Harvest Scheduling and Policy Analysis

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An exercise in the use of harvest scheduling tools to explore various aspects of a resource capability model with multiple objectives

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Harvest Scheduling and Policy Analysis

  1. 1. Harvest Scheduling & Policy Analysis Karl R. Walters, Forest Planning Manager, Forest Technology Group 1
  2. 2. In this section… We will review terminology Outcomes Conditions Activities Linear programming (LP) Develop a base LP model for the Daniel Pickett forest Stratification Yields Actions & Transitions Make changes to the base model to evaluate different policies 2
  3. 3. Terminology Review Outcomes More traditional outputs of economic goods & services Timber harvest volume, recreational visitor days, forage in AUM’s, etc. Conditions Current & future spatial and element structure of forest ecosystem Area by stand or habitat type, # of snags/ac, road densities, etc. Activities Human related disturbances occurring on the forest Harvest acres, prescriptions used, miles of road built, etc. Any of these can be viewed as positive or negative depending on goals 3
  4. 4. Terminology Review Linear programming Constrained optimization problems Without constraints, there is no LP problem Allocation or scheduling of scarce resources Key assumptions Linearity: relationships are strictly linear If you double the acres harvested, the volume harvested also doubles Divisibility: any fractional quantity is allowed Any fractional acre can be harvested; otherwise is mixed-integer programming (MIP) Deterministic: all coefficients are known with certainty 4
  5. 5. Daniel Pickett Forest* Could be anywhere Specifics of site quality, location & species not identified 2500 acres 1000 ac = good site, well stocked, healthy, 100 yrs (old growth) 500 ac = poor site, cutover, diseased, 100 yrs (old growth) 1000 ac = poor site, well stocked, healthy, 10 yrs (young growth) * Based on material from Davis et al., Forest Management, 4th ed. 2001. Chapters 3 & 12. 5
  6. 6. Daniel Pickett Forest 3 Watersheds Dogwood Creek Trout Creek Whitewater Creek 6
  7. 7. Daniel Pickett Forest Streamside Management Zones 100 ft buffers 7
  8. 8. Daniel Pickett Forest 2 Site Classes Good (red) Poor (green) 8
  9. 9. Daniel Pickett Forest Stand Condition Healthy, well stocked (green) Diseased, cutover (red) 9
  10. 10. Daniel Pickett Forest Existing Forest Characteristics Mixed forest type* Watershed Management emphasis (timber production vs SMZ) Site quality* Stand Condition* Harvest Units * drivers of growth & yield 10
  11. 11. DP Resource Capability Model Known Management Objectives/Constraints Maximize net present value of forest using 4% discount rate Harvest volume not to vary by more than 20% period-to-period At least 200 ac must be set aside in park-reserve status At least 100 contiguous acres of existing healthy old growth must be set aside as uncut park to protect the habitat of endangered owl No more than 700 ac can be harvested in each of the first 3 periods to give a good distribution of area by ages Even-aged prescriptions should not exceed 40% of total forest Clearcut prescriptions = no more than 20% of forest area and no more than 30% of each watershed Desired future conditions based on WHR system 11
  12. 12. DP Resource Capability Model Outcomes & Activities (Outputs) Model codes PNV (4%) OFpnv4 Harvest volume OQvol Acres in park-reserve status OAreserve Acres in owl habitat status OAowl Acres harvested OAharv Acres clearcut harvested OAcc Acres in evenaged Rx’s OAeven Acres clearcut in each OAccdc, OAcctc OAccwwc watershed (spatial constraint) 12
  13. 13. DP Resource Capability Model Desired future conditions Outcomes Based on Wildlife Habitat Acres within each desired Relationship classification WHR class Species (1 class – mixed species) OAm1m, OAm1d (250 ac @8) Size class (6 diameter classes) OAm2m, OAm2d (250 ac @8) Stand density (2 classes) OAm3m, OAm3d (500 ac @8) OAm4m, OAm4d (750 ac @8) OAm5m, OAm5d (250 ac @8) OAm6m, OAm6d (500 ac @8) DFC in period 8 No more than 20% change period-to-period thereafter 13
