SMC Quar ter ly News
www.standmgt.org
Stand Management Cooperative
College of Forest Resources, University of Washington
4th Quarter 2006
From the Director
As we start the new school year and 06/07 field season, we realize how rapidly the
very busy and productive summer disappeared. Progress on a number of activities is
reported in the summary of the SMC fall meeting in this issue. In addition
•
Owner Survey # 5 was sent in April. Responses from six companies have
been received and entered into a database for summarization and
comparison to earlier surveys. If you have not completed the survey we
would appreciate receiving it this fall.
•
We were able to pool funds from the SMC, Precision Forestry Cooperative,
and grants to hire a summer crew to visit installations for a variety of
measurement and sampling activities. A short article on the crew and
accomplishments appears elsewhere in this issue.
•
Four new articles were published in journals and another has been accepted.These are listed in the publications section of this issue.
Dave Briggs, SMC Director
In this issue you will also find an article by Aaron Weiskittel, Sean M. Garber, Greg
Johnson, Doug Maguire, and Robert A. Monserud titled “Development of annualized
diameter and height growth equations for Douglas-fir and western hemlock: preliminary results.” This issue also introduces Gonzalo Thienel, who is pursuing his Masters
degree under the direction of David Briggs. He is working on the AGENDA 2020
project “Non-destructive evaluation of wood quality in standing Douglas-fir trees and
logs.”
SMC FALL MEETING NOTES
inside:
SMC Fall Meeting
1
Protocol for Geo Referencing
Type IV Installations
3
Summer Field Crew
3
Development of Annualized
Diameter and Height Growth
Equations for Douglas-fir and
Western Hemlock: Preliminary
Results
4
Abstracts and Publications 10
Student Bio
11
TheSMC Fall Meeting was held on September 11-13 at the University of British
Columbia Research Forest in Haney, BC. 24 attendees arrived on the evening of the
11th for an informal social. Policy Committee Chair Gene McCaul opened the meeting
and introduced our hosts, Louise de Montigny, BC Ministry of Forests Research
Branch, and Bruce Larson, University of British Columbia. Many thanks to Megan
O’Shea and Dave Paul for organizing the program and field tour. Dave Hyink
announced that he is retiring and that this would be his last SMC meeting as the
Policy Committee representative of Weyerhaeuser Company. Attendees expressed
their thanks to Dave for his participation and support since the very inception of the
SMC.
Since the SMC began in 1985, the cumulative budget has reached $16.1 million of
which landowner members contributed 64%, institutional members 20%, and
external grants, which have been growing over the past several years, 16%. So far
$232,000 in new external grant funding has been received and other proposals are
in review.These projects support five continuing and one new graduate student. We
also held meetings of the Silviculture, Nutrition and Wood Quality Technical Advisory
Committees and the Strategic Planning Committee.
GGT/T
ype IV Installation Progress: These installations are a collaboration of the SMC,
GGT/Type
NWTIC, and USFS PNWRS Genetics Team. The remaining three of the six planned installations were planted in late February 2006. The total in-kind cost to the SMC for all six
installations was $107,507. In addition NWTIC paid $64,000 for all work associated with
producing and planting the seedlings. The in-kind credit to landowners was for fencing, site
preparation spray and pin-flagging the planting lines. The installations have been visited for
seedling survival; the average survival on all plots is 98% and the lowest survival on any single
plot is 90%. Plots on all six GGTIV installations were geo-referenced for future indexing to
remote sensing. Plots on the three installations planted in 2005 will be measured during the
06/07 field season.
Modeling Project: The fertilization response component of ORGANON has been reestimated and produces more realistic results. The hemlock growth component has also been
reestimated using a larger dataset. A Windows based version of ORGANON has been
developed and is being tested. Nick Vaughn summarized progress on the young stand model.
The process of combining and editing the SMC and RVMM data sets has been completed
and model fitting is now underway.
