ThesisPDF Available

Nondestructive Testing of Ponderosa Pine Wood Quality: Influence of Stand and Tree-Level Variables on Acoustic Velocity and Wood Density


Abstract and Figures

The Four Forest Restoration Initiative (4FRI) is a landscape-scale collaborative project aimed at reducing the threat of catastrophic wildfires and improving forest health by moving forest ecosystems in northern Arizona on a trajectory that is more resilient to future disturbances and guided by historical reference conditions. A key component of this initiative aims to support sustainable forest industries by increasing markets for value-added wood products made from small-diameter trees. Currently, traditional markets for ponderosa pine in the region consist of mainly low-value products. The aim of this study was to provide information to forest managers and investors on the quality of the wood harvested during 4FRI operations. In the Centennial Forest, near Flagstaff, Arizona, we measured acoustic velocity (a proxy for wood stiffness) and radial density profiles to investigate the relationship between internal wood properties and stand-and tree-level variables. We also collected acoustic velocity data from the Taylor Woods levels-of-growing-stock study on the Fort Valley Experimental Forest. Wood density and acoustic velocity relate to stiffness and strength, important properties that determine end-use potential. Acoustic velocity was higher, on average, in trees from stands with higher basal areas, while basal area had only a small effect on wood density. This indicates that wood quality may improve with increasing basal area, but these gains may be offset by lower volume production from harvesting small-diameter material. Our findings may help dispel the notion that wood from small-diameter ponderosa pine trees is unsuitable for high-value applications. We hope these findings encourage investment in wood processing infrastructure in the region; without such investment, forest restoration projects in the Southwest may not be economically viable over the long-term.
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Nondestructive Testing of Ponderosa Pine Wood Quality
Influence of Stand and Tree-Level Variables on Acoustic Velocity and Wood Density
Submitted to the faculty of the Northern Arizona University School of Forestry in partial
fulfillment of the requirements for the degree of Master of Forestry
Matthew Ruggirello1
Advisor: Dr. David Auty
Readers: Dr. Kristen Waring, Dr. Thomas Kolb
Fall 2017
1Candidate for Master of Forestry, Northern Arizona University School of Forestry
The Four Forest Restoration Initiative (4FRI) is a landscape-scale collaborative project
aimed at reducing the threat of catastrophic wildfires and improving forest health by moving
forest ecosystems in northern Arizona on a trajectory that is more resilient to future disturbances
and guided by historical reference conditions. A key component of this initiative aims to support
sustainable forest industries by increasing markets for value-added wood products made from
small-diameter trees. Currently, traditional markets for ponderosa pine in the region consist of
mainly low-value products.
The aim of this study was to provide information to forest managers and investors on the
quality of the wood harvested during 4FRI operations. In the Centennial Forest, near Flagstaff,
Arizona, we measured acoustic velocity (a proxy for wood stiffness) and radial density profiles
to investigate the relationship between internal wood properties and stand- and tree-level
variables. We also collected acoustic velocity data from the Taylor Woods levels-of-growing-
stock study on the Fort Valley Experimental Forest. Wood density and acoustic velocity relate to
stiffness and strength, important properties that determine end-use potential.
Acoustic velocity was higher, on average, in trees from stands with higher basal areas,
while basal area had only a small effect on wood density. This indicates that wood quality may
improve with increasing basal area, but these gains may be offset by lower volume production
from harvesting small-diameter material. Our findings may help dispel the notion that wood from
small-diameter ponderosa pine trees is unsuitable for high-value applications. We hope these
findings encourage investment in wood processing infrastructure in the region; without such
investment, forest restoration projects in the Southwest may not be economically viable over the
Part One: An Overview of Forest Operations and the Wood Products Industry in
Norther Arizona
More than a century of inappropriate forest management activities in northern and central
Arizona, principally fire suppression and exclusion, grazing, and irresponsible logging practices,
has resulted in high basal area stands of predominantly small-diameter trees vulnerable to
catastrophic wildfire, insect attacks, and disease outbreaks (Covington and Moore 1994;
Covington et al 1997). In response, the United States Forest Service has undertaken a massive
restoration initiative known as the Four Forest Restoration Initiative (4FRI). Across four national
forests, the Forest Service has begun work to “restore the structure, pattern, composition, and
health of fire-adapted ponderosa pine ecosystems; reduce fuels and the likelihood of unnaturally
severe wildfires; and provide for wildlife and plant diversity” (, 6
September 2016). More than 600,000 acres of forest are scheduled to be treated over the next 20
years (, 6 September 2016), potentially producing over one
million cubic feet of stem wood and 9.6 million green tons of biomass from tree crowns
(Hampton et al 2008). However, ponderosa pine (Pinus ponderosa), is considered to be of little
commercial value in much of the southwestern United States. Though commercially exploited in
other parts of its range, including in other parts of Arizona, processing of ponderosa pine is not
seen as economically lucrative throughout much of Arizona and New Mexico (Covington et al
Public skepticism and resistance from environmental groups to timber removal has
largely limited the Forest Service’s social license to implement forest restoration and fire-hazard
reduction treatments that are ecologically and economically sensible (Chapman N, pers. comm.,
April 2017). Though ambitious in its scope, 4FRI has been limited in its operational objectives.
Operations are generally limited to the harvesting of trees under 16 inches in diameter, which
often results in basal areas and trees per acre above the historical range of variation for the region
(USFS Old Growth and Large Tree Retention Strategy 2011). There is evidence that a
considerable number of larger ponderosa pine trees should in fact be removed from the forest for
a variety of reasons, including reducing torching indices and improving water yield and seedling
regeneration post-treatment (Abella et al 2006, Sánchez Meador et al 2015, Flathers et al 2016).
Given the negative perceptions of ponderosa pine wood in the region, policies that
impede the harvesting of larger trees present challenging economic barriers to efficient, self-
sustaining restoration initiatives. This resistance among the public and environmental groups
stems from a history of irresponsible logging practices. After Euro-American settlement in the
late 1800s, the largest pine trees in the region were cut without restraint: “in the late 1800s, the
northern Arizona forests provided an abundant timber supply of valuable and easily harvested
southwestern yellow pine [i.e. Pinus ponderosa] for railroad ties. The harvesting process
required the heavy cutting of old-growth timber with little attention given to future productivity”
(Geils 2008, pp1-2). By the early 1900s, intensive logging of large ponderosa pine trees
threatened the viability of the logging industry in northern Arizona. As a result, the Fort Valley
Experimental Forest was established to conduct studies relating to the health and sustainability of
forests in the region. Though the logging industry declined from an initial boom period, industry
remained relatively stable in the Flagstaff area until the early 1990s. It was during this period
that unfavorable market conditions and high volumes of unmerchantable stems, coupled with
lawsuits from environmental groups, applied even more pressure on an already stressed wood
industry (Ffolliott 2008). The result was the near total collapse of the private, commercial
logging industry of north-central Arizona.
After a period without significant logging operations and wood products manufacturing,
the U.S. Forest Service became essentially the only significant forest management group in the
region. With high frequency, low-intensity fire and private commercial logging largely removed
from the landscape, non-commercial, mechanical thinning has become the dominant silvicultural
technique applied to reduce stocking levels in the high basal area forests around Flagstaff. To
date, the Forest Service claims to have mechanically thinned approximately 150,000 acres across
the 4FRI project area (,
18 June 2017). However, the consensus among the scientific and forest industry communities is
that 4FRI is significantly delayed, with some sources claiming that the Forest Service is
approximately 140,000 acres behind schedule
4fri-progr/, 18 June 2017).
Although the obstacles to efficient, successful forest restoration across the 4FRI area are
complex, a lack of market demand for wood, which could help offset treatment costs, is often
cited as the main cause of operational delays. Only a handful of small mills are functioning in
north-central Arizona. NewPac Fibre is one of these facilities. It is largely through collaboration
with The Nature Conservancy that NewPac has been able to stay in business, producing cants
that are exported to Mexico as low-value pallet stock (Chapman N, pers. comm., September
2017). Small operators like these are simply unable to absorb the large volume of small-diameter
trees from fuels reduction and other treatments in the region.
A relatively successful project in eastern Arizona known as the White Mountain
Stewardship Project also stimulated local industry and partially met restoration goals: through
the stewardship program, loggers received subsidies from the federal government to treat tens of
thousands of acres of vulnerable forest in eastern Arizona; local wood products manufacturers
received substantial support as well (Sitko and Hurteau 2010). Given the near complete absence
of significant industry in north-central Arizona, such stewardship agreements will be an essential
component of reestablishing the wood products industry around Flagstaff. The White Mountain
Stewardship Project, though innovative and somewhat successful, was not without its challenges
and pitfalls (Mottek et al 2017). The myriad of lessons learned while implementing stewardship
projects in the White Mountains can be applied to improve initiatives in the Flagstaff area aimed
at reinvigorating local industry while reducing fire-hazard (Mottek et al 2017).
Despite relative success in other parts of Arizona reviving local wood products industries,
larger-scale manufacturers have so far been deterred from returning to the Flagstaff area. The
reasons for this include, in addition to a lack of detailed information about ponderosa pine wood
properties, the Forest Service’s complicated contract system sometimes discouraging industry
growth, and small logging contracts of only a few thousand acres being offered to loggers with
no guarantee of long-term supply (Chapman N, pers. comm., September 2017). Both loggers and
mills are limited by the annual fluctuation in the size of these contracts. Loggers awarded
contracts to fell timber near Flagstaff often cannot obtain sufficient capital loans to complete
operations and frequently subcontract their work to other operators (Chapman N, pers. comm.,
September 2017). This lack of operational continuity results in an inefficient and imperfect
implementation of restoration prescriptions, which is an impediment to entrepreneurial
commitment and large-scale investment in high volume, value-added wood processing facilities
in the region.
At present, hopes for meeting restoration and fuel-hazard reduction objectives on the
western extent of the 4FRI area lay in the potential construction of biomass energy facilities
(, 18 June 2017). Despite the completion of
several feasibility studies and ongoing plans to use ponderosa pine wood as biomass feedstock,
the construction of a fully operational plant has not yet been realized. In eastern Arizona,
however, the utilization of small-dimeter pine as biomass, supported by federal grants, has
helped to address lackluster regional markets while simultaneously boosting rural economies
(Davis et al 2014). However, directing the entire wood supply of north-central Arizona toward
biomass facilities neglects the fact that much of the volume across the landscape may be
appropriate for higher-value uses. Though directing some small-diameter ponderosa pine for use
in biomass energy plants may be an appropriate part of a larger plan to solve the region’s
resource oversupply problems, it is likely not a stand-alone solution.
