Effects of tree harvesting forest floor
ARTICLE IN PRESS
Soil Biology & Biochemistry 38 (2006) 1734–1744
www.elsevier.com/locate/soilbio
Effects of tree harvesting, forest floor removal, and compaction on
soil microbial biomass, microbial respiration, and N availability
in a boreal aspen forest in British Columbia
Lucero Mariania,, Scott X. Changa, Richard Kabzemsb
a
Department of Renewable Resources, 442 Earth Sciences Building, University of Alberta, Edmonton, Alta., Canada T6G 2E3
b
Ministry of Forests, 9000–17th St., Dawson Creek, BC, Canada V1G 4A4
Received 30 May 2005; received in revised form 27 November 2005; accepted 29 November 2005
Available online 17 February 2006
Abstract
The effects of timber harvesting and the resultant soil disturbances (compaction and forest floor removal) on relative soil water
content, microbial biomass C and N contents (Cmic and Nmic), microbial biomass C:N ratio (Cmic-to-Nmic), microbial respiration,
metabolic quotient (qCO2), and available N content in the forest floor and the uppermost mineral soil (0–3 cm) were assessed in a longterm soil productivity (LTSP) site and adjacent mature forest stands in northeastern British Columbia (Canada). A combination of
principal component analysis and redundancy analysis was used to test the effects of stem-only harvest, whole tree harvest plus forest
floor removal, and soil compaction on the studied variables. Those properties in the forest floor were not affected by timber harvesting or
soil compaction. In the mineral soil, compaction increased soil total C and N contents, relative water content, and Nmic by 45%, 40%,
34% and 72%, respectively, and decreased Cmic-to-Nmic ratio by 29%. However, these parameters were not affected by stem only
harvesting or whole tree harvesting plus forest floor removal, contrasting the reduction of white spruce and aspen growth following forest
floor removal and soil compaction reported in an earlier study. Those results suggest that at the study site the short-term effects of timber
harvesting, forest floor removal, and soil compaction are rather complex and that microbial populations might not be affected by the
perturbations in the same way as trees, at least not in the short term.
r 2006 Elsevier Ltd. All rights reserved.
Keywords: Available N; Boreal forest; Long-term soil productivity (LTSP); Microbial respiration; Microbial biomass; qCO2; Redundancy analysis
1. Introduction
Forest harvesting has been reported to decrease soil
evapotranspiration, increase soil temperature and its
diurnal fluctuations, and create a large amount of debris
and dead roots that are easily decomposed by soil biota
(Greacen and Sands, 1980; Lenhard, 1986; Williamson and
Neilsen, 2000). In addition, forest-harvesting machinery
may cause soil compaction and uneven forest floor
displacement or disturbance, and common site preparation
practices such as harvest residue removal and forest floor
Corresponding author. Present address: Muse´um National d’Histoire
Naturelle, 4 avenue du Petit Chaˆteau, 91 800 Brunoy, France.
Tel.: +33 1 60 47 92 14; fax: +33 1 60 46 57 19.
E-mail address: lucero.mariani@wanadoo.fr (L. Mariani).
0038-0717/$ - see front matter r 2006 Elsevier Ltd. All rights reserved.
doi:10.1016/j.soilbio.2005.11.029
scalping can affect site organic matter (OM) content and
soil porosity, the two ecosystem properties most likely to
impact long-term soil productivity (Powers et al., 2005).
Assessing the effects of forest harvesting and site
preparation practices on soil biological properties and
processes is a crucial step towards the conservation of
forest ecosystem functions and productivity (Li et al.,
2004). Soil organic matter (SOM) content and quality, soil
microbial biomass, microbial respiration, and N availability have been used as indices to assess soil biological
activity and health (Nambiar, 1996; Burger and Kelting,
1999; Schoenholtz et al., 2000). SOM content and quality
are generally considered as key indicators of forest soil
quality and sustainability because SOM is linked to the
fundamental attributes of the soil: water-holding capacity,
nutrient availability, soil buffering capacity, rates of gas
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exchange, and soil biological activities (Powers et al., 2005;
Nambiar, 1996). Soil microbial biomass is a small but very
active part of the SOM and has frequently been suggested
as a sensitive indicator of change, whereas total SOM
content appears to be quite resilient to soil disturbance
(Johnson et al., 1991; Bauhus et al., 1998; Stone and Elioff,
1998; Piatek and Allen, 1999; Li et al., 2004). Microbial
respiration is a measure of soil biological activity that can
be combined with microbial biomass to derive specific
microbial respiration (qCO2) that can be used to assess the
efficiency of soil micro-organisms in utilizing C substrates
(Insam, 1990; Pietikainen and Fritze, 1995; Bauhus et al.,
1998). Being at the core of plant nutrition, soil N
availability is also a critical index for evaluating the
sustainability of soil productivity (Marshall, 2000; Li et al.,
2003).