Wood Quality Project Repor
t: The AGENDA 2020 project “Non-destructive evaluation of
Report:
wood quality in standing Douglas-fir trees and logs” is moving forward. Acoustic testing of trees
on the five plots on each of the four Type II installations being used for the study has been
completed and selection of the 12 sample trees from each plot (240 total trees) is nearly
complete. Half of the trees will be processed into lumber and the other half into veneer. We
plan on doing the veneer phase at the Weyerhaeuser mill in Foster, OR. before the end of the
year and the lumber phase at UW’s Pack Forest with portable mill in early 2007.
The bear damage milling study is underway but was interrupted when the crew assisting with
the work was called away for fire duty. It should be wrapped up as soon as the fire season is
over. The study of wood quality in relation to composite wood products by Chris Langam
(graduate student), Dr. Vickram Yadama (Washington State University), and Eini Lowell (PNW
Research Station) has been completed. Chris has finished his PhD and publications are being
developed. An opportunity exists to use the levels of growing stock (LOGS) plots for wood
quality studies; possibilities and plans for this will be discussed at a Wood Quality TAC
meeting being planned for later this fall. If you would like to attend this meeting, please
contact Eini Lowell (elowell@fs.fed.us).
Silviculture Project Repor
t: The database update which includes the 05/06 field season was
Report:
completed and sent in mid-June. A summer crew gathered data from installations for various
projects; understory vegetation surveys, habitat assessments, pitch moth surveys, soil sampling,
stem mapping and acoustic testing of trees.
2
Nutr
ition Project Repor
t: Rob Harrison and Eric Turnblom led a discussion of new nutriNutrition
Report:
tion-fertilization trials. Rob reviewed past trials, their limitations, and the new questions that
many have expressed in recent years. Two key limitations in making progress have been
associated with clearly defining the experimental issues and realizing that the experimental
design approaches traditionally used costly large area experiments with little or no replication.
New developments in remote sensing offer opportunities to consider treatment responses
on larger operational size areas. Response-surface designs were reviewed as a means for a
more efficient way to address the nutrition-fertilization research questions. A future meeting
will be held to focus on defining research questions and research methods. If you would like
to participate, please contact Rob Harrison (robh@u.washington.edu) or Eric Turnblom
(ect@u.washington.edu).
Protocol ffor
or Geo Ref
erencing
Referencing
Type IV Installations
In 2006 the SMC field crew (Bob Gonyea, Bert Hasselberg and Precision Forestry Cooperative grad student Jacob Strunk) gathered latitude, longitude, and elevations for plot
corners and a sample of trees in all six Type IV Installations. This data will be useful in future
lidar and associated work.
The protocol for collecting this data is
as follows:
1. Sample every installation (#601606)
2. Sample every plot (#1-22)
Jacob Strunk and Bert Hasselberg geo-referencing
Donkey Creek north of Humptulips.
4.
*
3. At each plot collect latitude,
longitude, and elevation of the NE,
NW and SW corners and the 5th tree
in row 5 (Row 5, column 5 starting
from the NE corner*). Data was
collected using a Javad GPS gathering
200, one second EPOCH’s per
location.
Data was stored as files in the Javad GPS labeled SMC 601, SMC 602, etc. Each
file contained 88 “points” (4 “points” per plot x 22 plots). “Points” were numbered consecutively as collected. “Descriptions” were manually added to each
“point” (i.e.; point 601_1 description =1NE, point 601_2 description =1NW,
point 601_3 description =1SW, point 601_4 description=1R5C5 (for plot 1, tree
in Row5, column5), etc. Also added manually was “height to GPS receiver”.
Manually added data was also recorded in a field book for backup along with the
time of each point collected.
See Field Manual, Type IV
Gonzalo Thienel and Randy Collier using cover
board in a habitat assessment.
Summer Field Crew
The summer field crew consisted of UW CFR undergraduates Royce Anderson and Paul
Footen and Masters student Gonzalo Thienel. They accompanied Randy Collier to visit a
variety of installations for the following:
9
Douglas-fir pitch moth survey - 9 installations (43 plots)
9
Acoustic testing of standing trees - 4 Type II installations, 19 plots, 52 trees/plot
9
Understory vegetation surveys - 12 installations (4 Type I, 2 Type II, and 6 Type III)
9
Habitat assessments - 5 installations
9
Stem maps - 5 installations
9
Soil pits – 22 plots on 6 installations
The crew was supported by funds from the SMC, Precision Forestry Cooperative, and
external grants.
