Content uploaded by Robert B. Harrison
Author content
All content in this area was uploaded by Robert B. Harrison on Jun 27, 2014
Content may be subject to copyright.
soils & hydrology
Predicting Risk of Long-Term Nitrogen Depletion
Under Whole-Tree Harvesting in the Coastal Pacific
Northwest
Austin J. Himes, Eric C. Turnblom, Robert B. Harrison, Kimberly M. Littke, Warren D. Devine,
Darlene Zabowski, and David G. Briggs
In many forest plantation ecosystems, concerns exist regarding nutrient removal rates associated with sustained whole-tree harvesting. In the coastal North American
Pacific Northwest, we predicted the depletion risk of nitrogen (N), the region’s most growth-limiting nutrient, for 68 intensively managed Douglas-fir (Pseudotsuga
menziesii var. menziesii [Mirb.] Franco) plantations varying widely in productivity. We projected stands to rotation age using the individual-tree growth model ORGANON
and then calculated a stability ratio for each stand, defined as the ratio of N removed during harvest to total site N store (soil and forest floor). We assigned a risk
rating to each site based on its stability ratio under whole-tree and stem-only harvest scenarios. Under whole-tree harvest, 49% of sites were classified as potentially
at risk of long-term N depletion (i.e., ⱖ10% N store removed in harvest), whereas under stem-only harvest, only 24% of sites were at risk. Six percent and 1% of
sites were classified as under high risk of N depletion (i.e., ⱖ30% N store removed in harvest) under whole-tree and stem-only harvest, respectively. The simulation
suggested that sites with ⬍9.0 and ⬍4.0 Mg ha
⫺1
site N store are potentially at risk for long-term N depletion and productivity loss under repeated whole-tree and
stem-only harvest, respectively. Sites with ⬍2.2 and ⬍0.9 Mg ha
⫺1
site N store are at high risk of N depletion under whole-tree and stem-only harvest, respectively.
The areas with the highest concentrations of at-risk sites were those with young, glacially derived soils on Vancouver Island, Canada, and in the Puget Sound region
of Washington.
Keywords: Douglas-fir, plantation, sustainability, stability ratio, nutrient
The use of wood and other biomass for energy is projected
to grow more than that of any other renewable energy source
in the United States during the next two decades (US
Department of Energy 2009). The largest source of available
biomass for energy not currently used in the United States is
forest product residues, including logging residues traditionally
left in the forest after harvest (White 2010). Utilization of these
residues for energy production has become an increasingly com-
mon practice internationally, particularly in European countries
attempting to meet Kyoto Protocol requirements (Jacobson et al.
2000, Stupak et al. 2008, Saarsalmi et al. 2010). As the demand
for forest biomass has risen, so has the need for information
regarding the effects of increased biomass removal, such as that attained
through whole-tree harvesting (WTH), on soils and the long-term sus-
tainability of productivity in intensively managed forest plantations
(Evans 1999, Fox 2000, Janowiak and Webster 2010).
With the development and increased use of mechanized WTH in
the 1970s, a number of researchers expressed concerns about the
increased export of nutrients due not only to greater biomass remov-
als but also to the relatively high nutrient concentration of tree
crown components that had traditionally been left on-site (Boyle et
al. 1973, White 1974, Ma¨lko¨nen 1976, Kimmins 1977, Marion
1979, Wells and Jorgensen 1979). Since then, a number of field
studies have been established to evaluate the effects of WTH, rela-
tive to those of conventional stem-only harvest (SOH), on soils and
long-term productivity (reviewed by Wall 2012). The largest field
study is the North American Long-Term Soil Productivity study,
established in 1989 and incorporating more than 100 core and
Manuscript received January 24, 2013; accepted May 23, 2013; published online August 22, 2013.
Affiliations: Austin J. Himes (himesa13@gmail.com), University of Washington, School of Environmental and Forest Sciences, Seattle, WA. Eric C. Turnblom
(ect@u.washington.edu), University of Washington, School of Environmental and Forest Sciences, Seattle, WA. Robert B. Harrison (robh@u.washington.edu),
University of Washington, School of Environmental and Forest Sciences, Seattle, WA. Kimberly M. Littke (littkek@gmail.com), University of Washington, School
of Environmental and Forest Sciences, Seattle, WA. Warren D. Devine (wdevine27@yahoo.com), University of Washington, School of Environmental and Forest
Sciences, Seattle, WA. Darlene Zabowski (zabow@u.washington.edu), University of Washington, School of Environmental and Forest Sciences, Seattle, WA. David
G. Briggs (dbriggs@u.washington.edu), University of Washington, School of Environmental and Forest Sciences, Seattle, WA.
Acknowledgments: This work was supported by the Stand Management Cooperative, by the Northwest Advanced Renewable Alliance, and by a grant from the US
Department of Agriculture. We thank Bob Gonyea and Bert Hasselberg for their assistance with data collection.
FUNDAMENTAL RESEARCH For. Sci. 60(x):000–000
http://dx.doi.org/10.5849/forsci.13-009
Copyright © 2014 Society of American Foresters
Forest Science • Month 2014 1
affiliate sites in the United States and Canada (Powers et al. 2005).
Most field studies of WTH effects on site productivity are still too
young to provide rotation-length data from even the first rotation
posttreatment (Eisenbies 2006, Thiffault et al. 2011, Wall 2012);
however, there have been numerous reports of WTH effects on
growth of young and mid-rotation plantations (e.g., Cole and
Compton 1994, Powers et al. 2005, Fleming et al. 2006). The
majority of studies reporting WTH effects on young trees found
either no effect on growth or small growth decreases; decreases were
attributed to factors specific to each region and site, associated with
WTH impacts on soils or the forest floor (Jacobson et al. 2000,
Nord-Larsen 2002, Powers et al. 2005, Walmsley et al. 2009, Saar-
salmi et al. 2010, Mason et al. 2012, Wall 2012).
Although measurements of the effects of WTH on forest produc-
tivity over multiple rotations are not yet available, numerous studies
have assessed the sustainability of these forestry systems based on
nutrient balance calculations, chronosequence and retrospective
data, and model simulations (Dyck and Cole 1994, Farve and Nap-
per 2009). Conclusions from studies evaluating WTH effects on
soils or nutrient budgets of individual sites have varied widely; how-
ever, meta-analyses and literature reviews spanning large geographic
areas and many soil types (e.g., Johnson and Curtis 2001, Eisenbies
et al. 2009, Thiffault et al. 2011) have shown several patterns. In a
meta-analysis of studies worldwide, SOH was associated with in-
creased A-horizon soil carbon (C) and nitrogen (N) in conifer for-
ests, whereas WTH of conifers was associated with small A-horizon
C and N decreases; this pattern was not present in hardwood or
mixed stands (Johnson and Curtis 2001). On many sites, soil re-
serves, weathering, and atmospheric inputs are predicted, over a
rotation, to replace most nutrients removed during WTH (Weet-
man and Webber 1972, Boyle et al. 1973, Turner 1981, Johnson et
al. 1982). Whereas there are no consistent, universal effects of the
increased biomass removal associated with WTH on forest soils
(Thiffault et al. 2011), low-productivity sites are usually considered
most vulnerable to nutrient deficiency after WTH (Ma¨lko¨nen
1976, Compton and Cole 1991).
