Northern Forest (G) Policy Design:
A Model-Based Learning Laboratory
UVA-OM-1158
This model-based learning laboratory has been designed as a policy-design case study to be used with “Northern Forest (A),”
(UVA-OM-1107). A PowerPoint presentation file is available from Darden Business Publishing. It was prepared from Jones,
Seville, and Meadows, “Resource Sustainability in Commodity Systems: The Sawmill Industry in the Northern Forest,“ System
Dynamics Review, 18, no. 2, (2000).
This learning-laboratory case was prepared by Andrew Jones, of the Sustainability Institute, and Professor Robert D. Landel, and based on
studies and the System Dynamics Review article by Drew Jones, Don Seville, and Donella Meadows, also of the Sustainability Institute. It was
written as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Copyright  2004
by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to
sales@dardenpublishing.com. No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted
in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School
Foundation.
Northern Forest Policy Design
The Sustainability of the Sawmill Industry of
the Northern Forest:
A Model-Based Learning Laboratory
Drew Jones
Don Seville
Donella Meadows
Bob Landel
The Darden School
University of Virginia
Sustainability Institute
November, 2004
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Background and Behaviors Over
Time
The Northern Forest is Pulled in
Several Directions
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Environmental
Goals
Industrial
and
Economic
Goals
Urban
Development
and
Fragmentation
Leaving the question:
 How can regional leaders resolve
the increasing forest products
industry and environmental goals
in the face of a potentially
shrinking forest base?
Slide 4
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Behavior Over Time Data: Is There Enough Timber Supply
Today? Yes. But What About the Long Term?
Inventory on Sawtimber Acres
Lumber Production
50
2500
Billion
Billioncubic
cubic feet
feet
feet per year
Million boardMMBF
Total
40
30
20
ME
10
NY
NH
VT
0
1970
1980
1990
2000
Data Source: USFS studies and NEFA estimates
2000
1500
1000
500
0
1970
1980
1990
2000
Data: U.S. Census -- Lumber Prod. and Mill Stocks
Slide 5
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Recent Trends or “Momentum” in
the Industry, Economy, and Forest
Lumber Production
Roundwood Pulpwood Harvest
5000
Thou Cords
2000
MMBF
The demand
for sawlog
harvest
has grown
strongly
6000
2500
1500
1000
4000
3000
2000
500
Inventory increases
are leveling
1000
0
1970
1980
1990
2000
0
1960
1970
1980
1990
Data: U.S. Census -- Lumber Prod. and Mill Stocks
Data Source: USFS, Rich Widmann
Total Urban Land Area
Inventory on Sawtimber Acres
Thousand Acres
Billion cubic feet
20
ME
NY
1980
2000
1990
Jobs are
falling
0
2000
Data Source: USFS studies and NEFA estimates
1945
30000
20000
1000
NH
VT
0
1970
Urban land
area is
expanding
3000
30
10
40000
Total
40
Note: Most
data shown
are for all four
NF states
2000
Maine Forest Industry Jobs
4000
50
Harvesting
pulpwood
has grown
and leveled
1960
1975
1990
10000
Note: Includes official logging, sawmill
wood products, and pulp/paper mill jobs
0
1980
1985
1990
Source: Department of Commerce
Data: NEFA, for four NF States
Slide 6
1995
2000
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Taking the Long View -- Sawmills Have
Grown And Contracted and Grown
NF State Lumber Production 1839 - 1998
Million board feet per year
3200
2400
1600
800
0
1830
1870
1910
1950
1990
Source: USDA, Steer, 1948 and US Census
Slide 7
“Event” explanations
 Capital shifted to other
regions
 1912-1920 spruce
budworm outbreak
 1929 stock market crash
 Timber diverted to
growing NF paper industry
 Land to farming and then
back
 (Excellent research on this
question by Irland)
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Our Reference Mode -- Can the Region
Sustain its Lumber Industry?
Lumber Production
feet per year
Million boardMMBF
2500
2000
1500
1000
500
0
1970
l
1980
1990
2000
2030
Data: U.S. Census -- Lumber Prod. and Mill Stocks
Slide 8
l
2070
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Systemic Structure
Our Dynamic Hypothesis
Young
trees
Aging
Middle age
trees
More
sellers
B
B
Lumber
price
Mill
profits
R
Scarcity
premium
Growth
New Invest
Costs
Mill
production
B
Stayin’
alive
Technology
Timber
demand
Scarcity
signal
Timber
price
Death
Harvest
Available
timber
B
Landowner
willingness
to sell
Harvestable
trees
Aging
R
Capacity creep
spiral
Slide 10
Mill
Capacity
Creep
Growth
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Closure
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Model Assumptions
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The Model World Crosses Four Sectors
Reserve
Fiber
Sawlogs
• Acres
• Age
• Volume
Other fiber
Conservation
Pulp/Paper
Investor
Mill source
General
• Profitability
• Harvest Level
• Yield mgt
Sawmills
• Capacity
• Technology
• Profitability
• Residues
Slide 12
Fuelwood
Lumber
• Market size
• Growth rate
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Each of the Landowner Categories Has a
Distinct Forest Management Behavior

