 49/-- Sp-3 16 X+1 26 15/80 14/- 17 2 28 14/80 13/- Sp-4 18 X+1 26 15/80 14/- 19 2 28 14/80 13/- Sp-Bf 20 X+1 2 30/35 29/120 21 2 4 30/35 29/80 Po-1 22 2 30 45/40 44/170 23 3 30 45/40 44/170 Po-2 24 X+1 32 88/40 87/170 25 2 34 79/40 78/170 26 3 36 66/40 65/170 Po-3 27 2 34 79/40 78/170 28 3 36 66/40 65/170 Po-4 29 2 62 53/40 52/160 30 3 63 48/40 47/160 REGENERATION YIELD CURVE AND OPERABILITY LIMIT SUMMAR FOR THE BAU SCENARIO Aggregate Site Yield Oper. Limits Group “No: Class Curve First Last (NMM^3/YRS) (NMM^3/YRS) Pj-1 1 X+1 43 150/50 140/120 2 2 44 140/50 120/130 3 3 45 120/50 100/130 Pj-2 4 X+1 46 120/60 100/190 5 2 47 120/60 100/190 6 3 48 50/80 40/160 Pj-3 7 X+1 49 150/50 140/120 8 2 50 140/50 120/130 9 3 51 30/-- 29/-- Sp-1 10 X+1 52 120/70 119/-- 11 2 53 120/75 119/-- 12 3 54 30/-- 29/-- Sp-2 13 X+1 55 120/70 119/-- 14 2 56 120/75 119/-- 15 3 57 50/145 49/-- Sp-3 16 X+1 58 100/70 99/-- 17 2 59 100/70 99/-- Sp-4 18 X+1 60 100/70 99/-- 19 2 61 100/70 99/-- Sp-Bf 20 X+1 41 100/70 99/-- 21 2 42 100/70 99/-- Po-1 22 2 30 60/60 59/130 23 3 30 60/60 59/130 Po-2 24 X+1 32 88/40 87/170 25 2 34 79/40 78/170 26 3 36 66/40 65/170 Po-3 27 2 34 79/40 78/170 28 3 36 66/40 65/170 Po-4 29 2 62 100/45 90/135 30 3 63 100/55 90/110 Net Mordianlablu Volume (m^) Aft CW4* lhve««« Figure l.a) The present, future and regeneration curves for aggregate number 1 (Pj“l: SCi X+1). Note: niimbers in boxes represent the operable net merchantable volume limits. 1 i 1 E PTYTL ^{CorWlQ - Figure l.b) The present, regeneration and spacing yield curves for aggregate number 1 CPJ-1; SCI X+1). Note: numbers in boxes represent the operable net merchantable volume limits. NGL MurclianlablG VOIUIIIG (III^) Vgt fPflJ Figure The present, future and regeneration curves fo“ aggregate number 2 SCI 2) . Note: numbers in boxes c^«?resent the operable net merchantable volume limits NGL MGrclianLablu Vohiiiio (in’) fTS*vMW>44 p)-i:sci2 I 4 rz RaQM. TC ^ ! I I I i. • I ! / \ \ ! I I I i / Pj-T:SC:2 ?»o- ^ SoAon^ YC ?*0— I i I : ! 200- i#oI— i I I I I I ’I tjo-I ^ / / 100—- I I /■ I : I I I I 300 240 1*0 220 2«0 Trp» y^^r%) SM va Tigure 2.b) The present, regeneration and spacing yield curves for aggregate number 2 (Pj-1; SCI 2) Note: numbers in boxes represent the operable net merchantable volume limits. flel MiM'diaiilablu VOIUIIK} (in’) 10 30 «o ro *0 • no iM tto ire teo no too no tn too 20 eo toe 14C IK isc zee Twmm Figure 3.a) The present, future and regeneration curves for aggregate nu/nber 3 (PJ : SCI 3) . Note: numbers in boxes represent the operable net merchantable volume imits Net NGrchantabiG VoliiiiiG (iii^) rydw » JO 60 ICO 140 «60 22Q 260 300 ■ ^nm vd :Conn«o * • S-C Vd <^9l Figure 3.b) The present, regenerat ton and spacing yield curves for aggregate number 3 (Pj-1; SCI 3). Note: numbers in boxes represent the operable net merchantable volume limits. NL'L HerclianUihl L' Voluiiio Af« C'»4< e>«4tu>* 2iO 280 260 300 - S*c. V«t Figur« 4. The present, future and regeneration curves for aggregate number 4 (Pj-2: SCI X+1). Note: numbers In boxes represent the operable net merchantable volume limits. Net Merchantable Volume (in’) to 90 to n to . lie <30 teo ITO I«O fio S9o 9to sro MO I Pwm, S*c VOL (PO) Figure 5. The present, future and regeneration curves for aggregate niimber 5 (Pj-2; SCI 2). Note: numbers in boxes r«pr«a«nc the operabie net merchantable volume limits. Net Mercltanlnble Volume (in’) to 00 so 70 00 . ito too tu 170 too no no aso 2n no Figure 6.A) The present, future and regeneration curves for aggregate number 6 (Pj-2: SCi 3) Note: numbers in boxes represent the operable net merchantable volume limits. Net Merchantable Volume (iii^) to 30 SO 70 00 110 tse too <70 too 310 no no STO no F Lgure 6.b) The present, regeneration and spacing yield curves for aggregate number 6 CPj-2; SCI 3) Note: numbers in boxes represent the operable net merchantable volume limits. Net HerchanlablG VoUinio (ni^) 10 30 SO 70 00 ■ no 130 ISO 170 100 »tO 230 3S0 270 200 - 2C. 6S 100 1*0 lac 220 2S0 300 r>ip^ W«k(C«r^w| V«s J Figure 7.a) The present, future and regeneration curves for aggregate number 7 (Pj-3: SCI X+1). Note: numbers in boxes represent the operable net merchantable volume limits. Net Merchantable Volume (m^) II Af* CU«« SiiMlt#* T*TW i«r») ^»T*V V«« 0 - Figurc 7.b) The present, regeneration and spacing yield curves for aggregare number 7 (Pj-3; SCI Xri). Note: numbers in boxes represent the operable net merchantable volume limits. NGL HerclianLablo Voliiiiie (n?) ” Vai(CAn4«} —: Figure 8.a) The present, future and regeneration curves for aggregate nucibcr 8 (Pj-3; SCI 2). Noce: members In boxes represent the operable net merchantable volume limits. Net Mercliantable Volume (iii^) {he i» 30 SO TO 00 • fi« 130 100 iro too aie no MO 2TO TOO HTTV Vat lCcnt*n »BL fPo) Figure 8.b) The present, regeneration and spacing yield curves for aggregate number 8 (Pj-3: SCI 23. Note: numbers in boxes represent the operable net merchantable volume limits. Net Merchantable Volume (iii^) At* CIM< to 90 SO 70 00 • 1*0 190 ISO 170 100 >10 >90 >SO 270 200 - V« Figure 9.a) The present, future and regeneration curves for aggregate nximber 9 n. YC »12 I 740-1 -L—d. 700- i»o- 160- 11 7" T~7T t«0 140 T*^ QrMT%( ’ va lCon4«r) ■ Figure 10. The present, future and regeneration curves for aggregate number 10 (Sp-1; SCI X+1) Note: numbers in boxes represent the operable net merchantable volume limits. NeL MGrcliaiitablo Volume (iii^) SM va. rPo) Figurc 11. The present, future and regeneration curves for aggregate number 11 •1 A|« 0»«« (>i^ fO 30 SO m 00' ito ISO iso iSo too 210 no 2*0 aro aoo T»^ VcMCorw>n - •Figure 13. The presenn, future and regeneration curves for aggregate number 13 (Sp-2; SCI X-tl) . Note: numbers In boxes represent the operable net merchantable volume limits. NGI Merclianlable Voliiiiio (in^) iu«lu> t (Nat ^f»Tv Voi S«c va figure The present, future and regeneration curves for aggregate number (Sp-2; SCL 2) Note; numbers in boxes represent the operable net merchantable volume limits. Net MurcliantablG Volume •€«.— S«c. Vet Figure 15 The pres«nt, future and regeneration curves for aggregate number 15 30 MO 2T0 tW> •Figure 19 The present, future and regeneration curves for aggregate number 19 (Sp-4; SCI 2) Note; numbers In boxes represent the operable net merchantable volutme limits. Net MorcItanLablo Vuliiiiic T#T» (yar>) ■ **rrn. 30 XO >70 >00 ^mv vet fCowoo —’ Soc. Vo F Lgure 21 The present, future and regeneration curves for aggregate number 21 (Sp-3f; SCI 2). Note: numbers In boxes represent the operable net merchantable volume limits. Net Mercliantable Volume (ni^) 20 OO 100 ««0 1«0 220 2«C 900 — - Pi*M voi <*oj — S«e VO Figure 22. The present and future yleic curves for. aggregate number 22 (Po-1; SCI 2) . Note: numbers in boxes represent the operable net merchantable volume limits. NeL MGrchanlable Volume (m^) woi ■ S*c voi rigure 23. Th« present and future yield curves for aggregate number 23 (Po-1; SCI 3). Note: numbers in boxes represent the operable net merchantable volume limits. Net MerchanLable Volume 20 60 IOC *40 ttc 220 260 ooo ■ v«i rcorw*n Figure 2^. The present and future vieic curves for aggregate number 2u (Po-2; SCI Note: numoers in boxe i represent the operable net merchantable volume limits. Net MerchanLable Volume 0»«< (Ky to 30 00 TO 00 no tao i«o ITO too oto no no STO MO !»»»• <•^1 ‘ &•< w (C«n^«o Figure 25. The present and future yield curves for aggregate number 25 (Po-2; SCI 2). Note: numbers in boxes represent the operable net merchantable volume limits. NeL Merchantable Volume (m^) Af« 0««« fO K to TV VO nc 190 1M 1TV tVO V10 tVO *V0 fTC tM T»TW tr««rt] ' »»m Vo (►©, ' Voi (Cor*t«o r:.gure 26 Tne preaeni and future y ieid curves for aggregate number 26 (Po-2; SCI 3). Note: nonoers in boxes represent the operable ne t merchantable volume limits. NeL Merchanlable Volume (ni^) Ti*« Ay* (h4 I to 90 S6 To ao 110 ISO toe tro too >to no »*e arc aoo Figure 27 The present and future yielc curves for aggregate number 27 CPo-3; SCi 2) . Note: numbers in boxes represent cne operable net merchantable volume iimits. NeL MGrchantable Volume (in’) R voi C^J &«c V«* fCerpt^ Figure 28. The present and future yield curves for aggregate number 28 CPo-3; SCI 3). Note: numbers in boxes represent the operable net merchantable volume limits. Net Mc'rchanlable Volume (in^) 10 - ao *0 re m no tso too iro i«o tio sse *•» **O — $ fZ-arm^, Figure 29. The present and future vieid curves for aggregate number 29 CPo"^; SCI 2), Note; nu.nbers in boxes represent tne operable net merchantable volume limits. Net MGrchaiilable Volume (in^) 0evMlgt« (K4 20 ftO 100 14C 1«0 220 260 30C T**«* 0'«tn) Ptiii va 1^1 Figure 30. The present and future yield curves for aggregate number 30 7+170+ 0= 177 (*577) Pj-2 4 p/pj HC C2,5 1.0 $630+310+280=1 220 5 p/pj HC C2,5 1.0 $630+310+280=1 220 6 S/Pj MC C2,5 1.0 $ 7+310+280= 597 (*997) Pj-3 7 S/Pj N G-3 1.0 $ 7+170+100= 277 (*677) 8 S/Pj M . G-3 1.0 $ 7+170+150= 327 (*727) 9 S/Pj M G-3 1.0 $ 7+170+200= 377 (*777) Sp-1 10 P/Sb M C2 1.0 $630+170+140= 940 11 P/Sb M C2 1.0 $630+170+140= 940 12 S/Pj M C3 1.0 $ 7+170+140= 317 (*717) Sp-2 13 P/Sb 1.0 $630+170+ 0= 800 14 P/Sb 1.0 $630+ 0+ 0= 630 15 N 1.0 Sp-3 16 P/Sb HC C2,5 1.0 $630+310+280=1 220 17 P/Sb MC C2,5 1.0 $630+310+280=1 220 Sp-4 18 P/Sb M G-3 1.0 $630+170+200=1 000 19 P/Sb H G-3 1.0 $630+170+250=1 050 Sp-Bf 20 P-L/Sb HM 1.0 $700+300+ 0=1 000 21 P/Sb H 1.0 $700+300+ 0=1 000 Po-1 22 N 1.0 23 N 1.0 Po-2 24 N 1.0 25 N 1.0 26 N 1.0 Po-3 27 N 1.0 28 N 1.0 Po-4 29 N 1.0 30 N 1.0 S = Seeded; P = Planted; P-L = Plant large stock; N = Natural H = Mechanical; MC = Hechanical/Chemical C# = chemical treatment at. # years; G-3 = Girdle 3 years prior to harvest PJ = Jack Pine; SB = Black Spruce * cost if spaced. Table 3. The silvicultural specifications for the aggregates under the 40% Herbicide Program scenario and the accompanying costs per hectare and percent yield of BAD yield curves. Agg. Agg. Regen./ Site Tending PCT of Cost Gr. No. Species Prep.. '(Type,yr) BAU Yield ($/ha) Pj-1 S/Pj 1.0 $ 7+170+ 0= 177 c*577) S/PJ 1.0 % 7+170+ 0= 177 (*577) S/Pj 1.0 $ 7+170+ 0= 177 (*577) Pj-2 4 P-L/Pj HHC C3 1.0 $700+400+140=rl 240 5 P-L/Pj HMC C3 1.0 S700+400+140=1 240 6 S/Pj HHC C3 1.0 $ 7+400+140= 547 (*947) Pj-3 7 S/Pj G-3 1.0 S 7+170+100= 277 (*677) 8 S/Pj G-3 1.0 $ 7+170+150= 327 (*727) 9 S/Pj G-3 1.0 $ 7+170+200= 377 (*777) Sp-1 