Effects of winter selective tree harvest (1)

Forest Ecology and Management 259 (2010) 257–265

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Forest Ecology and Management
journal homepage: www.elsevier.com/locate/foreco

Effects of winter selective tree harvest on soil microclimate and surface CO2
flux of a northern hardwood forest
Jennifer L. Stoffel a,b,1,*, Stith T. Gower a, Jodi A. Forrester a, David J. Mladenoff a
a
b

Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, 120 Russell Labs, Madison, WI 53706, United States
Division of Science and Mathematics, Upper Iowa University, 605 Washington Street, P.O. Box 1857, Fayette, IA 52142, United States

A R T I C L E I N F O

A B S T R A C T

Article history:

Received 9 March 2009
Received in revised form 4 October 2009
Accepted 5 October 2009

Soil surface CO2 flux (Sflux) is the second largest terrestrial ecosystem carbon flux, and may be affected by
forest harvest. The effects of clearcutting on Sflux have been studied, but little is known about the effect of
alternative harvesting methods such as selective tree harvest on Sflux. We measured Sflux before and after
(i) the creation of forest canopy gaps (simulating group tree selection harvests) and (ii) mechanized
winter harvest but no tree removal (simulating ground disturbance associated with logging). The
experiment was carried out in a sugar maple dominated forest in the Flambeau River State Forest,
Wisconsin. Pre-treatment measurements of soil moisture, temperature and Sflux were measured
throughout the growing season of 2006. In January–February 2007, a harvester created the canopy gaps
(200–380 m2). The mechanization treatment consisted of the harvester traveling through the plots for a
similar amount of time as the gap plots, but no trees were cut. Soil moisture and temperature and Sflux
were measured throughout the growing season for 1 year prior to harvest and for 2 years after harvest.
Soil moisture and temperature were significantly greater in the gap than mechanized and control
treatments. Instantaneous Sflux was positively correlated to soil moisture and soil temperature at 2 and
10 cm, but temperature at 10 cm was the single best predictor. Annual Sflux was not significantly
different among treatments prior to winter 2007 harvest, and was not significantly different among
treatments after harvest. Annual (+1 std. err.) Sflux averaged 967 + 72, 1011 + 72, and

1012 + 72 g C m2 year1 in the control, mechanized and gap treatments, respectively, for the 2-year
post-treatment period. The results from this study suggest selective group tree harvest significantly
increases soil moisture and temperature but does not significantly influence Sflux.
ß 2009 Elsevier B.V. All rights reserved.

Keywords:
Soil surface CO2 flux
Selective tree harvest
Northern hardwood forest
Harvesting
Microclimate

1. Introduction
Soil carbon accounts for approximately 60% of the terrestrial
carbon (Landsberg and Gower, 1997) 34% of which occurs in forest
soils (Post et al., 1982). Soil carbon is the long-term balance between
detritus production and decomposition. Temperate forest soils
generally accumulate 5.6 g C m2 year1, which is second only to
the boreal forest (Schlesinger, 1997; Landsberg and Gower, 1997).
Even small accumulation rates when summed over a biome can

comprise an important carbon sink. Therefore, the storage of carbon
in forests soils is an important area of research, especially as the
atmospheric levels of CO2 continue to rise (Houghton et al., 2001).
Soil surface CO2 flux (Sflux) is the second largest carbon flux in
temperate forests (Raich and Schlesinger, 1992). Sflux is the sum of

* Corresponding author at: Division of Science and Mathematics, Upper Iowa
University, 605 Washington Street, P.O. Box 1857, Fayette, IA 52142, United States.
Tel.: +1 563 425 5847; fax: +1 563 425 5332.
E-mail address: stoffelj@uiu.edu (J.L. Stoffel).
1
Formerly: Jennifer L. Martin.
0378-1127/$ – see front matter ß 2009 Elsevier B.V. All rights reserved.
doi:10.1016/j.foreco.2009.10.004

autotrophic root respiration and microbial respiration. The root
contribution to total Sflux ranges from 30 to 50% for most terrestrial
ecosystems (Bond-Lamberty et al., 2004) suggesting that heterotrophic respiration is the largest contributor. Microbial respiration
is strongly influenced by soil temperature and moisture, while root
respiration is influenced by root mass, soil temperature and canopy