Ultimately, landscape-scale restoration efforts in the region will depend on more efficient
and profitable utilization of small-diameter logs (Lowell and Green 2001). A key component in
realizing this goal is a more accurate and comprehensive understanding of the properties of the
wood supply. Current knowledge about ponderosa pine wood properties is largely anecdotal:
many foresters in the region view the wood as soft, knotty, and unfit for structural applications.
Scientific quantification of the wood properties of these trees is therefore an essential component
in dispelling these conceptions.
Significance of Acoustic Velocity and Wood Density
Wood stiffness and strength are often seen to be of paramount importance by the wood
industry, as they play a large part in determining the end-use potential of logs (Grabianowski et
al 2006; Wang et al 2007a; Wang et al 2007b; Auty and Achim 2008). Measured in miles per
second, the speed at which sound travels through a tree correlates directly to its dynamic wood
stiffness, which in turn correlates to the stiffness determined in static bending. Assuming green
wood density remains constant, faster acoustic speeds suggest stiffer wood. This relationship is
driven by, among other factors, the proportion of latewood present in a stem (Carter et al 2005).
Theoretically, acoustic velocity is directly related to the dynamic modulus of elasticity, or
dynamic wood stiffness, and wood density by the equation:
MOED = dynamic modulus of elasticity (lb in-2), ρ = green wood density (lb ft-3), v = acoustic velocity (mi sec-1).
Though acoustic tools provide individual, tree-level values, they are most useful at the
forest level where they can be used to compare wood stiffness across stands for proper
segregation of stems. Toward such ends, field use of acoustic tools has increased in recent years
throughout both the commercial and research forestry sectors (http://www.fibre-, 12 October 2016). The use of acoustic tools for early genetic selection
of stock in commercial tree-breeding programs is also increasing, as wood stiffness is strongly
influenced by genetics (Jayawickrama et al 2011, Lenz et al 2013, Lowell et al 2014). This has
encouraged forest geneticists to consider acoustic velocity when selecting families for
commercial tree breeding (DeBell J, pers. comm., July 2017). Geneticists and reforestation
foresters are also empowered through acoustic velocity measurements to include wood stiffness
in their reforestation plans, further increasing managers’ ability to maximize profits from their
forested lands. Further commercial applications for acoustic tools exist at the wood-processing
level: in New Zealand and Australia, for example, acoustic testing of logs before processing has
enabled more efficient segregation of stems based on their structural qualities (Carter et al 2013).
Though more difficult to collect, wood density measurements are also strong indicators
of the mechanical properties of a stem (Shmulsky and Jones 2015). Wood density can be
measured through X-ray densitometry, where the radial density profiles of samples prepared
from increment cores are scanned at a fine scale using X-rays. As this is a complex and costly
process, it is not applied widely by field foresters; companies and organizations likely do not
have the financial capital or manpower necessary to collect, cut, and scan wood samples from
their forests. Still, models for commercially valuable species such as Scots pine and Sitka spruce
do exist that link wood density to stand and tree-level variables (Guilleya et al 1999, Repola
2006, Gardiner et al 2011, Auty et al 2016). The potential exists for these models to be applied in
determining the end-use potential of stems on a commercial scale. No such model or basic
relational description exists for ponderosa pine in the Southwest.
Together, wood density and acoustic velocity data give a strong indication of the
structural properties of a stem by providing information on the strength and stiffness of trees and
logs. For structural applications, most timber must meet certain minimum standards for strength
and stiffness as expressed through the moduli of elasticity (MOE) and rupture (MOR) (Auty and
Achim 2008). Higher strength and stiffness values may allow for the use of stems in higher-value
structural applications such as building construction or composite lumber manufacturing. Still,
such utilization depends largely on the variance and uniformity of strength and stiffness
properties across an entire stem. Stems producing wood with poor or highly variable strength and
stiffness properties have traditionally been chipped for landscaping, utilized as biomass energy,
piled and burned in the forest, or processed into cants to manufacture low-value products such as
Factors Impacting Wood Properties and End-Use Potential
Of importance in understanding the results of this study is a discussion of the role of
latewood in determining wood density and stiffness. Commonly, latewood is the term used to
describe the thick-walled tracheid fibers added radially to a tree’s stem toward the end of a
growing season. Latewood contains more densely compacted xylem tracheids than earlywood,
which is developed in spring and early summer. The open cavities at the center of xylem
tracheids, or lumen, are also smaller in latewood fibers. The proportion of latewood in a stem
relative to earlywood is correlated to wood density and the end-use potential of a log: “wood
density may be closely approximated and evaluated by the proportion of latewood in the growth
rings” (Larson 1963, p28).
Many factors contribute to latewood proportion in annual growth rings. Of these, the
extent of a tree’s live crown is strongly linked to earlywood formation. The live crown produces
auxin, a growth-regulating hormone that increases in concentration with crown growth and size.
Large crowns generally lead to greater auxin production, resulting in higher earlywood
percentages in annual growth rings. Additionally, the presence of photosynthates, often linked to
live crown vigor, late into the growing season is commonly associated with the thickening of cell
walls and the formation of latewood (Larson 1969). However, trees with exceptionally small
crowns will not produce enough photosynthates to allow for the formation of thick latewood
bands during late summer and autumn (Larson 1969, Shmulsky and Jones 2015).
The relationship between the live crown and water demands is also related to latewood
proportion: larger crowns require more water from their roots to satisfy greater photosynthetic
demands; a greater proportion of earlywood cells would therefore be expected, as they are better
conduits for water (Larson 1963). Smaller crowns, associated with lower photosynthate
production and reduced water demands, correlate to higher percentages of latewood in a stem
(Larson 1969). In the United States Southwest, latewood formation may be connected most
closely to late-season soil moisture availability and summer vapor pressure deficits (Kerhoulas et
al 2017).
The proportion of juvenile wood in trees also helps determine end-use potential. Juvenile
wood tends to be low in density, contains considerable amounts of tension and compression
wood, and is generally of inferior quality with respect to structural uses than mature wood
(Shmulsky and Jones 2015). Dependent on species and site conditions, trees between the ages of
15 and 25 begin to reduce production of low-density juvenile wood and transition to the
formation of structurally superior mature wood (Zobel and Sprague 2012). After this, juvenile
wood production is restricted to the areas close to the live crown. Therefore, trees with larger
crowns will likely produce relatively high amounts of juvenile wood, regardless of their age.
Conventionally, manufacturers of solid wood products have sought uniformity in wood
properties, namely the evenness with which latewood and earlywood bands are distributed across
annual growth rings. Larson (1969, p47) states that one of the greatest wood quality problems
facing all wood-using industries is lack of uniformity…the more erratic the growth conditions,
the greater the non-uniformity of the wood produced.Ponderosa pine in the Southwest grows
under such erratic conditions; largely due to the region’s dry climate, ponderosa pine’s annual
growth is highly variable. Additionally, intense crowding in many stands can compound drought
stress, increasing irregularities in internal wood properties (Martinez-Meier et al 2015). Highly
variable stand basal areas and intense competition also contribute to the formation of irregularly
sized growth rings that result in variable internal strength and stiffness properties.
However, with the development of composite wood products, a greater variety of raw
material is suitable for commercial use. Irregularities in growth ring width, variation in latewood
and earlywood bands, and stress-gradients created by knots can be mitigated by many of the
processes that form composite wood products (Shmulsky and Jones 2015). With the growth of
composite wood industries, less dense, structurally inferior wood may sometimes be preferred, as
it is more mechanically efficient to process this weaker wood into products such as oriented
strand board (Shmulsky and Jones 2015). A feasibility study from the early 2000s concluded that
a small number of ponderosa pine logs may be of suitable quality for use as structural lumber
and that a greater number may be appropriate for use in composite wood products, such as
glulam beams and oriented strand board (LeVan-Green and Livingston 2001).
Still, the investment necessary to establish a composite wood product manufacturing
plant is extremely prohibitive: depending on the product to be manufactured, processing plants
require capital investment levels in the tens to hundreds of millions of dollars. Small-diameter
ponderosa pine in the United States Southwest will be harvested almost exclusively from federal
lands and investors are likely wary of their investments depending entirely on operational
contracts administered by the federal government. Additionally, the climate and fire regime of
the region further destabilize the resource base necessary to maintain composite wood product
Ultimately, resolving the economic and scientific problems facing the region will require
complex, nuanced, and proactive strategies that target a cluster of end-uses and forest industries
to diversify markets. It is unlikely that a single product or market will suffice to absorb the bulk
of ponderosa pine wood removed in fire-hazard reduction operations. Only a thorough
quantification of the strength, stiffness and other important wood properties across the regional
landscape will determine the appropriate potential end-uses for the stems harvested in northern
Part Two: Using nondestructive techniques to assess wood quality in
ponderosa pine forests near Flagstaff, Arizona.
Study Objective
To use nondestructive testing (NDT) methods to investigate the relationship between
internal wood properties, namely wood density and stiffness, and tree and stand-level variables
in replicated ponderosa pine levels-of-growing-stock experiments.
Study Sites
Data were collected in the summers of 2015 and 2016 in Northern Arizona University’s
Centennial Forest and the Forest Service’s Taylor Woods levels-of-growing-stock study, both
near Flagstaff, Arizona. The area has a semi-arid climate with most significant precipitation
falling as winter snow or as late summer, monsoonal rain. The forest at our sites is dominated by
ponderosa pine and Gambel oak (Quercus gambelii).
Throughout this study, stand density is expressed in terms of basal area. At the
Centennial Forest, a thinning in 2005 resulted in the creation of five replicated basal area
treatments of 60, 80, 100, 120, and 150 ft2 ac-1 across a total of 20 treatment blocks, each
approximately five acres in size. Post-thinning basal areas ranged from 62 ft2 ac-1 to 175 ft2 ac-1
across the twenty distinct treatment units. The study was created using an uneven-sized group
selection with even spacing; pre-treatment basal areas ranged from 58 ft2 ac-1 to 174 ft2 ac-1
(Gaylord et al 2011). The experiment has not been treated again since the initial thinning. Pre-
treatment basal areas and trees per acre across the site were highly variable: several replicates
were already at post-thinning targets in 2005 and did not require thinning; however, in most
replicates, there was no apparent link between pre- and post-thinning basal area (Gaylord et al
2011). Basal area classes did not exist in any distinct, systematic manner prior to 2005. The
study at Taylor Woods had a similar design. It was established in 1962 and has been periodically
thinned to maintain replicate treatment units near 30, 60, 80, 100, 120 and 150 ft2 ac-1, which
range in size from 0.75 to 1.24 acres (Bailey 2008). Taylor Woods also contains unthinned and
non-forested units. As of 2016, actual basal areas varied slightly from targets (Flathers et al
Many of the stands to be treated by the Forest Service under 4FRI are above 55% of
maximum stand density index (SDI) and have basal areas greater than 200 ft2 ac-1 (McCusker et
al 2014). However, a certain number of treatments will occur in stands with basal areas between
150 ft2 ac-1 and 200 ft2 ac-1 (4FRI Landscape Restoration Strategy for the First Analysis Area
2010). Comparatively, the highest basal area stands at our two study sites are analogous to the
most open stands to be treated across northern Arizona. The lower basal area stands at the
Centennial Forest and Taylor Woods more closely resemble some of the desired post-treatment
conditions detailed in 4FRI’s objectives (USFS Proposed Action for Four-Forest Restoration
Initiative 2011, McCusker et al 2014).