10 P/Sb C2 1.0 S630+170+140= 940 11 P/Sb C2 1.0 $630+170+140= 940 12 S/Pj C3 1.0 $ 7+170+140= 317 (*717) Sp-2 13 P/Sb 1.0 $630+170+ 0= 800 14 P/Sb 1.0 $630+ 0+ 0= 630 15 N 1.0 Sp-3 16 P-L/Sb HMC C3 1.0 $700+400+140=1 240 17 P-L/Sb HMC C3 1.0 $700+400+140=1 240 Sp-4 18 P/Sb G-3 1.0 $630+170+200=1 000 19 P/Sb G-3 1.0 $630+170+250=1 050 Sp-Bf 20 P-L/Sb HM 1.0 $700+300+ 0=1 000 21 P/Sb M 1.0 $700+300+ 0=1 000 Po-1 22 1.0 23 1.0 Po-2 24 1.0 25 1.0 26 1.0 Po-3 27 1.0 28 1.0 Po-4 29 1.0 30 1.0 S = Seeded; P = Planted; P-L = Plant large stock; N = Natural M = Mechanical; HM = Heavy mechanical; HMC = Heavy mechanical + chemical C# = chemical treatment at P years; G-3 = Girdle 3 years prior to harvest PJ = Jack Pine; SB = Black Spruce * cost if spaced. Table 4. The silvicultural specifications for the aggregates under the Aerial- Tending-Only (A) scenario and the accompanying costs per hectare and percent yield of BAU yield curves. Agg. Agg. Regen./ Site Tending PCT of Cost Gr. No. Species Prep.. (Type,yr) BAD Yield (S/ha) Pj-1 1 S/Pj H 1.0 $ 7+170+ 0= 177 (+577) 2 S/PJ H 1.0 $ 7+170+ 0= 177 (*577) 3 S/Pj H 1.0 S 7+170+ 0= 177 (*577) Pi-2 4 P/Pj HM C2,5 0.85 $630+170+280=1 080 5 P/Pj HH C2.5 0.85 $630+170+280=1 080 6 S/Pj HH C2.5 0.85 $ 7+170+280= 457 (*857) Pj-3 7 S/Pj H C3 1.0 $ 7+170+140= 317 (*717) 8 S/Pj M . C3 1.0 $ 7+170+140= 317 (*717) 9 S/Pj M C3 1.0 $ 7+170+140= 317 (*717) Sp-1 10 P/Sb H C2 1.0 $630+170+140= 940 11 P/Sb M C2 1.0 $630+170+140= 940 12 S/Pj H C3 1.0 $ 7+170+140= 317 (*717) Sp-2 13 P/Sb 1.0 $630+170+ 0= 800 14 P/Sb 1.0 $630+ 0+ 0= 630 15 N 1.0 Sp-3 16 P/Sb HH C2,5 0.85 $630+170+280=1 080 17 P/Sb HH C2.5 0.85 $630+170+280=1 080 Sp-A 18 P/Sb H C3 1.0 $630+170+140= 940 19 P/Sb H C3 1.0 $630+170+140= 940 Sp-Bf 20 P/Sb H C2,5 1.0 $630+170+140=1 080 21 P/Sb H C2,5 1.0 $630+170+140=1 080 Po-1 22 N 1.0 23 N 1.0 Po-2 24 N 1.0 25 N 1.0 26 N 1.0 Po-3 27 N 1.0 28 N 1.0 Po-4 29 N 1.0 30 N 1.0 S = Seeded; P = Planted; N = Natural H = Hechanical; HH = Heavy mechanical; HC = Hechanical/Chemical; C# = chemical treatment at # years PJ = Jack Pine; SB = Black Spruce * cost if spaced. Table 5. The silvicultural specifications for the aggregates under the Aerial- Tending-Only (B) scenario and the accompanying costs per hectare and percent yield of BAU yield curves. Agg. Agg. Regen./ Site Tending PCT of Cost Gr. No. Species Prep. (Type.yr) BAU Yield aced. Table 8. The silvicultural specifications for the aggregates under the Other- Weed_Control (A) scenario and the accompanying costs per hectare and percent yield of BAU yield curves. Agg. Agg. Regen./ Site Tending PCT of Cost Gr. No. Species Prep.. (Type.yr) BAU Yield (»/ha) Pj-1 1 S/Pj M 1.0 $ 7t170+ 0= 177 (*577) 2 S/PJ M 1.0 % 7+170+ 0= 177 (*577) 3 S/Pj M 1.0 t 7+170+ 0= 177 (*577) Pj-2 4 P/Pj HSSM BS5,7 1.0 $630+500+800=1 930 5 p/pj HSSH BS5,7 1.0 $630+500+800=1 930 6 S/Pj HSSH BS5.7 1.0 $ 7+500+800=1 307 Pj-3 7 S/Pj H G-3 1.0 $ 7+170+100= 277 (*677) 8 S/Pj M . ■ G-3 1.0 $ 7+170+150= 327 (*727) 9 S/Pj H G-3 1.0 $ 7+170+200= 377 (*777) Sp-1 10 P/Sb HSSM BS5 1.0 $630+500+400=1 530 n P/Sb HSSH BS5 1.0 $630+500+400=1 530 12 S/Pj HSSH BS5 1.0 $ 7+500+400= 907 (*1 307) Sp-2 13 P/Sb 1.0 $630+170+ 0= 800 14 P/Sb 1.0 $630+ 0+ 0= 630 15 N 1.0 Sp-3 16 P/Sb HSSM BS5.7 1.0 $630+500+800=1 930 17 P/Sb HSSH BS5.7 1.0 $630+500+800=1 930 Sp-4 18 P/Sb H G-3 1.0 $630+170+200=1 000 19 P/Sb H G-3 1.0 $630+170+250=1 050 Sp-Bf 20 P/Sb HSSH BS5,7 1.0 $630+500+800=1 930 21 P/Sb HSSH BS5,7 1.0 $630+500+800=1 930 Po-1 22 N 1.0 23 N 1.0 Po-2 24 N 1.0 25 N 1.0 26 N 1.0 Po-3 27 N 1.0 28 N 1.0 Po-4 29 N 1.0 30 N 1.0 S = Seeded; P = Planted; N = Natural M = Mechanical; HSSM = Heavy site-specific mechanical C# = chemical treatment at # years; BS# = Brush saw treatment at # years PJ = Jack Pine; SB = Black Spruce * cost if spaced. Table 9. The silvicultural specifications for the aggregates under the Other- Weed-Control (B) scenario and the accompanying costs per hectare and percent yield of BAU yield curves. Agg. Agg. Regen./ Site Tending PCT of Cost Gr. No. Species Prep.. '(Type.yr) BAU Yield (S/ha) Pj-1 1 S/Pj M 1.0 $ 7+170+ 0= 177 (*577) 2 S/PJ H 1.0 S 7+170+ 0= 177 (*577) 3 S/Pj M 1.0 S 7+170+ 0= 177 (*577) Pj-2 4 P/Pj HSSH BS5,7 0.85 $630+500+800=1 930 5 P/Pj HSSM BS5.7 0.85 $630+500+800=1 930 6 S/Pj HSSM BS5,7 0.85 $ 7+500+800=1 307 Pj-3 7 S/PJ H G-3 1.0 $ 7+170+100= 277 (*677) 8 S/Pj M ■ G-3 1.0 $ 7+170+150= 327 (*727) 9 S/Pj M ' G-3 1.0 $ 7+170+200= 377 (*777) Sp-1 10 P/Sb HSSM BS5 0.9 $630+500+400=1 530 11 P/Sb HSSM BS5 0.9 $630+500+400=1 530 12 S/Pj HSSM 6S5 0.9 $ 7+500+400= 907 (*1 307) Sp-2 13 P/Sb 1.0 $630+170+ 0= 800 14 P/Sb 1.0 $630+ 0+ 0= 630 15 N 1.0 Sp-3 16 P/Sb HSSM BS5,7 0.85 $630+500+800=1 930 17 P/Sb HSSM BS5.7 0.85 $630+500+800=1 930 Sp-4 18 P/Sb M G-3 1.0 $630+170+200=1 000 19 P/Sb M G-3 1.0 $630+170+250=1 050 Sp-Bf 20 P/Sb HSSM BS5,7 0.85 $630+500+800=1 930 21 P/Sb HSSM BS5,7 0.85 $630+500+800=1 930 Po-1 22 N 1.0 23 N 1.0 Po-2 24 N 1.0 25 N 1.0 26 N 1.0 Po-3 27 N 1.0 28 N 1.0 Po-4 29 N 1.0 30 N 1.0 S = Seeded; P = Planted; N = Natural M = Mechanical; HSSM = Heavy site-specific tnechanical C# = chemical treatment at # years; BS# = Brush saw treatment at # years; G-3 = Girdle 3 years prior to harvest PJ = Jack Pine; SB = Black Spruce * cost if spaced. Table 10. The silvicultural specifications for the aggregates under the No- Weed-Control scenario and the accompanying costs per hectare and percent yield of the BAD yield curves. Agg. Agg. Regen./ Site Tending PCT of Cost Gr. No. Species Prep. . ‘(Type.yr) BAU Yield 000 0000 •000 ' 0000 «OO0 ••00 OBOO •eoQ • •ACXM« L«V«L IIU/XTIkATIOMI : 509 500 500 500 500 500 500 500 500 500 500 500 509 500 500 500 500 500 509 500 ■ •ACIMS •IMDO« 50 - 20 * ftULSl * BVU2 rXHB BAMa 100 i 0 0 0 OOP 0 - iOQ TXMOIB VALUS4 (t/H3); • BOOUCT- - 45 HOW-BRODUCr - 55 MCOHOABT VOL - 25 BEAL OIBCOUMT KATI - .040 OONttOMI 0: CaOBN CURVS ttT riLt: TC3.RAU rOKKT CLAOS tlLM^ BJ2. OAU, COST riu COBt.BAV • ■■XDUAl. rOBIBT •TATttTtCB BOB TM BBRIOO OMRABLt VOUIM m3) voLUMi evr m3) coatB iiiaooi noRTAxxry m3) • BACB MABVItI • UXrT AAIHT. BBACB BOT. 753. 200 29410 732 200 44292 700 200 49207 4 159 200 41575 352 t 4530) ««04 200 50920 5001 41424 4B92 200 43250 2526 47011 4954 300 36«05 1936 5I294 5301 200 4050 1515 •9403 702' 200 2410 100451 40)4 200 2530 52936 9021 199 2073 S95«-< 502* 14*7 57014 «7ia 1572 70144 1490 529 977** 2272 451 42«0l 200 2156 503 • 1033 300 3092 709 5353 I 200 3366 72? 5219'’ 200 3557 701 9153 3 A6I cuiaa •TRVCTvaa Ad CUL49 20*40 io*ieo loo'kio 130> 40 140*160 160*lao l4D-2eC 23«9 25419 iai59 2215 3134 21300 20945 1341 27490 4193 15355 2137S 2007-1 1555 1 0«2 3 23144 19704 20IB9 21524 19544 24135 4*4 14214 27490 072 ll«5' 20Q77 732 5171 19709 340 19544 472 22144 19495 530 21990 1973C 305 21714 19942 •54 19429 22205 527 1947J 22144 955 19949 2X356 357 19056 017 19424 596 19473 026 •24 WW»AMW4»T UM3T t «aoaiMC 490C4 AAtA RAirVl»rtO A«5A t»tAT4t> • uwrr TN15 44ArvB •uwrr 745 4943 465) 745 4945 4645 745 4751 47H 745 5049 5t*9 4404 4404 4491 4441 4994 49«5 5301 5>e: 54< 7#f7 94J7 546 44)4 41)4 56« 745 4120 4434 2022 745 45J7 5074 1496 745 4234 47)4 157 • 4342 4474 1944 137] 5)4« 227J l»0 5721 . 2*55 304 3 3355 3556 NMVtlT C04T 76)5’ 9; Buwrr. 9N1M. * --f —ri~-—i 6542 3 « TOTAI. •BMirXT 135551 1C •4M ilXCL NAAVttr CM71 U593t o: PM IIMCL. MBVlar CM7I 52553 «4 The Jack Pine Forest Type's primary qrowing stock and harvest volumes at five-year intervals in future time. The Jack Pine Forest Type's secondary growing stock and harvest volumes at five-year intervals in future time. The Jack Pine Forest Type's harvested, regenerated and spaced areas as a function of time. SHORT REPORT FOR SP IN THE BAU SCENARIO rOftMAM VCIIICM 2. 1 • ACKOAOUMO NAlrvSIT tUUIVItT LKVCL inS/lTKKAtlOMI : 4&&ooa 4SSOOO 45&eoo 4&&000 4SSDOO 4SJOOQ 4Si009 4»&000 rLAirriMC LIVIL (NA/iriiiAria4fi: lOOQ laoo 1600 1000 II 1000 1000 loos ioeo 11 tPAClMC LSVIL (HA/lTOItATtCWl : HAJtVIOT KWUt » RUUl *UU2 100 100 0 0 0 T1M6IK VALVIt K/N3): 3S ■tCCWDAilY VOL - CUMVt OIT rlLI VC3.S< ite&. 4**000 707*4 42* 3011 303a. 4**000 31*4* 2-»»l aaot. 4**000 27071 2433 2404 4**000 2*2*1 20^0 23Pa 4**000 244*71 114S 2432 4**000 2410*1 14' 2*41 4**000 7*1*1 2*21 4**000 «S7« 3070 4**000 1007*7 2P10 4**000 &33«7« 4**000 1*2*44 4**000 207*01 AC4 Cl»* OTOUCTVBI ACO ClAS* 40>*0 *0>60 60 140-1*3 140-iOO )00-20e ■ *4C 14*0 12412 1«70« 13*13 *** 0*21 1*710 1*70 I too* t«e*« 13007 **74 10701 1*442 •*40 70*4 1*020 12*33 4240 14«*2 1*7*1 14 4 14 130*7 13*21 1*442 132*0 1*020 12*31 *1* 12011 14**2 1*7*3 1002 12*2* 130*7 •*74 1240C 1*27C 0*27 137** 13013 12270 1*34* 11144 14*04 l***C 12133 *77C 1**24 13321 10*47 1*S14 112*0 101*1 170*4 12001 10274 17*31 12*2* 10*2C KMtACCnOWT WMI7 • 2300 leo; 2 IS* IOCS 200J lOOC I*B; loee teoe 3002 220* 10*3 2404 lltl 2347 4*00 lose loec 2*10 *20* iso: 312* 1732 3221 4217 MKViar ODOT 4*412 44 -PI.M4T.' 4M1M. 4 IMJaTCMMfC-l *131 *4 404A1. o'calPIT 4*144 2: 044* ICXCL HAKVB04 eo*T] *•03* *S mm IlMCL KMiVBtr COST] 40*31 >1 ¥«. Stuck 'tU, The Spruce Forest Type's primary growing stock and harvest volumes at five-year intervals in future time. The Spruce Forest Type's secondary growing stock and harvest volumes at five-year intervals in future time. The Spruce Forest Type's harvested and regenerated areas as a function of time. SHORT REPORT FOR PO IN THE BAU SCENARIO romuMt viaaiOM 2. 1 »ACKC«OUND HAKVItT HAMVtIT LCV«l. IK3/ITBRAT10WI : •OOOO tOOGO tOGOO tOSOQ •GOOD *0000 GOOGO GOOOO ITLMrriWC UVtL out/ITIHATIOHI : GGACINC UMVtL (HA/ITGftATXOW) : lUUIVflT aULtl \ RULIl m/uz 100 100 0 0 0 f rmtR VALUGl (G/M3I : 33 GGCOMBAGT VOL - cVKvm air riu YC2.»M> rOVCGT CLAGG riLG PO- GAU COGT fXU- COGT. OAU OIGXOUAJ. POPGGT PGGIOO OPCRAGLG VOUMG tH3 VOLUNG eVT ACGA (NAi coara ISIQOOI nOMTALZTT (N3) PGIIUUIY GGcoaiMaT PHIIUjrr GGCOMDMY MOOUCT CVt puwrr GPACB RAAVIGT PLAKT MAJIT GGACG POt. ■tAl. 3YY7 GOOOO 0 41492 34103 3YGY. GOOOO 0 &19G& 44321 3Y00 SIZ. GOOOO 0 7G043 70336 JSAS SG& GOOOO 0 111G31 103332 3413 »G« GOOOO 0 132200 124573 33*1 'TOG. GOOOO 0 122043 114359 3243 G«S. GOOOO 0 1143G7 105725 943 Goeoc 0 109S93 100315 9*3. GOOOO 0 9G914 G2497 102* Goeec 0 G407J **311 10*0 Goeee 0 GGG31 *0914 10*1 GODOG C 12G7G7 54742 IDS* GOOOO 0 1391)4 591*5 1GT> GOOOO 0 11319* *333t 1079. GOOOO 0 10*00) 10*521 1074 GOOOO 0 2025*1 202531 Gooea 0 3G3994 303954 GOOOO 0 395914 315074 00000 0 230927 150922 GOOOO 0 2*0172 1G0132 Afil CLAGG OTGVCTWGI IMK> 40-«Q 0 120-146 140-1*0 1*G-I*a IG0-20C 7DG3 *375 422* *547 2144 009 43*9 710 200 3*11 003 3*4 2333 3*9] 22* 12*1 2333 4144 1*10 144 2144 2330 1*3'’ 42*« 521 2*3* 2323 2315 3*10 10*4 2333 3**1 5**: 2333 002C 2330 1*57 12924 2323 2315 11*1' 23'»‘' 2333 11*11 2430 2333 1134.