photosynthesis.
Minor changes in soil carbon turnover rates could have major
implications on regional carbon dynamics given the size of the
temperate forests and their importance as a source for wood fiber.
Scientists have suggested that harvesting unmanaged or mature
forests decreases soil and forest floor carbon content (Covington,
1981; Mattson and Smith, 1993; Brais et al., 1995; Seely et al., 2002;
Yanai et al., 2003). The decreased carbon content in the forest floor
and mineral soil may result in increased microbial respiration,
leaching, and decreases in detritus inputs (i.e. fine roots and coarse
woody debris) (Alban, 1982; Landsberg and Gower, 1997; Yanai
et al., 2003). However, results from both a meta-analysis (Johnson
and Cutis, 2001) and a case study (Martin et al., 2005) indicate that
harvesting does not have a consistent effect on soil carbon.

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Table 1

A comparison of Sflux, soil temperature, and moisture data between selection
harvests and control by percent; asterisks denote significant differences while n.s.
denotes non-significant differences.
Study

% difference (selective harvest versus
control)
Soil temperature

Soil moisture

Sflux

Peng and Thomas (2006)
Concilio et al. (2005) (TEF)
Concilio et al. (2005) (MOFEP)
Schilling et al. (1999)
Scott et al. (2004)

*8

*2–20
n.s.
*16
n.s.

n.s.
*20–40
n.s.
–
n.s.

*55
*43
*14
*20
n.s.

Most forest management studies have concentrated on the
effects of clear-cut harvest on soil carbon dynamics and few have
focused on alternative management practices, such as selective

tree or group harvest on soil carbon dynamics (but see Schilling
et al., 1999; Scott et al., 2004; Concilio et al., 2005; Peng and
Thomas, 2006) (Table 1). In particular, the effects of these less
intensive silvicultural systems on Sflux are inconsistent and
unclear. Some studies have measured a significant change in Sflux
following harvesting; although the direction of change varies
among studies. Additionally, there is variation in the intensity and
timing of forest harvesting among the studies.
A selective thinning in mixed-conifer stands in the Sierra
Nevada Mountains and hardwoods of the Ozark Mountains
resulted in significant increases in Sflux, soil moisture and soil
temperature although the magnitude of the response to thinning
was greater in the mixed-conifer stand than the hardwood stand
(Concilio et al., 2005). Schilling et al. (1999) reported that Sflux was
significantly greater in the selection harvest and clear-cut than
control treatments only during the active growing season; Londo
et al. (1999) reported similar results.
Finally, there are a few studies which found that smaller scale
forest cuts significantly reduced the overall Sflux. Peng and Thomas
(2006) compared Sflux in the gaps and non-gap locations in unevenaged managed northern hardwood forests in central Ontario and

found that Sflux increased by 55% immediately after harvest,
declined to 20–40% below pre-harvest rates in 1–3 years, and
gradually returned to pre-harvest rates by years 5–6. Tang et al.
(2005) reported Sflux was 13% less at a given soil temperature and
moisture for thinned versus control ponderosa pine stands. The
thinning treatment removed about 60% of the trees (30% of the
total biomass and LAI) and the harvested trees and shrubs were
mulched on the site. Therefore, the effect of selective harvest on
Sflux is not uniform.
Soil temperature (Witkamp, 1969; Singh and Gupta, 1977;
Schlenter and Van Cleve, 1985; Kirschbaum, 1995; Winkler et al.,
1996; Rustad and Fernandez, 1998; Qi et al., 2002) and soil
moisture (Schlenter and Van Cleve, 1985; Singh and Gupta, 1977;
Davidson et al., 1998) influence Sflux. Often incident photosynthetic
active radiation, soil surface temperature and moisture are greater
in canopy openings or gaps, than beneath intact canopies
(Minckler and Woerheide, 1965; Moore and Vankat, 1986; Gray
et al., 2002). However, like Sflux, not all forest harvests or thinning
result in an increase in temperature or moisture within the created
gaps (Table 1). Significant differences in soil microclimate were not

evident between thinned and control areas in hardwood forests
(Concilio et al., 2005) or in a shelterwood harvest (Scott et al., 2004)
(Table 1). In a northern hardwood forest, Nauertz et al. (2004)
reported significant changes in photosynthetic active radiation
between harvested (even-aged and uneven-aged management)
and control locations, but not soil temperature.
Harvesting creates gaps belowground as well that may reduce
autotrophic root respiration, turnover, and exudates that could
decrease Sflux (Edwards and Ross-Todd, 1983; Yin et al., 1989;