Sampling Techniques and Data Collection
In the Centennial Forest, three randomly located fixed-area 0.1-acre plots were
established in each of the 20 treatment blocks, for 60 plots in total. Study plots were chosen by
selecting a random number of paces and a random azimuth. We established the first plot by
walking the decided number of paces along a random azimuth from the corner of a given
treatment unit; the two subsequent plots in each unit were established using the same technique,
starting from the center of the previous plot. In this way, we hoped to overcome the natural bias
to walk toward open areas. We repeated this process at Taylor Woods, but sampled in fewer total
replicate treatment blocks than at the Centennial Forest. Total trees per plot varied greatly
depending on a given treatment unit’s basal area. In some of the most open treatment blocks,
fewer than six live ponderosa pine trees greater than five inches in diameter were suitable for
measurement per sample plot. In the highest basal area stands, as many as 40 trees per plot were
appropriate for sampling.
At Taylor Woods, tree diameter at breast height (DBH, in.), total tree height (ft.), height
to the base of the live crown (ft.), and acoustic velocity were recorded for each tree over five
inches in DBH in a given plot, for a total of 333 trees. Due to permission restrictions, increment
cores were not taken from trees at Taylor Woods. In the Centennial Forest, we measured tree
diameter and recorded acoustic velocity for 720 individuals. Total tree height and height to
crown base were measured on a subsample of approximately six trees per plot, totaling 279
measurements. A single increment core was extracted at breast height (4.5 feet from ground
level) from the same subsamples of 279 trees, using standard increment boring techniques. To
select our subsample of trees, we chose individuals that would theoretically be suitable for
commercial harvest and utilization based on DBH, total height, crown height, and stem
straightness. After extraction, cores were secured in modified drinking straws and placed in a
freezer for storage.
Measuring Acoustic Velocity
Acoustic velocities were recorded at both Taylor Woods and the Centennial Forest using
the ST300 Hitman tool (Fibre-gen, Christchurch, New Zealand). Gambel oak trees were not
tested, nor were ponderosa pine trees under five inches in diameter due to the heightened risk of
damage to the trees from the insertion of the ST300’s acoustic probes. In addition, acoustic
velocity measurements from the Hitman tool are known to be less reliable in trees under five
inches in diameter. We placed the tool’s two probes in each ponderosa pine tree to be sampled,
one near the base of the tree and the other, for practical purposes, just above breast height
(Figure A2). Though recording acoustic velocity at breast height may seem to be an
inappropriate technique for measuring the internal qualities of an entire stem, various studies
have concluded that such data can be interpolated to an entire stem with relative confidence
(Haines and Leban 1997, Auty and Achim 2008). Additionally, acoustic data allow for a very
accurate comparison of internal wood properties between trees at a specific, user-determined
point along a stem.
To operate the ST300 tool, the user taps the lower probe 24 times with a hammer,
producing a velocity measurement. The distance traveled by the wave from the lower probe to
the upper probe is measured and the transit time is recorded. Knowing the distance between
probes, velocity (miles per second, mi s-1) is calculated as the distance over the time-of-flight of
the acoustic wave (Figure A3). Opinions vary on whether consistent placement of probes on a
specific side of a tree is important. Wang et al (2007a) chose a side randomly for each individual
tree, while Mora et al (2009) did not identify consistency in probe placement as a significant
factor in producing accurate acoustic readouts. We chose to take measurements on the north side
of all trees for consistency.
Measuring Wood Density
Wood density was measured on samples from the Centennial Forest using the Quintek
QMRS-01X Tree Ring Scanner (Quintek Measurement Systems Inc., Knoxville TN). Before
scanning, the cores were conditioned in a climate-controlled chamber to approximately 6-8%
moisture content. As the QMRS-01X is unable to analyze intact cores, our samples were
prepared with the assistance of Dr. Joseph Dahlen from the Warnell School of Forestry and
Natural Resources, University of Georgia. In the scanning process, 2-mm-thick bark-to-pith
samples were secured in a five-millimeter cartridge and mounted on a linear stage. The stage
then moves in 25-µm increments and the X-ray beam scans the sample on the tangential face. A
camera also creates a detailed image of the radial profile of the sample. The result is a graphical
representation of a sample’s radial density profile, measured in pounds per square inch (lb in-2),
accompanied by a photograph of the sample. The QTRS-01X software also produces a ring-level
density summary, which quantifies, in tabular format, the average density for each year of
growth based on the density variation between adjacent latewood bands. As wood density is
usually averaged for each annual ring, we often refer to our results in terms of ring-level wood
density throughout this work. The ring-level summaries also include average earlywood and
latewood density values for each annual ring.
Before scanning, we calculated a mass attenuation coefficient, which is used to calibrate
the densitometer. This coefficient is an estimate of the amount of energy that is absorbed by any
given wood sample. The mass attenuation coefficient is species- and region-specific and is
necessary for accurate density measurement. To calculate this, we measured the specific gravity
of ten randomly selected intact cores by suspending them in a beaker of water. Dividing the mass
of each core (lb) by its volume (ft3) gave us the specific gravity of each sample. We averaged the
samples to get an approximation of average specific gravity for our cores in lb ft-3. We entered
this average into the scan set-up parameters as the target wood density value for a particular
sample. We then scanned the sample and the software used the known specific gravity of the
core to calculate a mass attenuation coefficient for use in future scans.
In measuring wood density, our methods paralleled closely those of Antony et al (2012),
who also used non-destructive sampling methods, i.e., extraction of increment cores.
Nondestructive methods for testing wood properties may limit the amount of information one
can gather from a given sample: for example, strength and bending tests to determine the exact
moduli of rupture and elasticity for a sample can only be performed on destructively sampled
trees. Still, nondestructive sampling allows significantly more samples to be extracted for wood
density analyses, providing the opportunity to collect data from many more individuals.
Data Analysis
The following analyses were conducted on the data from the Centennial Forest and
Taylor Woods:
Centennial Forest: we linked tree height and DBH to basal area treatment and acoustic
velocity using 720 diameter measurements and 279 height measurements.
Centennial Forest: we described a linear relationship correlating acoustic velocity to wood
density using paired velocity and wood density measurements from 279 trees. Acoustic
measurements were averaged over the last 50 years of growth, as acoustic waves tend to
travel through the stiffest material, i.e., the outerwood portion of the stem.
Centennial Forest: using 279 wood density samples, we described relationships between
wood density and cambial age, year of ring formation, and stand-level basal area, as well as
the relationship between cambial age and average annual ring width.
Centennial Forest: using data from 279 trees we linked DBH and average tree height to tree
age at breast height.
Taylor Woods: we established relationships between acoustic velocity and tree height and
diameter and basal area treatment using 333 data points per analysis.
Study Limitations
This experiment did not have pure controls; untreated stands were not included in our
study. In part, untreated stands were not sampled because their trees were too small for both
application of the ST300 Hitman acoustic probes and safe extraction of increment cores; these
stands also contain trees with insufficient volume for value-added uses, making their internal
wood quality properties largely irrelevant.
Our analysis was limited in that it did not relate wood quality characteristics directly to
climate variables. Drying and warming patterns throughout the Southwest have their own effects
on wood formation in ponderosa pine; some of these effects have already been documented
(Martinez-Meier et al 2015, Dannenberg and Wise 2016). Drought, for example, is known to
induce production of smaller diameter tracheids, resulting in false rings (Larson 1969). These
slight changes in wood density and color can make proper delineation of ring boundaries
difficult. Though an X-ray densitometry analysis of the average wood density of an entire sample
is unaffected by these false rings, examining annual variation in wood density becomes
challenging when many false rings are present; determining the true end of a tree’s annual
growth can become nearly impossible. For this work, cores were not cross-dated due to time
constraints. Without matching annual ring patterns across multiple cores, identifying the true
location of a given year on a particular scan or ring-level density summary was difficult.
Consequently, years of ring formation and dates associated with wood density scans contain a
degree of error. Future experiments might address this by cross-dating cores and may incorporate
climate data more directly into analyses of wood density and acoustic velocity. Such a study may
help determine the relative influence of stand basal area and climate on ponderosa pine internal
wood properties.
Another limiting factor of this research was that levels-of-growing-stock studies at the
Centennial Forest and Taylor Woods have not been strictly maintained. Lower basal area classes
are beginning to converge with higher ones. This may confound results linking stand-level basal
area to wood density and acoustic velocity. Future studies would benefit from stricter
maintenance of target basal areas. Our analysis may also be limited in its scope of inference: we
did not sample stands from across the southwestern United States. Such ambitions were beyond
the scope of this pilot study.
Results and Discussion
Acoustic velocity results incorporate data collected from both Taylor Woods and the
Centennial Forest, while wood density results have been derived from increment cores collected
only from the Centennial Forest.
General Trends
Tree Characteristics by Site and Basal Area Treatment
The summary statistics presented in Table 1 allow comparisons to be made across study
sites. Mean tree DBH and heights were generally higher at Taylor Woods than at the Centennial
Forest, which is likely related to of the longer duration of the study at Taylor Woods. The levels-
of-growing-stock study at Taylor Woods was established in 1962, so trees in the more open
treatment blocks at Taylor Woods would likely have had greater access to resources for longer
than at the Centennial Forest. Basal areas would have been higher across much of the Centennial
Forest until the thinning of 2005 (Gaylord et al 2011). The standard deviations for both tree
heights and diameters tended to be greatest at the Centennial Forest, with only a few exceptions
in the lowest basal area treatments of Taylor Woods, where new cohorts of young ponderosa
pine have established.