Reports on the impact of forest harvesting, soil
compaction, and forest floor removal on biological properties of forest soils are still scarce and some experiments
were designed in such a way that compaction and forest
floor removal treatments are confounded (i.e., Dick et al.,
1988; Pietikainen and Fritze, 1995; Corns and Maynard,
1998). In addition, some published studies report contradictory results, such as those summarized in Table 1. Table
1 indicates that stem only harvest and forest floor removal
either cause no effect or decrease the parameters listed;
while whole tree harvest and soil compaction can cause no
effect, increase, or decrease the measured properties. A
most recent publication reports that compaction alters soil
physical properties and tree growth but not the biological
indices of soil health, indicating a strong resilience of the
microbial communities (Shestak and Busse, 2005). While
tree growth can be impaired by the decrease of large pores
due to compaction, microbes were found to take advantage
of the increased volume of small pores (Shestak and Busse,
2005). Forest floor removal could also alter mineral soil
properties in a contrasting way for plants and microbes.
Therefore, no definitive conclusions can be made regarding
the impact of forest harvesting and soil disturbances on soil
biological properties, particularly in the boreal region in
North America.
The objective of this study was to investigate the effects
of soil compaction and forest floor removal on microbial
biomass C and N contents (Cmic and Nmic), microbial
respiration, and soil N availability in a long-term soil
productivity (LTSP) experiment established in a representative mesic aspen ecosystem in northeastern British
Columbia, Canada. Under boreal aspen forests, SOM
contents, total soil N and S contents, available N and P,
and other nutrients are significantly higher in the forest
floor and the first few centimetres of the mineral soil than
in deeper horizons (Neville et al., 2002) and the highest
concentration of roots are at the organic/mineral–soil
interface (Strong and La Roi, 1985). We therefore sampled
the forest floor and the uppermost mineral soil (0–3 cm) in
order to study the most biologically active soil horizons.
Forest floor removal and soil compaction on the studied
site have been shown to reduce white spruce and aspen
Table 1
A summary of published studies on the effects of timber harvest, soil compaction, and forest floor removal on soil biological properties
Forest floor
Cmicb
Resp.
qCO2
Corg
Navail
Ntot
Stem only harvest
Whole tree harvest
No effect
No effect
Decrease
Decrease
No effect
Increase
Forest floor removala
Decrease
No effect
Decrease
9c
9
5
5
Surface mineral soil (0–15 cm)
Cmic
Nmic
Cmic:Nmic
Resp.
5
Corg
Navail
8
Ntot
8
WC
8
a
Increase
Soil compactiona
9
5
9
5; 12d
5
1; 9
1
1
1
12
2; 4; 7; 10
4
11
5
8
8
5
8
11; 10
2; 6
4; 6
6
4; 12; 3
6
6; 3
7
7
6
2
5; 12
8; 6
8; 12
8
4
4; 7
8; 6
4
6
4
Additional effects over timber harvest.
Cmic, microbial biomass C; Nmic, microbial biomass N; Resp., microbial respiration; qCO2, specific microbial respiration; Corg, soil organic C; Navail,
available N; Ntot, total soil N; WC, water content.
c
References: (1) Corns and Maynard (1998), (2) Dick et al. (1988), (3) Gomez et al. (2002), (4) Jordan et al. (2000), (5) Laiho et al. (2003), (6) Li et al.
(2003), (7) Li et al. (2004), (8) Piatek and Allen (1999), (9) Pietikainen and Fritze (1995), (10) Shestak and Busse (2005), (11) Startsev et al. (1998), (12)
Stone and Elioff (1998).
d
Forest floor removal effects on properties of the newly accumulated forest floor.
b
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growth which will likely delay future stand development
and reduce site productivity (Stone and Kabzems, 2002).