- 24*0 2330 7547 300* 2323 2377 257; 34 10 v*l*/4 utt AGO* KUVIOTrD AAIA fatATtO COOT (Jkjm VALUt PLA4TT talH MArvK plApr* *«!■ M*V« a«t i >«( ■ t«*l 1 J97J I«>l 0 11*1 IV*' 3*44 0 >1*5 15*5 15*5 0 3151 1551 3412 C 3 I »i 154' 31*0 12*1 II** 15** 1131 B 3124 1V2* 3044 1 1211 1*12 2*75 2 325* 1*5' 2905 Q 377» |*->» 2044 »I2 23)1 2’7# 0 402* 243* 2712 0 3*2 * 202 4 2*02 0 492* 242* 239* 0 40* 24 I* 2093 0 49)9 24)4 177* 0 40 1* 2* >* - 1*3* e 4924 24:4 «AGVt*r «*T PLA4TT. TMIA. 4 ItAlWTCMMM 909 A1 GGMGGI7 *M ICXCL RAG5/IGT COtTl *W« (il*CL AAAVGGT COGT > The Poplar Fores^t Type's secondary growing stock and harvest volumes at five-year intervals in future xime. The Poplar Forest Type's harvested and regenerated areas as a function of time. The wood-supply and regeneration results from the forest level analysis of the Seine River Forest Management Unit under the Business-As-Usual management scenario. Forest Type Wood-Supply Regeneration Softwood Hardwood Planted Seeded Spaced (m'^3/yr) (m^3/yr) (ha/yr) (ha/yr) (ha/yr) Spruce 91 000 32 000 200 Jack Pine 149 000 12 000 151 869 100 Poplar 6 000 16 000 Total 246 000 60 000 351 869 100 Treatment Activity BAU Scenario Tknt (yri) The treatment activity for the BAU scenario for the 100-year forecast period. SHORT REPORT FOR PJ IN THE 67%HP SCENARIO rouMAtt viaaioi RACVtIT V«L «N3/irKHAtlOMI: 'M&oaa T«sfioo K&aflo 74S000 74SOOO 745090 745000 745000 >LAWTZM« UVft. (HVI70MATICW) : •OOO 0000 0000 0000 •< •eao ooee ooeo OAOO ‘ oi • PACZM6 LCVIL IMA/7TtKATI04l) ; 500 $00 500 $00 500 ■OACiwo aiMOaB 10 - 20 ■AJtWIY auui I «UU1 MUU2 riMi uuic« lOO too 0 0 0 0 - 100 rxwotn vAu^i* rc/MO loecNboy VOL CVRVI iOT riu yc3. Clip rcMIlST CLAII riL$: C04T riiu c*«t. CAP ■ ttOPT OH TNI rONIIT •I41DUAL roatST ITArilTICI PO« TNI PSNIOO OPCCMU WOUMI VOUIMC cut (N3> AMA IMA' COITt ISlOOOl fMNITALITT (M3) TIMI MINAIY ICCCMDAIT MIOOUCT «IRAIT IICDHDAJIY OCOeuCT CUT PLAHT lOAiCt uavtlT OLAfTT HAIHT. lOACt »OT ftlXt, 5 5771 7CJ 0 745000 43$$$ 200 $4$$$. 29418 1C $34« 732 0 7450DC 4394Q 200 79049 44292 IS 47J3 TOO 0 745000 49914 200 13170. 49207 2= 415t. Cll 0 745000 43549 200 77013 41575 25 3C21 C7J e 745000 45303 200 05425. 50921 30 3041 C*«. 0 745000 44424 200 77I36. 43250 3S 3534 C73 0 745000 47Q$| 200 $4972. 2$itS 40 1934 CC7 0 745000 5929I 200 43$03. 4050 45 1515 $41 0. 745000 $9403 200 33308. 0 50 2411 $14 0. 745000 100451 200 2008. 0 55 2531 427 a 745000 $2936 4031 199 2$$7. 0 $0 2023 $31 0 745000 59$$7 503 4 203 0 D $5 1447 $42 0 745000 57011 4734 173 200 0. 0 70 1C72 439. a. 745000 70194 753 199 0. 0 75 1944 $30 0 745000 977$4 09$ 2DC 0 8 •C 2372 $53 0. 745000 $3001 3023 200 0. 0 •5 315$ $13. 0. 745000 $1013 200 0. 0 9C 3093 70». 0. 745000 $3$31 ZOO 0. 0 95 33$4 737 0. 745000 $3307 200 0. 0 100 35$7 70$ 0 745000 93$50 200 0. 0 AfiC C1A99 •TAWCTVai A6I CLA99 9*20 20-40 40-90 CO-40 $0-100 100-120 : lO 140-190 190-140 It0-2SG 20199 2340 4 155 25414 14254 2315 34135 3138 14*9 31300 20945 37490 8193 1072 IC395 21270 1954 20077 1555 1 1732 1121 23144 19708 3et$9 2180 2192$ 19544 24135 3134 1419 14218 19495 27490 1072 1957 19730 2007T 1732 19992 19704 2300 22205 19544 2472 33149 19445 2$30 2J99D 19730 10305 19942 10$$4 22205 10$27 22141 19495 3 139$ 19$4« 190$$ 19422 12012 2 1545 19429 1939) 1159$ 22 17' 19473 1202$ 21157 19134 13924 OAIH VAlAlt 342 I 30i; 252$ 44}l 251$ 4429 2037 502* 144$ 4714 }$7 1 4979 1994 5301 237 1 $721 500 . 3455 494: 50C 304 1 54$C 500 3395 451* 500 359$ HA»V8«t COOT • UMTT. TNIH. * I4A21 »MAHCf tOTAI. acMBPIT 13$5$3 10 Mra mcU. MAAVtlT C09TI 12$9«1 $C mm IIHCU MAlIVtaT C04T1 57413 94 SHORT REPORT FOR SP IN THE 67%HP SCENARIO rOMAN VlRttOH 2. ■ ACVCaCMMD MAJtVSrr MAMWIT LWVl. m3/rTiaATtQH} : 4&»Q00 4&SQOO 4SSOOO 4SS0OO 4S&000 4&SOOO 4SS0D0 4SSDOO ruW4TIHC UVtL (MA/lTCKArXCM) : IQQO lODS iOOO lOBO 1< lOOC lOOO iOOQ voeo ' II irAClna UVtL J«tQ HAflVlVr HAJtVTIT LWIL (113/ZTIHAT XCM ) : 74&00Q 74&000 T«se«6 ?4&aoo 71SOOO 743000 T«i000 74SOOO rUUrrXMC LCVIL 4NA/tT(«ArZCM) : •BOO BOBO BSBO BSOO II ■BOO BOBO BBOO BOBO ' B« ■ BACTMC UVtL IMA/ITBUTtOHJ . BOO SBC BOO SOO ! SOO BBQ BOO BOO ! B»ACXW« VIMDOB ID • MAJtVBBT BVUa « BUU1 lOO 100 BOD TtMBC* VAlrUBB (t/N]| 43 MOM-tMOOWCt 3b BBCONbAJrv VOL ■ aCAt. OIBCOUWT MAT! - OMBBBMXP CMOm euavB BIT rtLi. ycJ.bha VOaaiT CLABB rXLB: coiT riu «*•«. Bli> • ItlDUAl. rOMBBT B7A7IBTIC4 rOB THB KaZOO OBfMABLt VOUMI 4143) VOUMB CUT fM31 ABBA IMA] COBTt ftlDOO) 9MTAUTY (M3) MtHABT aBCaHDAJIY MINABY •tCOMOAAT PMOOVCT CVT BLAa>7 BBACt MABVSir rLMTT NAIHT SBACt BOT i77i. 7«3 00 200 646«6 3344 732 00 43*40 200 7*049 4733 700 00 4BV16 200 • 3170 4134 «B3 00 4234* 200 77013 3&S 1 *7 3 00 43303 200 •3423 3sa 1 •69. 00 44424 200 7?t36 3336 *72 00 470BI 200 •4172 1B36 •*7. 00 3B294 200 43BB3 1313 *41. 00 ■ 9403 200 3330a 3416 *ia 00 100431 4B34 200 2011 233t *27. •2*36 4B2* 2*67 2023 •33 3«*B7 3024 14B7 •42. 3701* 473* 200 l«72 •3* 701*4 4«7* If* i««a •20 •77*6 3304 200 2272 •31 •2601 •73 t 200 2B36 MJ. • 1033 4*42 200 3042 70* •3*3 1 3460 200 3366 727 •23B7 43 3 4 200 33*7 708 92 *30 4331 200 ACS CIAIB BTBWCTUBI (KA) 0-20 •e-iBO 100 0 120-140 140-1*0 1*0'1BO lBO-200 2B1B* 4133 1123* 24133 14*4 21300 20»B3 27440 1072 1*J*3 21270 30077 1732 ■ 12 1 23 14a 1*700 2380 3 1*3 6 1934* 313a 1419 ia2ia 706 1*4*3 414] 1072 tia37 i*2a 1*730 1333 1 1732 2*00 i*«a2 20ia4 2310 1211 22203 24133 2472 22i*a 27«*0 2*30 2>««0 20077 10303 2 |7ia 19701 I0**4 1*42* 1*344 10*27 1*473 t*««3 104*« l««4a ia*«4 11332 2 1*41 1*B32 12012 2 1343 1*3*) I 1*4« 22127 1137k 213>7 J7307 MMiAt^iwt wMiT a 1 CMcaiMC r^orrt VAUIt Ml? AJIIA MAJrVlOTlP AABA TMATIC COOT CAIM VAIXII >UWrf TMIM MATVa OLMT? TMIM MATVB Mil Mil Ml 0 *203 7*9 3 377* 7*2 743 43 0 8 4**3 4*63 30C 10 3244 732 743 41 0 0 4443 4443 SOO 13 4732 710 743 4t 0 0 47V. 4731 SCO 2C 4131 ••) 743 43 0 0 • 04* 304* SOO 23 a*2 1 •73 743 43 0 0 4004 4a04 SBC 30 3011 •64 743 44 0 0 4a*l 4a41 300 33 2326 •72 743 47 0 0 «*•• 4466 300 43 l*Jk •66 743 3t 0 0 3301 S30I SOO 43 1314 *4 t 743 MOO 7077 707’ 30C 3C 24|7 •it 743 100 0 0 40)4 4«)4 SOO 33 231t *36 743 •2 0 30a 4130 4021 300 60 3022 •32 743 3* 0 442 43)7 sez* *oe •3 1416 •4) 743 3? 0 300 «2)B 47)t 300 12 7C 1171 •)4 745 70 36 300 4)42 4071 300 73 !**• •14 743 *7 2771 1140 1371 S304 sec ■0 2771 •30 *43 •2 404} 300 too ft?!) sec •3 . 2133 ••2 743 •I 40*0 30C 32 4*42 300 *9 3041 704 743 •3 4021 300 13* 3460 sec *3 3363 726 743 43 4034 see 0 43)4 SBC 100 3366 707 743 *2 2t3l 300 0 4331 too MAavBs? eo«? 74337 *1 BLAirr. TMIN, 4 MAJMTCMMfCI *721 33 707AL •■■■•?? IJ434J 1C ■MM (ixcL MAjrviat coot I 12M4 1.40 •M* IIMCL. MAMVla? 00*71 32403 •• SHORT REPORT FOR SP IN THE 50%HP SCENARIO rowwi VHflOM 3.1 • AneMOUHD HAJtVItT NAMVirr LKVIL IHj/ITtaAtXaN) 4S&0Q0 4S&000 4S&mO 4S6QSO «SSOOC 4S&00a «bseoo 4S&aoo 4^kQ0C 4S»S0C 4S&000 4S5000 4&SOOO 4»»000 «&&eOC 4SS00C «sieoo 4S«0D0 4SSOOO 4&&00S VLAMTIMS LCVlk Bt (I/M3) OOOOUCT - 4S WOM-MOCMCT • 3& 08COMDAJIY VOL - 21 ■ 8AL DIICOUHT HAT! - .040 CWOOONl f C«OM( CVOV1 OtT rxLi yc3. Shp rOOtIT CLAIf riLt: • ^kf.»4U COOT riLl eaac. Sfip • lotouAi. roaooT OtATJOTtCO ro* T«C 8BBIOD OOCOABLC VOUM8 0*3) VOLUHB CVT (Ml) MBA IHAi COBTB ItlQOOl HMTAUTY CHS I Tint OOIlUJrr 0BC«atDAftY MOeoCT MIMAOV BBCOMMOT noOUCT evt Ot-MT OOAiCB ■MVBOt OLM4T MAIHT. BOACB OOT OBAl.. 1 312'* 30*4 0 4bS0OO 1104*2 e toil leoD 0 19*09 10 3**0 343T 0 4bbOCO 33**«t e 183b leec 0 10771 11 4013 3300 0 438800 X336H 0 10*« 1009 0 4*00* 0 . 20 4133 21*0 0. 488880 llllia 0 194G >eC3 0 40149 21 4131 2001 0. 488080 182094 0 18*4 loeo 0 31938 30 4003 1903 Q 488000 1*8**0 0 J4«'< loe: 0 14847 JS 3341 3tb2 0 488000 114**'’ 0 1410 lOSf 0 4742 40 313'’ lObl 0 488000 lOTiet 0 3144 too: 0 707 4b 3234 190S 0 488000 70780 0 3234 IOC 0 0 92* bC 30'>3 2030 0 48808C 31890 e 30B? loec 0 72 bb O')*! 3200 0 488000 27071 0 10*3 los; 0 30 0 *C 7413 2*04 C 48800C 39201 0 3111 lOo: 0 084 0 *b 20SC 23*0 fl 488000 3449T3 0 480C lose 0 8 1131* ■»C lT4b 2433 0 488000 341*81 0 4*7J HOC 0 0 10077 lb 1444 2*41 0 488000 78141 0 3870 teec 0 D 1788 OC 13*C 392b e 488000 *874 0 3000 loec 0 80 Ob 1014 30TO 0 488000 1007*-’ 0 4390 leec 0 873 90 OC) 3910 0 488000 833*19 0 *20* leee 0 *B4 9b lit 3121 0. 488800 1*3944 0 *084 iceo 0 1270 lec 93b 3323 0 488000 387*01 0 8900 loee 0 9099 1174 *34 *|SB CLAft BTBVC9UBB 20*40 100-US 120 140-1*0 1*0-100 100-300 l**C 1*73* 989 1*804 100b *0** 18049 *974 0791 1*810 18442 0840 70*4 18030 13833 1***2 187*1 130*7 18442 18020 14**3 1282* 144 14 13*23 llTb* 133*0 1834b 13103 180*C 1282* 18*24 13*90 18819 1378* 17084 1814b 783b 18B*0 MOMAeCNBWT MMIT • 1 090C9 HMVBiT VAAl/9 BO 4 !■ M} (■ nil MIA kMVBOTiO MCA 9O0A9BC COOT *A10 WAIA'I ro *oiM ooc Ml* ooc OLAMTT 901M BATOO OLAtTT 9010 OMTVO Mil Mil IMb C 31*1 3032 b 3820 3**J 48b 170 0 0 4011 lie: 10 3984 2*3* «8b 33* 0 0 3828 loec IS 4003 2300 08b 132 B 0 19*« 1*00 25 4172 2184 *8b 171 0 0 3*40 2b 413b IOC) *8b 1*2 0 0 380* teec i*ee JS 4003 1*02 «8b i*0 S B 3447 }9oe 3b 379C 108) *8b 114 0 0 2410 HOC 40 3817 14SC *8b 10’ 0 0 31*4 loec 4b 327* ifQs ■8b 70 0 0 3314 loec 80 3073 203’ *88 31 0 0 3oo: loe: 8b 2791 2200 *8b 27 C 0 3*4] loec OC 2*1} 2*04 488 24 8 0 3111 lie: *b 2044 21*7 488 2*4 0 8 480C lec: 7C lT4b 74JI 488 241 e 0 **7 7b 1*4* 2*43 *88 7b 0 0 387*| lOOC: too 6 387| 05 12b* 3928 *8b * 0 0 2**0 toot e 1**0 Ob 10)9 307C *88 1*0 0 0 *390 loee S I34C *0 *00 2*10 088 »31 e 0 *30* IBOC t 820* 9b 711 112* 088 1*2 3327 0 1712 ites e 108* .03 93b 3223 488 207 IMJ 0 4217 tiOC 0 ««0C ■MVBtl COOT *8*12 *« WIMTI, tJMW. * lOAJirtBMMiCl 90TA1. BBwartT *»l*9 2C BM» ItilCL HMVtOT COOTl *187] 19 OOM riBCk MABVBOT CD«T I 4*1*1 32 Treatment Activity 50HP Scenario The treatment activity for the 50HP scenario for the 100- year forecast period. SHORT REPORT FOR PJ IN THE 20%HP SCENARIO rOMAN VIKtlCM 2.1 • ACTCBOUNO MAMWIT HAKVfIT LCVIL (H3/ITIRATICW1 74iOOO 74S000 T4SBD0 74&00D 74&000 745000 745O0C 745D0D 745000 745000 74S00Q 74S0Q0 TtSfiOO 74SS00 745000 745000 745000 745090 74500C 745000 fUUVTJNC bCVBL (M H3l A*BA MASytOTCO ISBA rSBATBI T4 MrM BBC MATUM SLAMT TNIM MATUB C «2CJ 74* 5 577B 752 745 0 «»5) «*5J 508 C 5344 73? 745 43 0 4*45 4*45 50C 5 47J2 700 745 4t 0 4751 *751 508 C 415B Ml 745 0 504* 504* 50C 5 352 1 •7? 