Average tree age at the Centennial Forest was highest for trees in the lowest basal area
class, while the inverse was true for trees for the highest treatment class, suggesting that older
trees were present before the thinning of 2005 in the 60 ft2 ac-1 replicates and were retained post-
thinning. Still, average tree ages suggest that few trees across the study site would have
established before Euro-American settlement. Ranges of recorded acoustic velocity values were
more variable at the Centennial Forest and the maximum velocity values in the Centennial
Forest’s highest basal area classes were considerably higher than values from comparable stands
at Taylor Woods. Relatively high standard deviations for acoustic velocity values at both sites
may be a result of crowded growing conditions and limited access to soil moisture causing
differential wood formation across trees sharing space and resources.
Table 1: Mean tree characteristics by site; CF = Centennial Forest and TW = Taylor Woods. Lacking increment cores
from Taylor Woods, average tree age per treatment class could not be calculated.
No. of Trees
BA 2015
Mean DBH (SD)
Range (in.)
Mean Ht (SD)
Range (ft.)
Mean Vel (SD)
Range (mi s-1)
Avg. Age
16.2 (3.8)
5.7 23.6
58.1 (10.7)
20.4 77.4
2.17 (0.25)
1.47 2.67
12.8 (4.1)
5.6 21.3
53.0 (11.9)
24.1 80.3
2.12 (0.26)
1.30 2.55
13.3 (4.3)
5.0 24.1
56.7 (11.0)
23.8 80.3
2.18 (0.25)
1.34 2.66
11.4 (4.0)
5.3 28.0
51.9 (15.3)
24.6 84.0
2.28 (0.27)
1.32 3.06
11.2 (3.6)
5.0 23.5
52.9 (11.7)
25.8 85.0
2.23 (0.26)
1.29 2.99
16.8 (7.3)
6.1 24.5
56.2 (19.7)
28.5 79.2
1.82 (0.28)
1.32 2.19
18.2 (1.4)
16.0 21.3
66.4 (5.4)
57.0 75.0
2.09 (0.19)
1.79 2.46
15.9 (1.9)
11.9 21.7
64.6 (5.7)
51.8 81.0
2.19 (0.15)
1.80 2.55
13.8 (2.1)
9.4 18.9
61.3 (8.2)
39.1 82.4
2.29 (0.15)
1.81 2.67
14.0 (1.8)
10.7 17.7
63.0 (5.8)
51.5 73.8
2.29 (0.13)
2.03 2.56
11.2 (2.1)
7.4 16.6
56.6 (6.2)
38.2 70.4
2.41 (0.15)
1.91 2.68
Average Tree Height and Diameter at Breast Height vs Basal Area Treatment
At the Centennial Forest, tree height and DBH decrease with increasing target basal area
(Figure 1). This negative relationship is stronger for DBH than for total tree height, suggesting
that trees with limited access to resources will prioritize height growth over diameter growth.
These results are as expected since in higher basal area stands, fewer resources will be available
to individual trees as competition will be more intense, thereby restricting growth. However, in a
following section, we show that acoustic velocity, a surrogate for wood stiffness, likely increases
with increasing stand basal area. This phenomenon suggests that there are tradeoffs between
stiffness gains and volume losses in higher basal area stands. Though higher basal area stands
may contain trees with stiffer wood, volume losses and the loss of total harvestable material in
these stands may offset improvements in wood stiffness. We would expect to see similar trends
at Taylor Woods.
Figure 1: Boxplots of average tree height and DBH for each basal area treatment at Centennial Forest and Taylor
Woods. Both average tree height and DBH decrease with increasing basal area. These results are from the
Centennial Forest; n = 279 (height); n = 720 (DBH).
Average Tree Height and Diameter at Breast Height vs Age at Breast Height
There was a positive correlation between average tree height and age at breast height in
the Centennial Forest. This correlation is weakest in our lowest basal area treatment, as more
open-growing trees have less need to emphasize height growth (Figure 2). The positive
relationship between height and tree age was strongest in the 80 ft2ac-1 and 120 ft2ac-1 classes.
Individuals in stands that are under moderate competition have likely allocated resources to
height growth to achieve more favorable crown positions; this growth has closely paralleled age
at breast height. The relationship weakens in the highest basal area class; though crown height is
still likely to be important, more intense crowding may have limited trees’ access to resources to
allocate toward height growth.
Though in the intermediate treatments there was a moderate positive correlation between
diameter at breast height and tree age at breast height, this relationship was significantly weaker
in our lowest and highest basal area treatments. In the 60 ft2 ac-1 class, this may be a result of
larger tree diameters. As trees become larger, they experience less overall diameter growth for
the same amount of overall growth. Trees must form more woody material around their stem as
their cross-sectional area increases. However, the lower correlation in the 150 ft2 ac-1 was likely
caused by other factors. Competition for soil moisture, light, and space in the higher basal area
treatment blocks have likely reduced the amount of resources available for individual trees to
allocate toward diameter growth. This obscures the relationship between tree diameter and age in
higher basal area stands. This phenomenon is common across much of the forested Arizona
landscape, where many stands have had basal areas over 200 ft2 ac-1 for decades.
Figure 2: Scatterplots of tree height (top) and DBH (bottom) vs. tree age at breast height for each basal area treatment
at the Centennial Forest. In the Centennial Forest, average tree height increases with age. The relationship between
diameter at breast height and age at breast height is also positive, yet both relationships vary significantly by basal
area class; n = 279.
Acoustic Velocity
Acoustic Velocity vs Basal Area Treatment
Our results indicate that acoustic velocity is positively correlated with basal area
treatment (Figure 3). This phenomenon is likely explained by an increase in the proportion of
latewood present in the annual rings of the relatively slow-growing trees in the higher basal area
treatments. Sound waves are conducted more rapidly through the compact, thick-walled cells of
latewood relative to the thinner-walled earlywood cells with wider lumen. Many factors
influence the ratio of latewood to earlywood cells in an annual ring. These include crown size; at
the individual tree level, the smaller crowns of trees in higher basal area stands have lower water
demands than the larger crowns of trees in open-grown stands and thus require less earlywood to
conduct water upward from the roots.
While we found only a weak correlation between acoustic velocity and basal area
treatment at the Centennial Forest, there was a stronger trend at Taylor Woods. The reasons for
this are not clear, though it may have to do with generally larger trees being present at Taylor
Woods. This suggests the possibility that trees at Taylor Woods with more extensive root
systems may have greater access to late-season soil moisture, allowing for increased latewood
Figure 3: Boxplots of acoustic velocity for each target BA treatment. Mean velocity (i.e. dynamic wood stiffness) is
positively correlated with stand basal area; this relationship is significantly stronger at Taylor Woods; n = 720
(Centennial Forest); n = 333 (Taylor Woods).
In addition to analyzing the relationship between acoustic velocity and basal area
treatment classes, we must consider a more fundamental question: are our reported acoustic
values “good” from a wood products perspective? Our reported acoustic velocity values in the
highest basal area units of 120 and 150 ft2 ac-1 at both Taylor Woods and Centennial Forests
ranged from approximately 1.24 mi sec-1 to 3.11 mi sec-1. Most values were clustered between
1.86 and 2.48 mi sec-1; however, approximately 10% of values were above 2.48 mi sec-1.
In general, acoustic tools allow for precise characterization of the forest resource before
processing. This deeper understanding of the internal wood properties of a stem gives foresters
and mill operators the power to maximize their profits by segregating logs based on their internal
properties. Examples of acoustic tools being used to study ponderosa pine in the United States
Southwest do not exist. It was thus inherently difficult to determine whether the ranges of
acoustic velocity values reported for ponderosa pine in this study should inspire confidence that
trees removed from 4FRI operations will be suitable for high-value end-uses.
Though problematic, we must look to other species to contextualize our results. In a study
of acoustic properties in plantation-grown New Zealand radiata pine (Pinus radiata), the authors
reported standing-tree acoustic velocity values ranged from just above 1.86 mi sec-1 to just below
3.11 mi sec-1, with the bulk of acoustic measurements clustered near the mean of 2.34 mi sec-1
(Matheson et al 2002). Although the relationship between downed log acoustic velocity and
static wood stiffness was stronger than that between standing-tree acoustic velocity and wood
stiffness, acoustic velocity in standing trees was still moderately correlated with dynamic wood
stiffness and had the power to inform pre-processing segregation decisions. The authors
ultimately concluded that based on wood stiffness, the top 50% of stems were appropriate for
structural end-uses while the bottom 50% would be best suited for non-structural applications.
Another study looked at acoustic velocity in white spruce (Picea glauca) growing in
plantations in Quebec, Canada (Bérubé-Deschênes et al 2016). The plantations were ready for a
first commercial thinning at around twenty years of age. The average acoustic velocity pre-
thinning ranged from 1.86 to 2.17 mi sec-1. The authors also described a similar relationship
between dynamic wood stiffness and crowding pre-thinning, where increased competition and
reduced crown size increased latewood percentages in stems and, ultimately, improved wood
stiffness. Ultimately, slow growth was also associated with higher latewood percentage and
acoustic velocity.
Drawing strong conclusions on appropriate end-uses for ponderosa pine through cross-
species comparisons would be problematic. Ponderosa pine wood from northern Arizona will
have to compete with domestic and international wood products from plantation settings; thus, a
broad contextualization of ponderosa pine wood properties relative to “the competition” is still
appropriate. Though standing tree acoustic velocities are not perfect for assessing the potential
end-use of a given stem, relative comparisons of acoustic velocities do allow us to understand the
stiffness of ponderosa pine in our region relative to stems growing elsewhere (DeBell J, pers.
comm., September 2017).
The Washington State Department of Natural Resources Genetic Resources Program has
set up over 30 Douglas-fir (Pseudotsuga menziesii) progeny test sites throughout the state. The
oldest sites were established in the 1970s, but currently the agency also maintains second- and
third-generation test sites. The department began collecting acoustic velocity data in its second-
generation sites, planted in the early 1990s. In second-generation sites, Douglas-fir trees between
20 and 30 years old had average acoustic velocities between 2.49 mi sec-1 and 3.11 mi sec-1
(DeBell J, pers. comm., September 2017). Comparing these progeny sites with our study results,
average acoustic values from the second-generation Washington state sites are higher than the
majority of values recorded from Taylor Woods and the Centennial Forest. It is not surprising
that Douglas-fir trees, with access to abundant resources in plantation settings, produced higher
acoustic velocity readouts than ponderosa pine growing in natural stands in the southwestern
United States. This suggests that, in terms of intrinsic wood properties, ponderosa pine wood
from our region will clearly struggle to compete with plantation-grown Douglas-fir from the
Pacific Northwest. Still, this does not preclude the possibility that stiffer, denser ponderosa pine
wood from certain stems may still be suitable for higher-value uses, rather than as biomass
feedstock or low-value pallet stock.