Regional risk assessment models of nutrient depletion after
WTH and SOH are necessary for land managers to make informed
decisions about resource utilization (Sollins et al. 1983, Abbas et al.
2011, Wall 2012). Several recent regional risk assessment models
have been developed based on geospatial analysis of nutrient budgets
(Akselsson et al. 2007) and soils and geology (Kimsey et al. 2011).
These models use a wide variety of data to assess risk of nutrient
depletion or productivity loss after intensive harvesting. However,
their accuracy and resolution are limited by the availability of exist-
ing data, and they are not designed to provide precise information at
Figure 1. Locations of 68 Douglas-fir plantations evaluated in this study, by site N store (total N content of soil to 1.0-m depth plus forest
floor).
2Forest Science • Month 2014
the stand level. Site-specific assessments of potential nutrient deple-
tion under WTH using nutrient balance methods have long been
applied in research (e.g., Boyle et al. 1973, White 1974) and may
also be used as a risk assessment tool if they are sufficiently accurate
and inexpensive to apply. Evans (1999) proposed the “stability
ratio” as a simple risk assessment metric to evaluate narrow-sense
sustainability (i.e., the capacity of a site to sustain productivity over
an indefinite number of rotations). The stability ratio is defined as
the proportion of a given nutrient removed in a single forest harvest,
relative to the total site store of that nutrient. Site store values may be
calculated in various ways, such as soil nutrient store or soil plus
aboveground store. Evans (1999, 2009) used a stability ratio of 0.1
(i.e., 10% of the site store) as an example of a harvest removal rate
below which there is little or no risk to long-term productivity. A
stability ratio ⬎0.3 potentially represents a significant risk to pro-
ductivity, and a stability ratio ⬎0.5 will probably result in a signif-
icant and immediate site productivity decline.
The US Pacific Northwest is potentially an important region for
utilization of harvest residue biomass, with an estimated 7 million
tons of logging residues left on-site annually (Smith et al. 2009).
Tree growth in much of the US Pacific Northwest and in British
Columbia, Canada, is limited by N availability (Turner 1977,
Miller et al. 1986, Chappell et al. 1991); thus, the risk of N deple-
tion is of particular interest under WTH. There is some evidence
that WTH of Douglas-fir (Pseudotsuga menziesii var. menziesii
[Mirb.] Franco) on poorer quality sites may lead to a decline in
productivity (Bigger and Cole 1983, Compton and Cole 1991).
Furthermore, the ability of Douglas-fir to grow under nutrient-poor
conditions, coupled with improvements in tree stock and silvicul-
tural innovations, may mask the decline of site N stores until after
significant depletion has occurred (Lattimore et al. 2009).
In the present study, stability ratios (Evans 1999, 2009) based on
N were calculated for 68 coastal Pacific Northwest Douglas-fir plan-
tations to assess the applicability of this risk assessment tool at a
regional scale. These sites include a wide range of soil types, with
parent materials such as young (i.e., ⬍15,000 years) glacial deposits,
igneous and sedimentary residuum, and volcanic ash. Data collected
at each site between plantation ages 15 and 30 years were used to
quantify site N stores and to project rotation-age N removals under
WTH and SOH scenarios. The objectives of the study were to use
the stability ratio to assess the site-specific risk of long-term N de-
pletion under WTH and SOH and to identify regional patterns
associated with predicted harvest sustainability.
Methods
Study Sites
The study used data from 68 Douglas-fir plantations (plantation
ages of 15–30 years) in western Oregon and Washington (United
States) and on Vancouver Island, British Columbia (Canada); these
research sites had been established between 2008 and 2011 for an
earlier study by the University of Washington Stand Management
Cooperative (Maguire et al. 1991, Littke et al. 2011). The sites are
located on private, state, provincial, and university lands and were
selected to represent the range of site conditions (e.g., productivity,
elevation, slope, slope position) characteristic of regional Douglas-
fir plantations (Figure 1).
Data Collection
At each site, a 15-m-square grid was established, and the Doug-
las-fir tree (dominant or codominant canopy class) closest to each
grid point (n⫽24– 40 at each site) was measured for diameter at
breast height (dbh), total height, and height to live crown (Littke et
al. 2011). Breast-height age was measured on five of these trees per
site. A 10-m-diameter circular plot was established, centered on each
selected Douglas-fir, and dbh and species of every tree in the plot
were recorded (hereafter called “plot trees”).
A soil pit was excavated at each site to a depth of 1.0 m or until a
compacted layer was reached (Littke et al. 2011). Bulk density sam-
ples were collected from each horizon by the core or clod method
(method choice was based on texture and hardness; Blake and
Hartge 1986). The forest floor was sampled by collecting all organic
materials from a 0.5-m
2
plot above each soil pit. Subsamples from
the soil bulk density samples and from the forest floor samples were
dried, ground, and analyzed for total N concentration using a CHN
analyzer (model 2400; Perkin-Elmer, Norwalk, CT). A comprehen-
sive description of soils and methods used to determine parent ma-
terial at each site is given by Littke et al. (2011).
Simulating Biomass Removal
To project harvest removals under WTH and SOH systems,
growth of each of the 68 stands was simulated to a rotation age of 50
to 55 years using the SMC variant of the individual-tree growth
Table 1. Projected stand volume, biomass, and N content at plantation age 50ⴚ55 for 68 coastal Pacific Northwest Douglas-fir
plantations and estimated values previously reported for regional Douglas-fir plantations 45ⴚ60 years of age.
Source
Stand age
(yr)
Stand density
(trees ha
⫺1
)
Stand volume
(m
3
ha
⫺1
)Stemwood biomass
Total aboveground
biomass
Total N content
of trees (kg ha
⫺1
)
...........(Mg ha
⫺1
)...........
This study (range; mean
in parentheses)
50–55 353–1,278 (698) 302–1,125 (830) 162–624 (430) 220–805 (577) 366–1,218 (887)
Ares et al. 2007
a
47 627 914 308 393 605
Bigger and Cole 1983
b
55 281 318 728
134 165 325
Ponette et al. 2001 54 243 747 293 363 440
Homann et al. 1992 50 1,100 275 216
Ranger et al. 1995 60 312 307 418 694
Heilman 1961
c
52 1,000 339 148 216 361
Turner 1980 50 1,110 319 404 737
Turner and Long 1975 49 1,070 178 234
In the previous studies cited here, stand-level estimates were derived by destructively sampling a subset of trees.
a
41% of biomass was naturally regenerated western hemlock; 59% was planted Douglas-fir.
b
Values are for two different stands.
c
Naturally regenerated stand.
