Strength and Stiffness 

Assessment of 

Standing Trees Using a 

Nondestructive Stress 

Wave Technique 

Xiping Wang 

Robert J. Ross 

Michael McClellan 

R. James Barbour 

John R. Erickson 

John W. Forsman 

Gary D. McGinnis 

United States

Department of 

Agriculture 

Forest Service 

Forest 

Products 

Laboratory 

Research 

Paper 

FPL−RP−585
Abstract 

Nature’s engineering of wood through genetics, stand conditions, and environment creates wide variability in wood as a 

material, which in turn introduces difficulties in wood processing and utilization. Manufacturers sometimes find it difficult to consistently process wood into quality products because of its wide range of properties. The primary objective 

of this study was to investigate the usefulness of a stress 

wave technique for evaluating wood strength and stiffness of 

young-growth western hemlock and Sitka spruce in standing 

trees. A secondary objective was to determine if the effects 

of silvicultural practices on wood quality can be identified 

using this technique. Stress wave measurements were conducted on 168 young-growth western hemlock and Sitka 

spruce trees. After in situ measurements, a 2-ft- (0.61-m-) 

long bole section in the test span was taken from 56 felled 

trees to obtain small, clear wood specimens. Stress wave and 

static bending tests were then performed on these specimens 

to determine strength and stiffness. Results of this study 

indicate that in situ stress wave measurements could provide 

relatively accurate and reliable information that would 

enable nondestructive evaluation of wood properties in 

standing trees. 

June 2000 

Wang, Xiping; Ross, Robert J.; McClellan, Michael; Barbour, R. James; 

Erickson, John R.; Forsman, John W.; McGinnis, Gary D. 2000. Strength 

and stiffness assessment of standing trees using a nondestructive stress 

wave technique. Res. Pap. FPL–RP–585. Madison, WI: U.S. Department of 

Agriculture, Forest Service, Forest Products Laboratory. 9 p. 

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The mean values of stress wave speed and dynamic modulus 

of elasticity for trees were in good agreement with those 

determined from small, clear wood specimens. Statistical 

regression analyses revealed strong relationships between 

stress wave properties of trees and static bending properties 

of small, clear wood specimens obtained from the trees. 

Regression models showed statistical significance at the 0.01 

confidence level. Results of this study also demonstrate that 

the effect of silvicultural practices on wood properties can be 

identified with the stress wave properties of trees. This indicates that this nondestructive stress wave technique can be 

used to track property changes in trees and help determine 

how forests could be managed to meet desired wood and 

fiber qualities. 

Keywords: nondestructive evaluation, standing trees, 

stress wave, wood strength, wood stiffness 

Contents 

 Page

Introduction............................................................................1

Fundamental Hypothesis........................................................2

Materials and Methods...........................................................2

In situ Evaluation...............................................................2

Laboratory Evaluation .......................................................3

Results and Discussion...........................................................3

Physical Characteristics .....................................................3

Stress Wave Properties ......................................................4

Static Bending Properties...................................................5

Stress Wave and Static Bending Relationship ...................5

Silvicultural Practices ........................................................6

Conclusions............................................................................8

References..............................................................................9
Strength and Stiffness Assessment of 

Standing Trees Using a Nondestructive 

Stress Wave Technique 

Xiping Wang, Research Scientist

Robert J. Ross, Project Leader

Forest Products Laboratory, Madison, Wisconsin 

Michael McClellan, Team Leader

Pacific Northwest Research Station, Juneau Forestry Sciences Laboratory, Juneau, Alaska

R. James Barbour, Team Leader

Pacific Northwest Research Station, Portland Forestry Sciences Laboratory, Portland, Oregon

John R. Erickson, Research Scientist

John W. Forsman, Assistant Research Scientist

Gary D. McGinnis, Professor

School of Forestry and Wood Products, Michigan Technological University, Houghton, Michigan

Introduction 

Our forests are an extremely valuable resource. In addition 

to wildlife habitat and aesthetic and recreational purposes, 

forests serve as a renewable source of raw material for an 

ever-increasing list of wood and fiber products. Nature’s 

engineering of wood through genetics, weather, and environment creates wide variability in wood as a material, which 

in turn introduces numerous difficulties in wood processing 

and utilization. Manufacturers sometimes argue that wood is 

difficult to consistently process into quality products because 

of the wide range of properties in this raw material. Users of 

wood products can be equally frustrated with the performance variability found in finished products. 