Ultimately, further, detailed information is needed about the intrinsic properties of wood
from our region, for example, mechanical bending tests need to be conducted on trees from
across the landscape to enhance results from this pilot study. Our results suggest that certain
individuals growing in higher basal area stands (120 ft2 ac-1 or above) may be suitable for higher
value, structural uses based strictly on their acoustic properties and predicted improved wood
stiffness. The average acoustic velocities in the highest basal area stands we measured
approached 2.50 mi sec-1; based on results from the studies detailed above, 2.50 mi sec-1 may be
an approximate cutoff for structural uses.
Undoubtedly, a threshold exists where the relationship between stand-level basal area and
acoustic velocity collapses. Very stressed trees in higher basal area stands may not have
sufficient resources to produce higher quality, denser and stiffer wood. Additionally, trees from
completely unthinned stands, with basal areas well above 200 ft2 ac-1, may simply be too small
for any uses other than as biomass energy feedstock. Researchers might focus future studies
solely on higher basal area stands (100 ft2 ac-1 200 ft2 ac-1) to determine up to what point the
relationship described in this subsection holds true.
Acoustic Velocity vs Diameter at Breast Height
In general, there was a weak relationship between acoustic velocity and DBH across the
different treatments at both study sites (Figure 4). While in the Centennial Forest there was a
positive relationship across all basal area treatments, this was not the case for Taylor Woods.
Potential confounding effects relating to differences in site quality or stand history may have
affected our results. The fact that fewer trees were sampled at Taylor Woods and that these trees
had a narrower range of diameters might also contribute to the differences seen between the two
Confirmation of the Centennial Forest results by future studies would indicate a
significant tradeoff between intrinsic wood properties and tree volume. Taller, small-diameter
individuals growing in relatively high basal area stands are likely to produce stiff wood suitable
for high-value applications; however, larger-diameter trees may also produce stiff wood, while
generating more merchantable volume. Additional work is needed across a greater range of sites
to confirm the relationship between diameter and acoustic velocity in ponderosa pine growing in
the Southwest U.S.
Figure 4: Acoustic velocity vs DBH for each basal area treatment at the Centennial Forest and Taylor Woods.
There was generally a positive correlation between acoustic velocity and DBH for trees in the Centennial Forest.
Patterns are less clear at Taylor Woods; n = 720 (Centennial Forest); n = 333 (Taylor Woods).
Acoustic Velocity vs Total Tree Height
The correlations between acoustic velocity and tree height were weak overall (Figure 5),
although a positive relationship between average tree height and acoustic velocity does appear to
exist across both study sites. For all basal area treatments at both Taylor Woods and the
Centennial Forest, acoustic velocity increased with increasing tree height. This relationship was
weakest in the mid-level treatments of 80 and 100 ft2 ac-1, but was still slightly positive. This
general relationship could be explained by a combination of factors: the relationship between
tree height and age likely played a role in shaping our results. Taller trees tend to be older
(Figure 2), and older trees tend to form denser wood (Figures 7 and 8). If we assume that denser
wood correlates with higher stiffness, this wood would transmit a sound wave more quickly
between the two probes of the ST300.
Additionally, after reaching approximately 25 years of age, trees will have transitioned
from producing juvenile wood to producing mature wood, which tends to be stiffer and denser
than juvenile wood. Somewhat independent of age, taller trees may also have more extensive
root systems. Coupled with more favorable canopy positions, taller individuals are likely better
prepared to sequester resources later into the growing season. However, higher basal area
treatments generally contain smaller, shorter trees. This suggests there may be tradeoffs between
dynamic stiffness gains and volume losses in these higher basal area stands.
Figure 5: Acoustic velocity vs total tree height in each basal area treatment at the two study sites. A clear, positive
correlation exists between tree height and acoustic velocity across both sites, with the pattern most clearly
expressed in the lowest and highest basal area treatments; n = 279 (Centennial Forest); n = 333 (Taylor Woods).
Acoustic Velocity vs Ring-level Wood Density
The correlation between acoustic velocity and ring-level wood density was examined
over the last fifty years of growth, as an acoustic wave only travels through the outerwood of a
stem. Our results indicate a weak positive correlation between acoustic velocity and wood
density (Figure 6). Regardless of treatment class, denser wood correlates to higher acoustic
velocity. These results are not entirely surprising. As discussed, wood density is often linked to
higher latewood percentage in a stem. Denser wood, containing higher amounts of latewood, will
likely conduct sound waves faster than wood with a lower proportion of latewood. These results
suggest that wood density may be inferred from acoustic velocity measurements. Such an
inference could be significant: whereas it is a laborious process to measure wood density at the
stand level, it is relatively simple to measure acoustic velocity in sample plots across multiple
The next logical step in this line of research would be to bolster this predictive model for
wood density based on acoustic velocity, which would allow analysts to infer both dynamic
stiffness and wood density from easily obtained acoustic measurements, among other variables.
The positive relationship between acoustic velocity and wood density across all basal area
treatments suggests that trees in higher basal area stands, regardless of their size, may not only
have stiffer wood than previously thought, but also denser wood.
Figure 6: Acoustic velocity vs the mean density of the last 50 annual rings in each basal area treatment. Results
exclusively from the Centennial Forest show a weak, yet positive relationship between acoustic velocity and wood
density across all basal area treatments; n = 279.
Wood Density
Ring-level Wood Density vs. Cambial Age and Year of Ring Formation
When comparing ring-level wood density to cambial age and year of ring formation, most
trees exhibited irregular density early in their lives (Figures 7 and 8). However, as might be
expected, ring-level wood density stabilized and slightly increased in recent years. This is most
likely linked to a reduction in juvenile wood production as trees age. Climatic variation,
undeniably tied to competition, also likely played a significant part in shaping these results.
Significant drought events and particularly strong summer monsoons at different times during
the 2000s likely contributed to spikes and dips in wood density over the last two decades.
Treatments of 100ft2 ac-1, 120ft2 ac-1, and 150ft2 ac-1 show a weak yet positive correlation
between cambial age and ring-level wood density, while in the lowest basal area stands there
appears to be no correlation between these variables. It is possible that in open stands (60ft2 ac-1
and 80 ft2 ac-1) greater production of earlywood offsets wood density gains associated with the
shift from juvenile to mature wood production. Open-grown trees should have greater radial
growth rates than trees growing in higher basal area stands. Much of this additional radial growth
will consist of thin-walled, low-density earlywood cells with wide lumen. In general, our results
suggest that the internal wood properties of ponderosa pine vary widely based on multiple
variables. Forest managers should consider average tree age when anticipating the intrinsic wood
properties of trees and their potential end-uses.
Figure 7: Mean ring density vs cambial age for all basal area treatments at Centennial Forest. The decrease in
wood density near the pith is followed by a weak trend of increasing ring-level wood density at higher cambial ages,
as shown by the red line representing a smoothed moving average. Grey lines represent individual tree density
profiles; n = 279.
Figure 8: Mean ring density vs year of wood formation averaged across all basal area treatments at Centennial
Forest. Excluding large variation in young trees, ring-level wood density generally increased with year of ring
formation; n = 279.
Ring-level Wood Density vs Basal Area Treatment
Given the highly variable conditions at the Centennial Forest before the thinning of 2005,
it is not possible to accurately link stand-level basal area to wood density before 2005 (Gaylord
et al 2011). In general, increased water availability late in the growing season is one of the most
significant factors influencing latewood formation and thus wood density in our region. It is
logical to assume that late-season water availability was historically a major contributing factor
in wood density differences over time.
We may more conclusively hypothesize about the causes of trends in wood density across
basal area treatment classes after the thinning of 2005 (Figure 9). As we did not cross-date our
samples, the position of 2005 on our graph is an approximation and it is therefore difficult to
detect the exact impact of thinning on wood density. Still, general trends and differences between
basal area treatments can be analyzed with relative confidence from the last ten years. In the
2000s, the higher basal area treatments of 120ft2 ac-1 and 150 ft2 ac-1 had generally slightly higher
average ring-level wood densities than the basal area treatment classes of 60ft2 ac-1, 80ft2 ac-1,
and 100ft2 ac-1. Several factors may have influenced the surprisingly high ring-level wood
density of trees in the highest basal area treatment blocks. Trees in higher basal area stands have
less opportunity for diameter growth; thinning blocks to 120ft2ac-1and 150ft2 ac-1 would not
necessarily have resulted in significant radial growth, depending on pre-treatment basal areas.
However, after the thinning of 2005, trees in these higher basal area stands would have had more
resources available to them later in the growing season. With small crowns and limited room to
grow radially, there would be little reason for trees in higher basal area treatment blocks to add
wide-lumen, earlywood cells. Given the smaller crowns of trees from higher basal area stands, it
seems logical that resources made available after a forest thinning would be preferentially
directed toward forming compact, latewood cells rather than low-density, earlywood cells
(Larson 1969).
Regardless of the cause of the phenomena described above, the implications for wood
utilization are significant: trees in higher basal area stands form wood that is at least as dense as
the wood formed by trees in more open stands. We do not know the point at which this
relationship might break down: doghair thickets of bent-over ponderosa pine may not be
producing particularly dense wood. This pattern may already be present in our data: the 150ft2 ac-
1 treatment class exhibits lower average wood density at many points in time relative to the
slightly more open 120ft2 ac-1 treatment class.
Figure 9: Annual ring density vs year of wood formation by treatment for the last 16 years of wood formation at the
Centennial Forest. Actual basal areas were not accurately known before the thinning of 2005 when the study was
established. Trees in the highest density treatments of 120 ft2ac-1 and 150 ft2ac-1 appear to form slightly denser wood
than those in lower basal area treatments; n = 279.
Annual Ring Width vs Cambial Age
A general trend of decreasing ring width with increasing age exists in trees from the
Centennial Forest (Figure 10). An initial rapid decrease stabilized over time; across most basal
area treatment classes, ring width leveled off between the ages of 25 and 50, except for in the 60
ft2 ac-1 treatment. The initial decrease in ring width as a tree ages is likely a result of wider annual
rings and more rapid growth when trees are younger and subject to less competition. Older trees
must produce increasingly more wood to cover their larger circumferences, resulting in
progressively narrower rings until diameter growth stabilizes at a much lower level.
However, wood formation at a finer scale is highly variable, resulting in annual
fluctuations in ring width. Irregular ring widths are present across all treatments. These
anomalies suggest that growth rates have been inconsistent over time, resulting in latewood and
earlywood bands that are highly variable in width. Images and graphical readouts of scanned
samples confirm this variability across many of our wood samples.