Forest Science • Month 2014 3
model ORGANON (the 5-year variation was due to differences in
initial stand age and the model’s 5-year time step) (Hann 2011). A
fixed rotation length was used in this analysis so that the rate of
biomass and nutrient removal could be compared across sites.
ORGANON model inputs at the stand level were the Bruce
(1981) site index, stand age, and breast height age. Site index values
for the stands were calculated using a 10-tree version of King’s
protocol (King 1966, Hanson et al. 2002); values were then con-
verted to the Bruce (1981) site index using an iterative method.
Variables used as tree input data were species, dbh, total height, and
crown ratio. For plot trees, heights and crown ratios were estimated
by ORGANON, except for Douglas-fir, for which heights were
estimated using the allometric equation:
ln(ht ⫺1.3) ⫽a⫹b(1/dbh)
where ht is total height in m, dbh is in cm, and aand bare param-
eters derived for each stand using all measured Douglas-fir heights
from that stand.
The ORGANON simulation was performed in R statistical soft-
ware using dynamic link libraries as described by Gould and Mar-
shall (2011). This approach allows incorporation of the total stem
volume equations of Bruce and DeMars (1974), which have been
determined to be the most accurate equations for regional Douglas-
fir plantations. For species other than Douglas-fir, default
ORGANON stem volume estimation methods were used with the
log top diameter set to 0.
Biomass and N content of Douglas-fir tree components were
estimated by first calculating individual-tree stemwood biomass
based on the stemwood volume output from ORGANON and a
site-specific estimate of Douglas-fir specific gravity, derived from the
western wood density survey (Forest Products Laboratory 1965).
Based on individual-tree stem biomass estimates, total aboveground
biomass and component biomass (i.e., stemwood, stem bark, coarse
roots, and foliage) were predicted using the component biomass
ratio equations of Jenkins et al. (2003). For species other than
Douglas-fir (⬍4% of all stems in the study), the same procedure was
followed, except that specific gravity values from Miles and Smith
(2009) were applied.
To simulate WTH removal, individual-tree estimates of total
aboveground biomass of every tree were summed and converted to a
per-hectare basis for each site; to simulate SOH removal, the pro-
cess was repeated for stemwood ⫹stem bark biomass only.
ORGANON biomass projections were compared with previously
published measured stand biomass values (Table 1) for sites similar
in productivity and age, confirming that the projections were com-
parable after adjustment for differences in stand density.
Simulating N Removal
The N content of total aboveground biomass and of stem-
wood ⫹stem bark biomass was projected for each site using biomass
estimates in combination with the Douglas-fir N concentration
equations from Augusto et al. (2000). These same N concentration
equations were used for the small number of stems of species other
than Douglas-fir, because species-specific equations do not exist for
Figure 2. Projected total aboveground biomass at age 50–55 for
68 coastal Pacific Northwest Douglas-fir plantations, by age 50 site
index (Bruce 1981) and soil parent material.
Figure 3. Projected N removal under WTH and SOH at age
50–55 for 68 coastal Pacific Northwest Douglas-fir plantations,
by site N store (total N content of soil to 1.0-m depth plus forest
floor) and parent material. The solid line represents a stability ratio
of 0.3 and the dashed line represents a stability ratio of 0.1; points
to the left of each line represent stability ratios greater than the
value represented by the line.
Figure 4. Projected total-tree aboveground N content at age
50–55 for 68 coastal Pacific Northwest Douglas-fir plantations, by
site N store (total N content of soil to 1.0-m depth plus forest floor)
and soil parent material.
4Forest Science • Month 2014
many of the other species. This probably resulted in conservative
projections of N removal for many of these species owing to the
relatively high N use efficiency of Douglas-fir (Marion 1979, Au-
gusto et al. 2000, Palviainen and Fine´r 2012).
Site N and Stability Ratios
For each site, per-hectare soil N content to a 1.0-m depth
(or to a compacted layer) was estimated by multiplying, for each
horizon, the measured concentration of total soil N by soil mass, as
determined through bulk density sampling. Horizon estimates were
summed, with any horizon exceeding a depth of 1.0 m truncated at
that depth. Per-hectare forest floor N content was estimated from
total N concentration and measured dry weight per sample.
A per-hectare site N store value was calculated for each site under
three different definitions, the first of which is the standard defini-
tion used in most of the calculations presented here:
1. Belowground N store: sum of soil N and forest floor N.
2. Belowground ⫹residue N store: sum of soil N, forest floor N,
tree coarse root N at rotation age, and logging residue N.
Logging residue N was calculated as the difference between N
removal under WTH and SOH.
3. Belowground ⫹total aboveground N store: sum of soil N,
forest floor N, tree coarse root N at rotation age, and total
aboveground tree N at rotation age.
N stability ratios were then calculated for each site as
N stability ratio ⫽N removal/N store
where N removal is defined as N content of the total aboveground
tree (WTH) or N content of stemwood ⫹stem bark (SOH) and N
store is based on one of the three definitions above. Relationships
among variables were evaluated using Proc Reg in SAS (version 9.2;
SAS Institute, Cary, NC).
Results
Tree Volume and Biomass
Projected stemwood volume for the 68 stands at plantation age
50–55 ranged from 302 to 1,125 m
3
ha
⫺1
, with a mean of 830 m
3
ha
⫺1
(Table 1). Across sites, Douglas-fir comprised an average of
96% of stemwood volume (range ⫽82–100%). Stem biomass pro-
jections (wood plus bark) ranged from 162 to 624 Mg ha
⫺1
, with a
mean of 430 Mg ha
⫺1
. Total-tree aboveground biomass projections
ranged from 220 to 805 Mg ha
⫺1
, with a mean of 577 Mg ha
⫺1
.
Total-tree aboveground biomass was linearly related to site index
(Figure 2). This relationship did not differ by parent material, al-
though none of the sites on sedimentary parent material had a site
index ⬍34 m.
Tree N Content and N Removal
Projected N content in the aboveground portion of trees (i.e.,
WTH N removal) at age 50–55 ranged from 366 to 1,218 kg N
ha
⫺1
, with a mean of 887 kg N ha
⫺1
(Table 1; Figure 3). Projected
SOH N removal ranged from 165 to 737 kg N ha
⫺1
, with a mean of
495 kg N ha
⫺1
. The relationship between tree total aboveground N
and site N store showed that, at lower values of site N store, tree
aboveground N declined at a greater rate (Figure 4). N content of
logging residues, expressed as a fraction of site N store, was approx-
imately 0.1 or less at all but six sites; these six sites all had soils
formed in glacial materials (Figure 5).