Demand-based



Rotation-based



NIPF General -- Non-industrial private
forestland. Small landowners with short
tenure, responding to the demand. Some
are not interested in harvesting.
Mill -- Mill-integrated working land. Used
as the primary source to meet the harvest
demand. May put some land in plantation.
Investment -- Investment-managed
working land. Seeks to maintain a
competitive ROI - works on “rotation” plan.
Can be sensitive to scarcity. May invest in
thinning or tree farming. Much of the
remaining mill-owned land fits here.
Conservation -- Conservation-managed
working land. Always sticks to a rotation
goal unless financial loss cause a halt to
logging.
Northern Forest Land in Landowner Behavior Classes
Estimates for 1997
5. Ecological
reserve
10%
4.Conservation
managed working
5%
2. Mill-integrated
13%
This is a rough estimate for
the entire four states
Not working

Reserve -- No sales
1. Non-industrial
private (unmanaged
working)
52%
3. Investment
managed working
20%
Slide 13
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Assumptions for Land Use Shifts
Land Class Status
1.0
12
1
2
Percent of Forest
0.8
1
0.6
0.4
2
3
3
3
4
4
4
0.2
5
5
5
6
6
6
0.0
2000
2050
Year
Slide 14
Export
Non Industrial Private Forestland
Mill-Integrated working land
Investment managed working land
Conservation managed working land
Ecological Reserve-not working land
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Core Assumptions for the Base Case Run
 Sawmills
invest in capacity as long as profits
goals are met (at 3% per year). As profits decline
technology cost savings and mills closures occur.
 When the sawlog supply is felt to be scarce
(sawmill demand exceeds “annual market
volume” or the amount that landowners would
like to sell normally each year), the forest market
will drive up the sawlog price.
 Urban Development at .25% per year in 2000.
 Lumber demand growth at 3% per year in 1970,
slowing to 2% by 2010.
Slide 15
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Two Caveats Before Running the Model
 This
is not a prediction, but rather the result of
model assumptions about how the forest,
landowners, mills, and market make their
deciosions and interact.
 We
are exploring the pattern of behavior over
time (e.g., growing, falling, s-shaped,
accelerating, oscillating), not trying to identify the
exact timing of events or specific levels (of
harvest, forest inventory, or mill profitability, for
example) that can be achieved.
Slide 16
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Base run of the model
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The Feedback Structure of the System Creates
a Boom and Bust of the Sawmill Capacity
Sawmill Capacity
4,000
mmbf/yr
3,000
2,000
1,000
0
2000
2050
Year
Slide 18
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This Pattern is Reminiscent of a Boom
and Bust around the Last Turn of Century
NF State Lumber Production 1839 - 1998
Million board feet per year
3200
2400
1600
800
0
1830
1870
1910
1950
1990
Source: USDA, Steer, 1948 and US Census
Slide 19
“Event” explanations
 Capital shifted to other
regions
 1912-1920 spruce
budworm outbreak
 1929 stock market crash
 Timber diverted to
growing NF paper industry
 Land to farming and then
back
 (Excellent research on this
question by Irland)
Return to Home
The Core Reason for the Boom and Bust is a Severe
Draw-Down of Inventory on the Market Lands
Harvestable Sawlog Inventory
25,000
net merch. mcf
20,000
15,000
10,000
2
2
Total
1
5,000
Market
1
0
2000
2050
Year
Slide 20
Rising Sawlog Price and Falling Sawmill
Profitability Trace Out the Remaining Steps of
the Core Balancing Feedback Loop
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Ave Sawmill Profitability
Sawlog Price
15
%
Annual Return
300
$
200
100
0
2000
2050
10
%
5%
0%
-5
%
2000
2050
Year
Year
Continue to Base
Run Analysis
Slide 21
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Analysis of the Base Run
What Caused “Overshoot” of the Sawmill
Capacity and a Drawdown of the Sawlog
Inventory?
600
2
500
mcf/year
Some
landowners
are
The Overshoot
Story
willing
to sell (at
the base price)
based on their
Market Volume vs
inventory
not
Growth vs Harvest
annual forest
growth.
700
400
300
200
1
3
12
3
100
2
1
3
2
3
1
1
0
1980
2000
2020
2040
2060
2
3
1
2
1
$
150
1
2080
1
1
1980
2000
1
Sawlog
price
1
1
100
50
0
8,000
1
2020
2040
2060
2080
1
1
6,000
Sawlog inventory on
market lands
4,000
1
2,000
1
1
2040
2060
0
1980
2000
2020
Slide 23
Some landowners will
sell above their
“market volume” if the
price increases (they
Market
Harvest
will always sell if the
Grow th
mills meet their price)
Annual 3
market volume 1
Year
250
net merchantable mcf
Overall
principle: The
forest inventory
declines when
the harvest rate
exceeds the
growth rate.
1
3
Growth
rate 3
2
200
Sawlog Price
Harvest
Rate 2
Return to Home
2080
1
Many balancing
effects dampen
price signal,
Saw the
log
leading to a long
delay before the
mill capacity and
harvest rate come
back into balance
with the growth
Market
rate.
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Why Does It Take So Many Years to Bring
Harvest Rate Down to the Forest Growth Rate?
Forest Growth exceeds
harvest,
mills profitable and growing &
Stock growing
700
Mill Demand exceeds what
landowners want to sell,
Sawlog price climbs
Capacity closure and
utilization cuts exceed
new investment
New technology
and higher lumber
prices mitigates
scarcity signal
Harvest exceeds growth,
sawlog stock begins
to fall
Falling production
boost residue price,
contraction slows
somewhat
Harvest rate
meets growth rate,
sawlog stock levels
600
1
mcf/year
500
1
400
300
1
2
200
1
1
1
2
2
1
2
2
Higher sawlog prices,
increase # landowners2
2 willing to harvest
normally
1
“Available”
2
inventory
drawn down
1
100
1
2
1
2
1
2
2
Harvest
Grow th
0
1980
2000
2020
2040
2060
Year
2000
2020
2040
Year
2060
Slide 24
2080
2080
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Why Don’t the Sawmills Receive a Clear
Signal of Sawlog Scarcity in Time?
 The
signal from the forest to mills is delayed and
dampened
 Signal Delayed