The semi-arid climate of the region is likely a significant driver of these results. Limited
soil moisture and periodic drought, coupled with years of heavy monsoonal rains, directly affects
latewood growth and consequently ring width (Kerhoulas et al 2017). Coupled with intense
crowding and increased competition in the highest basal area treatments, these factors likely
explain much of the variability in ring width seen in our results. Production of latewood that
varies in density by year results in inconsistent ring widths, likely creating highly variable
mechanical wood properties within a given stem.
Figure 10: Average annual ring width vs cambial age for each treatment at Centennial Forest. Annual ring width
initially decreased rapidly in the annual rings near the pith, but stabilized over time across all basal area
treatments. Red line indicates a smoothed moving average. At the individual tree level (gray lines), ring width was
highly variable; n = 279.
Broader Significance
In general, the significance of our results is nuanced and complex. In understanding these
results, perhaps the most significant factor to consider is the relationship between age and tree
size across much of the forested landscape of the southwestern United States. Though the vast
majority of the trees in our region are under 12 inches in diameter, many of these individuals are
approaching one-hundred years old. This potentially misleading age-diameter relationship
suggests that traditional, plantation-based knowledge of the wood quality of smaller trees cannot
be applied to many of the forests of the southwestern United States. Whereas throughout much of
the world, small, young trees will produce low-density, juvenile wood, small, older trees produce
much different wood. As our results suggest, small-diameter ponderosa pine that have survived
significant competition for resources are likely to have a high percentage of mature wood.
Furthermore, as annual rings are narrow in width in these trees, a substantial proportion of these
stems will be composed of high-density, latewood.
However, growth irregularities confound our results and may impede the utilization of
ponderosa pine wood in the region regardless of the intrinsic wood properties. Many stands in
northern Arizona have experienced cycles of rapid and slow growth. Variations in growing
conditions and climate have resulted in inconsistent ring widths in many trees. Traditionally,
wood processing industries have valued consistent, uniform growth. These growth irregularities
will most likely preclude the use of a given stem for structural applications as high-value solid
lumber products.
Incorporating the knowledge presented in this study into forest management decisions
may be difficult if direct acoustic and wood density measurements cannot be taken across the
4FRI landscape. Still, by considering stand development histories, managers may be able to
segregate forest resources more efficiently without taking these measurements. If basic stand-
level basal area information dating back several decades are available to forester managers,
internal wood properties may be roughly approximated at the stand level: individuals that grew
in relatively constant, moderately-high basal area stands may have stiffer, denser wood that may
be suitable for higher-value end-uses.
Wood density and acoustic velocity results from this study give cause for tempered
optimism in the northern Arizona forestry community. From our results, we have concluded that
a certain proportion of small-diameter ponderosa pine trees in the region could likely produce
wood suitable for high-value applications. Increased fundamental knowledge of the internal
wood properties of trees in our region is essential to helping address some of the crucial issues
facing northern Arizona’s researchers and forest managers. I would like to conclude by providing
some closing thoughts on how the oversupply of small-diameter timber and absence of
significant wood industry in north-central Arizona might be addressed:
1. Develop a more nuanced and informed understanding of the actual internal wood
properties of the trees in our forests.
This understanding will allow for the proper segregation of stems before processing, and
will ultimately contribute to more efficient and informed planning of forest treatments, directing
trees from different stands to appropriate markets for the wood products they will ultimately
produce. At present, a lack of local processing facilities and heavy competition from domestic
and international markets has impeded large-scale utilization of ponderosa pine in the Southwest.
There likely exists no “golden egg” solution to this problem. A diverse cluster of processing
facilities in terms of size and output must be encouraged to develop around Flagstaff. The first
step towards achieving this is to have detailed information on the properties of the available
timber supply. This pilot study provides an initial step toward this more complete understanding
of ponderosa pine and its true value. Faculty and students at Northern Arizona University are
already at work on studies that will further increase our knowledge of the internal properties of
the ponderosa pine growing in the Southwest.
2. Increase stewardship programs for loggers and entrepreneurs.
Given the international nature of wood markets and competition from regions that more
easily grow timber suitable for structural applications, there is simply no way the private sector
can establish and maintain itself in northern Arizona without some degree of outside assistance.
In the long-term, the federal and state government should look to help establish a mix of
composite wood product manufacturers and biomass plants in the region. The responsibility of
such stewardship does not fall squarely on federal and state governments though: The Nature
Conservancy has been active in forging new relationships and supporting local mills through
unfavorable economic times. The Nature Conservancy is open to greater participation in
worthwhile restoration projects where their capital and technical support can help achieve
restoration goals through supporting efficient forest operations and the growth of local industry
(Chapman N, pers. comm., September 2017).
The city of Flagstaff has also pioneered innovative projects to increase forest treatments
around the city: following the Schultz fire of 2010, which burned approximately 15,000 acres
near Flagstaff’s Timberline and Doney Park neighborhoods, the residents of the city approved a
ten-million-dollar bond that was paid through taxes levied on individuals
(, 10 Sept 2017). This money has been used to fund
the Flagstaff Watershed Protection Project, which connects forest managers with loggers from
the region to treat the forested landscape around the city, focusing on areas that are essential to
the long-term quality and stability of the town’s water supply.
In our neighboring state of Colorado, the state forestry division has been active in
multiple areas of the wood utilization process. Through the Colorado Forests Products Program,
experts in wood utilization, research, and forest management are working across agency and
social boundaries to increase the local use and value of their forest resources
(, 8 Nov 2017). These experts provide technical support to a
diverse group of forest landowners, conduct applied research to improve wood utilization in the
region, and work to both educate and train the public in issues and skills relevant to local wood
utilization. To the authors knowledge, no such program to assist private and public landowners
exists in Arizona.
Although there are examples of successful, creative partnerships to improve restoration
and wood utilization throughout the Southwest, the U.S. Forest Service and the Arizona
Department of Forestry and Fire Management have been reluctant to play an active part in
establishing creative partnerships with local loggers, landowners, and entrepreneurs.
Consequently, potential industry and investors avoid north-central Arizona. Implementation of
restoration and fire-hazard mitigation treatments in the region continues to be impeded by a poor
wood-processing landscape and an uniformed local consumer base.
3. Develop and implement a certification system for wood sourced from local fire-hazard
reduction treatments and cultivate responsible wood-products consumers.
When we consider the suitability of southwestern ponderosa pine wood for high-value
uses in a national and international context, encouraging industry to invest in large-scale
processing plants near Flagstaff seems problematic. The dry conditions in the Southwest mean
that trees producing high quality wood will grow faster and cheaper elsewhere. Currently, it is a
near certainty that ponderosa pine wood products from north-central Arizona cannot compete
with products from Douglas-fir grown in the Pacific Northwest, or those from Southern yellow
pine species from the Southeast. The local public must therefore be encouraged to pay a
premium for wood removed to save their homes and communities. This will require long-term
collaboration between foresters, marketing professionals, entrepreneurs, and consumers to
emphasize the hidden value of locally-produced wood products.
In the southwestern U.S., increased consumer awareness must accompany any
revitalization of industry. We must convince the public to view wood products as many view
their food: local is better. The details of how to develop this consumer consciousness are beyond
the scope of this work. However, it is important to note that communities elsewhere in the U.S.
have embarked on a similar mission: local wood-workers and builders throughout Colorado have
begun to use beetle-killed wood to construct homes, floors, and more
(,, 10 Sept 2017). These projects remove flammable
wood from the forested landscape, while infusing new life into local communities. Capitalizing
on markets in Flagstaff, Tucson, and Phoenix, there is no reason to believe similar projects, using
wood removed during fire-hazard reduction treatments, could not have success throughout
4. Provide training to community members in woodworking, construction, tree felling, and
basic wood processing.
In searching for the “golden egg” solution to the wood oversupply problem in the
Southwest, we often think of large-scale projects, such as biomass energy, OSB and
particleboard plants, or chipping large amounts of wood for use in landscaping. However,
smaller, local-level solutions remain an important part of these efforts. Incorporation of local
landowners, builders, and woodworkers into solutions aimed at utilizing the bi-products of forest
restoration and fuels reduction treatments is crucial. Focusing on small landowners, training and
encouraging them to remove and utilize small-diameter ponderosa pine on their properties would
be an easy and straightforward way to encourage people to reduce fire hazard on their own lands.
Interested community members should be supported in purchasing portable mills. Support in
drying methods for ponderosa pine lumber, which has a reputation for warping and cracking, is
also important. This training and support could be more significantly incorporated into the
Firewise USA program (
landscape.aspx, 10 Sept 2017). In considering the large amount of woody material we need to
remove from our landscape, we must not forget the role that individual communities can play in
forging solutions.
The resolution of the issues surrounding wood utilization in north-central Arizona will
have to be nuanced and multi-disciplinary, functioning at various levels of society and
government. Ultimately, foresters may have to venture into unfamiliar territory in search of long-
term solutions. However, as a first step toward addressing the wood oversupply problem in the
region, we must understand the basic internal wood properties of the trees to be removed and
retained during thinning operations. Incorporated at the stand level, information on acoustic
velocity and wood density can be used to more efficiently identify and categorize the quality of
the forest resource, maximizing yields and potential economic gains from stands and ultimately
enticing industry back to the region (Matheson et al 2002; Wang et al 2007a). It is our hope that
forest managers will be able to incorporate the results of our analysis in their landscape-scale
planning, and that our study will help direct silvicultural treatments toward more careful
consideration of the end-use potential of trees removed in restoration and hazardous-fuels
treatments. This will require additional research on ponderosa pine wood quality, which will help
refine and broaden these results to the greater southwestern United States forested landscape.
I would like to thank my wife, Alejandra, for supporting me throughout this process and
my parents for their unwavering, constant support of my pursuit of higher education. I am also
very grateful for the support of Northern Arizona University: without the financial aid offered to
me by the university, I would not have been able flourish in such a rigorous academic
environment. I would like to thank my readers Dr. Tom Kolb and Dr. Kristen Waring for their
time and effort in revising my work and would like to extend an additional thanks to both of
them for their exemplary teaching and advising, which has truly prepared me for a career in
forestry. I would like to thank Dr. Joseph Dahlen from the University of Georgia for his
assistance preparing our increment cores for scanning. I would also like to thank the Rocky
Mountain Research Station Forest Service Staff, with a special thanks to Dr. Keith Moser, for
their collaboration with this project. I would like to thank Mr. Neil Chapman of The Nature
Conservancy and Dr. Jeff DeBell of the Washington State DNR for providing me with detailed
background information that greatly aided me in completing this work. Lastly, I owe a very
special thanks to my advisor Dr. Dave Auty. Dr. Auty has offered me constant guidance and
attention throughout my time at the university. His dedication and availability serve as a shining
example of faculty mentorship and I am extremely indebted to him for his guidance and support.