Stability Ratios
Stability ratios under SOH ranged from 0.02 to 0.46 (mean ⫽
0.08), whereas stability ratios for WTH ranged from 0.04 to 1.03
(mean ⫽0.14) (Figure 6). Under the SOH scenario, 24% of sites
had stability ratios ⱖ0.1, and 1% of sites had stability ratios ⱖ0.3.
Under the WTH scenario, 49% of sites had stability ratios ⱖ0.1,
and 6% of sites had stability ratios ⱖ0.3.
Stability ratios were also calculated based on alternative defini-
tions of site N store (Table 2). The first of these alternative defini-
tions included belowground plus residue N. Under this definition of
site N store, stability ratios under SOH ranged from 0.02 to 0.26
(mean ⫽0.07), and stability ratios for WTH ranged from 0.04 to
0.84 (mean ⫽0.14). Under the SOH scenario, 16% of sites had
stability ratios ⱖ0.1, and no site had a stability ratio ⱖ0.3. Under
the WTH scenario, 49 and 6% of sites had stability ratios ⬎0.1 and
⬎0.3, respectively.
The second alternative definition of site N store included below-
ground plus total aboveground N. Stability ratios under SOH
ranged from 0.02 to 0.21 (mean ⫽0.06), and stability ratios for
Figure 5. Projected N content of logging residue at age 50–55, as
a fraction of site N store (total N content of soil to 1.0-m depth plus
forest floor), for 68 coastal Pacific Northwest Douglas-fir planta-
tions, by site N store and parent material. One data point is not
shown (a residue N value of 0.56).
Figure 6. Stability ratios (SRs) for WTH and SOH scenarios in 68
coastal Pacific Northwest Douglas-fir plantations, by site N store
(total N content of soil to 1.0-m depth plus forest floor). The dashed
gray line represents a stability ratio of 0.3; the solid gray line
represents a stability ratio of 0.1. One data point is not shown (a
whole-tree harvest stability ratio of 1.03).
Forest Science • Month 2014 5
WTH ranged from 0.04 to 0.46 (mean ⫽0.11). Under the SOH
scenario, 10% of sites had stability ratios ⱖ0.1, and no site had a
stability ratio ⱖ0.3. Under the WTH scenario, 43 and 1% of sites
had stability ratios ⱖ0.1 and ⱖ0.3, respectively.
Definition of site N store had a greater effect on the stability ratio
for sites with smaller soil N stores. For sites with ⬍3.0 Mg ha
⫺1
soil ⫹forest floor N, the belowground ⫹residues definition of site
N store reduced stability ratios by an average of 0.06 across both
treatments compared with the original definition (i.e., belowground
N). Under the belowground ⫹total aboveground definition of site
N store, the stability ratio on these N-poor sites was reduced by an
average of 0.14 compared with the original definition. In contrast,
for sites with ⬎3.0 Mg N ha
⫺1
, the alternative site N store defini-
tions produced only a negligible reduction in stability ratios (a
change of ⬍0.01).
Based on the relationships between site N store and stability ratio
under WTH and SOH scenarios (Figure 6), it was possible to esti-
mate a site N store value above which the stability ratio is predicted
to be ⬍0.1 (i.e., no anticipated risk of long-term N depletion) for
sites and plantations comparable to those in this study. For SOH,
this site N store value was 4.0 Mg N ha
⫺1
and for WTH it was 9.0
MgNha
⫺1
. A high risk of N depletion (stability ratios ⱖ0.3) would
be expected on sites where the N store was ⱕ0.9 Mg N ha
⫺1
under
SOH and ⱕ2.2 Mg N ha
⫺1
under WTH.
Discussion
Tree Biomass and N Projections
The total-tree and stemwood biomass projections for most of the
stands in this study exceeded those previously reported for Doug-
las-fir at a similar rotation age (Table 1). Because projections of tree
N content were based in part on these biomass projections, N con-
tent projections also were higher than the estimates of most previous
studies. There are several factors that probably contributed to the
higher biomass projections in this study. First, five of the eight
previous studies (Heilman 1961, Turner and Long 1975, Turner
1980, Bigger and Cole 1983, Homann et al. 1992) were on sites
with relatively low soil N content and low productivity; biomass
estimates from these studies (mean ⫽259 Mg ha
⫺1
) fall within the
lower end of the range of values from our study. Three of the eight
previous studies were on productive sites (Ranger et al. 1995,
Ponette et al. 2001, Ares et al. 2007). However, in two of these three
studies (Ranger et al. 1995, Ponette et al. 2001), the low tree bio-
mass values were influenced by low stand densities (312 and 243
trees ha
⫺1
). The third study (Ares et al. 2007) was located on a
highly productive site and had rotation-age stand density and vol-
ume values comparable to the means from our 68 stands; yet the
biomass estimates of that study were lower than those of the high-
productivity sites in our study. This discrepancy may be explained
by a difference in wood density. Stemwood specific gravity mea-
sured in the Ares et al. (2007) study was 0.36 for Douglas-fir and
0.30 for western hemlock (Tsuga heterophylla [Raf.] Sarg.); these
values are unusually low for the region. Other regional studies of
stemwood density, including studies of intensively managed stands
and highly productive sites, have found mean values for Douglas-fir
ranging from 0.43 to 0.51 (Forest Products Laboratory 1965, Gart-
ner et al. 2002, Miles and Smith 2009, Kantavichai et al. 2010,
El-Kassaby et al. 2011). Because most of the recent studies have
reported specific gravity values for Douglas-fir comparable to those
of the western wood density survey (Forest Products Laboratory
1965), we determined that values from the 1965 wood density
survey were still applicable in the present analysis, despite the in-
creased tree growth rates associated with improved genetics and
more intensive management.
Regional Stability Ratios for WTH and SOH
Based on Evans’ (1999, 2009) proposed stability ratio guidelines,
only a small percentage of the 68 sites (1% in SOH and 6% in
WTH) had stability ratios suggesting a high risk of N depletion (i.e.,
ⱖ0.3 using the belowground N store definition: the sum of soil N
and forest floor N) (Table 2). All four sites with stability ratios ⬎0.3
under WTH had soils formed in glacial materials; three of these
were on Vancouver Island and one was in the southern Puget Sound
region of Washington. Site N store for these four sites averaged 1.4
MgNha
⫺1
. In contrast, the 64 sites with WTH stability ratios ⬍0.3
averaged 9.9 Mg N ha
⫺1
. Only one site, located in central Vancou-
ver Island, British Columbia, had a SOH stability ratio ⬎0.3. That
site had a SOH stability ratio of 0.47 and a WTH stability ratio of
1.03, both substantially higher than those of all other sites. The high
stability ratios at that site were a result of extremely low soil N (0.4
MgNha
⫺1
). The soil was formed in glacial parent material, shallow
(0.40 m), coarse textured, and with a high coarse-fragment content.