745 • 5 0 4404 •BO* 508 C 30B 1 M« 745 0 4**1 **«I 500 5 3525 r>7 745 0 4*45 4*a* 500 C 1435 •54 745 54 0 5 30 I 5101 508 0 702’ 702’ 50C 3*1’ 745 IOC 8 0 4i34 40)4 508 25)4 •3* 745 52 0 504 4320 4*24 50C 2022 •32 745 5* 0 442 45)7 502* 50C 54 1 745 57 0 505 4331 <7)1 508 534 745 70 35 500 4342 4B74 503 • 14 745 47 3771 llAfi 1371 5304 500 550 745 52 5041 500 IBS *7;-. 50C 45 . 2455 M2 745 51 4040 50C 52 4542 508 48 last 70* 745 51 4421 500 11* 5*58 veo 45 3355 73* 745 52 4014 500 0 4534 508 IOC 3555 707 745 *2 3451 500 0 4352 5DC MABVBOT COST 74157 fi • UW4T. TMIM. 4 MAIMTBMJM* *757 t’ TOTAL BBMCPIT 1J555J 1C BM IBKCL MASVBBT COBTI 125B05 3C BMM IlMCL MABVBST COST I 52447 37 SHORT REPORT FOR SP IN THE 20%HP SCENARIO rOMMAM VI«aj(M 3. 1 BACBCaOUNO mJtVBIT •UmVlBT L.WXL fU/IftRATSOMy : 4&S000 «&&OCO 4&500Q 4SSOOO <&S000 4SSOOO 4S5000 4S&000 BLMrrtMS LSVBL IHA/XTtRATIQM) ; laoo 1000 looB laoo 1000 2000 lOOO 1000 ■ OACZHC LSVIL fK*/1YBBATIOM) : NAJtvoaT Kvua « RUUl TtllO *M*6t ICO 100 TiRora VAXUOO (I/M3! 0*MIItHIt CUOVI (IT riLO. yc3.Ihp rooiiT ciAft rxLi coat a t LB. e*aa.thp ■ttlOUAL rOBttt •YATtOTtCt VO« tat MUOO orcaAiu voLMi* nO) VObUPB CVT IHll M*A (HAJ COVTC ItlOBOl NOCTAUTT (lOl ttMl MIHAJtt MCCMaAIIY MlMlUCT MIHAJtY HeOWaJUtY MOOUCT Cirr OLMTT B»AC1 MIVItT WlMtr HAIITT. BOT. RKAL S IS}'! 2*«4 0. 43&e00 17ft«*2 0 40)1 leoo 0 100 1134 0 0 19*99 10 J«*0 7137. 0 4&SOOO 33*««i 0 3131 099 1141 0 0 10771 IS 4003 2300 0. 4S&DOO 133017 0 394* 099 1141 0 0 4*99* 30 «ltl 21*0 0 4&3OO0 171710 0 394C 101 1141 0 0 40149 3S «13& 7003 0. 4»seee i03»«4 0 310* lOl 1141 0 0 21931 30 *003 1003 0 41SOCO lM*«f 0 S4«7 100 1117 5 0 1*147 3*> St*l 10&3 O. «b000D 114M7 0 3419 101 901 0 0 4742 40 3S37 lail 0 4S&000 107301 0 3149 099 0*0 0 0 707 4S 3274 1*05 0. 41SCOO 7070* 0 333< 101 092 0 0 426 30 3073 3010 0 4S&000 31S»* 0 3002 099 029 0 0 72 33 Ztfl 2200 0 401000 27071 0 30*3 100 022 6 0 30 *C 3433 3«04 0 4SS00C 29203 0 3111 101 097 6 0 «14 *•> 20SC 33C0 0 411000 744971 0 41CC 1069 102 1141 0 0 11316 7C IT4S 2432 a 411000 241411 0 4*7 1 loeo 101 1141 0 0 10*77 1\ 144« 7*43 0 411000 71191 0 3179 too: 099 94* 0 0 1711 •0 12*0 3«33 0 41100C 4179 0 2100 loec 100 971 0 0 10 • 1031. 3070 0 411000 10074'* leeo 100 lOOO 0 0 173 9C 001 3910 0 411000 133*79 1006 IC2 1197 0 0 4*4 *S 711 3120 0 411000 1*3944 101 113« 0 D 1270 IOC »J3 3323 0 411000 2*7401 094 112C C Q 93* 0 ACt CltAO* ftYaVCYW*! <«Ai 0-20 00-130 120 140-1*8 1*0-108 100-200 0140 >*706 I0730 9919 12133 • 19 31710 10109 709* 11711 1O01 1404* 11*49 10107 13007 497 9 1070 1 14116 121*0 1144? 4140 7094 13947 13*10 11020 12133 4340 944* 11020 14942 J1701 711* 13*11 14414 13QI7 1341* 1342 ) 111* itiee 132*9 911 *714 1200] 1002 1*47 X2129 *97* 1249C 13*23 #127 1171* 13240 I227B 11J41 12i*3 1440* 110*0 12120 itMufiOMtarr iMit o i aooaiMfi oToct MAJVltt VAlj)/t «lt >44 all ABBA aABVYBYBD *B*A Y4*AtBC C^at 4*1* VA1WI *•!■ ttc Buwrr YMia 44A9V* »UMrr •■!■ iMrv* w>i mi mi e 3t*) 3032 1 312* 2*«] 911 I7C 0 0 4011 lec: 10 1919 3419 411 23* 0 0 3121 1000 IS «0*2 2309 *11 132 0 0 3**« looe 20 4172 2117 411 17) C 0 >*4C 1*00 21 4131 2001 411 1*2 0 0 310* leoc 30 4002 1902 411 1*0 0 0 34*7 looe >1 37*c toil 911 114 0 0 3411 leec 4: 3137 U43 911 107 0 0 3144 toee 41 3271 1901 #M 70 0 e 33)4 1000 10 3*73 *03' 911 31 0 0 30*2 leee 11 279) 2301 911 77 e D 30*3 loec *e 2431 240« 911 3* 0 0 3111 tooc *1 204* 2397 411 344 0 c 4100 toae 79 1*41 2431 *11 341 0 0 9*7) itoe 74 l««9 2*«2 911 71 0 0 3171 lOflC •0 1219 2921 911 « 0 0 ' 2*00 1006 01 1039 2970 *11 1*« 0 D 43*0 1006 9C toe 2910 411 133 0 0 020* lOOO 91 711 Jilt 411 1*2 2)27 6 1732 1006 109 ' 911 3223 *11 207 1A«} 0 42)7 WABYiar CB9T 414)2 46 • UW9.* THm. • WAHr9t».mCt 13*7 3; T09*i BCMtfir t*l*9 20 wmm I4BCL. KABViat cooti *JO«t *• Mi ttiKL. aMtWBOT COOt 1 4*3*4 11 Treatment Activity 40HP Scenario T*»» (jr«) The treatment activity for the 40HP scenario for the 100-year forecast period. SHORT REPORT FOR PJ IN THE ATO-A SCENARIO t vtKaton z.: •AClieROUHB NAIIVItr HASVIIT LW1L (lOi'ITBItATIOMI : 74&000 74SODO 74SOOO 745060 745000 745000 745000 745000 auurrtac LTWI (kA/ZTSHATteW) •000 loeo •eoo 1600 •000 0660 •000 *000 • •AC1KG Utvil. («A/ITIMATICM| : 500 500 500 500 50i 500 560 500 500 50' •0AC3M« aZMOaB 10 * ZO MAMWtT RUU* % miu 1 4 auuz rznt RAwc« IDO 100 0 a 0 0 0 - 100 Ylltaill VALWBt (S/H3> : CU«W 4C7 ■JIA. rO*B«T CLAB* rtl4: COST rZLS ■ BB01I7 OM THC BOBBBT BBBZDUAl rO«BBT •TATIITICB BOB TMB BCaiOO eMAAILI VOLUBU (H3l voLUKB an IHJ} eOBTB 440CTAU7T (M3j TIPtB BAZRAAY BBCOMOABY MOOUCT MZHAAY BBCOMCMJtT MOCP4*CT Cm PtMn aOACB KAflVlBr BLAftT MAZWT. BBACB BOT. HEAl.. 5 577* 7*J e. 745000 43*«« 0 44A3 4**3 00 0 200 *4*** 2*411 to 5Z44 733. 0. 745000 43*40 D 4*45 4*45 0 300 74044 44392 15 473Z 701 0 745000 4**1* 0 4751 4751 0 300 03170 4*307 20 415* MJ 0 745000 43544 0 5044 5044 500 0 200 77013 25 3&21 «74 0. 745000 45303 0 4B04 4*04 500 0 200 astsi 30 3011 C70. 0. 745000 44434 Q 40*1 4*41 500 0 300 77136 35 Z53* *73. 0 745000 *7004 8 4*0* 4*0* 500 0 200 *4072 40 1*32. ••* 0 745000 5I3*B 0 5301 5301 500 0 300 43**3 45 1511 545 0. 745000 0*401 0 7037 7037 500 0 300 33304 50 34B5- 525. 0. 745000 100451 0 4034 4034 500 0 200 30IO 55 3533 k34 0 745000 *2*54 0 4*24 ••34 500 0 1*4 2**7 •C 3005 *44 0. 745000 5a**7 0 5024 5024 5DC 00 1005 0 301 0 *5 14*« *54 0. 745000 57010 0 473* 4711 50C ec 0*3 0 200 0 70 1*3* *54. 0. 745600 70733 0 •••i 4*a« 500 0 149 0 75 1*23 *35. 0 745000 101204 0 540* 540* 500 0 300 0 •0 313* *73 0. 745000 43300 0 *73* r*34 500 0 200 0 •5 3*31 70* 0 745000 *25*4 0 4700 4700 500 0 zoo 0 *0 a««e 7«2. 0. 745000 **3*« 0 5514 551« 0 300 0 *5 30B* 7*3 0. 745000 **0*t 0 4*«e 4**Q 0 300 0 too 33*1 735 0. 745000 le***5 0 475* <75* 0 300 0 A6t CtJl*0 •T*\WTV«I IRAI 2B->40 40 140-1*0 1*0-100 toe-3oe 3310 35414 1«35« 313* 21300 20*05 374*0 4103 1*3*5 21270 3007Y 15551 • 021 2314* I470B 30104 4155 31*24 1*54* 24135 1 «*4 1*311 1*4*5 27**0 1072 11157 1*30 1»7J0 20077 1732 5375 2*00 1**03 1*700 2300 17#1 121* 32305 1954* 3472 1*7 3314* 1*4*5 3*30 4* I 3J**1 1*730 10304 2171* l»»«2 i0*«3 1*430 23205 10*2* >*4t« 23>4t to*** 300*1 313C7 112J7 2 174.1 1*0*7 1 ll*4 21725 1*430 11515 32 351 19404 117*1 21*01 t»*53 AABA MAJIVBaYIl AABA 7aBA7BC> •iABrr THin BATva tiMrr TNIN MArva C *2BJ 7** 5 577* 7*3 0 4**3 4**3 50Q 10 534* 7J3 0 4*45 4*45 500 15 *732 700 0 475 1 4751 *B0 3C 4154 *01 0 >044 504* 50C 35 3*31 *7) 745 0 4t04 4*04 500 1C 3040 *4* 0 4B41 4«41 500 -35 2535 «7J 0 4**« 4*0* 500 4S 1433 *** 5* 0 0 5101 53C1 500 45 1510 *45 04 0 0 7027 7827 500 5C 2404 *25 too 0 0 4«34 4*34 500 55 2522 *31 *2 0 *oa 4131 •az« 50C *C 2005 *4) 5* 0 442 45J7 1034 500 *5 14*5 *54 57 0 500 4230 4731 500 7= 1*34 *54 70 3* 500 4352 4«04 50C 75 1*?2 *35 101 3*0* 11*0 13*3 540* 500 •: 2134 «7; *2 *04* 500 ItO C724 500 •5 . 2*31 704 *3' 4I4* >00 53 4700 500 *C 3a4C 741 *5 4075 500 134 5514 50C *5 30*4 7*2 *4 41*0 500 0 4**0 500 103 32*0 735 10* 435* 500 0 475* 500 KAcvia* eo*T 74357 77 • UWT. Tala. 4 HAJaTBMAW •301 *5 TOTAl. BBaaBIY 13*542 7C mm lUCL MAAvitT coari 127274 70 mm iiacL MAAVBOT coaTi 53*30 *4 SHORT REPORT FOR SP IN THE ATO-A SCENARIO rOMAM VIIIIOM 2-1 ■ ACautOUWO KA*VT«T KAJIVSrr LrtrSL rM3/XTKaATXaN> : 4&&000 4&&aee 4&&000 «&ssoo 4»b000 4»SOQO 4»3000 4S»SOO ruWrrtMS l.«VSl. INA/trBRAtlOMI : }000 1009 lOOO 1900 II iOQO 1000 1000 1000 ' ll ■ 0AC3P(S UVBL yiTBKATIOMI : uJtvKir ituui « MWUCl ■VU2 IQO 106 0 0 0 TIMOO* VAUIB4 (I/N3): 4b MOM- aiBAXT VOL - CV4VX icT riu rOOBIT CUBV B2LI C04T riUB BBBlOVAt. BOBBBT OTATIBTIC ■BBABUB VOUmB CK3I VOUMII CVT mil •KMITAXITY mil VBZNABY BBCOHOMIT CLTf Bwvrr B4ACB RABWtT BWtfrT KAJVT BBACS I •sBoeo 1T0443 14407 •bbOOO 21BM1 10771 4SSDO0 1J2B1'’ 400 4SS00C iimo 4bbooe IB2B44 «bb00C 1M**4 «Sb000 114M'’ 4SSOOO aeijoI 4&b0Q0 7B7B4 B71 4SSOOO 31144 027 tbsoeo 2>0-» 1 023 4SSOOO 2B2B1 047 ibbooc 244471 1000 11310 4bbDOC 34i«bi lOBC 10077 4»DOC 7bl« 1 020 17bS 4sseee «b7« 030 bO «bb006 110741 00b S73 ION 2. t •ACXCaOUMD HAKVItr NAIIWST LtVKL (M?/*ITttATlOMI ; 74SOOO 74SOOO 74S000 74»0ff0 74SOOD 7«SeaQ 7«soao 7C«MOAIIT > CV«Vt ttt riL<: yc3-a.aco foastr cuAaa tiu ■ ja.fcau cofT riu can-a.K« ■ ItORT 0« THI r ■ ■ i T ■••TouAX. ao*a«T ■TATitTica roa raa MRIOO OMRAILI VOLUHI <1131 IN3) COB7a iSlOOOl l»OaTAl.Z7Y IM3) HOMY apoouct ■kM>r HAjirr ItACt POT . ■ tAL. 000 30S 2SQ •4 4a* 2*4ia. 000 300 300 7*044 44242 701. see 4»»14 300 300 ■ 3170 4*207. 44 3 . 42>4* 300 200 77013 41373. 474 4330] 300 ■ 3423 30420. *70. 44424 300 77a36 432 40 *73 470B4 44«* 300 200 44a72 24aib 444 ooo 4«3«t 330 1 300 4 34*3 4130 ISll . 44k ooc ■ 740] 702“' 300 3330* 240S 424 ooo 100431 4*]« 200 20tl 2S23 43434 2447 200S 3440'’ i«e« 37014 143« 70732 l«23 1S1304 3404 300 213* 43J0C 4’37 300 2*J 1 42344 470C 300 300 2240 . 300 300 3&»7 30C 300 3241 300 ASl CtAta ■TMUCTVai <«4AJ ao'< *a-«e 3310 334 19 1*23* 24133 313« 21300 2a*a3 2744D 41*3 1072 1*343 31270 30077 13331 1732 ••21 33l4i 1470* 30ia« 33i0 4133 31424 1*34* 34133 311* 14(f 1*2 !• 1*443 274*0 1072 11*37 1*730 1732 l*«i2 ZJiO 322C3 1934* 2472 2214* 1*4*3 3430 1*730 10104 1«««2 10441 1*430 33203 i«34* 10424 1*4*4 32 141 194*3 10*44 30043 31347 1*4*4 11237 21743 1*«47 l«a22 31723 1*430 1*3*1 22333 I«4*4 1*374 31403 t**37 1730* •MMMCRKirr UMtr cost MUM VALVf 0 430J 7** 3 377* 743 7*3 41 0 0 4*47 4*4) 300 0 10 4244 732 743 43 C 0 4«43 4*43 300 1> *732 700 743 4* 0 0 4731 4731 300 2C 414* 401 743 43 0 0 4044 3044 300 23 1 42 I *7) 743 43 0 0 4*04 4«04 309 3C J0«C 44* 743 44 0 0 4a«l 4**J 400 33 2323 473 743 #7 0 0 4*44 4**4 400 40 1*32 44* 743 3* 0 0 4101 4101 400 443 743 •* 0 0 7B37 7*27 340 30 2404 433 743 1«0 0 0 4*14 4»]« 300 S3 2327 4)1 7*3 *2 0 sot 4121 4«2* see 40 7003 44] 743 3* 0 4*2 44J7 4I.2* SCO 43 1443 434 743 37 0 300 42J* 4714 300 0 70 143* *34 743 70 34 300 4132 4*44 400 c 73 1*22 *33 743 lOI 30«4 1140 1143 440* 440 ■C 213* *72 743 42 404* 300 1*0 *72* 40: •3 3431 *2 414* 300 32 470C 4CC *0 aa*c 741 7*3 43 ••73 300 11* 3314 300 *3 30*4 7*2 743 4* *140 300 0 44*0 30C 103 1240 733 743 104 4234 300 0 4734 400 >A«VC*T COIT 74)37 71 PLM47. TMIM. 4 HAimUAWCt *444 *4 TOTAL aiMtrir 11*3*2 7C (CXCL a*«ViaT COtTl 334713 70 mm (t»cL MANvtaT ooaTi 43137 91 SHORT REPORT FOR SP IN THE ATO-B SCENARIO rOMUN VIBIXCM 2.1 ■ ACBCltauND KABVtlT MAJIVtir LtVKL (MS/JTIHATIOH; : 4&SOBO 4S&oee <&sooo ISSOQO 1SSOOO 4S&000 «ssioo «sseoo BUMTf tne UVIL (WA/IttkATjaO : 1009 1000 1000 1000 1000 1000 1000 1090 tOAClWa LWBl. («A/ITMATS«M) : KUL92 100 100 0 0 0 I VAUUII (t/NlI. atCOMCUUlY VOL - CUBVt 9fT rtLC rOBCaT CLA9I rXU: COtT rikl: ■■■lOUAl. roBBBT BtAfftTiea 90* tMt OBKIOe oaa KABLI VOUMC (nil VOLMU CUT llO) MCA (tlOQOl MOBTAUrr Itl3l r{M( BBlnABV BfCOnpABT BBOOUCT 9«|NABT BaC^MBT BBOCVCT CUT flMrr • BACt BAinAIT BUVfT PUUirr. IPACl POT. RkAA. i J&ST 3««4 0. 