Strigel and Wickland, 1998; Schilling et al., 1999). Conversely, the
sudden pulse of fine roots and mycorrhizae turnover from the
harvested trees may stimulate decomposition (Peng and Thomas,
2006).
The objectives of this study were to quantify the effect of a
simulated selection harvest in a northern hardwood forest on (1)
the soil microclimate (temperature and moisture), (2) Sflux, (3)
determine if the size of the harvest influences Sflux, and (4) compare
the modeled annual Sflux (soil and forest floor flux) budgets for the
northern hardwood forest treatments. We hypothesized that: (1)

soil temperature and moisture would be significantly greater in the
selective harvest gaps than control gaps, (2) Sflux would not differ
between gap size, and (3) Sflux would be greater in selective harvest
gaps than the control gaps, (4) mechanization treatments would
not significantly increase Sflux.
2. Methods
2.1. Site description and experimental design
This study was conducted in the Flambeau River State Forest,
(458370 24.5100 N, 908470 7.7200 W), Rusk County, in north-central
Wisconsin, U.S.A. The study area is comparable to many of the
forests in the Great Lakes State forest region and typifies maturing
northern hardwood forests with one predominant age cohort (ca.
80 years) (J. Dyer, unpublished data). The forest was selected
because it is reasonably representative of the age structure of many
forests in northern Wisconsin, there was a sufficient area of
relatively uniform forest to implement the large scale manipulations, and the Wisconsin Department of Natural Resources will
host the experiment for 50 years.
The dominant soils in this region were silt loams (Glossudalfs)
of the Magnor, Freeon, and Ossemer series overlying dense till
(David Hvizdak, USDA, NRCS). Mean annual temperature for 2006–

2008 was 7.4, 6.1 and 4.4 8C, respectively. The annual precipitation
range for 2006–2008 was from 558, 618, and 530 mm, respectively
(J. Forrester, unpublished data).
Sugar maple (Acer saccharum (Marshall)) is the dominant
overstory tree species throughout the research area while species
of lesser dominance such as white and black ash (Fraxinus
americana L. and F. nigra), basswood (Tilia americana L.), bitternut
hickory (Carya cordiformis (Wagenh), and eastern hemlock (Tsuga
canadensis) vary moderately within the plots (Table 2). The
experimental design included three blocks to account for the
natural heterogeneity of pre-treatment of plant species composition throughout the research area. The presence of eastern
hemlock and ash species described the most variation between
plots. The presence of hemlock influences soil carbon and nitrogen
dynamics (Campbell and Gower, 2000). Therefore the three blocks
designated prior to treatment were: (1) maple-hemlock, (2)
maple-ash, and (3) maple. The third block included plots where
several other species at the site were more abundant, including
bitternut hickory, American basswood, red and white elm (Ulmus
rubra (Muhl.) and U. americana (L). Within each block treatments
were randomly assigned to plots.
This study was a part of a larger experiment that included
additional treatments (Fig. 1), but this study focused on only three
of these treatments: group selection cuts referred to hereafter as
‘‘gaps’’, mechanized control, and control (no treatment). The
experimental design was a split plot design with gap size
(subplots) nested within three whole plot treatments. Each
treatment consisted of five, 80 m  80 m whole plots that were
randomly assigned across treatments in the total study area
(9.6 ha) and of those of the larger study (Fig. 1). Only four of the five
subplots were used in this study because of logistical constraints
associated with measuring soil surface CO2 flux over a large area.

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Table 2
Structure and composition of trees >10 cm diameter at breast height of the study area in Flambeau River State Forest (N = 35, 80 m  80 m whole plots).
Basal area (m2/ha)

Species

Density (stem/ha)

Mean

Std. err.

