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)

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

Imputation Model Growth Model Volume Model Quality Model The Organon Model Chain Individual-tree Spatially 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 Diagram Sample, Unit and Activity List Impute Missing Information Grow Trees, Quality, Volume To Specified Age Projected Tree, Quality, Sample, Flags and Figures Split up Orders by Sample and Unit Amalgamate the Orders Compute a Few Sample 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

6-ft spacing (1200) 10-ft spacing (435) 21-ft spacing (100) Lewisburg Saddle Installations

CONTPARELYRELR Thinning Treatment Initial Planting Density (trees per acre) 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*llad *jp 2 ) 1650f 1.5E 38.1*exp(0.79*llad-0.702*llad *jp f 1.3E Obtained by subtraction No *exp(3.41*llad-0.76*llad 2 )+0.003*jp 2 Economy 2.93*exp(1.10*llad *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

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 1650f 1.5E 1450f 1.3E No. 3Economy $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 | | 11/15/2013