Nondestructive evaluation (NDE) technology has contributed 

considerably toward eliminating these frustrations. In the 

forest products industry, NDE technology has been developed and is now used in structural product grading programs 

that result in engineered material with well-defined performance characteristics. Currently, there is a strong interest in 

developing and using new, cost-effective NDE technology to 

evaluate wood quality in standing trees. One NDE technique, 

which uses stress wave propagation characteristics, has received considerable attention. Stress-wave-based NDE techniques have been investigated extensively during the past few 

decades and have shown promise for predicting the mechanical properties of wood materials. Several wood and woodbased materials, including small, clear wood specimens, 

lumber, veneer, and wood-based composites, have been 

investigated. Recent research has focused on determining 

whether stress wave techniques could be used to determine 

the quality of logs. Several studies have shown a good relationship (R2

 = 0.44 to 0.89) between the stress-wave-based 

modulus of elasticity (MOE) of logs and the static MOE of 

lumber cut from logs (Aratake and others 1992, Aratake and 

Arima 1994, Arima and others 1990, Koizumi and others 

1997a,b, Ross and others 1997, Sandoz and Lorin 1994). 

Although research efforts have paved the way for the successful use of NDE with various wood materials, little effort 

has been extended to develop NDE techniques for use in 

grading or sorting trees for structural quality. Existing tree 

grading procedures in the United States consist of only visual 

assessments of tree quality (Green and McDonald 1998). 

These procedures do not incorporate MOE estimates of the 

wood in a tree. It is questionable whether the visual grading 

procedures currently used for trees adequately assess the 

potential quality of structural products to be manufactured 

from them, especially those in which MOE is of primary 

concern. It is expected that relating the MOE of wood in 

trees to lumber MOE holds great promise for improving the 

ability to select mature trees that have superior potential for 

the production of structural products. Considerable savings in 

material and processing costs could be realized if nondestructive tree sorting technology, based on anticipated final product quality, can be achieved. The addition of NDE techniques 

to visual assessment procedures could also ease industrial 

adaptation to a changing resource base that may result from 

increasing emphasis on ecological forest management. 
2 

The primary objective of this study was to investigate the 

usefulness of a stress wave technique for evaluating wood 

strength and stiffness of young-growth western hemlock and 

Sitka spruce in standing trees. A secondary objective was to 

examine whether the effect of silvicultural practices on wood 

quality can be identified using this technique.

Fundamental Hypothesis 

Stress wave propagation in wood is a dynamic process that is 

internally related to the physical and mechanical properties 

of wood. Several different types of waves can propagate in 

wood structures, such as longitudinal waves, shear waves, 

and surface (Rayleigh) waves. Of these waves, longitudinal 

waves travel fastest and are the most commonly used to 

evaluate wood properties. An in-depth examination of using 

longitudinal stress wave NDE technology with wood products is included in Ross and Pellerin (1994). 

Two fundamental material properties are measured with 

longitudinal stress wave techniques: energy storage and 

energy dissipation. Energy storage is manifested as the speed 

at which a wave travels in a material. In contrast, the rate at 

which a wave attenuates is an indication of energy dissipation. Jayne (1959) hypothesized that these properties are 

controlled by the same mechanisms that determine the static 

behavior of such material. As a consequence, useful mathematical relationships between these properties and static 

elastic and strength behaviors should be attainable through 

statistical regression analysis. 

This fundamental hypothesis has been successfully verified 

on clear wood, lumber products, wood-based composites, 

and logs using various stress wave techniques (Jayne 1959, 

Kaiserlik and Pellerin 1977, Pellerin 1965, Ross and Pellerin 

1988, Ross and others 1997). However, the validity of this 

hypothesis on standing trees has not been tested. Compared 

with finished wood products, standing trees tend to have 

variable external and boundary conditions that greatly limit 

the application of stress wave techniques. Current stress 

wave methods for wood property evaluation are limited to 

wood members with a simple boundary condition, where one 

end of the material (in longitudinal direction) is usually 

accessible. Therefore, these methods are not adaptable to 

trees. In this study, we used a newly developed approach to 

conduct stress wave testing in standing trees (Wang and 

others, in press). A stress wave was induced into the tree in 

such a manner that it flowed primarily along the stem of the 

tree. We hypothesized that the characteristics of the resulting 

wave would be related to the mechanical properties of wood 

in the tree. 

Materials and Methods 

The study sites selected were from the permanent plots of a 

stand density study, which are distributed across southeast 

Alaska in 59 installations. Trees, 84 western hemlock and 84 

Sitka spruce (168 total), were selected from seven different 

sites. The stands were roughly 15, 20, 25, and 45 years old at 

the time of precommercial thinning and covered an unthinned 

control plot and three other plots that had received light, 

medium, or heavy thinning. These thinning treatments were 

performed to simulate a range of forest management practices. The ages of the stands ranged from 38 to 70 years old. 

From each plot, three western hemlock and three Sitka 

spruce trees that had diameters close to quadratic mean 

diameters were sampled. In situ stress wave testing was 

conducted on all selected trees. After field tests, 56 trees, one 

for each species in every thinning plot, were felled. A 2-ft- 

(0.61-m-) long bole section in the test span was cut from each 

felled tree, wrapped in plastic, and shipped to the Institute of 

Wood Research at Michigan Technological University 

(MTU) in Houghton, Michigan. The sections were then cut 

into small, clear specimens for further stress wave and 

destructive evaluation. 