Royce Anderson gathering info
for a vegetation survey.
3
Dev
elopment of Ann
ualiz
ed Diameter and
Development
Annualiz
ualized
wth Equations for Douglas-f
ir and
Height Gro
Douglas-fir
Growth
Wester
n Hemlock: Preliminar
estern
Preliminaryy Results
Aaron Weiskittel, Sean M. Garber, Doug Maguire, Department of Forest Science, OSU,
Corvallis, Greg Johnson, Weyerhaeuser Company and Robert A. Monserud, PNW Research
Station, USDA Forest Service
Introduction
Most individual-tree based growth and yield models in the Pacific Northwest (PNW) use a
5- to 10-year time step, which can make projections for intensively managed plantations on
a shortened rotation quite difficult. Further, it is rather cumbersome to simulate the effects
of intensive silvicultural treatments such as fertilization or thinning on a time step longer
than one year given the highly dynamic nature of growth following treatment. The goal of
this project was to provide preliminary annualized individual tree diameter and height
growth equations for untreated Douglas-fir and western hemlock. In addition, a modeling
technique was used to partition out the variation in growth unexplained by attributes of
the trees and stands and an attempt was made to relate it to installation edaphic characteristics.
Methods
For this analysis, the untreated control plots from Stand Management Cooperative Type 1
(respacing silvicultural trials) and Type 3 (variable planting density) installations were used
(Table 1). The diameter and height growth equation forms of Hann et al. (2003) were
utilized:
(1)
ΔDBH = eβ10 +β11log(DBH +1)+β12DBH
2
BAL2
⎛ UCR +0.2 ⎞
+ β13log⎜⎜
+ β16 SBA + β17 ICR
⎟⎟+β14log(SI -1.37) + β15
log(DBH +5)
⎝ 1.2 ⎠
+ ε1
(2)
ΔHT= PHT*β20⎡β21eβ22CCH+(eβ23
⎢⎣
− β21eβ22CCH)e−β26(1−UCR) eβ25
CCH
2
CCH⎤
⎥⎦
+ε2
where: ΔDBH is the annual diameter growth in cm, DBH is diameter at breast height (cm),
UCR is uncompacted crown ratio estimated using the equation of Monleon et al. (2004), SI
is a 50-year site index, BAL is basal area in larger trees (m2 ha-1), SBA is stand basal area (m2
ha-1), ICR is an indicator crown ratio measurement (1 if CR wasn’t measured, 0 otherwise),
PHT is potential height growth estimated from a dominant height growth curve and tree
growth effective age (Ritchie and Hann, 1986), CCH is percent crown closure of the plot at
the tip of the subject tree, the â i’s are parameters to be estimated from the data using the
iterative method of Cao (1999), and åi ~ MVN(0, Ó). SI at 50-yr base age for Douglas-fir
was calculated by solving Bruce’s (1981) dominant height equation. The Bonner et al. (1995)
equation was used for western hemlock. For CCH estimation, the crown profile equations
of Hann (1999) and Marshall et al. (2003) for Douglas-fir and western-hemlock, respectively
were used.
4
Following model fitting, the random coefficients were extracted for the installation level
and were regressed on physiographic (longitude, latitude, elevation, slope, aspect), soil
(depth, texture, rock content, water holding capacity), and mean climate variables (temperature, precipitation, vapor pressure deficit) to identify influential factors on growth
variation. Slope and aspect were transformed using the suggestions of Stage (1976), while
soil water holding capacity was estimated as outlined in Schwalm and Ek (2004). Mean
climate variables were derived from 23-year daily weather records obtained from
DAYMET (http://www.daymet.org).