Sugar maple Acer saccharum
American basswood Tilia americana
Ash Fraxinus spp.
Bitternut hickory Carya cordiformis
Eastern hophornbeam Ostrya virginiana
Red oak Quercus rubra
Yellow birch Betula alleghaniensis
Red maple Acer rubrum
Cherry Prunus spp.
Eastern hemlock Tsuga canadensis
Trembling aspen Populus tremulodies
Elm Ulmus spp.
Butternut Juglans cinerea

287.72
51.43
45.4
23.66
18.04
4.91
5.54
7.01
3.75
2.50
3.13
2.37
0.76

8.35
4.59
5.75
5.4
4.98
1.14
1.2
3.35
1.82
0.64
2.46
0.57
0.31

16.34
4.62
4.33
1.19
0.25
0.66
0.49
0.36
0.38
0.29
0.17
0.07
0.07

0.59
0.4
0.52
0.27
0.07
0.17
0.13
0.16
0.22
0.08
0.11
0.02
0.03

All species

456.38

13.34

29.25

0.49

Mean

The four plots were chosen to include each of the subplot
orientations. Plot orientation was not a significant pre- or posttreatment effect; therefore, this effect was not included in any
statistical models. Within each whole plot, three ‘‘gap’’ subplots
with 22, 16, and 8 m diameters were created. Only the 22 and 16 m
gap subplots were used in this study because these sizes are more
representative of selection cuts in the northern hardwood forest.

Std. err.

2.2. Treatment implementation
Treatments were implemented during January–February 2007.
The soil was frozen and a snow pack (10–20 cm) was present when
the treatments were initiated. Group selection cuts were made
using a harvester (Ponsse Ergo, Ponsse Oyj, Vieremä, Finland)
operated by a certified master logger. Timber (including slash) was

Fig. 1. The Flambeau River State Forest is located in west-central Wisconsin, USA. Plots were randomly chosen from these 35 plots located within three blocks based on
overstory species differences that existed across the site.

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J.L. Stoffel et al. / Forest Ecology and Management 259 (2010) 257–265

removed from the experimental plots with a forwarder (Ponsse
Buffalo, Ponsse Oyj, Vieremä, Finland). The mechanization treatment consisted of the harvesters traveling within an experimental
plot for a similar amount of time as spent in the gap plots, but no
trees were harvested.
2.3. Meteorological monitoring
A meteorological station was established within one plot of
each treatment prior to treatment (winter 2005). Within the gap,
soil moisture and temperature were measured 5.5 m from the
subplot center in the north and south directions. Soil temperature
was measured continuously at two depths (1.6 and 7.5 cm) using
thermocouple wire (type-T) (Fig. 2) Soil moisture was also
measured at all of these locations to a depth of 3.2 cm and then
an average over a depth of 20 cm using two ECH20-20 probes
(Decagon Inc., Pullman, WA, UA) (Fig. 2). Air temperature was
recorded at a height of 1 m. All environmental data were recorded
using Campbell Scientific CR 10X data loggers (Campbell Scientific,
Logan, UT, USA) (Fig. 2). The continuous meteorological data was
used only for modeling annual Sflux.
2.4. Soil surface CO2 flux (Sflux) measurements
Soil surface CO2 flux (Sflux) was measured with a Li-Cor 6200
portable CO2 infrared gas analyzer (IRGA) (Li-Cor Inc., Lincoln, NE)
equipped with a 15.2 cm (inside diameter) clear acrylic chamber.
The chamber fit on PVC (polyvinyl chloride) collars (15.4 cm
diameter  6 cm tall). The collars were beveled at the bottom to
minimize soil disturbance when they were placed in the soil. The

collars were placed along two north–south transects in the large
and medium subplots. In the large subplot, the two transects were
located 2.1 m on the east and west side of plot center and four
collars were evenly spaced 4.1 m from each other along each
transect for a total of eight collars. In the medium subplot,
transects were located 2.0 m on the west and east side of plot
center. Sflux was not measured for 3 weeks after the collars were
installed to avoid any disturbance artifact associated with
installation (Vogel and Valentine, 2005).
The IRGA was calibrated by LiCor at least once a year and was
calibrated daily prior to use. The IRGA was configured to
automatically measure five times every 10 s at every collar
location. This method provides accurate estimates of Sflux
compared to other approaches (Norman et al., 1997). Pretreatment Sflux measurements were made approximately every
2–4 weeks. Pre-treatment data was used to calculate the
coefficient of variation in Sflux to ensure that enough collars were
in every plot and subplot. The variability was less than 15%
standard error of the mean so no additional collars were added for
post-treatment collections. In 2007, Sflux was measured bi-weekly
during the growing season and monthly during days 108–131 and
days 239–310. In 2008, the second post-treatment year, soil Sflux
was measured monthly during times with no snow (days 113–
286). Snow surface CO2 flux was measured once in early 2008
following the methodology described in Wang et al. (2003).
Discrete soil temperature at 2 and 10 cm depth (T2 and T10) was
measured simultaneously at each soil collar using digital long
stem thermometers (model no. 15-078k, Fisher Scientific,
Pittsburg, PA, USA). Discrete soil moisture measurements were
made to a depth of six cm using a portable soil moisture probe

Fig. 2. Daily average air temperature (8C), soil temperature (8C) at 7.5 cm and soil moisture (m3 water m3 soil) averaged to a depth of 20 cm from control, gap and
mechanized treatments collected from meteorological stations.