4s*eee i70442 D 4011 1900 eo 7* 0 19*99 10 19*0 ZalT 0 4**000 23***1 0 2*2* 1900 ♦ 9 Q 1*771 IS «091 2309 0 4**000 133017 0 29*4 loeo 99 90 0 4*99* 2C IflJ 21*0 (I «**D0D 17IT10 0 2940 1000 01 0 4*149 3S «13S 200J 8 4**000 192*94 0 3*9* 01 0 2192* 9C 4001 1903. S 4**000 1M*«9 to 0 14*47 3S 33*1 19&2. 0 4**000 114*47 «1 0 4742 4C 3&3T 1*31 e 4**000 107J01 99 0 707 «S 32T« 1903 C 4**000 79T9* 0 223* ec 91 0 426 33 3033 2039 0 4**000 31»9« 0 3097 00 99 0 72 3S 7T91 Z209 0 4**000 27071 0 3**3 00 90 0 20 »C 3933 Z«04 Q 4**000 392*3 0 3111 00 0 9*4 «S 30*0 2399 0 9**000 34497J 0 4*90 ec *192 1090 0 11316 TO IT«S 2432 0 4**000 24t**l C 44T i oc 9191 109C 0 1**77 TS 1449 2*43 0 4**000 7*191 0 3*T* 0 17*i a: 12*0 292* 0 4**000 **T9 0 299C 00 9190 930 0 *0 tS 1039 >070 0 4**000 190TCT 0 4190 *100 1119 0 *73 9C aCl 2910 0 4**000 »32*T9 0 «20k ec *192 1249 0 *94 9S 711 2129 0 4**000 1*3944 0 40*9 oc till 107* 0 1270 103 933 2223 0 4**000 207*01 0 *9oe ec 9049 10B4 0 934 *09 CLA99 9TBVCTUBB (NA i TXRC 0-30 20-40 40-*0 *0-90 0-iee 100-120 120 1*0-100 100-20C * 9*40 14*0 12913 1*79* 107)0 a**9 10 12*33 9*9 9*31 1*710 10*09 709* l»7ii iOQ* 9447 i*e*« 1*049 10107 30 130*7 *974 3799 187*1 14*10 12109 2* 1*442 9*40 14*0 7094 1J947 13919 JC 1*020 13*33 *** 4240 9*0* 1*039 149*2 1*7*1 loe* 23*1 7*19 1)1*1 130*7 *97* 1*42 I)*I4 13*23 1*442 9*40 >1*9 132*1 1*030 13*33 *1* *7*4 12**3 14**2 1*791 1092 12*2* 14414 130*7 *97* 134*0 13*31 1*270 0*37 137*4 1>3*I 13011 12270 3*4 1*34* 129*3 11144 14*04 2*9 1*9*0 12*39 12133 *770 *794 3*9 1**2* 12499 13323 >0047 7494 1**1* 137*4 13349 10141 9*4* 170*4 1*34* 12993 10271 1713S 1*9*0 12*2* 10*2C CBOBtOC 9TOCB «■ R3 poiB otr 9BIH MATV9 C 314) 20)2 * 3*34 2**3 9** 0 4011 190C 1: 19*4 24)4 9** 0 2*2* 1909 1* 4092 2)0* 9** 0 )9*« 1000 3C 417; 21V4 0 3940 109C 2* 41)7 2003 0 )*|9 itec 3C 40C2 1907 0 34*7 1900 )* 3790 1**1 0 341* I9DC 4a 3*3'’ 1**9 9 3149 1900 4* )27« 1907 0 33)4 190e \e )07) 30>7 ** 2791 3209 *0 24)3 2404 ** 204* 2)97 70 )’4S 24)1 9 4*7i IfOC 7* 1444 J442 0 3*7* 1900 93 12*4 293* 9 29*0 I90C a* I03« 3070 8 4)90 ItOC 9C 90S 2910 4** *33 0 ■ 9 *204 loec 9S 711 Jl7i 4** 1*2 2)37 0 17)3 toeo IOC *1* 323) 4** 297 1«*1 9 42)7 Ito; KAAVItr C09T 4*413 *4 PUtfrr. TBIM. * MlWTtMMKt kl*< 01 TOTAL Bnaarr **l*9 2C 9M« I9XCL. MABVI9T C09T> 9*029 It MS (t«CL «A«7/B9T C09T1 90*1* 7l SHORT REPORT FOR PJ IN THE ATO-C SCENARIO 2.1 •ACSCMOUMO KMWI-r HAJtVlST LCVSL tR3/2TtRATIOMI : 74SOOO 74SODO 74S000 74S900 74&ODO 7«S000 74SOOO 7«&00C 74SDQC 74&000 7«SflllO 7«see0 7«&000 74S900 74S0ee 74S000 7«seee 7«sAeo 74&00C 74&000 UMTTXMO t.*WL^ IHA/TTBRATXflM) . 66 BAao taoa tooe toso •000 •000 •000 •ooc •000 Qc avoo taoo coao ' tooo •00 0 •000 ••00 ••00 •000 AC3MC 1.EVSL f KAy irBaATZOM) : 00 voo too »00 *99 *09 *00 *00 *90 >00 00 100 000 BOG *00 *00 *00 *00 *ec *00 ■ •AflMO •mOB 10 ■MWOT m/UI * BWUl ■UU2 100 100 0 D 0 TtMKt VAUIBi 1>/R2): PVOOPCT - 4* KBr-MOWCT • 3* ••CM&AMV VOI. - 3* •EAL DZSCOUHT MAT! - .940 CUBVI BIT tllA. rOBBBT cut*! nU: COOT riU: BBBIDWAI. rO«99T •TATltTICB VO« TMB NKIOO OrtBAaLI VOUXB (M3) VOUM* CVJ (H3) ABBA 4HA> COBTO CS1600) OKMTALinr MIHAJtV •BCaHCABV MOOUCT MtNAItY •■COnAAV fttOOUCT CV7 0UW47 SOACt HABVBOT OUWTt AA2W7 . B9M S *770. 7*3. 0 74*000 «3**4 00 •01 1305 0 300 10 *244 732. 0. 74*900 41040 •01 1040 0 300 IS 4711 700 0 74*000 41*14 •01 1741 0 300 2C 41*4 403 0 74*900 43*** •00 1*14 0 300 2S J«2> <71 0 74*000 «*101 ••■ 1440 0 ZOO 10 3001. *4f. 0. 74*090 44424 •4* 1377 0 300 IS 2*24 472 0. 74*000 «744* *01 1**0 0 200 40 1914 447. 0. 74*000 *«3*0 *00 1*** 0 200 4S ISIS 441 0 74*000 0*403 •97 4774 0 ZOO *0 2410 410. 0 74*000 1004*1 •01 S745 0 300 ** 2*10 *27 0. 74*000 *2*1* •01 1*74 C 14* 40 2021 411 0 74*000 >*4«7 *00 1912 0 301 4S 1417 442 0. 74*000 *7Blt *00 943 0 300 70 1*72 *1*. 0. 74*000 701** *03 !••• C 1«* 7S l«f0 420 0. 74*000 *77** •ea 1427 0 300 •0 2272 **1 0. 74*000 B30QI •eo 1*37 e 300 OS 20*4 4«1 0. 74*000 410n •00 1431 C 200 6. 0 *0 10*2 70* 0 74*000 43*11 *00 29*4 0. 0 •S 3144 727 0. 74*000 •3307 oo •08 1*44 0 300 0^ 0 160 3*47 leo 0 74*900 *34*9 00 •01 1111 0 200 0. 0 0-30 20-40 120-ltB 140-140 140-100 140-30C 3010* 3300 3*41« 34135 1110 31100 30*05 1141 374*0 41*3 14145 31370 t*54 30077 1***1 002 2 31140 13*7 1*70B 3010* 4155 3 1424 4*04 30 t**4« 34115 140* *441 784 35 l*4*5 33«*0 1072 4*41 1438 40 1*730 18673 1712 7*47 344C 4S 1**02 1*701 3300 1314 *c 23205 1**4* 241 2472 23344 1*4*5 274 3430 3 1**0 1*730 300 lOJOS 31711 1**02 1*7 10444 1*43* 33305 145 10427 1*473 33144 1*4*5 10*44 |**4* 31144 l***« 111*2 2 1441 >•044 1*0Z2 12012 3 1*45 lOiPO 101*1 114*4 22127 1*471 10»7* 12034 211*7 t*01« 17*07 13034 WAWACmn** VMIT 0 1 kOOBIBQ 4TOC* ■ABVtlT (H Mil ABBA HABVBOTBO ABBA 1 •Bin OIC OLAir* tain MATV* OUMrt *• 7*« 743 *•41 4*43 *00 712 500 *00 *00 473 745 *084 >00 44* 745 40ft 4041 *00 •72 745 4*04 • *•4 *00 745 *18 I *80 745 *•3' *08 *8C 4*37 BOO 4334 43* *00 4142 *•7* 41* IMO 1J7J *18* 450 472 1 442 - 40*0 4B3I ' 4814 18*1 HAItViB* CO«T 7415’ *1 • L444T.' TniH. 4 AAJWTSnAMCB 18185 OS •OTAL BBItBriT 134*41 1C •*** IBXCl.. «ABVBrr OOBTI 12445’ le wmm (XMCL. MABVBB7 C0471 *34*4 43 SHORT REPORT FOR SP IN THE ATO-C SCENARIO rOMHMI VtiatOH 2.1 ■ACcaouMD HAavtat NAIIVIBT L«VBL (H3/ITiaAriCWI ' 4SS0C0 4&SOOO IS&aflO 4SSQ00 asseoc 4&&OOQ 4)50ac 4Si0a& 4SS000 4SSSD0 4SSeOO 4SS0ee 4SSS00 4SSaDO 4SSDG0 4SSOOC 4&»000 4)SOOO 4»>000 rLANTXMe LCVtI. (■A/tTIKATXGMl : toeo iGOO laao 1*00 i»ob 1000 1*40 looe leoQ 1000 1000 iOOO 1000 1000 1000 1000 1000 looe 1000 1000 BfACINS UV«L IHA/irtUTI XSXY 3««4. 0. 4SSOB0 1704*3 0 toil 1*90 0 *190 1071 0 0 19*99 10 30*0 243Y. 0 4SSO0O 23*««1 0 3121 1000 0 *099 1000 0 0 1*771 11 4001. 2301. 0. 41*000 132017 0 3*** 1000 0 *099 1000 0 0 4*99* 20 4171 21*0. 0 4»000 171710 0 3040 1000 0 9101 1010 0 0 40149 21 4131. 3003. 0. 411000 1*2**4 0 31*9 1009 0 9101 10*C 0 0 21931 30 4003. IfOl. 0. 411000 1*0*«4 0 S4«7 1044 0 9100 10*« 0 0 14147 31 3741 1*12. 0. 411000 114*47 0 341* 10*9 0 9101 009 0 0 4742 40 3137 1*11. 0 411000 107301 0 3149 10OO 0 9*99 017 0 0 707 41 3274 1401 0 411000 7*7** 0 3234 10OO 0 9101 914 0 0 42* 10 3071 3031. 0 411*00 31194 0 30*2 lies 0 90*9 024 0 0 72 11 27B1 2201. 0. 411000 27071 0 30*3 1*00 0 9100 *23 0 0 30 *C 2433 2404 0 411000 3*303 0 3111 1*00 0 9101 *9* 0 0 914 •1 2010 2391 0 41100S 244973 0 4100 1000 0 9102 1090 0 0 1131* 73 1741 2432 0 411000 341*11 0 4*71 1000 0 9101 1000 0 0 10*77 71 144* 2*43 0 411009 71191 0 3170 10OO 0 9099 *20 0 0 1711 •C 12*0 2931 0 411000 *174 0 2*00 xeee 0 9100 932 0 0 10 41 1037 3070 0 411000 1007*7 0 439C leec 0 9100 1172 0 C 173 *C *01 2910 0 411000 133*79 0 *20* 1*00 0 9102 1332 0 C M4 >1 711 3120 C. 411000 1*2944 0 4*1* I0OC 0 9101 1074 0 0 1270 IOC 931 3223 0. 411000 2*7*01 0 1*00 1000 0 9099 I0*« 0 0 934. Afi* C1AB9 tTRUCTVRI fRAt A6* ClABI 0-20 40'*0 M«*0 *1 1*0-120 120- 40 140-1*0 1*0*1*0 100-200 • 140 13912 1*7** I 491' 12113 •131 11710 I 799 117*1 9447 IM*« 1*1* 130*7 27*0 107*1 131*1 11442 14*0 70*4 13910 11020 •&9 4240 1102 14**3 1001 2211 13*1 14414 *97 9 1«4Z S3«l 111 13*23 *140 111* 1*100 112 112*9 13133 911 *71 34* 120*3 11701 1002 1*4 12120 13007 12490 11370 1371* 13011 13270 31* 11341 1 1144 14*0* XI* 11**0 12LJJ *770 21* 11*29 13323 111 19 2 33*9 129B3 13129 aiBVT VWTT 4 MJ ■ WAiA/4 10C 2032 3*43 411 401 I 1000 343* 411 3121 19B9 330* 411 39*« 1«*0 3119 411 3940 3001 411 31*9 1**0 1907 411 34*7 1*00 3011 341* itoe 1*10 3149 1*00 1901 3334 1*90 3037 3042 •••e 3200 411 S0*J 1040 2404 411 3in 1000 2397 411 4100 1000 343 1 4*71 l*«0 3*42 . *07* 3931 3**0 3070 4390 3910 •XO* 1732 4337 NAjrVRBT CO*T 40412 4* BlAnrr.. TRIM. « HA3WTRMMB 1147 4C TOTAL BDltriT 991*9.30 *«• IRXCL. «UkjrV997 COB7> 94B3I 7* itM flKL. HiaVIBT CQ9TI 40*09 32 SHORT REPORT FOR PJ IN THE OWC-A SCENARIO rO«HAH VltlZOM 2. 1 ■AcmcaouHO NAjrvirr ItABVTtf LTS/IL ma/ttttATtdM) : '’4SB0C 7«»009 7«»eOC 74&000 rWWTXWO LCVIL (■A/ZTtKATtOMI: •000 0000 •000 0000 ■000 ■OOO 0600 0000 ■000 •009 ■ ■ACIMa LTVIL {MA/irtOArXOMI soc soo soo soo 0 bOO soo soo soo 0 •OACINS WJMOfm 10 - 20 ItMtVIST BVUIt t RUU) % OUU2 TM( UUKK 100 lOD ooeo e> loo TINOB* VAUIBO (S/H2): roocwcT - 4S aoM-OMogucT - oocariMitY voi - 2S ■OA^ oioeoutrr KATI - ,O40 OaMOktNlP I.BI.MI CVKVI •■T rxkf rO«BB7 CLASB OZLO COIT riLi. ■ t 0 O b T r ■ I r o • • • 7 ■B»t0UAL rOOOBT rTATimC* POO TIM pt«ioo OPtKAOt^ VOUMt IM31 WOUMI Cl/T mil MIMAIIY ■BCOMOARY »«iKMiY •tcaie*iiY fgacucT CVT ObMTT •»*C« BAlIVttT OUMPt HAIKT. RIAL. ••••• 2»41« 01 194B 7tD4T 44292 ♦ 732 •3170 4*207 • 1ST T7013 41S7S S&21 •oo« ■S42S S092« 3oat • •Tl T703S 43260 2S2* •••• ••■72 2»O0S !•!• 43««3 • •SO ISIS 33309 2«17 30«9 2S3I 24«7 2022 l*a* • 42 1«71 •27. 407T !••• •20. bSO' 200 2271 *73 1 200 2*bS 4*41 290 lOf:. TOT. S4A£ 200 114S . T27. 4»JS 200 2sat Toa 4JSi 200 ACf CUiai 0-20 20-40 40-*0 •o-ao oo-ieo l•e'U0 130- 20l«4 2900 41SS 3S41* 1«2S« 2tk3S 313* 149* 21300 30*iS 274*0 41*3 1072 143 as 31270 20077 ISSSl 1712 0021 21t4( IT?0* 20ltt 2309 41SS 2 1A2* 1«S44 3413S 311* 14«4 1«2I« IT44S 27140 4 1*1 1072 11»S 1*730 20077 1733 1**02 1*700 23«C 3220S 14S4T 2472 33 140 1*4*S 274*0 2»30 401 31*91 1*730 20077 10304 •IS 217JT 1**02 1*70» 1064J ••c 1*430 233DS 10S4T 106Z* 22I4* 1*4*S 10**4 313«7 1*«T* 1134* 1*0*7 1*022 12009 1*410 1*3T1 1*47« 10S74 l«0*t 1TS09 • *•1 4*41 soc 74S • 7J1 soc T4S SOS 74S sac • ••4 7*S siei 74S 7027 • 19 7#% •3* 74S •32 74S 4S37 *4S 431« T4S 4343 • •7| 74S 1372 • 30' T«i • 72 I *4S 46*1 • •4 ) T4S ••21 • 4M 403S 3*S1 4MW««T CO«T PUMT*. *RIN. 4 *0*A* ■BHOrtT 04M (KXCL. HABW** CM71 mm UNCI. «A*v«oT eo**i SHORT REPORT FOR SP IN THE OWC-A SCENARIO roMMi vtiaioH 2. 1 BACKCMOUWO lUUIVVrT HAinnaT MvtL v« oar rzu: roaasT ckoaa riLi; coar riLO ) a ^ o a T ■ i BBaiDUAi. roaaar aTATiatxca ro«> raa ataioe oaCKAOU VOUMI <1131 VOUMB cur mil MBA COBtl IflOOOl NORTJU.irY (Nil rini aaiHAav BBCOHDA*Y HIOOUCT paziwuiY aacomMar PBOOUCT CVT auwrr aaAca BAawatY BLAKT MAJKT. aPAca ^rr. BBAI.. !> 352'' 2**4. 0 455000 1104*2 e 4011 ■ ec 0 100 1411 0 0 14**4. 0 10 sa*o ooi. e. 455000 33***1 0 352 5 too 0 Off 1*30 0 0 10111. 0 15 «0<3 2301 0. 455000 132011 6 3*** 800 0 Of* 1410 0 0 4*89*. 0 2C BI73 21*0 0 455000 lime 0 3440 oeo e 10} 1430 0 0 4014*. 