Silviculture and Its Relationship to Timber SupplyTSR 101Patrick Bryant (pbryant@forsite.ca)

Coas

tal S

ilvic

ultu

re C

omm

ittee

Nan

aim

o - F

ebru

ary

27, 2

014

1

TOPICS

•Assumptions•Results• Influencing Timber Supply

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

2

ASSUMPTIONS

Initial ConditionsRules of ChangeObjectives, Criteria and Indicators

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

3

?

Coas

tal S

ilvic

ultu

re C

omm

ittee

Assumptions – Initial Condition

• 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

Nan

aim

o - F

ebru

ary

27, 2

014

4

Netdown table

Coas

tal S

ilvic

ultu

re C

omm

ittee

Assumptions – Initial Condition

• Age Class Distribution (also species, volumes, products, land base type, etc.)

Nan

aim

o - F

ebru

ary

27, 2

014

5Reported in other periods (e.g., 50yrs, 100yrs, 200yrs)

Assumptions – Rules of Change

• 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)

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

6

Coas

tal S

ilvic

ultu

re C

omm

ittee

Assumptions – Rules of Change

• 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

Nan

aim

o - F

ebru

ary

27, 2

014

7

Assumptions – Criteria & Indicators

• 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

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

8

Assumptions – Criteria & Indicators

• Management objectives and options (continued)• Forest cover requirements (non-timber)

• Habitat suitability; ECA recovery; VQO, Green-up

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

9Levels for targets & accounts / Ages for constraints & recovery

Assumptions – Criteria & Indicators

• Cont’d... Forest cover requirements (non-timber)• Patch size and distribution

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

10

Assumptions – Criteria & Indicators

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

11

Monitor over “time”

Product profile

Build and Run Model

• “…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

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

12

Forest Estate Models

• 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

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

13

RESULTS

Harvest FlowsSensitivitiesMetrics

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

14

Harvest Flow – Elements

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

15

Harvest Flow - Elements

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

16

rise

Harvest Flow - Patterns

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

17

Harvest Flow - Patterns

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

18

Harvest Flow - Sensitivities

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

19

Compare the impacts on harvest flow of changing one or more assumptions

Metrics - Indicators

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

20

Harvest Profile by age class

Harvest Profile by average age, area, & volume

Metrics - Indicators

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

21

Sustainable = stable growing stock & harvest rate

Pinch-point & cushion limits harvest flow

Merchantable growing stock directly influences harvest rate; and vice-versa

Growing stock is the PRIMARY INDICATOR

Metrics – Value

• 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

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

22

Forest-level NPV over time

INFLUENCING TIMBER SUPPLY

Methods of InfluenceExamples

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

23

Growing stock

Harvest rate

Stand Yields

Methods of Influence

• 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”

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

24

Methods of Influence – by Era

• 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

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

25

Examples - Site Index and Species

• 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

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

26

Examples - Site Index

• But beware the “Evils of Averaging”… …for Tactical Planning

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

27

(Interior example)

Examples - Minimum Harvest Age

• Minimum age at which harvesting is commercially viable• Determines merchantable growing stock• Criteria: Volume, % CMAI and/or diameter

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

28

38%

25yrs

Examples - Minimum Harvest Age

• A big lever (∆ treatment assumption)• Reducing MHAs also lowers long-term harvest level• Easy to model; resolves some issues quickly – but risky…

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

29

Examples – Initial Density

• Beyond a certain level, initial density has little effect on yield (so it’s not just about TPH)

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

30

Examples – Method (Spatial Patterns)• TIPSY uses hybrid of initial density and one

of 3 spatial distribution patterns (species dependent)

• So be careful with regen method

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

31

Natural

Clumped

Planted

Examples – Stocking

• 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

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

32

EPILOGUE

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

33

TSR vs. Scenario AnalysisTimber Supply Review

What was/is…

• Past and current practices

• Balance uncertainties• Periodic• AAC implemented

immediately• Some scenario analysis

to support AAC determination

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

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

34

What do we know?

• 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)

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

35

What do we need?

• 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”

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

36

What do we need to know?

• 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?

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

37

Many thanks to those whose ideas I’ve borrowed…• FAIB (too many to name)• Bryce Bancroft• Gordon Baskerville• Cam Brown• Reg Davis• Jeremy Hachey• Peter Kofoed• Bill Kuzmuk• Antti Makitalo• Colin Mahony

• Eleanor McWilliams• Jeff McWilliams• Simon Moreira-Munoz• Ed Mulock• Stephen Smyrl• Jordan Tanz• Guillaume Therien• Jim Thrower• Gordon Weetman• Doug Williams

Nan

aim

o - F

ebru

ary

27, 2

014

Coas

tal S

ilvic

ultu

re C

omm

ittee

38