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 • • • • • • • 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! • • • • • • • 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 • • • • • • • 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 • • • • • • • 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 • • • • • • 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 • • • • • • • 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 • • • • • • • • 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 • • • • 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.? S T A T S A W 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 | nathaniel.osborne@oregonstate.edu | 11/15/2013