Many landowners are managing on short time horizons and willing to
harvest above growth rate, so sawlog price rises only when the inventory
has been drawn down severely
 Signal



Dampened
Higher sawlog prices draw more sellers into the market, pushing sawlog
price back down
In several ways, sawmill technologies allows mills to remain profitable
and running despite higher sawlog prices
When sawmill growth slows, higher lumber prices boost mill profitability,
slowing the mill contraction
Slide 25
Why Do the Mills Continue to Grow
Despite Low Sawlog Inventories?
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 Mill
investors are making rational decisions given
the information available and their incentives
 Can’t track total wood demand relative to forest
supply


Demand -- don’t know of others’ mills expansion plans until work is
underway
Supply – information is delayed
 Key
to survival is to adopt new technologies and
grow bigger



Cut costs and outbid others in the market or die
“Someone will be left standing -- it’ll be me”
Creates a “downward spiral”
Slide 26
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“What If” Policy Simulator
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Eliminate Canadian
Sawlog Exports
Land Owners
End Development of
Forestlands
Invest in “Yield
Management”
More Land in Reserve
and Conservation
Change General Land
Management
Harvest Limit
Mills
Public Policy
“What If” Policy Simulator Choices
Slide 28
Boost Sawmill
Material Efficiency
What If…End Development of
Forestlands
 Currently
Return to
Simulator
Home
.25% of forestlands are lost to
housing and other developments
 What if the losses were eliminated?
 Would it stop the boom and bust cycle from
occurring?
Slide 29
Ending Development Decreases the Depth of
the Bust But Doesn’t Balance out the Cycles
Sawmill Capacity
4,000
Policy
Policy
mmbf/yr
3,000
1
1
2,000
Base
1,000
0
2000
2050
Year
Slide 30
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Simulator
Home
Inventories Show Little Benefit from the
End of Development
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Simulator
Home
Total - policy
Total - base
Market - policy
Market - base
Slide 31
End of
policy test
section
What if….Ban Sawlog Exports to
Canada?
 In
Return to
Simulator
Home
1997, approximately 25% of Northern
Forest Sawlogs exported to Canada
 These Canadian mills (that depend on
Northern Forest sawlogs) are included in
the model as “Northern Forest” mills
 If sawlog export ends, will it balance out
the cycles?
Slide 32
Eliminating Exports Delays the Overshoot
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Simulator
Home
Policy
Total - policy
Base
Total - base
Market - policy
Market - base
End of
policy test
section
Slide 33
What If… Increased Yield Management?