0 35 «135 2001 0 455000 103044 0 3501 000 0 lot 1*30 0 0 21*35. 0. 30 «003 tool. 0. 455000 1M**0 0 34*'’ 000 0 ICO 1081 0 0 14547. 0 35 31ft 1052 0. 455000 114*«1 0 341* 000 0 101 1111 0 0 4742. 0. to 3531 1051. 0. 455000 101301 0 314* oeo 0 04* 1003 0 0 701. 0 45 3314 1005. 0 455000 7010* 0 323« oec 0 101 1121 0 0 42* 0. 50 3013 203t 0. 455000 3154* D 3002 eoo e 04* *54 0 0 72. 0. 55 210J 3201 0. 455000 21011 0 30*3 oeo 0 too *11 0 0 30. 0 *0 3433 2404. 0. 455000 24303 0 3111 too 0 IQl 1103 0 0 054. Q. *5 3050 2341 0 455000 344413 0 4500 eoo 0 102 1430 0 0 1131*. 0. ID 1145 3432 0. 455000 341*51 0 4*11 oec 0 101 1*30 0 0 1*071. 0 15 1444 3*43 0 455000 15141 0 3510 000 0 B4* 1330 0 0 1155. 0 OS 12*0 2435 0. 455000 *514 0 2000 oeo 0 ICO 10*1 0 0 50. 0. 05 1034 3018 e 455000 1001*1 e 43*0 oeo c too 1500 0 0 573. 0. 40 001 2410. 0 455000 533*14 0 *30* oeo 0 182 1101 0 0 *04. 0. 45 111 312* 0. 455000 1*2*44 0 405* oec 0 181 1B12 0 O 1270. 0. lOO 415 3333 e 455000 301*01 0 5000 oeo 0 0*4 1004 0 0 *34. 0 A«* cutao arawcTvac IMAI ACO CLAB* 30-40 4O-*0 *11-80 80-100 100-120 120- *0 iBO-loe : 0540 14*0 12*12 1*10* 10138 12533 *54 053 1 15110 185B4 10*0 151*1 1005 4441 i*e*« 15041 10101 11001 •41* 214* 10101 1*510 121*0 15443 0540 14*0 1094 13*4’ 11*10 15030 12511 454 4340 15*28 14**2 15111 1005 2251 151* 11*55 14414 13081 •414 1*42 4031 11*14 11*33 15442 8540 1154 21*0 1050C 112*0 1503C 12533 *15 *154 12003 14**2 15181 1002 5841 1252* 144 11 13081 • 41* 3114 1244C 13*23 15210 0527 1315* 133*8 13013 12210 15145 130*1 11144 14*0* 15**C 13534 *110 *104 15*24 13448 10041 1444 13154 10141 4*4 5 15145 10214 0*40 15**8 10520 jaic 11*1 3*12 153* 34*1 0 4011 ioec >45« 34J4 0 3525 1006 4082 3108 0 19** ioee 4112 3154 e 3*40 looc 4115 2001 0 3504 lOOC 4002 1402 0 34*1 looe ]1*e 1*51 0 3410 leoo 1*50 0 3l4t leOQ 121 1*05 0 3314 loec 1013 2011 0 3082 1800 31*1 2300 0 30*1 1800 141) 3404 0 3111 19*0 2044 214' 0 4500 laec 1145 3411 8 4*11 18*0 1444 3*«2 8 351* laae 1254 2*35 0 2*80 18*0 101* 3010 0 4190 loec OOC 3410 513 0 8 *304 18*0 111 312* 142 212'' 0 1112 1*00 915 3333 201 1**3 8 4337 1**0 HABVtai C04T 45412 44 auarr. .1NI4(. « HAfirroatA**Cf 0501 53 101AJ. aaitiair 4*1*4 30 *•*• lexCL MABV041 C04TI 40501 *4 : «»JkClM« ■IMDOO 5 > KAjrV>t7 m/UB t OVUI Ttitl RMM> 100 100 0 - 100 TllfOBB VAUJtC (t/N3l ; 35 OBCCMDAirr vot ■ n/BV¥ BBT riLC. VC3'B.O«C roaiBT CUIBB rXLB.; 0J2. mu coir rxu cofT.eat •tOlOUMp rO«BB7 rtikTirMct roB TMO »«RIOO OMRABLB VOLMtC l«3l vouMB orr cn3j WTALXTV |M3) MIRABV BBCOMPAJIY OBINAIIY BtCOMOABY OOOCVCT CV7 BbMTf BBACB KAtVlB' • i.Mrr luawT BBACB POT. 703 43**« 9410 732 4174D 4292. 760 4B71B *207. •02. 42549 1575 *73. 45303 0*2* •*P 44424 33 50 23BB. •72 47001 • 0*5 1B55 •4B 5029> 4150 14*5 0*403 2371 10045} 24B« • «451 1«B5 • 12*3 1425 •52 57011 15*5 • 45 77*03 1B76 *33. 20«« *70 25(2 TO* 274 I 740 *5254 3035 751. •4*07 XlBl 73* 10«*5B AC* ClAB* BTBWCnmt IBA) AC* CUIB4 20*40 BO-BO BD-100 100 40 140-100 IBO-IOS 100-300 2300 1025* 24115 1134 20*05 27470 4193 1072 21270 20077 1555 I 1732 23144 1*704 30IB4 2300 3 1*2* t*54* 24135 313B 102 14 1*4*5 274*0 4i»J I1B57 1*24 1*730 20077 15551 3500 19*B2 I970B 301** 1214 22205 1*54* 34135 22152 1*4*5 22175 1*710 22154 1«*B2 >••*4 22205 1*544 14004 22152 1*445 201B4 21552 19544 21*30 1*504 i*a22 1*754 l*341 1***7 10510 20073 17041 ■ «0»»a*mi4T UilTT * VABUf »«T COOT UX« VBUUt •Wt M4{ 0 *203 744 5 5774 7*1 745 43 0 0 4**3 4*«] 500 13 5243 7JI 745 4 3 0 0 4*45 444' 50; 15 4724 700 745 4* 0 6 4751 475; 5tCi 20 4140 •02 745 42 0 0 5049 504* 5»e 25 3544 *72 745 45 0 0 4004 tool 500 30 3*49 *04 745 44 0 0 4091 4041 500 >5 2145 *72 745 4 7 0 0 ««*« 99*9 50C 40 1054 •** 745 5*0 0 5301 5301 50C 45 1445 *44 745 04 0 0 7027 702' 50C 52 2370 •25 745 100 0 0 4030 4*19 500 6 55 244} *J4 745 *4 0 0 5010 5010 500 0 40 1**4 *42 745 *10 0 5303 539} 50C •5 1425 •51 745 57 0 500 *230 4730 500 70 1544 •45 745 77 3* 500 4241 4777 5tc 75 1*74 •33 745 *4 31*2 31*0 1034 519* 5D0 •0 2044 ••9 745 •2 *«4* 500 100 *724 500 05 2502 70* 745 •3 41*7 *tl 52 9025 5IC *C 2741 71* 745 *5 4075 500 139 551* 59B 45' 303* 7*1 745 ** 4132 500 0 4*32 500 100 3143 735 745 14* 4350 500 0 4750 50C MAOVTOT COOT 74357 02 95AITT. TBIH. « WAXITTOimiCB 11*77 01 TOTAL OBMOriT 13*5*5 70 *9Mi ttOCL. MAirVOIT CD9T I 125110 70 IlMCL' MAVIOT COITI 507*0 91 SHORT REPORT FOR SP IN THE OWC-B SCENARIO PORRAH VIIBZOI 2. I •ACKOIOMfO MAirVBB? LirvtL (MS/ITIRArtOR) : «»»«0D «»S0S0 «SSOOO 4»»00Q «»SOOO 4BS00S asaoeo «a&Poo laacoo isasoo •saeso «&aooo aaseon «»aaoo tssooo «a»ooo «aaooo «saead «b»too 41^000 PWMrrxM« v*v«L «MA/IT»«AT10M) : IBOO 1000 1000 1000 leeo 1000 lOOO 1000 1000 1000 1000 leeo leoe 1000 1000 1000 ; LOV11. IHA/trlKArtOM) RMWIT ItWUI % OUU t t RUU2 100 I 0 e 0 0 0 0 0 - left riRBia VALUIO |S/R0>: P«OCVCT - 41 WCM-PROVUCT - IS S*Ca(SA>T VOL - 2S kKAL DiaCOUWT KATB - .040 CMMBROMXt caoM CU*V« rZLl: VC3-O.ORC POOOtT CULOO riLO; BO-OP.OAU COST VZLI COOT.eOC •■tIDUAL POROtr BTATiartci I I m PBOJoo OPORABU VOlAmO VOUUHl CVT IN3) COOTS iSlOOOl MWTAUrr IMS) ■•iHAor ■■coMBAar MOOUCT MIRATY OCCCaiaAaT MO) kOWOT PUMTT MAllrr. aOACS OOT. RCAL. 312‘» 2664 1704A2 100 39*0 2437 33M41 099 40tJ 330t. 132017 099 4173 2160 171710 413S 2001 193094 4003 1904 IMMt 319 1 11S3 114*47 JSJ7 1BS3 107101 3234 190B 70706 307 3 2042 31S9* 27f 1 22X3 2707J 2433 2410 29203 20SC 3404 344973 11316 1730 2434 3414S1 I0S77. i4ia 2O&0 7S191 099 1230 17SS 1204 2934 ♦S79 903 3000 100747 *9p 2923 133479 102 170 Stl 3134. I7S0*4 706 3229 394499 AiC« CLA09 OTOWCTtmO IMAI AC4 cuiaa 0-20 1-40 *0-00 00-100 100-120 120- OS40 !913 1470* 10730 49S9 1 ilVSl IS21 1S710 1**04 7*9* ii7ai 101*7 1J007 2790 1210* IS442 14*0 13910 13020 9*4 1602* 14943 100& 13011 *97* 13*16 13423 • S40 2790 1*100 11249 12V33 13S4 *714 12 003 IS7I1 lOCl 104’ 12121 1300* 1249C 137S* IS341 11X44 1S04C 12133 •770 13429 13323 10147 IMlt 11240 10161 17014 12003 10274 10004 12S20 10444 awtaaoiiowT VMXT a HAOV99T «■ AJIIA HABWOTtD AOtA TBOATIO IK ate MATV* puwrr 1600 3194 laeo 344’ laec >419 i«oc 1000 leoc leac leac 3Ul lOOt 4100 loot 24ia 4*7 1 loor 2*44 3179 2931 '2000 4390 •206 1733 4217 IUU»V«B7 COPT 41412 46 ouwrr.'TNiM. 1 RAiirromwac* •101 13 TOTAL OhfiriT 44191 02 wn (CXCL MAOVS9T CO»7' 90199 49 OBI* ilRCL. MAOVltT COOT 1 41107 17 SHORT REPORT FOR PJ IN THE NWC SCENARIO rOAMAW VCRllOM 2. 1 •ACRcaoimp MMrvia7 HANVTtr LfVIL CH3/irl*ATtaMI: *>«kOOC 74SOOO 74&00Q 7460ac • LMnXMC IXVSL (HA/xrBKJLTXOMI : •000 iOBO *000 *000 •000 •000 fOOO *000 •BOO •000 aVACXHC LCVIL (KX/ZTIKATICB SOO »00 *00 *00 soo *00 ■ OACIHS ■»!»«)■ to - 20 KAivitr avui % auui t *^1X2 OtM OJMiW too too 0 000 0- too TlMiia VAU/tl (f/Ul : ••ocwcT - «& «a(-«*on»cT - 3* ••cfwr VOL - 3* ••XL MiCOUirT KATB - .040 CV»VK ttT rxu. •oatiT cLX>i rxu cotr riLt: ftllXPUAI. rOfttOT •TATiorica ro« TM rouoc OMKAALO VQUMt IM3I WOUMa art IMtl cp«T« (fteooi MOAtAurr m3) : wurvaat auwrt nxzirr. ••Aca ao7. aaAj.. S S17* 7*3. 0 74*0e0 41M4 0 4*43 4*43 00 14401 2*42 0 200 Moao. 2»41« 10 *3«« 73*. 0. 74*000 43*40 0 4««* 4*4* 00 14401 2*07 0 200 74044. 44342 11 4732. 70*. 0. 743000 *••]« D 47*1 47*1 00 14401 2720 0 206 ■3170. 44207 2C 41*7 • *7. 0 741000 42*44 0 *0«« *044 ee 14409 2**7 0 200 77Q13. 41*7* 2i 3«0a. •*2. 0 74*000 4*303 0 40a« 4I04 00 14(4« 2*37 0 200 0*42*. *0424 30 30*» • 71 . 0. 74*000 4442« 0 4041 4t«l 00 14*44 2*11 0 200 77f3«. 432*0 3* 2442 **7. 0 74*000 4700* e 4a04 44*4 00 14401 2143 0 200 *4072. 2A44S 4C t«7f eta 0 74*000 *B2*4 0 *301 *301 60 14400 3441 0 200 43*43. 44*0 4* 14l« ••3 0 74*000 «*40J 0 7027 70T7 00 14*47 *B1* 0 200 333B4. 6 *0 232* *•* 0 74*000 100*04 0 4*3« 4*ia 00 14401 *131 C 20Q 204«. 0 ** 2414 *71 0 74*000 *4203 0 4041 4*41 00 14400 24*3 0 144 2**7. 0 *C •*» 0 74*000 M**l 0 *044 *044 00 I44&0 2174 0 203 0. 0 •* 130* 71* 0 74*000 *a37V 0 4*10 4*>: 00 14400 2434 0 200 0 0 70 13*4 721 . 0 74*000 7*M2 0 *01* **14 ■0 14«4f 3324 0 144 0. 0 7* ISVO 70* 0. 74*000 1073*3 0 *•*! **>l 00 14400 3440 0 ZOO C. 0 73* 0. 74*000 771*7 0 741* 741* 00 I44QI 3412 0 zoo 0. c 7*« 0 74*000 *2*43 0 **J4 fc*l« 00 14400 2444 0 200 0. 0 7i3. 0 74*000 a*0J7 0 *3*0 *34C OO 14401 1142 0 200 0. 0 •* 2ia* 7f7 0 74*000 *73*3 0 *734 *7|4 00 14400 3224 0 200 0 0 leo 3ia* 7*7 0 74*000 12*02* 0 *h*3 **•) 06 I4t0l 4134 0 200 0 0 Aca ciAaa aTavcnni iiui Aca cutai B-20 20-40 40-40 M>40 ao-ioo lDO-120 120*140 140-1*0 l*O-]40 144-200 20144 2300 41»* 3*414 1*2*4 321* 11* 2413* 3134 14«4 31300 2044* 1341 344 27440 4143 1072 l«3A* 21270 14*4 3*4 20077 1***1 1732 *431 3314* 3347 |0« 14704 20144 2340 14*44 2413* 3134 704 1444* 37440 4141 1073 1*24 14736 28077 1***1 1733 2**C 14442 14704 23*0 1214 2226* 14*44 2472 221*2 1444* 27440 2A3* 220*7 14730 20077 10334 2 ia*2 14443 14704 18*36 1443* 2320* 14*44 1843 1 1401* 221*2 1444* 104*4 2077* 31433 14244 104*4 23044 14300 I4a32 1842* 23414 14*3* 140*4 • 4*4 2*246 1441* laoe* *247 3*120 30**4 17343 *391 Mnrr 4OTI4 4 ii»c rroc* HAirvaBT vAwa Mat **ax 4uurva«Tfo A*** TBEATBO CO4T WUM vAi«t y* **j* ate HIM ate PLAMT T«IM MATWa aUUTT THIM MTV* HI HI HI 0 *203 744 * 7*3 74* 41 0 0 44«) 44*3 *00 10 731 74* 4] 6 0 444* 444* *00 1* 731 70* 74* 44 6 0 «7»J 47*1 *00 20 1*7 *•* 74* 42 0 0 **4« *••• *«e 2* 407 *43 74* 0 4404 4404 *00 le 30 0*4 0 4441 4441 *09 1C 3S *•• 74* 47 0 0 4444 44*4 *6C <0 *44 74* 44 8 8 *381 *381 *86 4 14 *43 74* • * 0 0 7027 70J7 *o: J2« too 0 • 4«30 4«lt 41* *77 *4 0 *80 4341 4441 *c • 44 *44 74* *C 0 443 4*04 **•• »•: *s 10* 71* 74* *• 0 *80 4310 4416 *06 70 34] 721 74* 74 3* *86 44*2 *814 *66 *4C 70* 74* IIP 140 1 l•^^ 1827 *•»! »e: *•2 734 74* 77 7043 142 340 741* *ea 4* 03* 7*7 744 •2 «7*S •27 *2 **3« *06 • 0 047 743 74* a* *341 ' *04 134 *340 *06 41 1*4 747 T«s B7 *a«2 147 0 *7J4 108 144 7*7 7«* 13* 44*1 «22 0 **41 *oo KAAHtf COOT 743*7 ** 9LAITT. 9B1N. • KAXVTBMAIVCt 1*3*2 43 tcrTM. BanartT 13**44 10 *M (axe* KABViaT COST) 121343 36 mm iiMCL. BAwtar cotTi 4«44* *7 SHORT REPORT FOR SP IN THE NWC SCENARIO rOMAD VIBCICM 2. 1 •ACXCaOUMD HAItVlBT HAJIVIIT ttVtL (MS/XYtHAtXCH) 1 4S&000 4S&000 4S5tOO 4SSOOO 4S&000 4SSOOO <55000 <55000 OLAMTIMC LWCb (M/irBRATJOHn 1000 1000 1000 1000 II loao 1000 ifloo 1000 ' ii OOACIHO LSVIL (HA/XTBKATZOM) : MAftWa-r HUUt » HUU I 100 100 TIROIB VALUOt (S/IU): 35 oocoafCkMty VOL - CURVY air rzu: poBtar ciJiaa rtu COaT PZU: ■aaiDWAi. POHaar OTATlYTICt fOa THY MRJOD OMHAJLI VOUOTt (H3I vouMia cm (MD (iieoDi HOHTALZTT (■31 TiHt MtMARr oaccw&ARy pHoowcT nuNAinr oaecwaARV P*O«WCT cm PbMn aoAci HAavitT autfrr HAzm OPACI OOY ROAL. 5 2M<. 