In situ Evaluation 

A surface-attaching method was used to conduct in situ stress 

wave measurements in this study. The experimental setup 

consisted of two accelerometers, two spikes, a hand-held 

hammer, and a portable digital oscilloscope (Fig. 1). Two 

spikes were imbedded in the tree trunk at about 45° to the 

trunk surface, one spike at each end of the section to be 

assessed. Accelerometers were mounted on the spikes using 

two specially designed clamps. 

A stress wave was introduced into the tree in the longitudinal 

direction by impacting the lower spike with the hand-held 

hammer. The resulting signals were received by start and 

stop accelerometers and recorded on an oscilloscope. 

2-ft- (0.6-m-) long 

section 

Oscilloscope 

L 

Standing tree

Accelerometer

Figure 1—Experimental setup used in field test 

(L = test span). 
3 

Figure 2 shows typical stress waveforms observed for the 

trees. The stress wave transmission time was determined by 

locating the two leading edges of these waveforms. Stress 

wave speed (SWS) was then calculated by dividing the test 

span L by the measured stress wave transmission time t. 

Dynamic modulus of elasticity (MOEd) was determined using 

a one-dimensional wave equation (MOEd = SWS2

!, where !

is wood density). A span of 4 ft (1.22 m) was found to produce good readings and rapid measurements. Therefore, this 

span was used for all tree testing. The in situ stress wave tests 

were approximately centered across the 2-ft (0.61-m) section 

previously described. 

Laboratory Evaluation 

After completion of in situ stress wave testing on the trees, 

the 56 bole sections cut from felled trees were shipped to 

MTU. All sections were still in a green state upon arrival. 

Eight 1- by 1- by 16-in. (25- by 25- by 406-mm) small, clear 

wood specimens were then cut from each section for additional stress wave and destructive evaluation of wood 

strength (MOR) and stiffness (MOE) (Fig. 3). For some 

sections, eight specimens were not obtained due to the small 

diameter of the bole section. In this case, two- to sevenspecimens were cut from the bole section. 

An experimental technique reported by Ross and others 

(1994) was used to obtain stress wave properties from the 

specimens. Static bending tests (destructive) were then performed on these specimens with a SATEC Universal Testing 

Machine (Satec Systems, Inc., Grove City, Pennsylvania). 

These tests were conducted according to ASTM D 143 

(ASTM 1988), with the exception that a loading rate of 

0.15 in/min (3.81 mm/min) was used rather than 0.05 in/min 

(1.27 mm/min) because of the large number of specimens 

and lack of available machine time. An average value from 

all eight (or fewer) specimens was assumed to be the average 

property of the section and was used for comparison with the 

MOE values obtained from the stress wave measurements on 

the standing trees. 

After arriving at MTU, each 2-ft (0.61-m) section was 

weighed with a platform scale. Density was determined from 

the bulk weight and volume of the sections. This density and 

the SWS obtained from the field were used to determine 

MOEd of the standing trees. The green density of the small, 

clear wood specimens obtained from bole sections was also 

determined and used in stress wave evaluation of the specimens. Following each static bending test, a 1- by 1- by 1-in. 

(25- by 25- by 25-mm) sample was immediately cut, near the 

failure, from each specimen. Moisture content (MC) and dry 

density–specific gravity were then determined by the ovendry 

method. 

Results and Discussion 

Physical Characteristics 

Physical characteristics of the stands and destructively sampled trees are given in Table 1. The diameter at breast height 

of trees ranged from 3.7 to 14.8 in. (94 to 375 mm) for 

western hemlock and 3.2 to 21 in. (82 to 533 mm) for Sitka 

spruce. The tree heights varied from 37.1 to 98.4 ft (11.3 to 

30.0 m) for western hemlock and 34.4 to 131.2 ft (10.5 to 

40.0 m) for Sitka spruce. The average MC of western hemlock was 78.1% for heartwood and 132.9% for sapwood. The 

average MC for Sitka spruce was 59.2% for heartwood and 

156.4% for sapwood. Note that for both species, the MC of 

sapwood was much greater than that of heartwood. Specific 

gravity ranged from 0.64 to 0.96 for western hemlock and 

from 0.61 to 0. 89 for Sitka spruce. 

The effect of bark on stress wave propagation needs to be 

accounted for in the procedures to conduct in situ stress wave 

tests. The thickness of the bark may change with location 

along the stem. For both western hemlock and Sitka spruce, 

Figure 2—Typical stress waveforms observed in 

a field test. 

Figure 3—Cutting pattern for small, clear wood 

specimens. 