Finally, the diameter and height growth equations were coupled with the annual mortality
model of Flewelling and Monserud (2002) and used to simulate 12 to 16 years of growth
and mortality on the control plots on 12 SMC Type II installations, which were not used
during model fitting. The installations were evenly distributed through the PNW with initial
breast-height age ranging from 23.5 to 46.5 and site index varied from 29.3 to 48.0 m at
base age 50. For comparison, the SMC version of the ORegon Growth ANalysis and
projectiON (ORGANON; Hann, 2005) model was also used to simulate growth on these
plots. ORGANON uses a 5-year time step so linear interpolation was used for growth
remeasurement periods that did not cover this time step. Mean bias (observed – predicted), % bias, and mean square error (MSE) were estimated for every simulation.
Results
The models fit well and the parameter estimates were consistent with biological expectations (Tables 2, 3). A few differences between the Hann et al.’s (2003) diameter growth fits
and these presented here are apparent, namely the significance of site index for western
hemlock and, for Douglas-fir and western hemlock, the negative influence of predicted
crown ratio in contrast to their positive effect. The models were statistically improved with
the use of the multi-level mixed effects (MLME) modeling approach.
Examining the installation random effects uncovered a few interesting relationships for
diameter growth (Table 4), but were highly variable for height growth. The intercept of the
Douglas-fir diameter growth equation showed a significant trend with annual precipitation
(PRCP), elevation (ELEV), slope (%SLOPE), and aspect (Table 4). Parameter estimates
suggested diameter growth peaked on north-east facing slopes and at 220 cm of precipitation. The Douglas-fir height growth equation showed a significant relationship with slope,
aspect, and percent rock content in the soil B horizon (%ROCK.B). The parameter
estimates indicated that the asymptote of the height growth modifier was greatest on
north-west facing sites. Western hemlock diameter and height growth showed no
significant relationship with any physiographic variable.
Mean bias, percent bias, and mean square error for the three equations were within
reason and are given in Table 5. The equations fitted with MLME performed significantly
better than the maximum likelihood (ML) equations or MLME with predicted random
effects. There were some trends in the residuals using ML, while no obvious trends were
present in the MLME simulations (Figure 1). In comparison to a model with a longer time
step, the biases achieved with the equations presented in this analysis were similar in
magnitude and actually smaller than ORGANON’s.
5
Discussion
The iterative procedure of Cao (1999) used here worked well for the development of
annual diameter and height growth equations for two of the region’s primary commercial
species. Despite its complexity, it has the advantage of using data across many
remeasurement intervals without additional manipulation (such as linear interpolation) to
achieve a desired time step and constraining predicted periodic growth rates reducing error
associated with annually updating a tree list. Preliminary long-term (>12 years) simulations
with these equations indicate a significant potential for increasing the precision of growth
estimates when compared to a regional model with a longer time step. Further, they offer
the flexibility to incorporate the effects of annual climatic conditions or update an inventory
to the present, which would be rather difficult to achieve with a longer time step.
Future efforts will concentrate on refining these models, developing silvicultural treatment
modifiers for these equations, and fitting annualized crown recession and mortality functions.
Literature Cited
Bonner, G.M., De Jong, R.J., Boudewyn, P., Flewelling, J.W., 1995. A guide to the STIM growth model. In,
Information Report BC-X-353. Canadian Forest Service, Pacific Yukon Region, Victoria, BC.
Bruce, D., 1981. Consistent height-growth and growth-rate estimates for remeasured plots. Forest
Science 4, 711-725.
Cao, Q.V., 1999. Prediction of annual diameter growth and survival for individual trees from periodic
measurements. Forest Science 46, 127-131.
Flewelling, J.W., Monserud, R.A., 2002. Comparing methods for modeling tree mortality. In: Crookston,
N.L., Havis, R.N. (Eds.), Proceedings of the 2nd Forest Vegetation Simulator conference (RMRS-P25). USDA Forest Service Rocky Mountain Research Station, Fort Collins, CO, pp. 169-177.
Hann, D.W., 1999. An adjustable predictor of crown profile for stand-grown Douglas-fir trees. Forest
Science 45, 217-225.
