Presentation Transcript

1. Silviculture and Its Relationship to Timber Supply

   Coastal Silviculture Committee TSR 101 Patrick Bryant (pbryant@forsite.ca)
2. Assumptions Results Influencing Timber Supply Coastal Silviculture Committee Topics
3. ? Initial Conditions Rules of Change Objectives, Criteria and Indicators Coastal Silviculture Committee Assumptions
4. Assumptions – Initial Condition Coastal Silviculture Committee Netdown table Land Base Netdown (ordered removals from THLB) Total Area Less areas that cannot produce timber Forest Management Land Base (FMLB) Less areas that meet non-timber objectives (e.g., parks) Less forested areas that not merchantable or operable Timber Harvesting Land Base(THLB) Harvest and grow timber
5. Assumptions – Initial Condition Coastal Silviculture Committee Age ClassDistribution (also species, volumes, products, land base type, etc.) Reported in other periods (e.g., 50yrs, 100yrs, 200yrs)
6. Assumptions – Rules of Change Coastal Silviculture Committee Stand development (growth and yield) Aggregate stand types with similar development patterns to reduce complexity Stands under various regimes or eras, typically: Existing natural; Existing regenerated; and Future regenerated. Link to silviculture options/investments Operational adjustment Factors (OAFs)
7. Assumptions – Rules of Change Coastal Silviculture Committee Natural disturbance (non-harvest removals) THLB = Non-recoverable losses Simply added to Harvest Rate (‘harvested’ but not reported) NHLB = Periodic disturbance events (forest health) Several approaches (e.g., Age Reset by Natural Disturbance Type – Biodiversity Guidebook – every 200 years for CWH in NDT2) If ignored, this could significantly misrepresent desired conditions for non-timber resources
8. Assumptions – Criteria & Indicators Coastal Silviculture Committee Management objectives and options Harvest treatments Utilization levels (net volume) Merchantable criteria (min harvest age - max too) Harvest flow pattern Silviculture treatments Basic silviculture typically “assumed” (informed by, but not actual data) Tree improvement Incremental silviculture (e.g., Type 4 strategies) Treatment Types Eligible Stands Response Windows available to optimize investments
9. Assumptions – Criteria & Indicators Coastal Silviculture Committee Management objectives and options (continued) Forest cover requirements (non-timber) Habitat suitability; ECA recovery; VQO, Green-up Levels for targets & accounts / Ages for constraints & recovery
10. Assumptions – Criteria & Indicators Coastal Silviculture Committee Cont’d... Forest cover requirements (non-timber) Patch size and distribution
11. Assumptions – Criteria & Indicators Coastal Silviculture Committee Product profile Monitor over “time”
12. Build and Run Model Coastal Silviculture Committee “…and then some magic happens…” REALITY CHECK Only interpreting a construct; not the real forest If an assumption was not explicit – it’s not in the model
13. Forest Estate Models Coastal Silviculture Committee A discussion for another time… by someone more knowledgeable… Several models commonly used in BC (no single model is the “prescribed”) More important to work towards understanding the forest-level dynamics
14. Harvest Flows Sensitivities Metrics Coastal Silviculture Committee results
15. Harvest Flow – Elements Coastal Silviculture Committee
16. Harvest Flow - Elements rise Coastal Silviculture Committee
17. Harvest Flow - Patterns Coastal Silviculture Committee
18. Harvest Flow - Patterns Coastal Silviculture Committee
19. Harvest Flow - Sensitivities Compare the impacts on harvest flow of changing one or more assumptions Coastal Silviculture Committee
20. Metrics - Indicators Harvest Profile by average age, area, & volume Coastal Silviculture Committee Harvest Profile by age class
21. Metrics - Indicators Sustainable = stable growing stock & harvest rate Growing stock is the PRIMARY INDICATOR Pinch-point & cushion limits harvest flow Coastal Silviculture Committee Merchantable growing stock directly influences harvest rate; and vice-versa
22. Metrics – Value Coastal Silviculture Committee Forest-level NPV over time Operability Assessments Costs for harvesting, road building and silviculture Develop and link blocks to roads Values for existing and regenerated stands (based on species/age/products/market prices) Adapt harvest flows to report NPV
23. Harvest rate Growing stock Stand Yields Methods of Influence Examples Coastal Silviculture Committee influencing timber supply