L

1 

2 

3 

5 

7 

6 

8 

4 
4 

thickness of the bark at breast height ranged from 0.16 to 

0.28 in. (4 to 7 mm). In the in situ stress wave measurements, 

the spikes used to mount the accelerometers were pounded 

into the trunk about 0.75 to 1.25 in. (19 to 32 mm), which 

was deep enough to go through the bark. We believe that this 

procedure eliminated or minimized the effect of bark on 

stress wave measurement. 

Stress Wave Properties 

Stress wave properties obtained from trees and small, clear 

specimens are tabulated in Table 2. In trees, the measured 

SWS ranged from 9,016 to 13,698 ft/s (2,748 to 4,175 m/s) 

for western hemlock and 9,787 to 13,858 ft/s (2,983 to 

4,224 m/s) for Sitka spruce. The average value for Sitka 

spruce was about 5% greater than that for western hemlock. 

In the specimens, the measured SWS ranged from 8,241 to 

12,461 ft/s (2,512 to 3,798 m/s) for western hemlock and 

8,714 to 13,215 ft/s (2,656 to 4, 028 m/s) for Sitka spruce. 

The average value for Sitka spruce was about 6% greater 

than that for western hemlock. For both species, the average 

SWS measured in trees was very close to that measured in 

the small, clear specimens. We observed that the average 

speed in trees was only 2.5% greater than that in small, clear 

samples for western hemlock and only 1.2 % greater for 

Sitka spruce. Statistical analyses indicated no significant 

difference between the mean SWS in trees and that in small, 

clear specimens. 

Table 1—Physical characteristics of stands and destructively sampled trees 

Western hemlockb Sitka spruceb

 Moisture content (%) Moisture content (%) 

Site Plot 

Thinning 

treatmenta

Stand 

age 

(years) 

DBH 

(in.) 

Height 

(ft) 

SG 

(green) 

Heartwood Sapwood DBH 

(in.) 

Height 

(ft) 

SG 

(green) 