Yield management involves growth-enhancing techniques
such as thinning and plantation management.





Return to
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Home
If the forest can just grow faster, the overshoot can be mitigated.
The mills start managing one half their land in highyielding plantations
Investment landowners increase their investment in precommercial and commercial thinning.
The result of these investments is to increase the growth
rate and the fraction of logs that are of sawlog quality
Will these changes balance out the boom and bust cycle?
Slide 34
Yield Enhancement Helps to Some
Degree
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Simulator
Home
Policy
Total - policy
Total - base
Market - policy
Base
Market - base
End of
policy test
section
Slide 35
What if….Boost Mill Efficiency?
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Simulator
Home
Accelerated
increases to “lumber
recovery factor”?



More lumber out of every sawlog
thinner sawblades, computer-aided scanners, curved
saw technologies
Policy boosts rate of improvement of lumber recovery
factor from 3.9% per decade to 6.1% per decade
Will
it address the boom and bust
cycles?
Slide 36
Boosting Mill Efficiencies Allows Mills to
Boom More But Still Bust
Sawmill Capacity
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Simulator
Home
Harvestable Sawlog Inventory
25,000
4,000
Ex
Mill
Inv
Con
2
1
3,000
mmbf/yr
Gen
2
1
2,000
Base
1,000
net merch. mcf
Policy
20,000
15,000
10,000
34
Total - base
34
Total - policy
Market - base
12
5,000
Res
Market - policy
12
0
0
2000
2000
2050
2050
Year
Year
Slide 37
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Simulator
Home
Sawlog Price Has To Rise Even Higher in
Order to Get the Mills to Stop Expanding
Ave Sawmill Profitability
Sawlog Price
15
%
2
$
200
12
Base
100
10
%
2
2000
2050
Policy
5%
0%
0
1
-5
%
2
Base
1
2000
2050
Year
Year
300
Continue to a causal
loop diagram
250
200
Slide 38
$
1
Annual Return
Policy
300
150
What if….Increase Reserve and
Conservation Land?

This scenario includes an increase in reserve and
conservation land.
1997
Reserve
scenario
General
52%
47%
Mill
13%
3%
Investor
20%
15%
Conservation
5%
10%
Reserve
10%
25%
Slide 39
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Simulator
Home
More Reserve/Conservation Land
Creates a Bi-Modal Forest
Return to
Simulator
Home
Total - policy
Base
Total - base
Policy
Market - base
Market - policy
Slide 40
“Squeeze the Balloon” Problem – More Reserve/ Return to
Simulator
Conservation Land Puts Harvest Pressure on
Home
Market Lands
Avg Harvest Levels
0.6
Cords/Acre/Year
0.5
Policy
2
0.4
1
2
1
0.3
Base
0.2
1
2
0.1
0.0
2000
2050
Y ear
Slide 41
General
General
What if….Different Management by Nonindustrial Landowners?

Longer planning horizon for harvesting

Less willing to harvest when sawlog price rises

Economics -- more “inelastic”
Slide 42
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Simulator
Home
Return to
Simulator
Home
In the Short Term, the Policy Seems to Hurt Sawmills
– Higher Sawlog Prices and Lower Profits
Ave Sawmill Profitability
Sawlog Price
15
%
Base
1
2
Policy
$
200
1
2
100
Annual Return
300
10
%
Policy
1
2
5%
2
Base
0%
0
2000
2050
-5
%
1
2000
2050
Year
Year
300
250
Slide 43
200
Sawmills Avoid a Major Boom-and-Bust
and the Forest Has Greater Inventories
Base
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Simulator
Home
Total - policy
Policy
Total - base
Market - policy
Market - base
End of
policy test
section

The sawmill industry may need higher sawlog prices
in order to maintain long term profitability
Slide 44
What If… A Public Policy Harvest Limit?




Return to
Simulator
Home
Industry reduces sawlog harvesting if the reported sawlog
inventory begins to fall
There is a delay in getting the report and the report
leading to a negotiated solution. A total of 8 years.
Sawlog sales from landowners is capped at the total
sawlog sale at the time the harvest limit is put in place.
What will happen to the boom and bust dynamic?
Slide 45
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Simulator
Home
Harvest Limit
Sawmill Capacity
Policy
4,000
Policy
1
12
mmbf/yr
3,000
2
2
2
1
2
1
2,000
1
1
2
1,000
0
1980
2000
2020
2040
2060
2080
Year
Slide 46