The foliar N concentration of Douglas-fir at the site was 8.4 mg g
⫺1
,
which was the lowest among the 68 sites and is within a range
diagnostic of very severe N deficiency (Ballard and Carter 1986).
Nearly half of the study sites had stability ratios of ⱖ0.1 under a
WTH scenario, and almost one-quarter of sites had stability ratios of
ⱖ0.1 under SOH. This 10% removal per rotation level used to
define sites as potentially at risk is relatively conservative, given that
regional rotation lengths for Douglas-fir are usually 40 years or
longer. During that period of time, even small annual inputs of N
Table 2. Summary of stability ratio (SR) values (i.e., the ratio of harvest N removal to site N store) for 68 coastal Pacific Northwest
Douglas-fir plantations, based on three definitions of site N store.
Site N store definition Harvest system Sites with SR ⱖ0.1 Sites with SR ⱖ0.3 Sites with SR ⱖ0.1 Sites with SR ⱖ0.3
..............(n).............. .............(%) .............
Belowground
a
Stem-only 16 1 24 1
Whole-tree 33 4 49 6
Belowground ⫹residues
b
Stem-only 11 0 16 0
Whole-tree 33 4 49 6
Belowground ⫹total aboveground
c
Stem-only 7 0 10 0
Whole-tree 29 1 43 1
A stability ratio (SR) value ⱖ0.1 indicates a potential risk of long-term nutrient depletion, whereas an SR value ⱖ0.3 indicates a high risk of long-term nutrient depletion
(Evans 1999, 2009).
a
Mineral soil N and forest floor N.
b
Mineral soil N, forest floor N, tree coarse root N at rotation age, and logging residue N.
c
Mineral soil N, forest floor N, tree coarse root N at rotation age, and total aboveground tree N at rotation age.
6Forest Science • Month 2014
(e.g., atmospheric deposition or biological N fixation) may cumu-
latively compensate for a meaningful portion of the N removed
during harvest (Boyle et al. 1973, Johnson et al. 1982, Bormann and
Gordon 1989). It is unlikely that all sites with stability ratios ⱖ0.1
are at risk of N depletion; however, sites with this level of nutrient
removal may warrant additional scrutiny and some may also warrant
further nutrient inventory if managed under an intensive harvest
system.
Although most of the sites with the highest stability ratios were
those with glacially derived soils, it is not possible to accurately rate
N depletion risk (i.e., stability ratio) or to predict site N store, based
on parent material alone. In an analysis of the soils on these sites,
mean N content of soils formed in glacial materials was 7.3 Mg N
ha
⫺1
and did not differ significantly from that of the much older
soils formed in igneous rock (9.5 Mg N ha
⫺1
) (Littke et al. 2011).
Furthermore, in the present study, several of the sites with the lowest
stability ratios had glacial soils. We tested site index and foliar N
concentration as potential predictors of stability ratio, but neither of
these variables was a statistically significant predictor. However, the
strong relationship between site N store and stability ratio (not
unexpected, given that site N store is used in the stability ratio
calculation) enables prediction of stability ratio based on N store for
sites within the range of conditions occurring in this study (Figure
6). Because of this relationship between site N store and stability
ratio in the region studied, assessment of N depletion risk based on
site N store alone may be sufficient for some applications. Doing so
would eliminate the need for prediction of N amounts removed
during harvest. For example, based on our findings, a regional site
under WTH with ⬍9.0 Mg N ha
⫺1
may warrant additional scru-
tiny or sampling and a site with ⬍2.2 Mg N ha
⫺1
should be criti-
cally examined to determine whether WTH is an appropriate har-
vest system.
Under the increased nutrient removal rates of WTH systems,
fertilization may be an important tool for maintaining productivity,
albeit one dependent on the fluctuating economics of fertilization
(Ma¨lko¨nen 1976, Fox 2000, Egnell 2011). Among the sites in this
study, fertilization may be particularly important where site N store
is low. The harvest residue N removed under WTH, materials that
would otherwise have been left onsite, represents a substantial por-
tion (⬎10%) of total site N store on the low-N sites (Figure 5). In
boreal and temperate forests, fertilization has been shown to com-
pensate for productivity losses that may occur after WTH (Helmis-
aari et al. 2011, Mason et al. 2012). The amount of a given nutrient
added through fertilization is not likely to have a significant effect on
a site’s total nutrient store, but it can compensate for a significant
portion of removal through WTH. In the present study, the pro-
jected additional N removed under WTH, relative to SOH, ranged
from 201 to 538 kg ha
⫺1
(average ⫽390 kg ha
⫺1
); a typical fertil-
izer application may include approximately 150–200 kg N ha
⫺1
.
Although smaller in magnitude than the N removed in harvest, the
fertilizer addition represents the available form of the nutrient and is
applied at a time and rate to most efficiently benefit tree growth.
Although the benefit of N fertilization on tree growth rate is often
considered to last only 5–10 years in the region (Miller 1988),
productivity gains associated with fertilization have been shown to
carry over into the next rotation. However, this carryover has only
been demonstrated under a SOH system and may not occur under
WTH (Footen et al. 2009).
Defining Stability Ratio
Stability ratio is intended to be used as a simple risk assessment
tool through which many regional sites can be compared to identify
those most susceptible to nutrient depletion. Although there are
many ways in which precision of nutrient balance estimates could be
enhanced beyond the stability ratio calculation, each would require
additional data. For example, if mineral N were used instead of total
N, estimates of atmospheric N deposition, soil N mineralization
rate, N fixation, and leaching losses could be incorporated into the
calculation, but these would necessitate additional site-specific data
that could be time-consuming and expensive to acquire for numer-
ous sites across a region. There has been no experimental validation
of the stability ratio concept in temperate forests; further field stud-
ies would be necessary to provide this information or to compare the
stability ratio concept with the more data-intensive nutrient balance
approach of assessing sustainability.
The stability ratio was calculated using the site nutrient store,
which can be defined in many ways, three of which are presented in
Table 2. The nutrient store definition selected for most of the anal-
yses in this study was total nutrient content of the soil (to a defined
depth and excluding coarse roots) plus that of the forest floor. This
definition treated N content of standing trees as an ephemeral nu-
trient pool, removed at the end of each rotation and thus not a part
of the site store. The mass and nutrient content of coarse tree roots
is a function of tree age and therefore was also considered ephemeral
rather than part of the site nutrient store. It should also be noted that
there are few equations for estimating root biomass and nutrient
content of most tree species. Except on a small number of N-poor
sites, the addition of coarse root and aboveground tree N pools had
little impact on the stability ratio; thus, in future applications of the
stability ratio concept, it may be appropriate to give particular at-
tention to nutrient cycling on nutrient-poor sites when choosing
how to define site nutrient store.
