Conceptual Framework on Planning for Timber Supply FORE 4212 Kevin Crowe

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

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

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

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 ?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

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

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

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

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

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

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'

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

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