24. Methods of Influence Coastal Silviculture Committee Fit the solution to the problem – consider growing stock Aim to treat stands eligible for harvest in the right period by: ∆ development pattern of individual stands ∆ age structure of a group of stands ∆ treatment assumption Explore in the field then develop assumptions… or vice versa Plug: typically knowledge gaps – need to support with real data ACE – risky, so “use caution”
25. Methods of Influence – by Era Coastal Silviculture Committee Existing Natural Stands Scheduled for harvest over the next ~20 years ∆ age structure of a group of stands (harvest pattern) Few ‘silviculture’ opportunities Existing Regenerated Stands Scheduled for harvest after ~20+ years ∆ age structure of a group of stands Typically incremental silviculture treatments Future Regenerated Stands Scheduled for harvest in ~60+ years ∆ the development pattern of individual stands Typically basic silviculture
26. Examples - Site Index and Species Coastal Silviculture Committee Regenerated SI – SIBEC/SIASI is the biggest lever (∆ development pattern) “Use species wisely” (ecologically suited; species adaptation strategies; product values)  Simply prorate yields for mixed or multi-layered stands
27. Examples - Site Index (Interior example) Coastal Silviculture Committee But beware the “Evils of Averaging”… …for Tactical Planning
28. Examples - Minimum Harvest Age Coastal Silviculture Committee 38% 25yrs Minimum age at which harvesting is commercially viable Determines merchantable growing stock Criteria: Volume, % CMAI and/or diameter
29. Examples - Minimum Harvest Age Coastal Silviculture Committee A big lever (∆ treatment assumption) Reducing MHAs also lowers long-term harvest level Easy to model; resolves some issues quickly – but risky…
30. Examples – Initial Density Coastal Silviculture Committee Beyond a certain level, initial density has little effect on yield (so it’s not just about TPH)
31. Examples – Method (Spatial Patterns) Planted Natural Coastal Silviculture Committee Clumped TIPSY uses hybrid of initial density and one of 3 spatial distribution patterns (species dependent) So be careful with regen method
32. Examples – Stocking Coastal Silviculture Committee Initial density in TIPSY ≠ total or well-spaced stems Ultimately, analysts tweak initial density and regen method/patterns to mimic stocking (considering reports generated at different ages) Are we aiming for maximum site occupancy? (wood quality/value)  silviculture surveys results do not provide easy inputs for stand-/forest-level modeling
33. Coastal Silviculture Committee Epilogue
34. TSR vs. Scenario Analysis Timber Supply Review What was/is… Timber Supply Scenario Analysis What if… Forward-looking assumptions Explore possible scenarios Anytime Used to support programs; implemented ONLY after responses are verified (years) Aimed to modify AAC Past and current practices Balance uncertainties Periodic AAC implemented immediately Some scenario analysis to support AAC determination Coastal Silviculture Committee
35. What do we know? Coastal Silviculture Committee Access to very good inventories (compared to other locales) Robust stand development models; knowledgeable people; methods for sharing information Array of suitable forest estate models But… How well do our assumptions reflect our existing regenerated stands? Depends where you’re at; forest health impacts Incorporating RESULTS information into forest-level analyses is NOT EASY (including depletion)
36. What do we need? Coastal Silviculture Committee Adapt to address climate change, forest health and products – ongoing progress Better GY – mixed species stands Better inventories – young stands But… How good are our predictions of stand development to rotation? Okay on average but treatments are typically required with stands “on the fringes”
37. What do we need to know? Coastal Silviculture Committee Information needed to support silviculture assumptions: Treatment criteria, windows, response and cost So… How do we build defensible assumptions for developing timber supply scenarios? Trials? Track the right information? Accounts?
38. Many thanks to those whose ideas I’ve borrowed… Eleanor McWilliams Jeff McWilliams Simon Moreira-Munoz Ed Mulock Stephen Smyrl Jordan Tanz Guillaume Therien Jim Thrower Gordon Weetman Doug Williams FAIB (too many to name) Bryce Bancroft Gordon Baskerville Cam Brown Reg Davis Jeremy Hachey Peter Kofoed Bill Kuzmuk AnttiMakitalo Colin Mahony Coastal Silviculture Committee