  14. 14. DP Resource Capability Model Four Management Prescriptions (Activities) Rx1=even-age, 30 yr rotation, plant & regeneration harvest in 30 yr All stand types are eligible for this prescription Rx2=even-age, 40 yr rotation, naturally regenerate with supplemental planting if need, commercial thin at age 20, regeneration harvest at age 40 Only good sites are eligible for this prescription Rx3=even-age, 90 yr rotation, plant & regeneration harvest in 90 yr All stand types are eligible for this prescription Rx4=uneven-age, small group selection, 2-ac or smaller openings, 60 yr rotation (enter 1/6 of area assigned to Rx each decade, regeneration harvest at age 60 Only good sites are eligible for this prescription 14
  15. 15. DP Resource Capability Model Stumpage Revenues Logging Costs Healthy old growth= $4/cu ft Healthy old growth, on good Diseased old growth= $2/cu ft sites = $1.00/cu ft Young growth= $2.50/cu ft Diseased old growth, on poor Site prep/Regen sites = $1.50/cu ft Good sites= $500/ac Healthy young growth on good sites = $0.75/cu ft Good sites= $300/ac Healthy young growth on poor Management fees sites = $1.25/cu ft Good sites= $30/ac/decade Discount rate Poor sites= $20/ac/decade 4% discounted to middle of planning period 15
  16. 16. DP RCM – Base Planning Horizon _LENGTH = 12 decades Objective _MAX OFpnv4 _LENGTH Constraints None: pure profit maximization Total forest acres = 2500 (LP constraint but always assumed) 16
  17. 17. DP RCM – Base Results PNV = $10,852,028 Maximum volume change period-to-period = +∞,-100% (<20%) 100% of forest in evenaged Rx’s (<40%) Maximum acres clearcut in 1st three periods = 443.92 (<700) 100% of Dogwood Crk assigned clearcut Rx (<30%) 100% of Whitewater Crk assigned clearcut Rx (<30%) 100% of Trout Crk assigned clearcut Rx (<30%) 0 ac assigned park-reserve status (>200) 0 ac assigned to uncut owl habitat preservation (>100) 17
  18. 18. DP RCM – Policy 1 (original DP) Original Daniel Pickett problem (Chapter 11) Planning Horizon _LENGTH = 12 decades Objective _MAX OFpnv4 _LENGTH Constraints OAreserve >= 200 1 ; at least 200 ac in park-reserve status OAowl >= 100 1 ; at least 100 ac of existing good old growth uncut for owls _SEQ(OQvol,0.2,0.2) 1.._LENGTH ; harvest volume to vary by < 20% OIGvol >= 5000000 _LENGTH ; preharvest inventory[12] > 5000000 OAcc <= 700 1..3 ; no more than 700 ac clearcut harvested in 1st 3 periods OArx2 >= 400 _LENGTH ; at least 400 ac of Rx 2 assigned 18
  19. 19. DP RCM – Policy 1 Results PNV = $8,279,139 Maximum volume change period-to-period = 20% (<20%) Maximum acres clearcut in 1st three periods = 700 (<700) 200 ac assigned park-reserve status (>200) 100 ac assigned to uncut owl habitat preservation (>100) Preharvest inventory in last period = 5,000,000 (>5,000,000) 92% of forest in evenaged Rx’s (<40%) 100% of Dogwood Crk assigned clearcut Rx (<30%) 93% of Whitewater Crk assigned clearcut Rx (<30%) 83% of Trout Crk assigned clearcut Rx (<30%) 19
  20. 20. DP RCM – Policy 2 Constraints OAreserve >= 200 1 ; at least 200 ac in park-reserve status OAowl >= 100 1 ; at least 100 ac of existing good old growth uncut for owls _SEQ(OQvol,0.2,0.2) 1.._LENGTH ; harvest volume to vary by < 20% OIGvol >= 5000000 _LENGTH ; preharvest inventory[12] > 5000000 OAcc <= 700 1..3 ; no more than 700 ac clearcut harvested in 1st 3 periods OArx2 >= 400 _LENGTH ; at least 400 ac of Rx 2 assigned OAeven <= 1000 1.._LENGTH ; no more than 40% of forest in evenaged Rxs OAcctc <= 0.3 * OAtc _LENGTH ; acres clearcut in Trout Crk < 30% of watershed OAccdc <= 0.3 * OAdc _LENGTH ; acres clearcut in Dogwood Crk < 30% of watershed OAccwwc <= 0.3 * OAwwc _LENGTH ; acres clearcut in Whitewater Crk < 30% of watershed 20
  21. 21. DP RCM – Policy 2 Results PNV = $4,006,265 Maximum volume change period-to-period = 20% (<20%) Maximum acres clearcut in 1st three periods = 700 (<700) 200 ac assigned park-reserve status (>200) 100 ac assigned to uncut owl habitat preservation (>100) Preharvest inventory in last period = 5,000,000 (>5,000,000) 30% of forest in evenaged Rx’s (<40%) 30% of Dogwood Crk assigned clearcut Rx (<30%) 30% of Whitewater Crk assigned clearcut Rx (<30%) 30% of Trout Crk assigned clearcut Rx (<30%) 21
  22. 22. DP RCM – Policy 1 Desired Future Conditions Acre proportions of period 8 Sequential change in proportions thereafter < 20% OAm1m/OAm1d (250 ac @8) OAm2m/OAm2d (250 ac @8) OAm3m/OAm3d (500 ac @8) OAm4m/OAm4d (750 ac @8) OAm5m/OAm5d (250 ac @8) OAm6m/OAm6d (500 ac @8) 22
  23. 23. DP RCM – Policy 1 Habitat Composition 2500 2000 M6D M6M M5D Acres of Habitat Type M5M 1500 M4D M4M M3D M3M 1000 M2D M2M M1D M1M 500 0 0 1 2 3 4 5 6 7 8 9 10 11 12 Planning Period 23
  24. 24. DP RCM – Policy 2 Habitat Composition 2500 2000 M6D M6M M5D Acres of Habitat Type M5M 1500 M4D M4M M3D M3M 1000 M2D M2M M1D M1M 500 0 0 1 2 3 4 5 6 7 8 9 10 11 12 Planning Period 24
