Transcript Modeling the Effects of Silvicultural Regimes on Douglas

Modeling the Effects of
Silvicultural Regimes on Douglas-fir
Crown Morphology and
Related Wood Quality Attributes
N. Osborne, D. Maguire and D. Hann
Oregon State University, Forest Engineering Department
Center for Intensive Planted-Forest Silviculture (CIPS)
IUFRO Meeting in France
• Conference on wood quality
in Nancy hosted by INRA
• Conference focused on
connecting wood science
and forest growth modeling
• Organon is well positioned
to respond the MeMo
challenge given in Nancy
The Organon System
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Specific to the Pacific Northwestern U.S.A.
A chain of four forest models
Extensions for the Organon system
CIPS Simulator (Doug Mainwaring)
Latest extension is for the R software (ONR)
Beta version available for download
Easily modified, and a product of three CIPS
members direct input already
• Open source, and freely available
The Organon Model Chain
Volume
Model
Imputation
Model
Crown ratio, total
tree height etc.
Growth
Model
Individual-tree
Spatially implicit
Quality
Model
Not Just Quantity, but Quality!
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Given at a tree, and whorl level
Branch height
Number of branches
Largest branches diameter
Juvenile core (Crown core)
Inside bark diameter
Very easily associated with
other tree and stand level
characteristics
Josza and Middleton 1994
Organon in R Process Diagram
Sample,
Unit and
Activity List
Split up Orders by
Sample and Unit
Impute Missing
Information
Compute a Few
Sample Level Attributes
Amalgamate the Orders
Grow Trees,
Quality, Volume
To Specified Age
Projected Tree,
Quality, Sample,
Flags and Figures
Silvicultural Effects on Quality
• Silviculture is the art and science of
growing trees
• Encompasses many treatments
• Initial planting density
• How long to grow the stand
• Timing and application of thinning
• Silviculture, crown morphology and
Different initial spacings
wood quality are strongly related
• Organon can simulate effects of
silviculture on crown morphology
and wood quality
• Explore the economy of silvicultural
regimes in a very simplistic way
Experimental Design
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Two by two factorial design
Four levels of thinning
Six levels of initial planting density
24 combinations of thinning and initial density
Simulated rotations between 20 – 100 years
Resulted in 408 Organon simulations
Worth noting this is a simulation experiment,
without any replication
Silvicultural Treatments
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TPA At age 20, thin to 200 trees per acre
RELY At age 20, thin to relative density of 30%
RELR When relative density is 50% thin to 35%
CON Do not impose a thinning
All thinning's were from below
In some cases, thinning was infeasible
Selected on the expectation that treatments
were representative for industry in Oregon
Simulation Dataset
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Located at the Lewisburg Saddle in Oregon
Installed by Stand Management Coop (SMC)
Six initial planting densities
Sites were of similar productivity
Bruce site index of 123 feet at 50 years
Simulated stands were fifteen years old (1989)
Lewisburg Saddle Installations
Lewisburg Saddle Installations
1200
100
300
680
Lewisburg Saddle Installations
6-ft spacing (1200)
10-ft spacing (435)
21-ft spacing (100)
Initial Planting Density
(trees per acre)
Thinning Treatment
CON TPA RELY RELR
100
200
300
435
680
1200
Merchandizing Specifications
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Buck up each tree, from each simulation
Assume 6-inch stump height
Maximize the number of 32-foot logs
Cut 16-foot logs when necessary
Assign bucking trim when cutting each log
Ignore chip-wood portions of the tree
Use log-level information to obtain the
Scribner volume in quality classes
Assigning Wood Stress Grade
• Estimated MSR grade with Fahey et al. (1991)
• MSR grade is a function of a logs largest limb
diameter and the percentage of juvenile wood
2100f 1.8E
18.69*exp(2.96*llad+0.025*jp-2.95*llad2-0.0007*jp2)
1650f 1.5E
38.1*exp(0.79*llad-0.702*llad2-0.000105*jp2
1450f 1.3E
Obtained by subtraction
No.3
Economy
0.93*exp(3.41*llad-0.76*llad2)+0.003*jp2
2.93*exp(1.10*llad-0.0106*jp
Assigning Wood Stress Grade
Fahey et al. 1991
Examples of MSR Wood
Small branches,
More mature wood
Large branches,
More juvenile wood
Less High
Quality
Lumber
More High
Quality
Lumber
Expected Benefits
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Translated observed effects into dollar values
Lumber prices from Western Wood Products Association
Assumed a green, surfaced 2 x 4
Estimated some prices with a quadratic function
Stand could be merchandized better
Used the Columbia River Scaling Guide tables
Given in dollars per thousand board feet (MBF)
Log value increase assumed to be 0.5% per year
2100f
1.8E
1650f
1.5E
1450f
1.3E
No. 3
Economy
$585
$528
$448
$308
$179
Expected Costs
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Most costs based on the CIPS simulator defaults
Inflation set at 2% per year
Interest rate set moderately at 6%
Planting costs set at $0.60 per seedling and were
inclusive of handling and material
• Chemical release cost $60 per acre
• Logging costs $175 per MBF for a thinning, and
final harvest costs $125 per MBF
Management Implications
• An economically optimal rotation age was found
between 55 and 65 years
• In terms of net worth, lower planting densities
performed better than higher densities
• Establishment costs greatly reduced profitability
of higher density plantings
• But, in forestry we consider the biologic,
economic and strategic rotation age
• Repeated thinning can extend the period of
economic viability for a stand
• Otherwise, thinning procedure did not
appreciably modify the net worth
Management Implications
• We know what kind of silvicultural prescription
minimizes branch size and crown wood
• We know that leaves grow trees… but their
branches influence wood quality
• We can identify the right balance of wood quality
and forest growth
• But quality doesn’t really pay for a landowner?
• Is that a problem for the Northwest?
• These questions can be explored using the
Organon model chain (in ONR very easily)
• We provide the tools so you can find the answers
Analysis Pitfalls
• Lumber prices and Fahey et. al are a snapshot of
value and utilization
• Planting costs are simplified
• Not even the Oracle from Omaha could predict
log price and interest rates in the next century
• In the end, it’s a highly sensitive guess best
evaluated across a variety of parameters
• No operational constraints on thinning
The Future of Organon Quality
• The glass log idea
• Build on the existing
Organon model framework
• Develop new equations
• Knot structures
• Wood density
• Early and late wood
• Branch orientation
• Interface with a statistical
sawing simulator
• Nate gets a Ph.D.?
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Auty, 2013 (top), Briggs, 2012 (bottom)
GMUG Surveys Suggest
• Models respond to well formulated questions,
and cannot respond to ever users need
• Most of you agree wood quality is important
• Many of you want to become R gurus
• Have no fear, SAS users, divine intervention is
rated as a good option in this group
• Some of you need input and output options
Nathaniel Osborne, Ph.D. Student | [email protected] | 11/15/2013