However we expected contrasting results between tree
growth and soil processes (Shestak and Busse, 2005).
Consequently, we hypothesized that tree harvesting, soil
compaction, and forest floor removal do not change
mineral soil microbial biomass, microbial respiration and
N availability, and that tree harvesting and soil compaction
do not affect these properties in the forest floor.
2. Materials and methods
2.1. Study site
The research site is located about 40 km northeast of
Dawson Creek (551580 N, 1201280 W; 720 masl) in the Peace
Forest District, in northeastern British Columbia. The site
is representative of mesic aspen (Populus tremuloides
Michx.) ecosystems in the moist, warm subzone of the
Boreal White and Black Spruce (BWBS) biogeoclimatic
zone (DeLong et al., 1990, 1991). The site has a south
aspect and a 4% slope gradient. The overstory tree species
were dominated by aspen, with small amounts of white
spruce (Picea glauca (Moench) Voss), cottonwood (Populus
balsamifera L.) and lodgepole pine (Pinus contorta ex
Loud. var. latifolia Engelm.). Soils on the study site have
20–30 cm of silt loam veneer over clay loam and are
dominated by Luvic Gleysols (Soil Classification Working
Group, 1998). The pre-treatment forest floor thickness
averaged 7.5 cm (Kabzems, unpublished data) and the
humus form was classified as a Lamimoder (Fons et al.,
1998). The pre-treatment forest floor contained
1350 kg ha1 of total N (SE of the mean: 71 kg ha1;
Kabzems, unpublished data). Annual precipitation ranges
between 395 and 660 mm, with 33–63% of this falls as
snow, mean annual temperature is 1.1 1C, and mean frost
free period is 150 days (DeLong et al., 1990).
2.2. Experimental design and sample collection
Forest floor and 0–3 cm mineral soil samples were
collected with a Dutch auger in September 2002 from all
three replications (replicated at the plot level) of four
treatments of the LTSP experiment and adjacent mature
forests. The sampled four treatments in the LTSP
experiment were: (1) stem-only harvest (forest floor intact),
no compaction (treatment code: NcFi), with two of the
replications installed in 1995 and the other in 1999; (2)
stem-only harvest (forest floor intact), heavy compaction
(HcFi), with two of the replications installed in 1995 and
the other in 1999; (3) whole-tree harvest plus forest floor
removal, no compaction (NcFr), with one of the replications installed in 1995 and the other two in 1998; and (4)
whole-tree harvest plus forest floor removal, heavy
compaction (HcFr). One of the HcFr replications was
installed in 1995 and the other two in 1998. The treatment
plots are randomly arranged. Due to the installation of the
experiment over a 4 year period (1995–1999), as it was
impossible to have all the plots installed in one single year
for an experiment of this size, there is no blocking in the
design. The time since installation was used as a covariate
in the analysis to remove it as a confounding factor as in
Kabzems and Haeussler (2005) and Tan et al. (2005). It was
found that plots installed in 1995 did not differ from those
installed in 1998 or 1999 for a wide range of soil properties
measured (Kabzems and Haeussler, 2005; Tan et al., 2005).
In the mature forest stands adjacent to the LTSP plots,
three transects were randomly located and they represented
the 3 replications of the mature forest treatment. In each
plot or transect, we collected one composite sample that
consisted of 18 sub-samples collected around 3 randomly
selected trees (6 sub-samples around each tree). The
samples were placed on ice in a cooler and transported
back to the laboratory.
2.3. Laboratory analyses
Fresh soil samples were passed through a 4 mm sieve.
Cmic and Nmic were measured on fresh samples by the
fumigation–extraction method (Brookes et al., 1985; Vance
et al., 1987). Each sample (20 g fresh mineral soil and 5 g
fresh forest floor sample) was fumigated in duplicates for
24 h with alcohol-free chloroform and then extracted in
60 ml 0.5 m K2SO4. Extracts of the duplicates were
combined prior to the measurement of their C and N
concentrations. Total N concentrations in K2SO4 extracts
was determined by Kjeldahl digestion (Voroney et al.,
1993) followed by colorimetric determination of the
NH+
4 –N (industrial method 98–70 W) concentration on a
Technicon Autoanalyzer II (Tarrytown, New York). Total
soluble organic carbon concentration in extracts was
determined with an ASTRO 2001 system 2 (Leagne City,
Texas). Extractability factors of 0.38 for Cmic (Vance et al.,
1987) and 0.54 for Nmic (Brookes et al., 1985; Bauhus et al.,
1998) were used to calculate Cmic and Nmic, respectively.