Heartwood Sapwood 

Harris River 1071 Control 38 6.9 65.9 0.72 43.2 90.8 9.9 73.5 0.76 67.8 147.1 

 1050 Light 8.9 71.5 0.74 88.9 108.0 10.4 77.7 0.73 42.9 173.9 

 1060 Medium 11.0 65.0 0.83 85.1 141.6 14.0 73.2 0.74 44.1 181.3 

 1080 Heavy 10.0 62.1 0.77 90.4 146.6 16.6 80.7 0.71 40.1 178.9 

Thorne River 24CT Control 70 9.6 81.4 0.68 36.6 95.1 17.7 138.5 0.71 56.4 98.5 

 1910 Light 11.6 97.3 0.75 49.8 86.7 19.7 124.3 0.70 45.2 93.4 

 1890 Medium 12.2 88.3 0.72 34.4 129.6 18.7 127.6 0.68 65.8 107.4 

 1900 Heavy 14.8 105.0 0.64 53.8 138.9 21.0 131.2 0.67 55.5 182.4 

Alder Creek 1730 Control 63 9.1 96.5 0.80 51.3 89.2 12.2 105.3 0.77 78.1 167.5 

 1740 Light 10.6 93.2 0.76 44.1 105.7 13.7 104.7 0.76 42.1 181.1 

 1760 Medium 12.7 97.6 0.75 57.7 119.1 14.6 107.6 0.76 46.4 152.1 

 1750 Heavy 13.3 106.3 0.73 59.8 157.3 16.7 107.7 0.74 84.1 181.8 

Tuxekan 1481 Control 50 8.0 72.7 0.84 41.6 137.8 11.4 96.9 0.73 59.8 126.4 

 1470 Light 8.6 83.7 0.95 91.3 106.9 13.0 99.5 0.69 60.5 188.6 

 1450 Medium 11.0 76.6 0.76 106.8 159.4 14.4 95.3 0.61 40.3 139.0 

 1460 Heavy 11.5 73.8 0.89 42.0 116.6 15.6 88.4 0.69 49.2 154.4 

Port Alice 1211 Control 42 4.1 46.2 0.91 149.6 5.4 61.6 0.82 40.4 120.0 

 1190 Light 7.6 62.7 0.85 80.9 153.6 8.9 70.1 0.74 49.6 197.1 

 1180 Medium 6.0 45.7 0.85 180.5 192.6 6.3 41.1 0.86 59.8 159.9 

 1200 Heavy 9.4 63.6 0.85 124.1 160.8 13.4 72.5 0.72 75.5 228.6 

Shrubby Island 2021 Control 49 3.9 43.0 0.80 110.3 5.6 48.5 0.79 36.2 125.7 

 2010 Light 8.0 61.8 0.87 90.4 156.3 9.2 71.3 0.74 86.4 159.3 

 2040 Medium 10.4 61.7 0.89 110.4 159.3 12.0 67.2 0.76 63.4 177.5 

 2030 Heavy 11.2 63.4 0.88 132.0 146.3 11.7 65.8 0.83 88.8 158.8 

Thomas Bay 2061 Control 38 3.7 36.9 0.93 90.6 3.2 34.5 0.89 98.4 

 2070 Light 6.9 45.3 0.89 41.4 181.7 5.6 58.1 0.86 71.1 148.2 

 2050 Medium 8.2 47.2 0.96 118.3 166.5 7.6 52.2 0.86 67.4 161.5 

 2080 Heavy 8.9 49.7 0.83 97.8 124.2 10.1 57.5 0.79 82.2 190.2 

a

Light, medium, and heavy thinning treatments correspond roughly to 8- by 8-, 12- by 12-, and 16- by 16-ft spacing. 

b

DBH, diameter at breast height of trees; SG, specific gravity; 1 in. = 25.4 mm, 1 ft = 0.3048 m. 
5 

From in situ measurements, MOEd ranged from 1.00 to 

2.02 × 106

 lb/in2 (6.89 to 13.93 GPa) for western hemlock 

and 1.01 to 1.97 × 106

 lb/in2 (6.96 to 13.58 GPa) for Sitka 

spruce. For small, clear specimens, MOEd ranged from 0.97 

to 1.89 × 106

 lb/in2 (6.69 to 13.03 GPa) for western hemlock 

and 0.95 to 1.84 × 106

 lb/in2 (6.55 to 12.68 GPa) for Sitka 

spruce. Average MOEd for Sitka spruce was 3% greater than 

that for western hemlock. For both species, the average 

MOEd determined from in situ measurements was in good 

agreement with that obtained from small, clear specimens. 

Compared with the MOEd of small, clear specimens, the 

MOEd of trees increased about 1.5% for both species. Statistical comparison analyses indicated no significant differences 

between the mean MOEd of trees and the mean MOEd of 

small, clear specimens. 

Static Bending Properties 

Results from static bending tests indicated that the static 

modulus of elasticity (MOEs) ranged from 0.60 to 

1.69 × 106

 lb/in2 (4.14 to 11.65 GPa) for western hemlock 

and 0.53 to 1.59 × 106

 lb/in2 (3.65 to 10.96 GPa) for Sitka 

spruce. The average MOEs value for western hemlock was 

about 8% greater than that for Sitka spruce. However, different results were observed in stress wave properties; that is, 

the average SWS and MOEd of hemlock were about 3% to 

6% less than those of Sitka spruce. There could be several 

reasons for this. First, the stems of many western hemlock 

trees had irregular shapes (not round) and showed much 

more variation of surface conditions and more frequent 

occurrence of wood defects (e.g., compression wood) than 

did Sitka spruce trees. This could cause measurement error in 

the in situ stress wave measurement and bulk density determination. Second, in situ stress wave measurements of this 

study were conducted on only one side of the stem. For 

western hemlock trees, as a result of variable surface 

conditions and different physical and mechanical properties 

that can occur on different sides of the stems, one measurement may not be enough to predict the global properties of 

the wood. Third, as a result of the relatively small stem diameter, the number of small, clear wood specimens cut from 

western hemlock sections ranged from two to eight, whereas 

most of the Sitka spruce sections were big enough to cut 

eight specimens. Uneven sampling between western hemlock 

and Sitka spruce could affect the estimated global properties. 

Results from static bending tests also indicated that the 

modulus of rupture (MOR) ranged from 4,660 to 10,640 

lb/in2

 (32.13 to 73.35 MPa) for western hemlock and from 

3,297 to 7,490 lb/in2

 (22.73 to 51.64 Mpa) for Sitka spruce. 

The average MOR values were 6,729 lb/in2

 (46.39 MPa) for 

western hemlock and 5,323 lb/in2

 (36.70 MPa) for Sitka 

spruce. These values agree with those from the Wood 

Handbook (Forest Products Laboratory 1999). 

Stress Wave and Static 

Bending Relationship 

We used statistical analyses to quantify the relationships of 

stress wave properties to static bending properties. Results 

obtained from various regression analyses are summarized in 

Table 3. 

Figure 4 shows the relationship of SWS measured in standing 

trees to that measured in the small, clear specimens cut from 

the trees. The SWS of the specimens was an average value 

taken from eight (or fewer) specimens obtained from each 

bole section. Analyses revealed a strong relationship between 

SWS in trees and that in small, clear specimens. The correlation coefficient (r = 0.83) was highly significant at the 0.01 

confidence level. The average SWS measured in trees was 

11,066 ft/s (3,373 m/s), which was very close to the average 

SWS of 10,800 ft/s (3,292 m/s) measured in the small, clear 

specimens. This suggests that the stress wave NDE technique 

Table 2—Stress wave and mechanical properties of western hemlock and Sitka spruce 

 Western hemlock Sitka spruce 

Propertya Mean 

Standard 

deviation Min. Max. Mean 

Standard 

deviation Min. Max. 