  25. 25. DP RCM – Policy 3 Constraints Constraints (cont’d) *OBJECTIVE _SEQ(OIM6,0.2,0.2) 9.._LENGTH _GOAL(g1,g2,g3,g4,g5,g6) ; minimize _SEQ(OIM5,0.2,0.2) 9.._LENGTH deviations from WHR goals _SEQ(OIM4,0.2,0.2) 9.._LENGTH *CONSTRAINTS _SEQ(OIM3,0.2,0.2) 9.._LENGTH OAreserve >= 200 1 ; at least 200 ac _SEQ(OIM2,0.2,0.2) 9.._LENGTH in park-reserve status _SEQ(OIM1,0.2,0.2) 9.._LENGTH OAowl >= 100 1 ; at least 100 ac of existing good old growth uncut for owls OIM6 = 500 _GOAL(G6,1,1) 8 OIM5 = 250 _GOAL(G5,1,1) 8 OIM4 = 750 _GOAL(G4,1,1) 8 OIM3 = 500 _GOAL(G3,1,1) 8 OIM2 = 250 _GOAL(G2,1,1) 8 OIM1 = 250 _GOAL(G1,1,1) 8 25
  26. 26. DP RCM – Policy 3 Results PNV = $229,564 Maximum volume change period-to-period = -50%,+147% (<20%) Maximum acres clearcut in 1st three periods = 302 (<700) 200 ac assigned park-reserve status (>200) 100 ac assigned to uncut owl habitat preservation (>100) Preharvest inventory in last period = 5,002,078 (>5,000,000) 40% of forest in evenaged Rx’s (<40%) 50% of Dogwood Crk assigned clearcut Rx (<30%) 41% of Whitewater Crk assigned clearcut Rx (<30%) 28% of Trout Crk assigned clearcut Rx (<30%) 26
  27. 27. DP RCM – Policy 3 Habitat Composition 2500 2000 M6D M6M M5D Acres of Habitat Type M5M 1500 M4D M4M M3D M3M 1000 M2D M2M M1D M1M 500 0 0 1 2 3 4 5 6 7 8 9 10 11 12 Planning Period 27
  28. 28. DP RCM – Policy 3 Why can’t we meet DFC? What do we need to do? None of the Rx’s will produce Develop new silvicultural Rx’s M6M/M6D – only existing that can produce M6M/M6D good old growth has it so it types must be largely left unharvested Few Rx’s produce early WHR Possibly find better growth & types yield models to predict WHR Some constraints are too Explore additional scenarios onerous Modify constraints 28
  29. 29. DP Resource Capability Model Features Scheduled: Clearcut final harvest, group selection, commercial thinning Natural and artificial regeneration Some variations of DP RCM not shown included fertilization Tracked Volume outputs, revenues, costs Activity levels (acres treated) Wildlife Habitat Relationship classification acres Could easily track products, forage acres, etc. 29
  30. 30. Forest Management Planning What is required? Computer hardware Fast CPU, lots of memory, disk space (all much cheaper in recent years) Computer software Forest planning models Commercial products: Woodstock, Ep(x), Habplan Public Domain: Spectrum (FORPLAN), SARA Growth & Yield models Stand-level for volume/product outputs Individual tree models for habitat/ecosystem variables Geographic Information/Inventory Sufficient and Complete Expertise Subject matter experts in economics, biometrics, forest management, GIS 30
  31. 31. Visualization Today 31
  32. 32. Visualization – 20 years later 20-years into future 20-years into future 32
  33. 33. Part 3 – Questions & Answers In this section… We will open up the discussion to questions from audience What planning problems can I address using this technology? How do I incorporate this facet of the problem into a forest planning model? How do I go from a strategic planning model to something I can implement on the ground? Discuss issues on technology and expertise Should I do this stuff in-house, or should I contract it out? Final take-away points 33
  34. 34. Issues Hardware is probably the cheapest aspect Capacity continues to grow Data availability is often more limiting Access to growth & yield models Plot data Research and Development In-house R&D, membership in cooperatives, public domain Expertise Requires a group of experts working together Limited supply Relatively few people available with the training/experience needed 34
  35. 35. Final Thoughts – 7 Points Know the long-term & short-term goals of the landowner/decision- maker. Are these priorities documented? Establish the time-frame for the analysis. Next year? Next 10 years? Next 20-50 years? All of these? Do you need to consider county, state, federal laws or regulations? Do outside interests need to be recognized in your plan? Is spatially-explicit information needed for implementation? Critically evaluate your available data. Is it sufficient and complete to meet your planning needs? How will your silvicultural prescriptions be generated? How will you generate estimates of outcome arising from them? Who are the people that will be doing this work for you? Are they in- house specialists? Out-sourced specialists? Combinations? 35

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