Available N (Navail) was measured by determining the
NH+
4 and NO3 (industrial method 487–77 A) concentrations in K2SO4 extracts of the non-fumigated soil samples
colorimetrically on a Technicon Autoanalyzer II following
the method in Maynard and Kalra (1993).
To measure microbial respiration, fresh soil samples
were pre-incubated for 7 days in the dark at 25 1C in 1 L
mason jars fitted with butyl rubber septa on the lids. For
the mineral soil, 6–8.5 g dry soil equivalent (in triplicates)
was used and for the forest floor samples 0.8–1.4 g dry mass
equivalent (in triplicates) was used. After the pre-incubation period, we ventilated the jars, closed the lids tightly
and immediately measured the initial CO2 concentration in
the jars. Concentrations of CO2 in the headspace of each
jar were measured with an HP 5890-II gas chromatograph
(Zibilske, 1994); 1 ml of the gas sample from each jar was
removed with a Gastights glass syringe and injected into
the GC. Then, the soil samples were incubated in the dark
at 25 1C for 7 or 8 days and we measured the CO2
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concentration in the headspace again. The difference in
CO2 concentrations between the initial and the postincubation measurements was used to calculate microbial
respiration.
Fresh samples of mineral soil (20 g) and forest floor (5 g)
were dried for 24 h at 105 1C to determine soil moisture
content gravimetrically. The relative soil water content was
expressed as water content as a percent of water holding
capacity. The water-holding capacity of the soils was
determined by the wet funnel method (Jenkinson and
Powlson, 1976). A sub-set of soil samples was air-dried and
ground to pass a 40-mesh sieve. Total C and N contents
(Ctot and Ntot) were determined by dry combustion
(Tabatabai and Bremner, 1991) with a Costech ECS 4010
elemental combustion analyzer (Milan, Italy). Carbonates
are absent from the soil. The results for all the measurements were expressed on an oven-dry soil weight basis and
converted to kg ha1 for each cm of depth of the material
using soil bulk densities of forest floor and mineral soil.
Data analyses were performed on the values expressed in
kg ha1 cm1.
2.4. Data analyses
2.4.1. Redundancy analysis (RDA)and permutation tests
The aim of the data analysis was to test the effects of
merchantable bole harvest, forest floor removal, and soil
compaction on the quantity and quality of SOM, including
Ctot and Ntot, soil C:N ratio (Ctot-to-Ntot), Cmic and Nmic,
Cmic-to-Nmic ratio, Navail, rates of microbial respiration,
qCO2, and relative water content.
We chose to run multivariate analyses because of the
strong correlations between the variables. Analysis of the
data by parametric MANOVA was not possible because of
heterogeneity of within-group variance (tested by Bartlett’s, Log-ANOVA, Cochran’s C, and Box’s M univariate
tests) and a high ratio of the number of variables to the
number of objects. In this paper, if the lowest variance is
greater than 33% of the highest variance, within-group
variance was considered to be homogeneous. Data
transformations were not able to correct the heterogeneity
of variance (heteroscedasticity).
RDA associated with permutation testing is an appropriate non-parametrical alternative to MANOVA for
ecological multivariate data sets (Verdonschot and ter
Braak, 1994; Legendre and Anderson, 1999; Anderson,
2001). We ran RDA on the correlation matrix (obtained
from data centred and standardized) and calculated the
multivariate within-group variances from the coordinate of
the soil samples. Permutation testing is impaired by
heteroscedasticity (Hayes, 1996; Legendre and Legendre,
1998). In case of heteroscedasticity, we have a two-part null
hypothesis: the multivariate locations (means) do not differ
and the within group variances do not differ. Consequently, a significant test might mean that the within group
variances are different but that the means do not differ. In
presence of heteroscedasticity, we used the ordination
1737
biplots to check the cause of a significant test (M.J.