Tree 

SWS (ft/s) 11,066 1,147 9,016 13,698 11,575 982 9,787 13,858 

MOEd (x106

 lb/in2) 1.37 0.292 1.00 2.02 1.41 0.255 1.01 1.97 

Small, clear specimen 

SWS (ft/s) 10,801 1,099 8,241 12,461 11,437 1,070 8,714 13,215 

MOEd (x106

 lb/in2) 1.35 0.22 0.97 1.89 1.39 0.225 0.95 1.84 

MOEs (x106

 lb/in2) 1.07 0.24 0.6 1.69 0.99 0.214 0.53 1.59 

MOR (lb/in2

) 6,729 1,040.90 4,660 10,640 5,323 922.4 3,297 7,490 

a

SWS, stress wave speed; MOEd, dynamic modulus of elasticity determined by stress wave method; 

 MOEs, static modulus of elasticity determined by static bending test; MOR, modulus of rupture; 

 1 ft/s = 0.3048 m/s, 1 lb/in2

 = 6.894 kPa. 
6 

used in this study provided relatively accurate and reliable 

stress wave information, therefore enabling the prediction of 

wood properties in standing trees. 

Laboratory investigation verified that strong relationships 

existed between MOEd and static properties (MOE and 

MOR) for small, clear wood specimens. Figure 5 shows the 

relationship between MOEd and MOEs for small, clear 

specimens obtained from the trees. The correlation coefficient was 0.91 for the two species combined. The linear 

regression analyses indicated that the developed regression 

models were statistically significant at the 0.01 confidence 

level. Figure 6 shows the relationship between MOEd and 

MOR for the small, clear specimens. The correlation coefficient was slightly lower for the combined species. However, 

good relationships were observed between MOEd and MOR 

if the two species were considered separately. The correlation coefficients were found to be 0.68 for western hemlock 

and 0.69 for Sitka spruce. The developed regression models 

were statistically significant at the 0.01 confidence level. 

Relationships between MOEd of trees and MOEd and MOEs

of small, clear specimens are shown in Figures 7 and 8. 

Constants for the linear regression models and correlation 

coefficients are summarized in Table 3. Results indicate that 

good relationships existed between the MOEd of trees and 

the MOEd and MOEs of small, clear specimens cut from the 

trees. The correlation coefficient for MOEd of trees compared with MOEs of small, clear specimens was less than that 

for MOEd of trees compared with the MOEd of small, clear 

specimens. This could be attributed to the variation in static 

tests as a result of the small size of the specimen and the 

specimen cutting method. Statistical regression analyses also 

revealed different correlation coefficients for western 

hemlock and Sitka spruce (Table 3). The r values of MOEd

of trees compared with MOEs and MOEd of small, clear 

specimens for western hemlock were less than those for Sitka 

spruce. Again, this could have been caused by the western 

hemlock, uneven sampling, and relatively small size of small, 

clear specimens. We believe that improvements could be 

achieved by conducting in situ stress wave measurements on 

two sides of the stem for western hemlock trees or by using 

larger specimens (lumber, timber, or stem section) instead of 

small, clear specimens to destructively determine static 

properties. 

Figure 9 shows the relationship between MOEd of trees and 

the MOR of small, clear specimens. The MOEd of trees 

correlated reasonably well with the MOR of small, clear 

specimens. Correlation coefficients r were found to be 

0.65 for western hemlock and 0.63 for Sitka spruce. However, the r value decreased to 0.56 when the two species 

were combined. 

Silvicultural Practices 

The quality and properties of wood are generally affected by 

silvicultural practices, especially the silvicultural control of 

stand density. Some silvicultural practices not only might 

increase the biomass production of trees but also might improve the quality of the wood in trees. In this study, the effect 

of thinning treatments on both stress wave and static bending 

properties were examined. Results are summarized in 

Table 4, with MOEd (trees) and MOEs (small, clear specimens) values listed in decreasing order. The highest MOE 

values (dynamic and static) for both western hemlock and 

Sitka spruce were in the control stands (70%) and the stands 

that received light thinning (30%). Whereas, the lowest MOE 

values (dynamic and static) were observed in stands that 

received heavy (64%) and medium (32%) thinning. 