Hann, D.W., Marshall, D.D., Hanus, M.L., 2003. Equations for predicting height-to-crown base, 5-year
diameter growth rate, 5-year height growth rate, 5-year mortality rate, and maximum sizedensity trajectory for Douglas-fir and western hemlock in the coastal region of the Pacific
Northwest. In, Research Contribution 40. Oregon State University, College of Forestry Research
Laboratory, Corvallis, OR, p. 85.
Marshall, D.D., Johnson, G.P., Hann, D.W., 2003. Crown profile equations for stand-grown western
hemlock trees in northwestern Oregon. Canadian Journal of Forest Research 33, 2059-2066.
Monleon, V.J., Azuma, D., Gedney, D., 2004. Equations for predicting uncompacted crown ratio based
on compacted crown ratio and tree attributes. Western Journal of Applied Forestry 9, 260-267.
Ritchie, M.W., Hann, D.W., 1986. Development of a tree height growth model for Douglas-fir. Forest
Ecology and Management 15, 135-145.
6
Table 1. Description of the diameter and height growth rate data sets for Douglas-fir and western
hemlock. Definition of variables are: DBH is diameter at breast height (cm), UCR is uncompacted crown
ratio, BAL is basal area in larger trees (m2 ha-1), SBA is stand basal area (m2 ha-1), BH AGE is mean breastheight stand age, and SI is site index.
Douglas-fir
Variable
Diameter growth
Mean
Range
Individual Tree
Western hemlock
Height growth
Mean
Range
N = 57,074
Diameter growth
Mean
Range
N = 20,709
Height growth
Mean
Range
N = 11,479
N = 8,077
DBH (cm)
10.7
0.1 – 97.5
14.7
0.2 – 97.5
6.2
0.1 – 35.1
5.4
0.1 – 33.8
UCR
0.75
0.10 – 0.99
0.77
0.1 – 0.99
0.97
0.47 – 0.99
0.78
0.1 – 0.99
10.4
0.0 – 178.0
11.94
0.0 – 178.0
3.9
0.0 – 36.9
2.98
0.0 – 36.9
2
-1
BAL (m ha )
Individual Plot
N = 356
N = 345
N= 7
N=7
SBA (m2 ha-1)
16.8
4.0 – 178.2
21.46
4.0 178.20
6.2
2.0 – 37.0
6.2
2.0 – 37.0
BH AGE
12.3
0.1 – 60.4
10.8
0.1 – 60.4
15.4
6.1 – 33.6
15.4
6.1 – 33.6
SI (m at 50-yr)
40.1
16.6 – 60.3
39.7
16.6 – 60.3
36.1
27.2 – 39.3
36.1
27.2 – 39.3
length of
growing period
(years)
4.7
1.0 – 12.0
3.8
1.0 – 12.0
2.5
2.0 – 4.0
2.2
2.0 – 4.0
Table 2. Parameters and asymptotic standard errors for predicting the diameter growth rate (equation
[1]) of untreated Douglas-fir and western hemlock fitted using maximum likelihood and multi-level mixed
effects. R2, residual standard error, and AIC value for each model are also given.
Parameter/
Standard error
β 10
SE(β10)
β 11
SE(β11)
β 12
SE(β12)
β 13
SE(β13)
β 14
SE(β14)
β 15
SE(β15)
β 16
SE(β16)
β 17
SE(β17)
R2
Residual standard
error
AIC
Maximum
Likelihood
-3.6865
(0.0392)
0.2121
(0.0081)
-0.00046
(0.00002)
0.1878
(0.0202)
1.0778
(0.0098)
-0.0069
(0.00007)
-0.1257
(0.0028)
0.0145
(0.0043)
0.88
Douglas-fir
Multi-level mixed
effects
-2.9553
(0.4009)
0.4222
(0.0063)
-0.00005
(0.00002)
0.3488
(0.0219)
0.8932
(0.1052)
-0.0036
(0.00005)
-0.2873
(0.0041)
0.0412
(0.0041)
0.97
Western hemlock
Maximum
Multi-level mixed
Likelihood
effects
-3.0984
-2.3867
(0.0479)
(0.8991)
0.4617
0.5818
(0.0059)
(0.0076)
-0.00032
-0.00041
(0.00001)
(0.00001)
4.2445
1.7334
(0.0767)
(0.0650)
0.9399
0.7173
(0.0144)
(0.2507)
-0.0010
-0.0009
(0.00003)
(0.00003)
-0.2488
-0.3074
(0.0021)
(0.0033)
0.0099
-0.0452
(0.0041)
(0.0053)
0.86
0.95
2.58
1.24
0.62
0.40
139,083.7
127,780.6
70,973
46,133
7
Table 3. Parameters and asymptotic standard errors for predicting the height growth rate
(equation [2]) of untreated Douglas-fir and red alder fitted using maximum likelihood and
multi-level mixed effects. R2, residual standard error, and AIC value for each model are also
given.