0 455000 170442 0 4011 lOOC 0 *ieo 1300 0 0 1*4*9 0 IC 33754 1324* 13011 13270 215 4343 25* 55 153*5 12**1 11144 14404 )4* *115 35* 54 15440 1253* 12131 *770 R7e* 4)5) 354 54 15434 134*0 13331 10147 155)4 13754 1324* 10141 3*1' C 7, |7*54 15145 124*} 1027* )t0*« 15440 1353* 104«> a70C« HAAVta* IM MS) (■ N3t R41M *ac MIH •ac RLMrr TRI* 3) 43 3525 455 4011 itee 345* 455 3525 leoc 40a3 230* 455 3*44 1000 4) 2154 455 3**0 ito7c 3 4115 2003 455 35*4 1006 1*63 455 34*7 1006 1*52 055 2410 1000 1*53 455 3144 lOOO 237* 1*0* *55 233* 1006 207) 30*1 *55 2003 lOOC 27* 1 32 11 455 3*43 1006 243) 3*64 455 3111 leos 2644 3401 *55 4506 1006 1724 3410 *55 4*71 1415 244* 455 357* 1305 3434 455 ' aooo • 43 3000 455 4140 4*1 343* 455 4364 1134 455 2732 3211 455 43)7 MRVBOT CPIT *5*12 44 . PLAI4T. *HIR, 4 MIVTCMA(BCa 5*04 3) TmAi. ORMOPir •41RI.05 OTM ItXCl. HARVt*7 CMti *1343 70 mm itMCL- MAAWYr coarr 477R6 24 SHORT REPORT FOR PJ IN THE NAA SCENARIO rOMKAH VtKIXOM 2.1 • ACXeCOUMD ■AMWtr HACVXtT UIVIL (HS/rTiaAtlOH) : 74&000 74S000 74JOIO 74SC00 74&000 74S0D0 745000 745000 OUklfTlMC LCVtL IHA/IVttArXONt: •000 >000 •OSO 0000 ■OQQ *000 •DOS aooo • tACXNS kCVtk IHi^ITtkArZOM) ; 500 500 500 500 500 500 500 500 ■•ACZMC atMOa* to - 2o WUIVttT BUUI 4 BULSl ■uuz rXRB KAiBOi joa t 0 I 0 0 0 0 - too TIRII" VAJA^CI (f/HJ) 25 aicoMOAOv vot. - cuavt atr rzLt: yc3 roaitr cuKta rxLt:. a}2.a«u COOT riLS aaatowAi. roaaaT too YM tcatoo oaaajtjLt vouwt msi VOIUU CVT fR3) COtTB ISieOD) ■ORTAUrr CM2) • aCCMOABY MOABT OOUOUCT ijwrr lOAca KACvaar mu t HAIWT . atAci aoi. BBAl. 742 • 345« 2*41* 722 42*40 7904* 44292 700 »a*t4 332* • 2170 4*307 ••3 4254* 3215 77013 41575 2*21 •72 45203 1*47 05425 5092a 2011 M9. 44434 1*05 77*24 43240 2524 472 *7oaa 344* •4*72 24ia5 447 5az*a 42443 4*50 ••403 33200 24 11 t00451 3O*0 2520 52*34 2447 202) 423. i*5a7 t4»7 442 5701* t«72 42* 701** 207J tata 420 *7754 3«2C 20C 2272 551 42001 24*2 200 2B54 5*3 4103 3 22*4 200 2042 70* 4243 I 271* 300 2244 422Q7 1*12 200 2547 *2450 27*0 200 Ac< ciAoa OTitvervat : ClAll O'Ze 40-a0 •S-lCO l•«-130 120 o-i»o 140-iao I0O-30C 3010* 4155 3541* ia35* 3215 24 135 14** 31380 2aaai 1241 374*0 1072 14355 21270 1*51 30077 1732 • •31 2JI40 22*7 1*70* 32*0 21424 4504 1*54* 213a 14a* 1B2I4 5441 194*5 41*3 1072 UI5'’ 4 1520 1*730 15551 1722 5375 7 244C i*«a3 20ia* 32*0 17*2 7 131* 33205 34135 3472 4J7* 23144 3520 4*0 10 205 10*44 10437 10*44 11152 13012 1 l**e nWACCMawT MIIT a CO«r 5AJ« 0 430) 5 5771 743 7*5 43 0 B 4*43 4*5J 500 IS 5344 7J2 7*5 4) 0 0 **«5 •*•5 500 15 *rjz 700 7*5 *0 0 0 *751 *751 500 2C 4150 *4) 7*5 43 0 0 5B4* 504* 500 3V )53i *72 7*5 45 0 0 *ao4 •004 50: )C 2001 *4* 7*5 *4 0 0 *•*! *••1 503 3<> 2534 472 7*5 47 0 0 *«•• t*o* 5o: 4: 1«)« 4*4 7*5 50 0 0 5301 5161 5or *V 1514 a* 0 0 7027 703~ 5C: 5: 34l' *14 745 100 e 0 *•}* 4*14 50; 55 35)1 524 7*5 52 0 5B* *320 «a3o 5o: 4C 3027 4)2 7*5 5* 0 4*2 *527 502* 50c 4S 1404 *4 I 7*5 57 0 500 . *720 *710 5i; 7 C 1«7 1 52* 7*5 70 34 500 *2*3 *•7* tos 75 l**t *1* 7*5 *7 r»71 114& 127] 510* 50C 10 2371 450 7*5 53 50 4 1. uo lao 4731 4*C 15 -2«55 402 7*5 *1 Ooto 500 53 *•43 50r *0 . 20*1 704 7*5 5) *021 500 12* 5*40 5BC *5 2145 734 745 53 *034 500 0 *5)4 509 IOC 2544 707 745 •3 3*51 500 0 *251 50C 5A»^*T C«*T • uurr. TRIM. « nURTCWMiCT 124)* *; YOTAi. ••■)•* IT 12*54) 1: mm (axcL. RARWtY coaY; 13413) 3C mm itRCL. RAavtiY coati 4*745 )) SHORT REPORT FOR SP IN THE NAA SCENARIO rOMUM VtItXCM Z. 1 •ACRCaOUMD NAaWtT MAJiVIIT LWTL IIU/1TCKAtION) : 4SSOOO «5Sg00 4&&0CC 4S»000 4SSOOQ 4SSS00 4fiSOOO 4S&000 riJWfTINS LTVIL (HA/tTSKATIOMI : 1000 1000 leeo leeo i 1000 1000 1000 1000 ’ 1' ■ •Junwa LCVEL IHA/StHHAriOM; : HAHVItT BUUO « RVLIl •vuz TINK BAKO lOO 10 0 0 0 0 0 - 100 ttIfaOH VAIA/C* (0/N3) CU4VC rxu' OOBIOT CUAlt rZLC: C04T riLA ■ COtDUAI. rOHOIT tTArtItiCS fO« THO MfetOO OriKAOU VOUJHB (N3) VOUIMI CUT nU) AOtA eOOTC iSlOOOl NMTAUrV m3) 4IHC MinAlIY •■OOMOAVr MOOWCT MINABT ■■COMOABT MMOUCT CUT »UW«T atACt MA«VC«r »LMrT RAi trT . • VAC* POt . HHAl. S l&Z’’ 3M4 0 433000 170442 0 40U 1000 Q «1C0 13*0 0 0 194*9 10 3*40. 2437. 0 433000 234441 0 3333 loec 0 *0** 1400 0 0 16771 13 400} 2300 0 433000 133017 0 3*44 1000 0 90*4 1400 0 0 44*94 20 4173 21*0 0 433000 171710 0 3*40 lOOO 0 9101 1400 0 0 46149 23 4133 2003. 0 433000 1020*4 0 330* lOOO 0 9101 1400 0 0 21933 3C 4003 1003 0. 433000 1404** 0 3447 ISO6 6 tlOO 134* 0 0 14347 33 37*1 10S2 0 433000 114447 0 3410 1800 0 9101 9*0 0 0 474Z 40 3337 lOSl. 0 433000 307301 0 314* loot 0 9094 921 0 0 707 4<> 3274 1901 0. 433000 70304 0 3234 1000 0 9101 971 0 0 424 SS 3073 203* 0. 433000 313*4 0 2602 1000 0 96*4 643 0 0 72 3^ 37*1 230* 0 433000 27Q71 0 3043 1000 0 9100 64* 0 0 30 40 3433 2*04 0. 433000 2*203 0 3111 1000 0 9101 9*0 0 0 934 0 AS 3030 33** 0. 433000 244*73 0 0300 1600 0 9102 1400 0 0 11316 0 70 17«S 2432 0 433000 241431 c 4471 leec 0 *101 1400 D 0 10677 7s 144* 2443 0 433000 331*1 0 337* lOOC 0 *0*4 103* 0 0 1733 OS 1240 3*33 e. 433000 437* 0 26*0 I60C 0 9160 1074 0 C 30 OS 103* 3070 0 433000 100747 0 43*0 1600 0 9160 12*3 0 C 373 oo oai 2010. 0. 433000 43343* 0 4264 1600 0 9103 1*42 0 0 4*4 «S 711 312* 0 433000 142*44 0 *03* 1600 0 *101 13*8 0 0 1270 100 *3S 3223 0. 433000 207401 0 4*00 1000 0 *0** 134* C 0 93« AM CLAti tTMKTlMt (MAl 0-20 20-4C 40-60 I 160-120 : 140-160 1*0-160 160-200 93*0 1440 12*12 147*4 4*3* 104 ; j7 12333 93* •371 13718 70*9 II* 7 c 13711 1003 44*7 14946 161*7 loe 7 0 13097 4*7* 27*9 10791 12t*9 1**1 333 7 5 13447 0340 1440 70*4 11*10 2*11 332 38 0 13020 12333 93* 4248 1302* 4387 •0* IOC 7 14*42 13701 1003 2231 11*33 *3*7 •22 IOC 7 14414 13097 4*7* 1442 13414 94 1* 11*4 33S 7 13423 13442 • 340 113* 16300 1074* 1302 312 10 13249 1302C 12333 *13 *73* 1337 k 2Z3* 14* 33 12*93 1*942 137*1 1002 3*47 10*7% 3|7t 0 3* 12321 14414 12697 497 4 16342 293* B 36 124*0 13423 13270 9327 • 173 4694 li 33 13734 1324* 13011 12270 471* 4342 23* 36 13343 12663 11144 14406 3434 6113 23* 36 13*40 1232* 1211} *770 • 0* 433] 234 36 1342* 12**0 13321 109*7 41* 1331* 1333* 1224* 10141 *6*3 236 17«34 13343 129*1 10274 **«e 30 0 17333 13*40 1232* 10320 30 30 M9WT W4VIT * A99A HABWtTtC A99< CO** 6AJ4 VAiAII ruwrr THIH MATVH puwrr wit wit wit 0 1141 2632 S 3326 2463 *33 17Q 0 0 4611 1900 18 20 K It 3*3* 2416 *33 236 0 0 1323 1900 io 3 1 1; IS 499? 210* 433 132 0 0 3444 jeae 20 4|72 213* *33 I7i 0 0 3*40 1900 10 20 13 23 4133 2001 *33 192 0 0 134* 1900 30 4003 1982 433 140 0 0 3447 1090 33 37*0 1*31 •33 III 0 0 1419 lOBO 40 ' 331' 1930 433 10' 0 0 114* 1090 *3 337* 1*03 433 *8 C 0 32)4 leo: 30 307} 201' *33 31 0 0 304? iOOC 33 27*1 2201 433 2’ 0 0 36AJ leo: 6C 2411 248< 433 34 0 0 2111 loor 38 16 •3 204* 23*7 433 241 0 0 4369 1668 i: 2? 1? 70 1743 2411 433 241 0 0 4971 190C 73 144* 244? 433 73 0 0 2379 loo: *0 123* 2*23 433 * 0 0 ' 2990 19*0 IC 16 6 *3 101* 3070 433 190 0 -0 4340 1600 It 20 ID «C too 2910 433 331 O 0 6206 1690 10 2* 1* *3 711 1121 433 162 -2327 0 173? 1680 1C |4 * 100 933 3221 433 9*7 1*43 D 6237 1960 >8 31 II MAirVtfT C09T 43413 44 -9kMf7. TalH. 4 4MUI*T»WA*tC9 6*23 91 9^46 •9M«ri9 9*14* 28 9*n irHCL. HA9VI97 CQ9TI *2741 2* *■• (faC6 HAAS'ltT C09T) *7330 0? SHORT REPORT FOR PJ IN THE FWS-GW SCENARIO rOMIAM VltaXOM 2. •ACVSMOUMO MAlIVtST murviBT L>viL ni3/ZTi«Art(»fi : loueoo lOBSOOO iB4S0A0 1&U090 1< lOUOOD lOUOOO tOASeSO lBASe«0 II BLMrrXWC LWBL lauk/tTBKATTON) : •ooo *000 BOOS aogo aeoi aooQ Booo 1000 aoGO -aooi BBACIMS LWIL (HA/XTIBAriOMI ; &SCD SBOO SSOO SSOO &SDI &SOO BSQO &&00 ssoo ssoi atAClHS •IHDOa iO - 20 NABVBBT BULBt « BW(41 t *11132 loo 1 e 0 0 000 rXMBBB VAU/BB (B/H3) ; 3i BBOONMBY VOL ClfllVB BBT rXLB rOUBBT CLABB BILB, COIT rXLX ■aaiOUAL fCWtBT BTATIBTXCB BM fMI BtRXOO OrBHABLB VOLUM IN2) VOLUHB CITT fR3l ARtR INAI COSTS itlOOOl NORTALITY (N: B«1>1ABY tBCOMOABY BBOOUCT MINARY BBOONOART MOOMCT CVT BLAAT BBACB RARViaT BLA#>T NAlITT . BtACt BQT RCAL. S S<32 Y«6 0 1044000 44443 0 70St 703* 400 21301 2013 0 17*7 *4*0*. 14**3 10 4*41 703. 0 1044000 44B4T 0 OB02 *702 40C 21301 1**1 0 2200 **147. 17701 13 3S32] *«3. 0 1044000 4B117 C *777 *777 400 212*7 17J« 0 2200 47206 10316 20 30A A30 e. 1044000 12403 0 i77« ofroe 4CC 21300 2*30 C 2020 374*3 33 2341 AOB. 0. 1044D0Q 744*4 0 *711 «71( 300 212*7 2177 0 217* 37***. 30 17tb &B6. 0 1044000 t040« 0 *0*1 *B*t 300 21300 32*3 0 2137 1**B«. 33 22CS 4B«. 0 1044000 l«»4aB 0 730* 73B* 400 21300 70*0 0 2201 0. «C XBJ2 47B. 0 1044000 7*242 0 7777 7774 400 212** 2147 0 2101 0. 43 1B74 47B. 0. 1D44000 03442 0 7BSZ 7B32 400 21301 1330 0 2001 0. SC 2147 472, 0 1044000 B2177 0 002B ooao 400 21301 233* 0 2047 0. 33 2073. 4BB. 0 1044000 7*723 C *7*3 ODOe 400 21301 22<7 0 217* 0 BC IBBB 4B0. 0 1044000 B044* 0 7727 7727 400 21300 2*74 0 21*7 0 «3 1SA4 4B2. 0 1044000 YY4B2 0 720? 7202 400 212*7 2B77 0 2200 0. 70 2247 4BB 0. 1044000 10440* 0 70B3 7011 400 212»a 74<3 0 219* 0. 73 1A2< 4B7. 0 1044000 110174 0 7714 7«1S 400 21300 7*7B 0 2201 0. as 1473 4?a. 0. 1044000 171B1* 0 o**o 0000 400 21277 7127 0 2200 0. B3 IBOB 443. 0. 1044000 Y2>77 0 77*4 77*3 400 212*7 2107 0 2070 0. *0 1434 447 0. 1044000 02373 0 0070 OOBC 400 21300 1177 0 2027 0. «3 Lsa« 443 0 1044000 7427B 0 7X37 71J7 40C 212*7 230* 0 2137 0. 100 1232 4BZ. 0 10*4000 ono* 0 7247 7247 400 21300 2373 0 20B3 Q. AOB CLASS BTRVC7VBB 0-20* 20>70 1*0-100 lBO-200 201B 23B*0 3441* 1024* 2*231 313 21300 1*474 31473 4193 1072 1*3*4 174*2 2*141 1444 1 1732 • 031 17*ti 2*23< 201B* 21*0 7144 1•4331 2*0*7 2*231 313S I4B4 BIT 3*04*. 31443 41*3 0 14 434* 2**42 2*14* 14443 *74 2*143 2**234 134*6 03* 10043 2 0B4 12201 312*0 2*044 10070 3 J**7 27 307 *321 13*02 300*4 4072 32*43 27323 0704 32BD7 30*1* 7*0] 30433 33*46 0 311*3 31247 *233 7*7 3142* 27036 3I»3J 2720B 31342 27101 AR*A NARVVBTBD LRBA TBBATtO BBC BLARt TRIM NAtVR BMSrr TRIM 0 *301 7«« 4 4471 744 4400 1C 4*44 702 4400 l-> 3*41 **2 10*4 4400 30 30*2 *10 10*4 • 4*4 44*0 24 23*'' *0* 10*4 4«il 4*i 1 4400 30 17*4 **4 *««i * ««l 4400 34 3301 4*3 10*4 737* 7*)*•»* V40C to 1*31 77* 10*4 127* 7 440C 44 1*7< 47* 10*4 7*24 23 7*42 440C 40 314* 472 10*4 7*41 37 0 •OOO 44 2071 4*7 10*4 7031 44 • 6«C *0 19*6 4*0 10*4 *701 372 7*3* 4400 *4 to** 471 10*4 *44* 422 T207 4400 7S 2277 *•• 10*4 10* 21*4 42*3 *26 7«*J 4400 74 1*23 *•• 10*4 A4T1 1X42 4400 •0 1*71 *27 1**4 3413 234 44*0 • 4 .l*0-> 773 1**4 7413 02 44*0 70 1434 *7* 1B44 7*41 4400 *4 13*6 4*3 »*«4 4400 100 1231 *01 421C 4400 ■AjrWBT CO*T ie«2*4 *0 BLMTT, VRIM. * HAJWTISIAMC* 320*7 *4 TOTAL RRMBPIT 1**3«2 70 MM IBXCL NARVVBT COST) 1734*< 70 mm IlWCL KARVBSt COWT I *7|*f 12 The Jack Pine Forest Type's primary qrowing stock and harvest volumes at five-year intervals for the FWS-GW scenario. The Jack Pine Forest Type's secondary growinq stock and harvest volumes at five-year intervals for the FWS-GW scenario. The Jack Pine Forest Type's annual harvested, regenerated and thinned areas for the FWS-GW scenario. SHORT REPORT FOR PO IN THE FWS-GW SCENARIO rOfMAK VIIIIOH 2.: ■AC«elkOUVT> M/UtVttT Hjuivvvr L.IVIL (K2/XT>RAriOM) ; 2t&oao 3t»eeo 2»sso9 2»kceo 29&000 2t&ooo 2*seeo 2«seoo PUWrriiK b«VIL laA/lTKJtAriOH) : ■ PACIMS LVVKL TMA/ITPHAT tOW ) : ■AKWIT WkSP « avLix RWVB2 TINS BJWiCB 100 100 0 0 0 0 • 100 TIMBII VALrUBB fOi'NlI : CVBVB BBT PILB: yc2-N«u PCNIBST ClABB FIU: p«3.