Table 3—Relationships between MOEd and mechanical properties of small, clear specimens obtained from tested treesa

 Linear regression model y = a + b x

 x: MOEd of trees x: MOEd of small, clear specimen 

Species 

Mechanical properties of 

small, clear specimenb

 

y a b rc Syx

c a b rc Syxc 

Western hemlock MOEd 0.597 0.5788 0.73 0.1604 — — — — 

 MOEs 0.6288 0.3189 0.63 0.1169 0.1751 0.6659 0.92 0.0929 

 MOR 4,360.6 1,709.09 0.65 594.89 3,816.80 2,148.47 0.68 765.46 

Sitka spruce MOEd 0.4958 0.6267 0.77 0.1359 — — — — 

 MOEs 0.394 0.4236 0.78 0.0873 0.1618 0.6217 0.91 0.0848 

 MOR 2,769.6 1,853.88 0.63 596.13 2,513.30 2,083.84 0.69 667.06 

MOEd 0.5455 0.5972 0.75 0.1462 — — — — 

MOEs 0.5355 0.3526 0.66 0.1105 0.1641 0.6447 0.91 0.096 

Western hemlock 

and Sitka spruce 

combined 

MOR 3,072.70 2,139.81 0.56 994.53 3,072.70 2,139.81 0.56 994.53 

a

Small, clear wood specimens were tested in static bending according to ASTM D143 standards (ASTM 1988). 

b

MOEd, dynamic modulus of elasticity determined by stress wave method; MOEs, static modulus of elasticity of small, 

 clear specimens; MOR, modulus of rupture of small, clear specimens. 

c

r, correlation coefficient; Syx, standard error of estimate. 
7 

Figure 4—Relationship of stress wave speed (SWS) 

measured in trees to SWS measured in small, clear 

specimens obtained from trees (1 ft/s = 0.3048 m/s). 

Figure 5—Relationship of MOEd to MOEs for small, 

clear specimens (1 lb/in2 = 6.894 kPa). 

Figure 6—Relationship of MOEd to MOR for small, 

clear specimens (1 lb/in2

 = 6.894 kPa). 

Figure 7—Relationship of MOEd of trees to MOEd of 

small, clear specimens (1 lb/in2 = 6.894 kPa). 

Figure 8—Relationship of MOEd of trees to MOEs of 

small, clear specimens (1 lb/in2

 = 6.894 kPa). 

Figure 9— Relationship of MOEd of trees to MOR of 

small, clear specimens (1 lb/in2 = 6.894 kPa). 

6

8

10

12

14

SWS in small, clear wood (x103 ft/s)

8 10 12 14 16

SWS in trees (x103 ft/s)

Western hemlock

Sitka spruce

y = 1899.2 + 0.8176x r = 0.83

2

4

6

8

12

 Western hemlock: y = 4360.6 + 1709.09x, r =0.65 

 Sitka spruce: y = 2769.6 + 1853.88x, r =0.63 

10

MOR of small, clear wood (x103 lb/in2)

0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2

MOEd of trees (x106 lb/in2)

Western hemlock

Sitka spruce

2

4

6

8

10

12

MOR of small, clear wood (x103 lb/in2) 0 0.5 1.0 1.5 2.0 2.5

MOEd of small, clear wood (x106 lb/in2)

Western hemlock

Sitka spruce

Western hemlock: y = 3816.8 + 2148.47x, r = 0.68

Sitka spruce: y = 2513.3 + 2083.84x, r = 0.69

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

MOEd of small, clear wood (x106 lb/in2)

0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2

MOEd of trees (x106 lb/in2)

Western hemlock

Sitka spruce

y = 0.546 + 0.5972 x

r = 0.75 

0.5

1.0

1.5

2.0

MOEs of small, clear wood (x106 lb/in2)

0 0.5 1.0 1.5 2.0 2.5

MOEd of small, clear wood (x106 lb/in2)

Western hemlock

Sitka spruce

y = 0.1641 + 0.6447x

r = 0.91 

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

MOEd of small, clear wood (x106 lb/in2)

0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2

MOEd of trees (x106 lb/in2)

Western hemlock

Sitka 

y x r

 = 0.536 + 0.3526 

 = 0.66
8 

This indicated that lower density stands exhibited a trend 

toward decreased stress wave and static bending properties.One limitation to this study was that only one sampled 

tree for each species was cut from each stand. Therefore, 

statistically, the obtained stress wave and static properties 

may not fully reflect wood properties for the entire stand. 

However, our results demonstrated that the effect of silvicultural practices on static bending properties of wood can be 

successfully identified by stress wave MOEd. The typical 

trends of stress wave and static bending characteristics as a 

result of thinning regimes are illustrated in Figures 10 and 

11. The stress-wave-based tree MOE follows the same trend 

with MOEs as thinning level changes. These results are encouraging and indicate that the nondestructive stress wave 

technique used in this study may be used to track wood 

property changes in trees and determine how forests could be 

managed to meet desired wood and fiber qualities. 

Conclusions 

Based on the results of this study, we conclude the following: 

1. In situ stress wave measurements provide relatively accurate and reliable stress wave information that could be used 

to assess the mechanical properties of wood in standing 

trees. Statistical regression analyses indicate that strong 

relationships exist between stress wave properties of standing trees and the strength and stiffness of small, clear 

specimens obtained from trees. 