To incorporate the rate of N removal into the stability ratio
calculation, we chose to use a fixed rotation length across all sites
when projecting tree biomass accrual and N removal. If stability
ratios were calculated using harvest N removal, without incorporat-
ing the length of time until harvest, ratios would not reflect the fact
that N removal occurs more frequently on more productive sites
where trees are harvested at shorter intervals. An approach to
calculating nutrient removal rate that may be more realistic in pro-
duction forestry is to project stand growth at each site to the rotation
age that optimizes the financial rate of return at that site. Subse-
quently, removals at all sites would be adjusted to a common time
frame (e.g., 50 years) to incorporate the rate of removal into the
calculation. For example, nutrient removal at a site with a 40-year
rotation would be multiplied by 1.25 to meet the 50-year time
frame. This alternative approach would be most practical if the
region of interest fell within a single ownership; in the present study,
we did not have sufficient site-specific information to apply this
approach.
Conclusion
This study shows that the stability ratio can be applied at a
regional level to indicate which sites warrant additional evaluation
for risk of nutrient depletion under a given silvicultural system. The
stability ratio concept is flexible in that factors such as site nutrient
store and rate of N removal can be adjusted to fit different assump-
tions and objectives. Based on the N stability ratio, there is a low risk
of N depletion and associated productivity loss under SOH for the
Forest Science • Month 2014 7
majority of Douglas-fir sites in the coastal Pacific Northwest. Under
a scenario of repeated WTH, nearly half of the sites assessed were
potentially at risk for long-term N depletion (sites with ⬍9.0 Mg
ha
⫺1
site N store), and 6% were at high risk (sites with ⬍2.2 Mg
ha
⫺1
site N store). Sites with the highest risk of N depletion had soils
with low N stores, most of which were young, glacially derived soils
on Vancouver Island, British Columbia, and in the Puget Sound
region of Washington. On these sites, WTH would remove mate-
rials, otherwise left on-site during SOH, containing N equivalent of
10 –20% or more of the total N store of the site. Fertilization may be
necessary to maintain productivity on these sites under WTH. In
contrast, harvest system (WTH versus SOH) had little effect on N
depletion risk for sites with large N stores. Based on the relationship
between the stability ratio and site N store, it was possible to calcu-
late site N store values representing guidelines for N depletion risk
under a given harvest system.
Literature Cited
ABBAS, D., D. CURRENT,M.PHILLIPS,R.ROSSMAN,H.HOGANSON,AND
K.N. BROOKS. 2011. Guidelines for harvesting forest biomass for en-
ergy: A synthesis of environmental considerations. Biomass Bioenergy
35:4538–4546.
AKSELSSON, C., O. WESTLING,H.SVERDRUP,AND P. GUNDERSEN. 2007.
Nutrient and carbon budgets in forest soils as decision support in sus-
tainable forest management. For. Ecol. Manage. 238:167–174.
ARES, A., T.A. TERRY, K.B. PIATEK, R.B. HARRISON, R.E. MILLER, B.L.
FLAMING, C.W. LICATA,ET AL. 2007. The Fall River Long-Term Site
Productivity study in coastal Washington: Site characteristics, experi-
mental design, and biomass, carbon and nitrogen stores before and after
harvest. USDA For. Serv., Gen. Tech. Rep. PNW-GTR-691, Port-
land, OR. 85 p.
AUGUSTO, L., J. RANGER,Q.PONETTE,AND M. RAPP. 2000. Relationships
between forest tree species, stand production, and stand nutrient
amount. Ann. For. Sci. 57:313–324.
BALLARD, T.M., AND R.E. CARTER. 1986. Evaluating forest stand nutrient
status. Land Management Rep. No. 20, Ministry of Forests, Victoria,
BC, Canada.
BIGGER, C.M., AND D.W. COLE. 1983. Effects of harvesting intensity on
nutrient losses and future productivity in high and low productivity red
alder and Douglas-fir stands. P. 167–178 in IUFRO symposium on forest
site and continuous productivity, Ballard, R., and S.P. Gessel (eds.).
USDA For. Serv., Gen. Tech. Rep. PNW-GTR-163, Portland, OR.
BLAKE, G.R., AND K.H. HARTGE. 1986. Bulk density. P. 363–375 in Methods
of soil analysis, part I. Physical and mineralogical methods, 2nd ed., Klute, A.
(ed.). Agronomy Monogr. No. 9, American Society of Agronomy, Inc. and
Soil Science Society of America, Inc., Madison, WI.
BORMANN, B.T., AND J.C. GORDON. 1989. Can intensively managed for-
est ecosystems be self-sufficient in nitrogen? For. Ecol. Manage.
29(1):95–103.
BOYLE, J.R., J.J. PHILLIPS,AND A.R. EK. 1973. “Whole tree” harvesting:
Nutrient budget evaluation. J. For. 71(12):760–762.
BRUCE, D. 1981. Consistent height-growth and growth-rate estimates for
remeasured plots. For. Sci. 27(4):711–725.
BRUCE, D., AND D.J. DEMARS. 1974. Volume equations for second-growth
Douglas-fir. USDA For. Serv., Res. Note PNW-RN-239, Portland, OR.
5p.
CHAPPELL, H.N., D.W. COLE, S.P. GESSEL,AND R.B. WALKER. 1991.
Forest fertilization research and practice in the Pacific Northwest. Fer-
tilizer Res. 27(1):129–140.
COLE, D.W., AND J.E. COMPTON. 1994. Effect of harvest removal on
productivity of a 15-year-old Douglas-fir plantation. Agron. Abstr.
86:375.
COMPTON, J.E., AND D.W. COLE. 1991. Impact of harvest intensity on
growth and nutrition of successive rotations of Douglas-fir. P. 151–161
in Long-term field trials to assess environmental impacts of harvesting,
Dyck, W.J., and C.A. Mees (eds.). Forest Research Institute, Bull. 161,
Roturua, New Zealand.
DYCK, W.J., AND D.W. COLE. 1994. Strategies for determining conse-
quences of harvesting and associated practices on longterm productivity.
P. 13–40 in Impacts of forest harvesting on long-term site productivity,
Dyck, W.J., D.W. Cole, and N.B. Comerford (eds.). Chapman and
Hall, New York.
EGNELL, G. 2011. Is the productivity decline in Norway spruce following
whole-tree harvesting in the final felling in boreal Sweden permanent or
temporary? For. Ecol. Manage. 261(1):148–153.
EISENBIES, M.H. 2006. Long-term timber productivity research on inten-
sively managed pine forests of the South. P. 139–153 in Long-term
silvicultural and ecological studies: Results for science and management,
Ireland, L.C., A.E. Camp, J.C. Brissette, and Z.R. Donohew (eds.). Yale
University, GISF Res. Pap. 005, New Haven, CT.