Parameter/
Standard error
β 20
SE(β20)
β 21
SE(β21)
β 22
SE(β22)
β 23
SE(β23)
β 24
SE(β24)
β 25
SE(β25)
R2
Residual standard
error
AIC
Maximum
Likelihood
1.5673
(0.0065)
0.2928
(0.0085)
-0.00047
(0.00003)
-0.0021
(0.00021)
6.0425
(0.2013)
0.0569
(0.0089)
0.85
Douglas-fir
Multi-level mixed
effects
1.3020
(0.1643)
0.4794
(0.0388)
-0.0018
(0.0008)
0.0187
(0.0018)
2.7961
(0.3484)
0.1126
(0.0126)
0.94
Western hemlock
Maximum
Multi-level mixed
Likelihood
effects
1.0033
0.9880
(0.0060)
(0.0282)
0.5722
0.5501
(0.0298)
(0.0238)
-0.0125
-0.0130
(0.0019)
(0.0016)
-0.0015
-0.0040
(0.0002)
(0.0016)
5.2812
6.4301
(0.4440)
(0.4793)
0.0
0.0
(NA)
(NA)
0.53
0.62
1.04
0.77
0.82
0.69
52,578.9
39,812.9
55,832.9
50,019.5
Table 4. Model, equation form, R2, and root mean square error (RMSE) for model predicting
the influence of physiographic features on the random effects of each model. All parameter
estimates were significant at á = 0.05.
Model
Douglas-fir
diameter growth
Douglas-fir height
growth
8
Equation Form
-26.6559 + 0.3792*ln(ELEV) + 0.4470*ASP22
– 0.0260*PRCP + 5.6702*ln(PRCP)
0.0301 + 0.0983*ASP1 – 0.0018*%ROCK.B
R2
RMSE
0.36
0.51
0.07
0.14
Table 5. Mean bias (observed – predicted), percent bias, and mean square error (MSE) for
predicted and observed diameter at breast height (DBH; cm) and height (HT; m) after 12 to 16
years of simulation on twelve Stand Management Cooperative (SMC) planted control plots
using the maximum likelihood (ML) and multi-level mixed effects (MLME) equations developed
in this analysis as well as the ORGANON growth model, which uses a 5-year time step. Initial
breast height age of the plots was between 23.5 and 46.5 years, while site index ranged from
29.3 to 48.0 m at base age 50.
