Modeling the Effects of Silvicultural Regimes on Douglas-fir

Crown Morphology and Related Wood Quality Attributes

N. Osborne, D. Maguire and D. HannOregon State University, Forest Engineering Department

Center for Intensive Planted-Forest Silviculture (CIPS)

• 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

IUFRO Meeting in France

• 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 System

ImputationModel

GrowthModel

VolumeModel

QualityModel

The Organon Model Chain

Individual-treeSpatially implicit

Crown ratio, total tree height etc.

• 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

Not Just Quantity, but Quality!

Josza and Middleton 1994

Organon in R Process DiagramSample, Unit and

Activity List

Impute Missing Information

Grow Trees,Quality, Volume To Specified Age

Projected Tree, Quality, Sample, Flags and Figures

Split up Orders bySample and Unit

Amalgamate the Orders

Compute a FewSample Level Attributes

• 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

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

Silvicultural Effects on Quality

Different initial spacings

• 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

Experimental Design

• 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

Silvicultural Treatments

• 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)

Simulation Dataset

Lewisburg Saddle Installations

Lewisburg Saddle Installations

100 1200

300

680

6-ft spacing (1200)

10-ft spacing (435)

21-ft spacing (100)

Lewisburg Saddle Installations

200

300

435

680

1200

CON TPA RELY RELRThinning Treatment

Initi

al P

lanti

ng D

ensi

ty(t

rees

per

acr

e)100

• 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

Merchandizing Specifications

• 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

Assigning Wood Stress Grade

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 0.93*exp(3.41*llad-0.76*llad2)+0.003*jp2

Economy 2.93*exp(1.10*llad-0.0106*jp

Assigning Wood Stress GradeFahey et al. 1991

Examples of MSR Wood

Small branches,More mature wood

Large branches,More juvenile wood

Less High QualityLumber

More High QualityLumber

• 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

Expected Benefits

2100f 1.8E

1650f1.5E

1450f 1.3E No. 3 Economy

$585 $528 $448 $308 $179

• 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

Expected Costs

• 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

Management Implications

• 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

Analysis Pitfalls

• 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.?

The Future of Organon Quality

Auty, 2013 (top), Briggs, 2012 (bottom)

• 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

GMUG Surveys Suggest

Nathaniel Osborne, Ph.D. Student | nathaniel.osborne@oregonstate.edu | 11/15/2013