1. Conceptual Framework on Planning for Timber Supply
FORE 4212
Kevin Crowe

2. Objectives of Lecture Overview timber supply planning
Step by step
Place each step in conceptual context
What does it mean?
Big picture

3. Topics of Discussion What is timber supply? How is it measured?
How do we estimate it?
Model and data
7 steps
Analysis
Planning for timber supply

4. What is Timber Supply ?
A measure of the permitted flow of merchantable logs out of the forest into mills
Pulled by price, governed by policy, limited by nature
Component of forest management plan
A bit of a misnomer
Not standing stock

5. Measure of Timber Supply
-AAC= planned cut level
- every 5 years
AAC
LRSY
LRSY = Σ (MAI * ha)
of target forest
What does this slope indicate ?

6. Context of this problem
Great consequences
Economic
Environmental
Social
Great complexity
Uncertainty
Therefore, use a decision support model

7. Since we use a model… What is a model?
A representation of reality that we hope to USE to understand that reality
Used for convenience
Typically categorized into abstract or concrete
Timber supply models are abstract

8. expressed quantitatively
How Does it Work?
INSIGHT
operative processes
expressed quantitatively
Real Managed
System
e.g., a forest
Model
Data

9. What insight ? Learning about something through something else?
Learning through analogy
A relation of likeness between things
The relation between the model and the thing modeled is one of analogy
Abstract models
Simplified vs. conceptual

10. Perhaps I digress, but…
A critical distance is needed, and not always present
You will use many models
Conclusions drawn should be tempered by
Quality of data
Operative processes
Room for improvement

11. Let us return to… Decision support model for timber supply problem
There is a generic approach for building decision support models

12. Decision Support Framework
Elicit Problem
Decision Problem
Formulate Model
Collect/Enter Data
Analysis
Loop
Generate Solution
Choice…
Action
Appraise Solution

13. Step 1 Elicit Problem Timber Objectives Portfolio of products
Product rests on economic assumptions
Mill capacity/technology
Silvicultural budget
Potential Target Markets

14. Step 1 Elicit Problem Social Objectives harvest flow policies
recreation and visual quality
Various stakeholders

15. Step 1 Elicit Problem Ecological Objectives
Common approach in B.C. and Ontario is

16. Coarse filter
-constraints operating at a variety of spatial scales
-habitat for a broad range of wildlife
-e.g. 80% clearcuts < 260 ha
Fine Filter
-required for species whose needs are not met by coarse filter

17. Step Two Elicit Problem Formulate Model Collect/Enter Data
Analysis
Loop
Elicit Problem
Generate Solution
Elicit Problem
Appraise Solution

18. Step 2 Formulate Model Mathematical formulation
Typically an optimization model
Maximize NPV or Total Volume
Subject to:
social and ecological constraints
In Ontario, the problem is modeled using SFMM

19. Step 3 Elicit Problem Formulate Model Collect/Enter Data
Analysis
Loop
Elicit Problem
Generate Solution
Elicit Problem
Appraise Solution

20. Step 3 Collect and Enter Data
Data preparation is over 85% of the effort
Define Resource Inventories
location of both timber and non-timber values
Growth and yield
Harvestable land base
Final product is a spatial data base
Polygons
Define set of Potential silvicultural prescriptions

21. Step 3 Collect and Enter Data
Defining the set of potential silvicultural prescriptions
One of the most important decisions in forest management
Emulation of natural disturbance is a guide..
Even-aged vs. uneven aged

22. Step 3 Collect and Enter Data
Even aged decisions
1. Regeneration Method
seed tree, shelterwood, clearcut and plant
severity of disturbance
probability of regeneration delay given seed tree
2. Rotation length(s)
recall frequency of disturbance
Age class distribution

23. Step 3 Collect and Enter Data
Even Aged Decisions (cont’d)
3. Commercial Thinning
The number and timing of entries
4 Opening size and shape
Recall disturbance history, fragmentation
5. Trees to leave at final harvest
Number and size of tress, snags, and down wood to be left in the opening
6. Adjacency Delay

24. Step 3 Collect and Enter Data
Decisions needed in uneven-aged management
1. cutting cycle: number of years between harvest entry on a stand
2. Size of cutting compartments: the maximum size of contiguous area that can be entered at one time
3. reserve growing stock level: residual volume or basal area per acre that can be left

25. Step 4 Elicit Problem Formulate Model Collect/Enter Data
Analysis
Loop
Elicit Problem
Generate Solution
Elicit Problem
Appraise Solution

26. Step 4 Generate Solution
Apply an optimization algorithm to solve the model
Generally two classes of algorithms
Linear programming
Used in SFMM
Integer Programming
Spatially explicit

27. Step 5 Elicit Problem Formulate Model Collect/Enter Data
Analysis
Loop
Step 5
Elicit Problem
Generate Solution
Elicit Problem
Appraise Solution

28. Step 5 Appraise Solution
Assessing Timber and Non-timber Outputs
Evaluate trade-offs
Multiple objectives
Use other analysis tools
Collaborative effort

29. Step 5 Appraise Solution
-e.g., input solution into analysis tools

30. Step 5 Appraise Solution
OMNR’s Models to Evaluate Output
Landscape Ecological Analysis Package (LEAP)
Landscape Diversity Analysis (LDA)
Regional Hydro Ecological Simulation System (RHESSys)
Socio-economic Impact Model (SEIM)

31. Step 6 Elicit Problem Formulate Model Collect/Enter Data
Analysis
Loop
Elicit Problem
Generate Solution
Elicit Problem
Appraise Solution

32. Change these and solve again
Step 6 Analysis Loop
Recall our model’s relation to reality modeled…
Change these and solve again
Operative Processes
Real Managed
System
e.g., a forest
Model
Data

33. Ecological Objectives
Step 6
Analysis
Loop
Ecological Objectives
Multiply determined
by uncertain factors
Timber
Supply
Economic Objectives
Social Objectives

34. Step 7 Elicit Problem Formulate Model Collect/Enter Data
Analysis
Loop
Elicit Problem
Generate Solution
Choice…
Action
Elicit Problem
Appraise Solution

35. Step 7 Choice of Plan Choice is fated
In reality, the long term plan will never be implemented
LRSY is a guide to short term
Plan, and then re-plan– in Ontario, every 5 years
Adaptive management

36. Step 7 Choice of Plan ACTION KNOWLEDGE Why plan without end?
To help make near-term actions and decisions consistent with:
Dimly perceived future condition
To learn about our ignorance of the managed system
Knowledge and data gaps
ACTION
KNOWLEDGE
“Models are to be used, not believed.”
H. Theil `Principles of Econometrics'

37. FINISHED Elicit Problem Formulate Model Collect/Enter Data
Analysis
Loop
Elicit Problem
Generate Solution
Choice…
Action
Elicit Problem
Appraise Solution

38. Conclusion Recall objectives of lecture Overview of modelling process
7 steps
Understand conceptual context
Model and Reality
Decision support framework
Analysis Loop
Nature of Planning