DBH (cm; n = 1767)
HT (m; n = 472)
Model
Mean
bias
Mean square
error
% bias
Mean
bias
Mean square
error
% bias
ML
1.6479
2.4881
6.1035
1.2157
1.7256
4.0544
MLME
0.1102
2.1665
0.4508
-0.1993
1.3567
1.1695
MLME with
predicted random
effects
1.2199
3.2797
5.1555
0.7156
2.0154
2.0503
ORGANON
-1.7883
2.6229
-7.0704
-1.4959
2.1820
-5.6759
Parameter/
Standard error
β 20
SE(β20)
β 21
SE(β21)
β 22
SE(β22)
β 23
SE(β23)
β 24
SE(β24)
β 25
SE(β25)
R2
Residual standard
error
AIC
Maximum
Likelihood
1.5673
(0.0065)
0.2928
(0.0085)
-0.00047
(0.00003)
-0.0021
(0.00021)
6.0425
(0.2013)
0.0569
(0.0089)
0.85
Douglas-fir
Multi-level mixed
effects
1.3020
(0.1643)
0.4794
(0.0388)
-0.0018
(0.0008)
0.0187
(0.0018)
2.7961
(0.3484)
0.1126
(0.0126)
0.94
Western hemlock
Maximum
Multi-level mixed
Likelihood
effects
1.0033
0.9880
(0.0060)
(0.0282)
0.5722
0.5501
(0.0298)
(0.0238)
-0.0125
-0.0130
(0.0019)
(0.0016)
-0.0015
-0.0040
(0.0002)
(0.0016)
5.2812
6.4301
(0.4440)
(0.4793)
0.0
0.0
(NA)
(NA)
0.53
0.62
1.04
0.77
0.82
0.69
52,578.9
39,812.9
55,832.9
50,019.5
Figure 1. Bias (observed – predicted) over observed diameter at breast height (DBH; cm)
and total height (HT; m) after 12- 16 years of simulation with the diameter and height
growth equations fitted using maximum likelihood (ML; b, d) and multi-level mixed effects
(MLME; a, c) on 12 Stand Management Cooperative installations not used during the fitting
process.
9
Abstr
acts and Pub
lications
Abstracts
Publications
Dave Cown. Understanding and Managing Wood Quality for Improving Product Value in New
Zealand. New Zealand Journal of Forestry Science 35(2/3): 205–220 (2005).
ABSTRACT
CT: Pinus radiata D. Don comprises about 90% of New Zealand’s plantation forests.
ABSTRA
CT
Management practices evolved rapidly during the twentieth century, and are regarded as advanced in
terms of the application of sound scientific and economic principles. However, since the 1970s, forest
managers in New Zealand have become more aware of the impacts of genetic selection for growth
and stem form, and the adoption of more aggressive silvicultural techniques, on the nature of the
resource.These trends have resulted in a significant reduction in rotation lengths from more than 40
years to around 25 years. Growing space, tree age, and geographic location create very pronounced
patterns of wood property development and, while growth rates can be impressive, some of the
resulting wood characteristics are somewhat limiting for demanding end uses. Scientific studies over
the past 20 years or so have defined the important wood characteristics (knot size and distribution,
resin pockets, intra-ring checking, density, spiral grain, microfibril angle) that affect product appearance,
stiffness, and stability. Two distinct approaches have been adopted to improve the plantation resource:
(1) Identifying and managing variability in the forest
(2) Breeding to manipulate specific characteristics
Value recovery from harvesting is in rapid change from a system based on volume to one based on
quality. There is now a strong emphasis on tools for log and lumber segregation, and reliable methods
are available for assessing stiffness at all stages from forest to lumber. For the immediate future,
traditional forest inventory methods are being enhanced by the inclusion of wood property information such as wood density and predicted stiffness. Acoustic tools in particular have become common
for standing tree and log stiffness assessment and a similar approach is being used for lumber and
veneer grading; spectroscopic tools are also under development. Tree breeders are actively selecting
material to improve future generations, and fortunately the heritabilities of wood properties are
generally high. However, many of these features are costly to evaluate on a routine basis and the
search is on for more sophisticated tools to assess performance capability directly. The next challenge
is to develop similar cost-effective techniques for predicting product stability. Faster progress will be
made when wood processors reward growers for quality wood.
Mauricio Acuna and Murphy, Glen, Geospatial and Within Tree Variation of Wood Density and
Spiral in Douglas-fir. Forest Products Journal. 56(4):81-85.