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Fig. 3. Discrete measurements of soil temperature (8C) and soil moisture (m3 m3) (depth of 6 cm) taken at the time of soil surface CO2 flux (Sflux) measurements. Asterisks
denote significant differences at measurement periods (a = 0.05).

Annual Sflux was modeled using the empirical relationships
between instantaneous Sflux and T10 for each year, plot, and
subplot. Parameters were also generated for each year, block, and
treatment to provide average parameters for each treatment. Three
models were evaluated: a first order exponential model (Landsberg
and Gower, 1997) R = aebT, an Arrhenius model of the form Rs ¼
1
aebT (Lloyd and Taylor, 1994; Tuomi et al., 2008), and a power
model with a fixed minimum temperature Rs = a(T  (20 8C))b
(Fang and Moncrieff, 2001; Bond-Lamberty et al., 2004). We
selected a minimum temperature of 20 8C because it occurred
well below temperatures measured in the field (Fig. 3), it was
below laboratory incubations microbial respiration threshold of
18 8C (Elberling and Brandt, 2003), and it provided parameters
that were statistically relevant. The three models were fit using a
nonlinear model (PROC NLIN). Models that provided reasonable
parameters, the smallest sum of squares error, and converged were
deemed to be the best fit. All models provided good visual fits to
the data, reasonable parameter values, good sums of squares, and
all residual distributions were satisfactory (data not shown). The
Fang and Moncrieff (2001) minimum temperature function with a
fixed temperature minimum provided the best sum of squares
error (86%) for all of the plots and subplots and provided good fits
(Appendix A1, Table 3, Fig. 5). The temperature was fixed to help
solve convergence problems or inappropriate parameter values.
Model parameters for the best model (Fang and Moncrief with
fixed temperature) were not significantly different among treatment (Table 3 and Appendix A1).

(Delta TH20, Dynamax Inc, Houston, TX) at the time of Sflux
measurements. These data were used in mixed effects models to
determine the effect of temperature and moisture on soil surface
CO2 flux.
2.5. Statistical analysis
Statistical analyses were conducted with SAS version 9.1
software (SAS Institute Inc 2003, Cary, NC), using multiple mixed
effects procedure (PROC MIXED) to determine differences among
treatments (gaps, mechanized, and control plots). Fixed effects
were species gradient (block), treatment, and gap size (subplot)
and the random effects included plot by the interaction of
block and treatment and plot by subplot. The multiple mixed
effects models were conducted by year and across posttreatment years. Repeated measures analyses were also conducted using a mixed effects procedure and compound
symmetry for the covariance structure. The random effects were
plot within treatment by block and plot within treatment, block
and subplot.
Regression analyses were performed (PROC REG) using the
Sflux versus discrete soil temperature and moisture data. The
results from the regression analyses were used to determine
which factor (s) were included in empirical models that
estimated annual Sflux from continuous soil temperature or
moisture data. Model assumptions were satisfied prior to
selecting the best model.

Table 3
Parameters were generated from a two parameter Fang and Moncrieff Function (2001) using PROC NLIN for each plot and subplot to determine if the parameters varied
significantly among treatment. Since no parameters varied significantly, parameters were generated directly for each block and treatment and Ntotal and Nerror are degrees of
freedom for the overall model and the error term, annually.
Year

Block

Ntotal

Nerror

a

b

P-value

2007
2007
2007
2008
2008
2008

Maple-ash
Maple-hemlock
Maple
Maple-ash
Maple-hemlock
Maple

412
435
841
217
208
482

410
433
839
215
206
480

0.00191
0.00536
0.00184
0.000019
0.000030
0.000052

2.1709
1.8801
2.1984
3.4893
3.3400
3.2096