2. Stress wave speed (SWS) measured in trees ranged from 

9,016 to 13,698 ft/s (2,748 to 4,175 m/s) for western hemlock and from 9,787 to 13,858 ft/s (2,983 to 4,224 m/s) for 

Sitka spruce. Dynamic modulus of elasticity (MOEd) of 

wood in trees ranged from 1.00 to 2.02 × 106

 lb/in2 

(6.89 to 13.93 GPa), with a mean of 1.37 × 106

 lb/in2 

(9.44 GPa)for western hemlock and 1.01 to 1.97 × 106

lb/in2

 (6.96 to 13.58 GPa), with a mean of 1.41 × 106 lb/in2

(9.72 GPa) for Sitka spruce. In this study, the mean values 

of SWS and MOEd of trees from both species are in 

agreement with those determined from small, clear 

specimens. 

3. The effect of the silvicultural practice of thinning on wood 

properties can be identified with the stress wave technique 

used in this study. As practices change, stress-wave-based 

MOEd of wood in trees basically follows the same trend as 

MOEs. Results indicate that the nondestructive stress wave 

technique used in this study may also be used to track 

wood property changes in trees and determine how forests 

could be managed to meet desired wood and fiber 

qualities. 

4. Although good correlations were observed in this study 

between stress wave properties of standing trees and static 

bending properties of small, clear specimens obtained from 

the trees, significant variability in static tests because of 

the small size of specimens and the specimen cutting 

methods did create some problems in predictive relationships. In future studies, we suggest that larger specimens 

(lumber, timber, or stem section) be used to determine 

static properties. 

Table 4—Thinning effects on stress wave and static bending propertiesa

MOE (x106 lb/in2)

b

Harris River Thorne River Alder Creek Tuxekan Port Alice Shrubby Island Thomas Bay 

MOEd MOEs MOEd MOEs MOEd MOEs MOEd MOEs MOEd MOEs MOEd MOEs MOEd MOEs

Western hemlock 

1.39, C 1.1,C 1.32, C 1.16, C 1.98, C 1.22, C 1.51, L 1.45, L 1.66, C 1.17, C 2, L 1.22, L 1.33, L 0.9, C 

1.23, M 1.09, L 1.31, M 1.15, M 1.56, L 1.16, L 1.43, C 1.12, C 1.42, L 1.15, L 1.63, C 1.15, C 1.2, M 0.9, L 

1.09, L 1.08, M 1.27, L 1.11, H 1.38, M 1.15, M 1.2, H 1.05, M 1.37, M 1.05, H 1.63, C 1.1, H 1.16, C 0.79, H 

1.07, H 0.87, H 1.1, H 0.9, L 1.14, H 0.98, H 1.07, M 0.96, H 1.36, H 0.97, M 1.57, H 1.07, M 1.04, H 0.75, M 

Sitka spruce 

1.63, C 1.12, C 1.51, C 1.11, C 1.65, L 1.06, C 1.45, C 1.09, C 1.58, C 1.23, C 1.75, C 1.21, C 1.75, L 1.24, L 

1.15, L 0.99, L 1.32, L 1.07, M 1.62, C 1.05, L 1.28, L 0.96, H 1.33, M 1.06, M 1.53, L 1.02, L 1.45, M 1.04, M 

1.1, H 0.82, H 1.22, M 1.06, L 1.42, M 1.04, M 1.26, H 0.92, L 1.25, L 1.01, L 1.52, h 0.96, M 1.27, C 0.96, H 

1.04, M 0.71, M 1.22, H 0.87, H 1.18, H 0.9, H 1.18, M 0.82, M 1.09, H 0.76, H 1.43, M 0.95, H 1.24, H 0.77, C 

a

MOEd and MOEs are tabulated in decreasing order for each site, with the letter after each entry indicating the level of thinning (C, control; 

 L, light thinning; M, medium thinning; H, heavy thinning.) 

b

1 lb/in2 = 6.894 kPa; MOEd, dynamic modulus of elasticity of wood in a tree determined by the stress wave method; 

 MOEs, static modulus of elasticity of small, clear specimen determined by static bending test. 
9 

Figure 10—Modulus of elasticity (MOE) of Sitka spruce 

as a function of thinning treatment (light, medium, 

heavy) (1 lb/in2

 = 6.894 kPa). 

Figure 11—Modulus of elasticity (MOE) of western 

hemlock as a function of thinning treatment (light, 

medium, heavy) (1 lb/in2

 = 6.894 kPa). 

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0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

MOE (x106 lb/in2)

Control Light Medium Heavy

Treatment

Static MOE of small, clear specimens 

Stress wave MOE of trees

Site: Port Alice 

Species: Western hemlock 

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

MOE (x106 lb/in2)

Control Light Medium Heavy

Treatment

Static MOE of small, clear specimens 

Stress wave MOE of trees

Site: Port Alice 

Species: Sitka spruce