Thank you.
Literature Cited
Abella S, Fulé P, Covington W. 2006. Diameter caps for thinning Southwestern ponderosa pine
forests: Viewpoints, effects, and tradeoffs. Journal of Forestry 104(8):407-414.
Antony F, Schimleck L, Hall D, Clark A, Daniels R. 2012. Modeling the Effect of Midrotation
Fertilization on Specific Gravity of Loblolly Pine (Pinus taeda L.). Forest Science
Auty D, Achim A. 2008. The relationship between standing tree acoustic assessment and timber
quality in Scots pine and the practical implications for assessing timber quality from
naturally regenerated stands. Forestry 81:475-487.
Auty D, Achim A, Macdonald E, Cameron A, Gardiner B. 2014. Models for predicting wood
density variation in Scots pine. Forestry 87:449-458.
Auty D, Achim A, Macdonald E, Gardiner B. 2016. Models for Predicting Clearwood
Mechanical Properties of Scots Pine. Forest Science 62:1-9.
Bailey J. 2008. Forty years later at Taylor Woods: Merging the old and new. Fort Valley
Experimental ForestA Century of Research 1908-2008. Proceedings RMRS-P-55:100-
Bérubé-Deschênes A, Franceschini T, Schneider R. 2016. Factors Affecting Plantation Grown
White Spruce (Picea Glauca) Acoustic Velocity. The Journal of Forestry 114(6):629-637.
Carter P, Briggs D, Ross R, Wang X. 2005. Acoustic testing to enhance western forest values
and meet customer wood quality needs. Productivity of Western forests: a forest products
focus general technical report Pacific Northwest Research Station: 121-128.
Carter P, Wang X, Ross R. 2013. Field application of processor head acoustic technology in
forest harvest operations. Proceedings of the 18th International Nondestructive Testing
and Evaluation of Wood Symposium: Sept. 24-27, 2013, in Madison, WI.
Covington W, Moore M. 1994. Postsettlement changes in natural fire regimes and forest
structure: ecological restoration of old-growth ponderosa pine forests. The Journal of
Sustainable Forestry 2(1-2):153-218.
Covington W, Fulé P, Moore M, Hart S, Kolb T, Mast J, Sackett S, Wagner M. 1997. Restoring
Ecosystem Health in Ponderosa Pine Forests of the Southwest. The Journal of Forestry
Dannenberg P, Wise E. 2016. Seasonal climate signals from multiple tree ring metrics: a case
study of Pinus ponderosa in the upper Columbia River Basin. Journal of Geophysical
Research: Biogeosciences 121:1178-1189.
Davis E, Mottek A, Kim Y, Moseley C, Bilek T. 2014. The Impacts of the Woody Biomass
Utilization Grant Program in Eastern Oregon and Eastern Arizona. Ecosystem
Workforce Program Working Paper Number 46:1-39.
Ffolliott P. 2008. Historical Review of Fort Valley Studies on Stand Management. Fort Valley
Experimental ForestA Century of Research 1908-2008. Proceedings RMRS-P-55:18-
Flathers K, Kolb T, Bradford J, Waring K, Moser K. 2016. Long-term thinning alters ponderosa
pine reproduction in northern Arizona. Forest Ecology and Management 374(14):154-
Gardiner B, Leban J, Auty D, Simpson H. 2011. Models for predicting wood density of British-
grown Sitka spruce. Forestry.
Gaylord M, Hofstetter R, Kolb T, Wagner M. 2011. Limited response of ponderosa pine bole
defenses to wounding and fungi. Tree Physiology 31:428-437.
Geils B. 2008. Fort Valley Studies: A Natural Laboratory for Research and Education. Fort
Valley Experimental ForestA Century of Research 1908-2008. Proceedings RMRS-P-
Grabianowski M, Manley B, Walker J. 2006. Acoustic measurements on standing trees, logs and
green lumber. Wood Science Technology 40:205-216.
Guilleya E, Hervéb J, Hubera F, Nepveua G. 1999. Modelling variability of within-ring-level
wood density components in Quercus petraea Liebl. with mixed-effect models and
simulating the influence of contrasting silvicultures on wood density. Annals of Forest
Science 56(6):449-458.
Haines W, Leban M. 1997. Evaluation of the MoE of Norway spruce by the resonance flexure
method. Forest Products Journal 47(10):91-93.
Hampton H M, Sesnie S E, Dickson B G, Rundall J M, Sisk T D, Snider G B, Bailey J D. 2008.
Analysis of Small-Diameter Wood Supply in Northern Arizona. Forest Ecosystem
Restoration Analysis Project, Center for Environmental Sciences and Education,
Northern Arizona University.
Jayawickrama K, Ye T, Howe G. 2011. Heritabilities, Inter-trait Genetic Correlations, G x E
Interaction and Predicted Genetic Gains for Acoustic Velocity in Mid-Rotation Coastal
Douglas-fir. Silvae Genetica 60(1): 8-18.
Kerhoulas L, Kolb T, Koch G. 2017. The Influence of Monsoon Climate on Latewood Growth of
Southwestern Ponderosa Pine. Forests 8(140).
Larson P. 1963. Stem Form Development of Forest Trees. Forest Science-Monograph 5:1-42.
Larson P. 1969. Wood Formation and the Concept of Wood Quality. Yale School of Forestry
Bulletin No.74.
Lenz P, Auty D, Achim A, Beaulieu J, Mackay J. 2013. Genetic improvement of white spruce
mechanical wood traitsearly screening by means of acoustic velocity. Forests 4: 575-
LeVan-Green S, Livingston J. 2001. Uses For Small-Diameter Trees: Exploring the Uses for
Small-Diameter Trees. Forest Products Journal 51(9).
Lowell E, Green D. 2001. Lumber recovery from small-diameter ponderosa pine from Flagstaff,
Arizona. USDA Forest Service Proceedings RMRS-P-22:161-165.
Lowell E, Todoroki C, Dykstra D, Briggs D. 2014. Linking acoustic velocity of standing
Douglas-fir trees to veneer stiffness: a tree-log-product study across thinning treatments.
New Zealand Journal of Forestry Science 44(1).
Martinez-Meier A, Fernandez M, Dalla-Salda G, Gyenge J, Licata J, Rozenberg P. 2015.
Ecophysiological basis of wood formation in ponderosa pine: Linking water flux patterns
with wood microdensity variables. Forest Ecology and Management 346:31-40.
Matheson A, Dickson R, Spencer D, Joe B, Ilic J. 2002. Acoustic segregation of Pinus radiata
logs according to stiffness. Annals of Forest Science 59:471-477.
McCusker N, Gonzales R, Fuller R. 2014. Silviculture Specialist Report Coconino and Kaibab
National Forests Four Forest Restoration Initiative. The United States Department of
Agriculture Southwestern Region.
Mora C, Schimleck L, Isik F, Mahon J, Clark A, Daniels R. 2009. Relationships between
acoustic variables and different measures of stiffness in standing Pinus taeda trees.
Canadian Journal of Forest Resources 39:1421-1429.
Mottek L, Kim Y S, Greco B, Becker D R, Hjerpe E E, Abrams J. 2017. Social and Economic
Contributions of the White Mountain Stewardship Project: Final 10-Year Assessment
Lessons Learned and Implications for Future Forest Management Initiatives. Journal of
Forestry 115(6):548-558.
Paradis N, Auty D, Carter P, Achim A. 2013. Using a Standing-Tree Acoustic Tool to Identify
Forest Stands for the Production of Mechanically-Graded Lumber. Sensor 13(3): 3394-
Repola, J. 2006. Models for Vertical Wood Density of Scots Pine, Norway Spruce and Birch
Stems, and Their Application to Determine Average Wood Density. Silva Fennica
Sánchez Meador A, Waring K, Kalies E. 2015. Implications of Diameter Caps on Multiple
Forest Resource Responses in the Context of the Four Forests Restoration Initiative:
Results from the Forest Vegetation Simulator. Journal of Forestry 113(2):219-230.
Shmulsky R, Jones D. Forest Products & and Wood Science: An Introduction. 6th edition. Ames,
IA: Wiley-Blackwell, 2015.
Sitko S, Hurteau S. 2010. Evaluating the Impacts of Forest Treatments: The First Five Years of
the White Mountain Stewardship Project. The Nature Conservancy. Phoenix, Arizona.
Wang X, Carter P, Ross R, Brashaw B. 2007a. Acoustic assessment of wood quality of raw forest
materials: a path to increased profitability. Forest Products Journal 57:6-14.
Wang X, Ross R, Carter P. 2007b. Acoustic evaluation of wood quality in standing trees. Part 1:
Acoustic wave behavior in standing trees. Wood Fiber Science 39:28-38.
Zobel B J, Sprague J R. Juvenile Wood in Forest Trees. Syracuse, New York: Springer Science
& Business Media, 2012.
Figure A1: Maps showing the layout of treatment units sampled at Centennial Forest (left) and the U.S. Forest
Service’s Taylor Woods (right) levels-of-growing-stock studies outside of Flagstaff, Arizona. In the Centennial
Forest, twenty treatment units have been maintained at or near five basal area classes of 60, 80, 100, 120, and 150 ft2
ac-1. Each basal area class contains four replicated treatment units. Actual basal areas that were 20 ft2 ac-1 or greater
over their targets at the time of sampling are labelled above replicate unit numbers. In the Taylor Woods levels-of-
growing-stock study, measurements were taken from trees from GSL 30 150 ft2 ac-1.
Figure A2: The ST300 Hitman in use at the Centennial Forest experimental site (left); the ST300 Hitman acoustic
measurement tool (right). Photo credit: Fibre-gen.
Figure A3: Diagrams of the ST300 operating principles (left) and operating system (right). An acoustic wave
produced by a specialized hammer travels between the lower and upper probes of the ST300 Hitman acoustic tool.
The transit-time of the wave between the two probes is recorded and velocity calculated in miles per second and
stored on a portable data logger. Photo credit: Paradis et al 2013, Fibre-gen.
Figure A4: The Quintek QTRS-01X Tree Ring Scanner scanning and recording the wood density profile of a
ponderosa pine sample.
Figure A5: A sample readout from the QTRS-01X Tree Ring Scanner X-ray densitometer. A photograph of the
wood sample accompanies the pith-to-bark density profile. Peaks and valleys in the readout indicate spikes and
drops in wood density correlated with latewood and earlywood bands across the annual rings.