EISENBIES, M.H., E.D. VANCE, W.M. AUST,AND J.R. SEILER. 2009. In-
tensive utilization of harvest residues in southern pine plantations:
Quantities available and implications for nutrient budgets and sustain-
able site productivity. BioEnergy Res. 2(3):90–98.
EL-KASSABY, Y.A., S. MANSFIELD,F.ISIK,AND M. STOEHR. 2011. In situ wood
quality assessment in Douglas-fir. Tree Genet. Genomes 7(3):553–561.
EVANS, J. 1999. Sustainability of forest plantations: The evidence—A review of
evidence concerning narrow-sense sustainability of planted forests. Depart-
ment for International Development, London, UK. 64 p.
EVANS, J. 2009. Sustainable silviculture and management. P. 113–140 in
Planted forests: Uses, impacts and sustainability. CAB International, Wall-
ingford, UK.
FARVE, R., AND C. NAPPER. 2009. Biomass fuels & whole tree harvesting
impacts on soil productivity—Review of literature. USDA For. Serv., San
Dimas Technology and Development Center, San Dimas, CA. 60 p.
FLEMING, R.L., R.F. POWERS, N.W. FOSTER, J.M. KRANABETTER, A.D.
SCOTT,F.PONDER JR., S. BERCH JR., ET AL. 2006. Effects of organic
matter removal, soil compaction, and vegetation control on 5-year seed-
ling performance: A regional comparison of long-term soil productivity
sites. Can. J. For. Res. 36:529–550.
FOOTEN, P.W., R.B. HARRISON,AND B.D. STRAHM. 2009. Long-term
effects of nitrogen fertilization on the productivity of subsequent
stands of Douglas-fir in the Pacific Northwest. For. Ecol. Manage.
258:2194–2198.
FOREST PRODUCTS LABORATORY. 1965. Western wood density survey: Report
no. 1. USDA For. Serv., Forest Products Laboratory, Madison, WI. 58 p.
FOX, T.R. 2000. Sustained productivity in intensively managed forest plan-
tations. For. Ecol. Manage. 138:187–202.
GARTNER, B.L., E.M. NORTH, G.R. JOHNSON,AND R. SINGLETON. 2002.
Effects of live crown on vertical patterns of wood density and growth in
Douglas-fir. Can. J. For. Res. 32(3):439–447.
GOULD, P.J., AND D.D. MARSHALL. 2011. Running ORGANON in R.
Oregon State University, Corvallis, OR. 8 p.
HANN, D.W. 2011. ORGANON user’s manual edition 9.1. Oregon State
University, Corvallis, OR.
HANSON, E.J., D.L. AZUMA,AND B.A. HISEROTE. 2002. Site index equa-
tions and mean annual increment equations for Pacific Northwest Research
Station Forest Inventory and Analysis Inventories. USDA For. Serv., Res.
Note PNW-RN-533, Portland, OR. 24 p.
HEILMAN, P.E. 1961. Effects of nitrogen fertilization on the growth and ni-
trogen nutrition of low-site Douglas-fir stands. Thesis, University of Wash-
ington, Seattle, WA. 426 p.
HELMISAARI, H.-S., K. HOLT HANSSEN,S.JACOBSON,M.KUKKOLA,J.
LUIRO,A.SAARSALMI,P.TAMMINEN,AND B. TVEITE. 2011. Logging
residue removal after thinning in Nordic boreal forests: Long-term im-
pact on tree growth. For. Ecol. Manage. 261:1919–1927.
8Forest Science • Month 2014
HOMANN, P.S., H. VAN MIEGROET, D.W. COLE,AND G.V. WOLFE. 1992.
Cation distribution, cycling, and removal from mineral soil in Douglas-
fir and red alder forests. Biogeochemistry 16:121–150.
JACOBSON, S., M. KUKKOLA,E.M
¨
ALK ¨
ONEN,AND B. TVEITE. 2000. Im-
pact of whole-tree harvesting and compensatory fertilization on growth
of coniferous thinning stands. For. Ecol. Manage. 129:41–51.
JANOWIAK, M.K., AND C.R. WEBSTER. 2010. Promoting ecological sus-
tainability in woody biomass harvesting. J. For. 108(1):16–23.
JENKINS, J.C., D.C. CHOJNACKY, L.S. HEATH,AND R.A. BIRDSEY. 2003.
National-scale biomass estimators for United States tree species. For. Sci.
49(1):12–35.
JOHNSON, D.W., AND P.S. CURTIS. 2001. Effects of forest management on
soil C and N storage: A meta analysis. For. Ecol. Manage. 140:227–238.
JOHNSON, D.W., D.C. WEST, D.E. TODD,AND L.K. MANN. 1982. Effects
of sawlog vs. whole-tree harvesting on the N, P, K, and Ca budgets of an
upland mixed oak forest. Soil Sci. Soc. Am. J. 46:1304–1309.
KANTAVICHAI, R., D.G. BRIGGS,AND E.C. TURNBLOM. 2010. Effect of
thinning, fertilization with biosolids, and weather on interannual ring
specific gravity and carbon accumulation of a 55-year-old Douglas-fir
stand in western Washington. Can. J. For. Res. 40:72–85.
KIMMINS, J.P. 1977. Evaluation of the consequences for future tree pro-
ductivity of the loss of nutrients in whole-tree harvesting. For. Ecol.
Manage. 1:169–183.
KIMSEY,M.JR., D. PAGE-DUMROESE,AND M. COLEMAN. 2011. Assessing
bioenergy harvest risks: Geospatially explicit tools for maintaining soil
productivity in western US forests. Forests 2:797–813.
KING, J.E. 1966. Site index curves for Douglas-fir in the Pacific Northwest.
Weyerhaeuser Co., Forestry Research Center, Weyerhaeuser Forestry
Paper No. 8, Centralia, WA. 49 p.
LATTIMORE, B., C.T. SMITH, B.D. TITUS,I.STUPAK,AND G. EGNELL.
2009. Environmental factors in woodfuel production: Opportunities,
risks, and criteria and indicators for sustainable practices. Biomass Bio-
energy 33:1321–1342.
LITTKE, K.M., R.B. HARRISON, D.G. BRIGGS,AND A.R. GRIDER. 2011.
Understanding soil nutrients and characteristics in the Pacific North-
west through parent material origin and soil nutrient regimes. Can. J.
For. Res. 41(10):2001–2008.
MAGUIRE, D.A., W.S. BENNETT, J.A. KERSHAW,R.GONYEA,AND H.N.
CHAPPELL. 1991. Establishment report: Stand Management Cooperative
silviculture project field installations. College of Forestry, University of
Washington, Seattle, WA. 42 p.