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ABSTRA
CT
ABSTRACT
CT: In many parts of the world, log markets are becoming increasingly competitive and
complex. Buyers are demanding, and suppliers are offering, logs that have been cut for very specific
end-uses and which may be specified in terms of internal as well as external properties. Optimally
matching logs to markets requires good measurements and/or predictions of the wood properties
in each stem. This information could be used either at the planning stage or in on-board computers
installed in harvesters to enhance bucking and sorting. To assess the geospatial and within-tree
variation in wood density and spiral grain in Douglas-fir stems, over 400 wood disks were collected
from 17 sites in the Cascade and Coastal Ranges of Oregon, Sites were selected from a range of
elevations and aspects. Trees selected at each of the sites were of a similar age (28 to 57 yr) and
average size (20 cm to 54 cm diameter at breast height). Disks came from different vertical
positions in each tree. No statistically significant relationship between wood density and either
elevation or aspect was found. There was evidence of a weak negative association between wood
density and the height in the tree where the samples were removed. No statistically significant
relationship between height, elevation, or aspect was observed for spiral grain.
NEW PUBLCATIONS:
Amoroso, M.M. and E.C. Turnblom. 2006 Comparing productivity of pure and mixed Douglas-fir and
western hemlock plantations in the Pacific Northwest. Can. J. For. Res. 36(6):1484-1496.
Amoroso, M.M. and E.C. Turnblom. 2006. On the effects of tree crop rotation: Red alder following
alder or Douglas-fir; Douglas-fir following fir or alder. IN: Proceedings. “Red alder: A state of
knowledge.” International symposium on red alder held at University of Washington Center for
Urban Horticulture in Seattle, WA 23 – 25 Mar 2005. USDA Forest Service, Pacific Northwest
Res. Station, Gen. Tech. Rep. PNW-GTR-669 p. 115 – 121.
Briggs, D.G., E.C. Turnblom, B.B. Bare. 2005. Non-destructive Methods and Process Capability Analysis
to Assess Conformance of Douglas-fir Stands to Customer Quality Specifications. New Zealand
Journal of Forestry Science. 35(2/3):170-188.
Strahm, B.D., and R.B. Harrison. 2006. Nitrate Sorption in a Variable-Charge Forest Soil of the Pacific
Northwest. Soil Science. 171:313-321.
Li, Y., E.C. Turnblom, D.G. Briggs. (accepted) Effects of Density Control and Fertilization on Growth and
Yield of Young Douglas-fir Plantations in the Pacific Northwest. Can. J. For. Res.
STUDENT BIO
Gonzalo Thienel, Masters in Science, University of
Washington, College of Forest Resources
My name is Gonzalo Thienel, currently I just started a Masters in
Science in the College of Forest Resources. I am working as a
Research assistant under advice of Professor David Briggs, who I met
in the winter of 2005 through an internship.
I graduated as a Wood Engineering in March of 2006 from the
Gonzalo Thienel working on the
2006 SMC summer crew
Universidad Austral de Chile. The area in which I am interested in is
the non-destructive evaluations of wood in standing Douglas-fir trees and logs and also any theme
related with wood technology.
I am really happy to be living in this beautiful city (that looks pretty much like “Valdivia”, my city in
Chile) and to be attending such a prestigious University.
In my spare time, I enjoy to do any kind of sport, but especially soccer, basketball and tennis. I also
enjoy spending quality time, cooking, jogging, reading and watching “American” television with my
girlfriend (Emily) and her wonderful family. My new favorite past time is watching any kind of Husky
game…Go Dawgs!
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Upcoming Meetings and Ev
ents
Events
No
vice and Agenda 2020 Conf
erence on Sustainab
le Forest Productivity Research.
Novv. 8-9, 2006, US Forest Ser
Service
Conference
Sustainable
Washington DC for more information visit:. http://www.agenda2020.org/
No
or Fire Ecology
national Fire Ecology and Management Congress. Town
Novv. 13-17, 2006, The Association ffor
Ecology,, Third Inter
International
and Country Resort & Convention Center, 500 Hotel Circle North, San Diego, CA. For more information visit: http://
emmps.wsu.edu/firecongress/
um (ILMF) Symposium. Baltimore, MD. For more information visit: http:/
Feb 12-13, 2007, The Inter
national LID
International
LIDAR
Forum
AR For
/www.lidarmap.org/ilmf2007.html
College of Forest Resources
University of Washington
Box 352100
Seattle, WA 98195
9