^u Co It B t LB : eTNT. f— kIBIOUAL PONBBT BTATfBTtCB TO* TMB MUOC OMNABLB WOIAMB tR3) VOUNtB art iMlI COSTS It 10001 NONTALirr m31 Tint SBJNABY SBCnstCANY SSOeuCT SSINAITY BBCOMOASY SAOeuCT O/T SLMrr BSACK IMirVItT SUliTT MAX NT . BSACI SOT. SAL. s ito2 as&. e 2*1000 40243 0 2211 02 0 0 0 414*2. 14411 10 314« Jif. 0 2*1000 310*3 0 2201 00 0 0 0 30343. 121*0 It 11S2 371 0 2*1000 30017 0 2043 OO 0 0 0 10**4. 24«>» 30 30&4 «»• 0. 3*1000 30473 0 1**1 so 0 0 0 79340. 124*7 2> 2it0. T«7. 0. 3*1000 *0*41 0 0 *7*21. 70*10 30 23S4 S73. 0 2*1000 471*4 C 0 910S4. *3412 3t 3040 110. C 2*1000 3012* 0 2*00 0 0 044*0 174** 40 1*04 12* 0 2*1000 2130* 0 2030 0 0 43111 34*41 4t 1774 4*7 0 2*1000 *1111 0 24*C 00 0 0 0 40770. 20710 10 1*** 444 0 2*1000 *73*7 0 27«J 03 a 0 0 31*S1. 11301 IV 11*0 3** C. 2*1000 10*177 0 30*0 0 01 0 0 0 290*0. 10432 *0 1**9 a*s 0. 2*1000 134*0* 0 3111 0 OO 0 0 0 20107 3133 *V 1*1* 232 0. 2*1000 C71B7 0 2BV3 OO 0 0 0 3*3**. 70 l«3t 23* 0 2*1000 31**4 0 3403 0 00 0 0 0 40*0. 7V 13*» 231 0. 2*1000 3200* 0 21** *• 0 0 0 0. •0 I3B* 23* 0. 2*1000 32011 0 21BB ** 0 0 0 0. *1 117* 231 0. 2*1000 32*11 0 3112 0 00 0 0 0 0. 0 *0 1374 234 0. 2*1000 37013 e 34*4 00 0 0 0 42 0. *1 13**. 233. 0. 241000 31*0* e 341* 01 0 0 0 0. leo 137* 33*. 0 2*1000 32«7« 0 774B ** 0 0 0 0. . ACO CLASS BTSVCTVBB e-30 i-ise tst-ise 3*1S 14371 11*3 14147 74*S 1400* **e* 4244 •710 t**i 3*10 7013 S302 11*3 433B • 311 7**f I2*0 *40* • 303 44** • 734 • 302 *313 0311 1010 10143 • 3*4 43*4 11B74 • 303 3*02 12237 • 734 132* 12S47 44*0 123*3 424* 11*40 403* 1113* 4014 10330 SS*2 10013 JOOJ mWMOiWiWT 4«1* • OMNIINQ «T<1C« 31*1 2*1 0 3311 3 3*4 2*1 0 2201 3112 2*1 0 204 3 2SV3 2*V 0 1**1 213* 2*1 0 201* 2313 2*1 0 2314 203* 2*1 0 2040 1*04 2*1 0 3030 2*1 0 3440 2*1 0 27*3 11*0 3** 2*1 0 30*0 i*«* 2** 2*1 0 3111 I4S* 331 2*1 0 2011 1427 237 2*1 0 140 3 13** 231 2*1 0 21*4 134* 334 2*1 0 'list 137« 23* 2*1 0 211; 1174 334 2*1 0 2444 J3*4 232 2*1 c 241* 137* 22* 0 274* aWtWKT COST 2*44* 13 •uyrr, TNIH. « WUNTBMMSCB as TOTAL anrcpiT **a2i 74 ma iKxcL HANrasT corn *•#21 74 ■MN itNCL NANviar com 27371 14 The Poplar Forest Type's primary (Po) growing stock and harvest volumes at five-year intervals for the FWS-GW scenario. The Poplar Forest Type's secondary (conifer) growing stock and harvest volumes at five-year intervals tor the FWS-GW scenario. The Poplar Forest Type's annual harvest areas for the FWS-GW scenario. Treatment Activity FWS—GW Scenario The treatment activity for the FWS-GW scenario for the 100-year forecast period. SHORT REPORT FOR PJ IN THE FWS-N SCENARIO romAw vtKtzoH 2. i ■ ACXSMCXWD aAirVIIT ■ACVlir l.rvlL rMS/ITtKATtOMI : UOODO •&0000 «&oaoo ASOOOB Asooeo «soooo MOOCD «&aooo rUkMTZItC 1.KV1L MIO«WCT - 35 OBCaMDACV VOL - 25 ■■AL OlOCCMrr KATO - .040 CU4VC «tr riLI: yc3. tvm roflioT ciAot riLx: pj2.^u COtT flkl- • oir.oM tNi tootir ■ISIDUAL roOtOT fTATIITICt rOO T«f PtKXOO OMRAOLA VOUJMS «»»3l VOUNI< CUT f»l3) MTAllrr 4H3) I ajurvosT ouwrr MAiirr. *^0800 3001 *4*4* 5422 *50000 3001 ' 42*55 4«44 *50000 3002 • 0943 4402 750 *50000 3*3 3000 •4134 3*01 742 *50000 300 2**4 101054 3353 0 12 *50000 3*2 2**4 4*443 tso uoeeo 400 3001 4*03 0 »0» *50000 3«3 45‘>5 300 1 701** *50000 5*7 405* 3000 «2*«0 *50000 714 *J5* 300; 41743 JH3 *50000 •04 3000 1150* 2»«5 *50000 • 42 2**4 5515 2054 *50000 522 3000 *50000 450 30QC *50000 5*7 300 1 *50000 54 •50000 • ••8 30DC 300C *50000 543 300 1 *50000 3800 *50000 3000 AS4 CtJL44 4TKVCTV44 l*AI *64 CW544 0'2D 20-40 40-*0 *0-40 40- 04 I4«>t20 120- .40-1*0 l*«-}4e 140-300 2014* 3340 4155 25414 11 23534 3134 144* 21300 2 2*244 41*3 1072 1*3*5 2: 14323 15551 1732 4421 2- 17J«7 20144 3340 4155 2: 172*7 23534 3134 1449 21 173*4 2*344 4143 1072 1! 175*4 14323 15551 1732 I 17707 173*7 2014* 2340 14271 17247 3353* 3134 20 142 17I«* 2*344 414) 1**03 17»*« 14323 X4347 14*42 17707 173*7 17141 14 14* 14271 17247 17075 1**75 20142 1*444 14311 14*03 12474 2 153* 1«*02 4**1 2 34*7 4754 24544 311*4 eaoviMC 4TOC* 41*4 44*2 4242 4445 •50 4345 *50 *50 •*41 4777 *131 MAAVttT CO*T ••177 0* 4UWTT ' THI*. t BAlwrBKMtCt . 00 Tmu. ioitriT 114*4* ID ••■4 (fXCL. HAOWaT COtT I 11**0* 10 II«CL MWaoT COBT) 54724 2) The Jack Pine Forest Type's secondary growing stock and harvest volumes at five-year intervals for the FWS-N scenario. The Jack Pine Forest Type's annual harvests for the FWS-N scenario. SHORT REPORT FOR SP IN THE FWS-N SCENARIO rOMMAW VCBfZOM 2- 1 ■ACKCAOUND MAMVKIT KAjrVltT LfWL mS/ITiaATIOMI : 2SOOOO 2SOOSO 2SOOOO 260000 2SOOOO 2SOOOO 260008 260000 tLJWTIMC UVIL IHA/lTIftAtlON) : •OACZNC urvtt. ^tTtUrXCM) : ■AAWOT >UUI t KULSl TtHt AMICa 100 100 TIMOln VAlAmS lt/M3) : 46 06 ftOOMOAKY VCL ' cuavT tiT riL( roooT CLAfO rzLi CCtT fit* • ■foat oa r o a I • T attiDUAt roatiT ■TATiffica roa fat acaioo oataAJtc vouMi moj VOUMt CVT IH3I AMA IMI COtTI 1(10001 nOBTAUTY (MO) TIRE aaiMABY ftCOMDAMV MOOUCY aMlNAMY aiCCMCAaY f«OOUCt CVT FtMET ■FACt MAFVItT FtAlTT HAIWT . SFACI POT. BEAL. 6 3YJ 1 2T2i 0 26OP0Q Fttas 0 2240 C 4*41 0 0 S 19*tf. 34*. 2*41 0. Z6000Q *0*00 0 2244 0 6001 0 0 0 14117. 0. IS 4«f2 261* 0 260000 TT27] 0 227} 0 6000 0 0 0 4*44*. 10*24 30 4F71 33aa 0 260000 TT271 0 227 1 0 6000 0 0 0 60213. 21046 3S 6t4< 3346. 0. 260000 *F*6« C 2630 0 600B 0 0 0 37*24 210*. 10 S22Y 2171 0. 260000 6411S 0 2l7-» 0 6000 C 0 0 1*247 0 IS 6262 2111 e. 260000 2332S 0 1*44 0 6000 0 0 0 *743 0 40 62*7 2077, 0 260000 4342 0 103* 0 6000 0 0 C 7B7 0 4S 63SQ 264 1. 0. 360000 10331 0 1034 0 «•*« 0 0 0 43* 0 SC 6241 362S. 0. 260000 list 0 lao) 0 6000 0 0 0 72. 0 SS 631* It24 e. 260000 1D07*4 0 344? 0 6000 0 0 0 3960 0 *8 6316 1*16 0 26DC00 12127) 0 26*4 0 6000 C 0 0 4464 0. AS 61CS 1*14 0 260000 23*e2S 0 3*24 0 6001 0 0 0 130*0 0 1411. 0 260000 2*2*37 0 3**a 0 6001 0 0 0 2004S. 0. 7S «TYi 12*2 0 260000 36«**C 0 3*34 0 6000 0 e 0 100*0 0 • 0 4M0 12 4 1 0 260000 12*073 e 2*40 0 6000 0 0 0 4361. 0 as asii 12 1* 0 260000 1YB377 0 2*76 0 6001 0 C O 10*4 0 «o oat 1370 0 260000 27041 0 1*34 0 6001 0 0 0 7*7 0. as ««3Q 166* 0 260000 247a* 0 111* 0 6001 0 0 0 1666 0 108 taol Q 260009 3*U« 0 2012 0 6000 0 0 0 1016. 0. ASO C1A*> >TavCTVBi lAAi ASt cusa 0*20 ao->*o *o-ao 00 100- 120 UO- 140-1*0 i*o-iaa 100-300 0640 12*12 1*70* 446* 1 toil* ■ 63 1 16710 733* 2 12*36 1*0** 01*7 1 • 44* 11346 36** 2 9136 03M 7677 a *3*0 •eat 7 *2 4 3 a*7a to 7*66 12 3*J7 las) 1002 7*44 •«7* • »«7 • 637 102*4 4S7S 12011 •*«e iseis 3370 133*1 1*77 1360'’ 106*1 43SS AAMAcantMT vHir eao4M>« BYOCf in nji *• raiH ate D 31*3 3ai2 6 1711 27?i 23«* 10 417S 3*42 23«4 IS 4**1 261S 2271 3C 4*71 23|7 227 1 26 614* 334* 2620 10 6227 2170 ai77 3S 62*2 3111 1*44 40 67*7 2077 1*2* is 62S0 2048 103* SC S7*l 2034 100) SS Slia 1F34 2*4} *C 6234 |*1S 2SD 121 2644 «S 6106 1*14 260 23* 343* 70 4*30 1411 2S0 3*2 36** 7S 477J 12*1 3*24 •C 4**C 1240 2**8 •6 4S3C 12IS 260 17* 2*76 •C 43*7 1370 •6 . *430 16S4 100 4*01 1744 268 1* ■ABVKBY £0*T 3*F61 *8 atMrT._ 7NSM. » •4A3WTCMAJ*Ct ao TOTAt BaMBFIT 6114} 46 FM (IXCL AA*va*7 COF* I 611*1 46 ■BM (II4CL 4UUtVtBT COB7 I 21241 *4 The Spruce Forest Type's primary growinq stock and harvest volumes at five-year intervals in time for the FWS-N scenario. The Spruce Forest Type's annual harvest levels for the FWS-N scenario. SHORT REPORT FOR PO IN THE FWS-N SCENARIO BACKCaOtWD HAJtWtT HAJIVtlT LTVIL (MJ/ITtKATlOM) ; 360000 360000 360000 360000 360000 360000 360000 360000 360000 360000 360000 360000 360000 360000 360000 360000 360000 360000 36000C 360000 • UML (KA/ITCKATTCMI : 0 0 0 0 0- 0 0 0 0 0 aPACXMS IXWL (kA/(TK6ATIOH) ; 0 0 0 0 0 D 0 0 ■AJtVfIT RUUt « MUX VIM 100 100 0 000 0- lOO TXMaCa VAU/lt (t/«t3> : PHOOVCT - «S nOM-MOCVCT - 3S OtCIMOiAJrr VOL - ■ KAi. DtaCOUHt tAtl - .040 CU6V1 aat Piu yo3.6«u roAltr CLAtt PILt: »«3. cotT riu ■SlIOUAL rOOfOT tVArimci P06 tot HOIOD OP6IUALS VOUMC nu) VO LAW! CUT (M3) A«6A COPT! ItlOOO) MOMTAUTT (H31 Tla> r«tMA6T tOCOMOJUrr MOOUCT P0XI«A*Y •■CWBMY MOOUCT CUT 6UWT aPACa MAirvOaT PLAMT NA3MT. aPACt POT. ROAL & 3S21 34T. 0. 360000 63906 0 7203 D 0 0 41492. 10236. 1C 33*a. 32T. 0. 360000 62171 0 7199 0 0 0 36661. 7382. 2tT-> 326. 0. 360003 36927 0 7200 0 0 0 46467 13683 20 2630 339 0 360000 36630 D 7200 e 0 0 68303. 36611. 3b 336b 367 0 360800 4173b e 7201 0 0 0 88746. 66676. 30 203b 36b 0 3600SQ 60370 0 7201 0 e 0 76811- 42677 3b 1669 189 0 360000 30299 6 7200 e 0 0 76876. 44048 «C lbl4 382 D 360000 96746 0 7202 e G 0 61016. 16607. «b 1312 320. Q. 360000 90647 0 T20C 0 0 0 32831 8b7b. be 13b4 241. 0 360000 110873 D 7201 0 0 0 38266. 2704. bb 1144 30b 0 360000 66923 0 7200 0 0 0 9771. 0. 60 1070 20b 0 360000 3844'’ a 7199 0 0 0 121. 0. 6b 99b 204 0 3600D0 3633b 0 7201 0 0 0 136 0 70 89b 19b 0 360000 9163b 0 720C c e 7b 77* laa 0 36000C 3993b a 7202 C 0 8: 666 180 0 360000 3983} 0 7179 0 0 0 0 0 8b SAb 17b 0 360000 40366 0 7201 C C 90 437 164 0 360000 92249 0 7200 0 0 9b 377 161. 0 360009 92641 0 7201 e 0 IOC 193 Ibb 0 360000 91631 a 7200 0 a r CLA8B OTaucTvaa ASK CtAai 0*20 60-80 80-100 188-120 120- 3618 16376 6694 641b 16111 6391 8991 13606 7627 •668 9602 996b 10976 7083 10647 10367 4228 10947 10419 2144 8607 10313 1621 10648 11981 11972 1810 12694 3292 14347 2643 16364 3110 16784 17033 16163 VALUt MtT CT>B7 VALl/9 I Mil mt Wit 2806 2672 262* 319 2920 2264 367 2469 2034 394 2969 166* 38a 2466 26bb 3392 3467 36C 3092 36C 4904 16C 4409 360 4979 369 3341 360 36C 360 829 32b 664 MAAVItr COPT 36933 39 puurr.' TMS4«. 4 HA TOTAL ttHtriT 69189 20 PMI I8JCCL MAAVTBT CUBT 69109 30 3326b 91 ^ZZ CfminQ S*»cte Vot. 1 10 30 SO 70 SO The Poplar Forest Type's primary growing stock (Po) and harvest volumes at five-year intervals for the FWS-N scenario. The Poplar Forest Type's secondary growing stock (Con.) and harvest volumes at five-year intervals for the FWS-N scenario.