M¨
ALK ¨
ONEN, E. 1976. Effect of whole-tree harvesting on soil fertility. Silva
Fenn. 10:157–164.
MARION, G.K. 1979. Biomass and nutrient removal in long-rotation
stands. P. 98–100 in Impact of intensive harvesting on forest nutrient
cycling, Leaf, A.L. (ed.). State University of New York, Syracuse, NY.
MASON, W.L., H.M. MCKAY,A.WEATHERALL,T.CONNOLLY,AND A.J.
HARRISON. 2012. The effects of whole-tree harvesting on three sites in
upland Britain on the growth of Sitka spruce over ten years. Forestry
85(1):111–123.
MILES, P.D., AND W.B. SMITH. 2009. Specific gravity and other properties of
wood and bark for 156 tree species found in North America. USDA For.
Serv., Res. Note NRS-RN-38, Northern Research Station, Newtown
Square, PA. 35 p.
MILLER, H.G. 1988. Long-term effects of application of nitrogen fertilizers
on forest sites. P. 97–106 in Forest site evaluation and long-term produc-
tivity, Cole, D.W., and S.P. Gessel (eds.). University of Washington
Press, Seattle, WA.
MILLER, R.E., P.R. BARKER, C.E. PETERSON,AND S.R. WEBSTER. 1986. Using
nitrogen fertilizers in management of coast Douglas-fir: I. Regional trends
of response. P. 290–303 in Douglas- fir: Stand management for the future,
Oliver, C.D., D.P. Hanley, and J.A. Johnson (eds.). College of Forest Re-
sources, Contrib. No. 55, University of Washington, Seattle, WA.
NORD-LARSEN, T. 2002. Stand and site productivity response following
whole-tree harvesting in early thinnings of Norway spruce (Picea abies L.
Karst.). Biomass Bioenergy 23:1–12.
PALVIAINEN, M., AND L. FIN´
ER. 2012. Estimation of nutrient removals in
stem-only and whole-tree harvesting of Scots pine, Norway spruce, and
birch stands with generalized nutrient equations. Eur. J. For. Res.
131(4):945–964.
PONETTE, Q., J. RANGER,J.OTTARINI,AND E. ULRICH. 2001. Aboveg-
round biomass and nutrient content of five Douglas-fir stands in France.
For. Ecol. Manage. 142:109–127.
POWERS, R.F., D.A. SCOTT, F.G. SANCHEZ, R.A. VOLDSETH,D.PAGE-
DUMROESE, J.D. ELIOFF,AND D.M. STONE. 2005. The North Amer-
ican Long-Term Soil Productivity experiment: Findings from the first
decade of research. For. Ecol. Manage. 220:31–50.
RANGER, J., R. MARQUES,M.COLIN-BELGRAND,N.FLAMMANG,AND D.
GELHAYE. 1995. The dynamics of biomass and nutrient accumulation
in a Douglas-fir (Pseudotsuga menziesii Franco) stand studies using a
chronosequence approach. For. Ecol. Manage. 72(2–3):167–183.
SAARSALMI, A., P. TAMMINEN,M.KUKKOLA,AND R. HAUTAJ ¨
ARVI. 2010. Whole-
tree harvesting at clear-felling: Impact on soil chemistry, needle nutrient concen-
trations and growth of Scots pine. Scand. J. For. Res. 25(2):148–156.
SMITH, W.B., P.D. MILES, C.H. PERRY,AND S.A. PUGH. 2009. Forest
resources of the United States, 2007. USDA For. Serv., Gen. Tech. Rep.
WO-GTR-78, Washington, DC. 336 p.
SOLLINS, P., J.E. MEANS,AND R. BALLARD. 1983. Predicting long-term
effects of silvicultural practices on forest site productivity. P. 201–211 in
IUFRO symposium on forest site and continuous productivity, Ballard, R.,
and S.P. Gessel (eds.). USDA For. Serv., Gen. Tech. Rep. PNW-
GTR-163, Pacific Northwest Research Station, Portland, OR.
STUPAK, I., T. NORDFJELL,AND P. GUNDERSEN. 2008. Comparing bio-
mass and nutrient removals of stems and fresh and predried whole trees
in thinnings in two Norway spruce experiments. Can. J. For. Res.
38(10):2660–2673.
THIFFAULT, E., K.D. HANNAM,D.PAR ´
E, B.D. TITUS, P.W. HAZLETT,
D.G. MAYNARD,AND S. BRAIS. 2011. Effects of forest biomass harvest-
ing on soil productivity in boreal and temperate forests—A review.
Environ. Rev. 19:278–309.
TURNER, J. 1977. Effect of nitrogen availability on nitrogen cycling in a
Douglas-fir stand. For. Sci. 23:307–316.
TURNER, J. 1980. Nitrogen and phosphorus distributions in naturally regen-
erated Eucalyptus ssp. and planted Douglas-fir. Aust. For. Res. 10:289–294.
TURNER, J. 1981. Nutrient cycling in an age sequence of western Washing-
ton Douglas-fir stands. Ann. Bot. 48:159–169.
TURNER, J., AND J.N. LONG. 1975. Accumulation of organic matter in a
series of Douglas-fir stands. Can. J. For. Res. 5:681–690.
US DEPARTMENT OF ENERGY. 2009. An updated annual energy outlook 2009
reference case reflecting provisions of the American Recovery and Reinvestment
Act and recent changes in the economic outlook. US Department of Energy,
Energy Information Administration, Washington, DC. 56 p.
WALL, A. 2012. Risk analysis of effects of whole-tree harvesting on site
productivity. For. Ecol. Manage. 282:175–184.
WALMSLEY, J.D., D.L. JONES,B.REYNOLDS, M.H. PRICE,AND J.R. HEA-
LEY. 2009. Whole tree harvesting can reduce second rotation forest
productivity. For. Ecol. Manage. 257(3):1104–1111.
WEETMAN, G.L., AND B. WEBBER. 1972. The influence of wood harvesting on
the nutrient status of two spruce stands. Can. J. For. Res. 2(3):351–369.
WELLS, C.G., AND J.R. JORGENSEN. 1979. Effects of intensive harvesting
on nutrient supply and sustained productivity. P. 212–230 in Impact of
intensive harvesting on forest nutrient cycling, Leaf, A.L. (ed.). State Uni-
versity of New York, Syracuse, NY.
WHITE, E.H. 1974. Whole-tree harvesting depletes soil nutrients. Can. J.
For. Res. 4:530–535.
WHITE, E.M. 2010. Woody biomass for bioenergy and biofuels in the United
States—A briefing paper. USDA For. Serv., Gen. Tech. Rep. PNW-
GTR-825, Pacific Northwest Research Station, Portland, OR.
Forest Science • Month 2014 9