Figure A6: Ring-level summaries provided by the QMRS-01X Tree Ring Scanner provide the user with information
on average ring density, ring width, and earlywood and latewood proportion of each annual ring.
Figure A7: A comparison of a plantation-grown softwood density scan (top) and a native Arizona ponderosa pine
density scan (bottom) reveals significant growth irregularities in ponderosa pine. In ponderosa pine, peaks in wood
density vary considerably from year to year, revealing large variation in annual growth. Growth varies from rapid
(green line) to slow (red line). These irregularities may make it difficult to use such trees for high-value end-uses.
Figure A8: The forested landscape throughout much of northern Arizona has transitioned from being dominated by
trees over 20 inches in diameter to having a preponderance of trees under 12 inches in diameter (Covington et al
1997); this has had drastic ecological and economic implications for the region.
ResearchGate has not been able to resolve any citations for this publication.
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The North American Monsoon delivers warm season precipitation to much of the southwestern United States, yet the importance of this water source for forested ecosystems in the region is not well understood. While it is widely accepted that trees in southwestern forests use winter precipitation for earlywood production, the extent to which summer (monsoon season) precipitation supports latewood production is unclear. We used tree ring records, local climate data, and stable isotope analyses (δ¹⁸O) of water and cellulose to examine the importance of monsoon precipitation for latewood production in mature ponderosa pine (Pinus ponderosa Dougl.) in northern Arizona. Our analyses identified monsoon season vapor pressure deficit (VPD) and Palmer Drought Severity Index (PDSI) as significant effects on latewood growth, together explaining 39%of latewood ring width variation. Stem water and cellulose δ¹⁸O analyses suggest that monsoon precipitation was not directly used for latewood growth. Our findings suggest that mature ponderosa pines in this region utilize winter precipitation for growth throughout the entire year. The influence of monsoon precipitation on growth is indirect and mediated by its effect on atmospheric moisture stress (VPD). Together, summer VPD and antecedent soil moisture conditions have a strong influence on latewood growth.
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Wood mechanical properties, such as modulus of elasticity (MOE) and modulus of rupture (MOR), are important determinants of solid lumber performance and value. These properties vary systematically at different scales owing to multiple, potentially confounding, factors. Therefore, a statistical modeling approach may be an effective way to predict the impact of silvicultural practices on mechanical properties. The aim of this study was to develop models for predicting MOE and MOR in Scots pine (Pinus sylvestris L.), as functions of cambial age, height in the stem, wood density, and microfibril angle (MFA). Thirty-six trees were sampled from four mature Scots pine plantations in Scotland, UK. Longitudinal MOE and MOR were determined in static bending on 513 small (300 20 20 mm) defect-free samples. Nonlinear mixed-effects models based on an exponential function of cambial age were developed to predict the within-stem patterns of variation. The best model for MOR included cambial age, height in the stem, and sample density as explanatory variables, whereas the best MOE model also included a density/MFA term in the predictors. In growth simulations over a range of typical scenarios, the largest effect of silvicultural interventions was on the proportion of juvenile wood in the stem, but these had a negligible impact on mean tree MOE and MOR. The models will be incorporated into a growth, yield, and wood quality simulation system.
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Projected changes in the seasonality of hydroclimatic regimes are likely to have important implications for water resources and terrestrial ecosystems in the U.S. Pacific Northwest. The tree-ring record, which has frequently been used to position recent changes in a longer-term context, typically relies on signals embedded in the total ring width of tree rings. Additional climatic inferences at a sub-annual temporal scale can be made using alternative tree-ring metrics such as earlywood and latewood widths and the density of tree-ring latewood. Here, we examine seasonal precipitation and temperature signals embedded in total ring width, earlywood width, adjusted latewood width, and blue intensity chronologies from a network of six Pinus ponderosa sites in and surrounding the upper Columbia River basin of the U.S. Pacific Northwest. We also evaluate the potential for combining multiple tree-ring metrics together in reconstructions of past cool- and warm-season precipitation. The common signal among all metrics and sites is related to warm-season precipitation. Earlywood and latewood widths differ primarily in their sensitivity to conditions in the year prior to growth. Total and earlywood widths from the lowest elevation sites also reflect cool-season moisture. Effective correlation analyses and composite-plus-scale tests suggest that combining multiple tree-ring metrics together may improve reconstructions of warm-season precipitation. For cool-season precipitation, total ring width alone explains more variance than any other individual metric or combination of metrics. The composite-plus-scale tests show that variance-scaled precipitation reconstructions in the upper Columbia River basin may be asymmetric in their ability to capture extreme events.
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Acoustic velocity (AV) data from 7,423 coastal Douglas-fir trees drawn from 347 wind-pollinated families on 14 sites, from four first-generation testing programs in the north Oregon Cascades, were analyzed. Families were measured on two or four sites at ages 23 to 41 years from seed using the Fakopp TreeSonic standingtree tool. Height (HT) and DBH data collected at ages 15 and 16 from seed, from all trees in the four programs (95,795 trees, 955 families), were used to calculate volume index (VOL = HT*DBH Across-site individual narrow-sense heritabilities for AV Across-site type B correlations for AV Selecting the top 10% of the families sampled based on AV
1 General Concepts of Juvenile Wood.- 1.1 General Concepts.- 1.2 What Is Juvenile Wood?.- 1.3 The Causes of Juvenile Wood.- 1.4 Importance and Characteristics of Juvenile Wood.- 1.5 Literature on Juvenile Wood.- 1.6 Summary.- 2 Characteristics of Juvenile Wood.- 2.1 General Concepts.- 2.2 Juvenile Compared with Mature Wood.- 2.2.1 Effects upon Wood Uniformity.- 2.3 Characteristics of Conifers.- 2.3.1 Specific Gravity Within and Among Species.- 2.3.2 Variation in Other Wood Properties Within and Among Species.- 2.4 Characteristics of Hardwoods.- 2.4.1 Specific Gravity in Hardwoods.- 2.4.2 Other Wood Properties.- 2.5 Summary.- 3 Occurrence of Juvenile Wood.- 3.1 General Concepts.- 3.2 Where Does Juvenile Wood Occur?.- 3.3 Radial Development in the Conifers.- 3.3.1 Estimation of the Juvenile Wood Zone in Conifers.- 3.3.2 Radial Development of Specific Gravity.- 3.3.3 Radial Development of Other Wood Properties.- 3.4 Radial Development in the Hardwoods.- 3.5 Development with Tree Height.- 3.5.1 In the Conifers.- 3.5.2 In the Hardwoods.- 3.6 Summary.- 4 Characteristics Affecting Juvenile Wood.- 4.1 Relationship to Reaction Wood.- 4.2 Genetics of Juvenile Wood.- 4.3 Relationship to Growth Rate.- 4.4 General Sampling Methods for Different Characteristics.- 4.5 Summary.- 5 Changing Juvenile Wood.- 5.1 General Concepts.- 5.2 Response to Genetic Manipulation.- 5.3 Response to Silvicultural Treatments.- 5.3.1 The Effect of Spacing and Thinning.- 5.3.2 The Effect of Fertilization, Irrigation and Site.- 5.4 Response to Geographic Location, Seed Source and Species.- 5.5 Response to Other Environmental Factors.- 5.6 Summary.- 6 Predictions of Mature and Total Tree Wood Properties From Juvenile Wood.- 6.1 General Concepts.- 6.2 Juvenile to Mature Wood Correlations.- 6.2.1 Predictions Across the Tree Bole.- 6.2.2 Predictions Along the Bole.- 6.2.3 Predictions For the Whole Tree.- 6.3 Summary.- 7 The Importance of Juvenile Wood.- 7.1 General Concepts.- 7.2 In Conifers.- 7.2.1 Utilization in the Hard Pines, Douglas-fir, Larches etc.- Utilization of Top Wood.- 7.2.2 Utilization in the Spruces, Firs, Cypresses etc..- 7.3 In Hardwoods.- 7.3.1 Utilization.- Diffuse-Porous Species.- Ring-Porous Species.- 7.4 Summary.- 8 Use of Juvenile Wood.- 8.1 General Concepts.- 8.2 Juvenile Wood for Pulp and Paper.- 8.3 Juvenile Wood for Solid Wood Products.- 8.4 Future Juvenile Wood Supplies and Utilization.- 8.5 Summary.- 9 Unusual Wood Properties Near the Tree Center.- 9.1 General Concepts.- 9.2 Heartwood.- 9.3 Growth Stresses.- 9.4 Summary.- References.- Species Index.
The White Mountain Stewardship Project (WMSP) was the first forest stewardship project of its size and duration, lasting 10 years (2004–2014). Based on in-depth interviews of local businesses, US Department of Agriculture (USDA) Forest Service staff, and stakeholders, we present an assessment of the WMSP and lessons learned in large-scale contracting. The assessment includes factors that promoted project initiation, the contractual process, the overall impact to the local forest products industry and economy, and the formation of key partnerships. Experiences from the WMSP offer unique social and economic perspectives that can inform other communities at risk of wildfire. The recommendations were derived from final WMSP performance metrics and respondents' reflections on the outcomes of the WMSP. The lessons learned from the WMSP offer improvements for future restoration initiatives in USDA Forest Service contracting mechanisms, industry capacity, and coordination of stakeholder interests, including agency-to-industry, business-to-business, and agency-to-stakeholder partnerships.
In Eastern Quebec, 36,000 ha of plantations will be ready for a first commercial thinning in the next few years. With the increase use of thinnings, managers are asked to also integrate the financial return of their operations into their decision process. They must thus take into consideration the quality of the harvested trees. Softwood is mainly used for commodity lumber production in Quebec, with mechanical properties being an important wood quality trait. To evaluate standing wood properties, the modulus of elasticity can be estimated nondestructively by measuring acoustic velocity. With the use of data from 94 sample plots in 48 plantations, the effects of tree size, competition, growth rate, and site index on the acoustic velocity of planted white spruce were studied. Competition was quantified using both distance-independent and distance-dependent competition indices. The various competition indices were also subdivided according to the competition type (conifer/broadleaved). The acoustic velocity was found to be proportional to tree size and inversely proportional to growth rate, site index, and competition. The distance-independent competition indices performed better, and discrimination between competition type did not improve the models. These results will help foresters evaluate tree quality before harvesting.
Cost effective and value-added uses of small-diameter and underutilized (SDU) material for effective forest management were discussed. SDU material refers to leftover timber in the forest that is economically unviable to remove or there is an absence of local capacity to process it. There are many beneficial uses of SDU materials such as improving the stand species and quality mix, increase in forest resiliency, reducing fire hazards, provide healthy wildlife habitat, protecting watersheds and restoring economic vitality of many forest-dependent communities.