Anderson pers. comm.).
We performed 3 sets of analyses: (1) for the 9 plots
(including the three mature forest transects and six forest
floor intact harvested plots) where both the forest floor and
mineral soil layers were present, we compared the forest
floor and the mineral soil by RDA with a dummy variable
indicating the layer of the sample (LAYER) as an
independent variable and dummy variables indicating if
the sample has been harvested (HARVEST) or compacted
(COMPACTION) as covariates. The 2 layers from the
same plot, autocorrelated, were treated as repeated
measures in the analysis. As we found a significant
difference between the 2 layers, we performed the
subsequent analyses for each layer separately; (2) to
analyse the timber harvesting effect, we first reduced the
number of biological variables by principal component
analysis (PCA). Then we used RDA as a form of inverse
analysis related to discriminant analysis (Legendre and
Legendre, 1998; Lepsˇ and Sˇmilauer, 2003) with the
resulting principal components (biological-PCs) as explanatory variables and HARVEST as dependent variable;
and (3) within the LTSP experiment, we tested the effect of
COMPACTION and organic matter removal by RDA.
The effect of organic matter removal was tested with
OMR, a dummy variable indicating if the organic matter
removal is low or severe. The time since installation was
used as a covariate. These 3 analyses were performed
separately for bulk density, because it is a parameter of a
different kind. All these RDA were tested by 999
permutations under the reduced model.
As RDA is a constraint PCA, we then used PCA to
evaluate the percentage of variation extracted by the RDA
by comparing it to the variation extracted by the first and
second principal components of the related PCA (Lepsˇ and
Sˇmilauer, 2003). We regard these variables that have a
correlation coefficient with the canonical axes greater than
the mean of all the correlation coefficients as making
meaningful contributions to the canonical axes (Heuer and
Smalla, 1997).
2.4.2. Spearmann R correlation coefficients
Spearmann’s R correlation coefficients represent the
proportion of common variation between the ranks of the 2
variables being compared. For the 10 variables under
study, 45 simultaneous correlation tests were performed.
We applied Hochberg’s method to correct for multiple
testing (Hochberg, 1988; Legendre and Legendre, 1998).
2.4.3. Statistical software
The Bartlett’s, Log-ANOVA, Cochran’s C, and Box’s M
tests for homogeneity of variances were performed by 999
permutations with the program Test_hv (Legendre, 2000);
PCA and RDA analyses were performed with CANOCO 4
for Windows (ter Braak, 1988) developed by Microcomputer Power (Ithaca, NY, USA); the Spearmann R
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correlation was analysed with the STATISTICA package
developed by StatSoft Inc. (Tulsa, OK, USA).
3. Results
3.1. Correlations between soil C and N contents and
microbial properties
When all 24 data points (five treatments with three
replications and one or two depths) were considered, soil
microbial respiration, Ctot, Ntot, Ctot-to-Ntot ratio, Cmic,
Nmic, and Navail were significantly and positively correlated
with each other, with 2 exceptions: between Navail and Ctot
and between Ctot-to-Ntot ratio and Ntot (Table 2). Cmic-toNmic ratio was not significantly correlated with any of the
other studied variables except for Nmic. Metabolic quotient
(qCO2) was significantly and positively correlated with
microbial respiration, Nmic and Navail, and Ctot-to-Ntot
ratio. Relative water content was significantly and negatively correlated only with Ctot-to-Ntot ratio (Table 2).
3.2. Soil biological activities in forest floor vs. mineral soil
and effects of timber harvesting
For the layer effect, the multivariate within-group
variances were heterogeneous with a variance for the
mineral samples reaching only 22% of the variance of the
forest floor samples. However, the plot of the samples in
the space of the dependant variables shows clearly that the
2 groups have different means (Fig. 1).
Reflecting the large differences between the forest floor
and mineral soil in the 10 studied variables (Tables 3 and
4), the difference between forest floor and mineral soil was
highly significant and explained 60% of the total variance
of the 10 variables under study (F ¼ 26:8, P ¼ 0:005; Fig.
1). This corresponds to 78% of the variance extracted by
the first 2 PCs of the related PCA. All the variables
contributed to the layer effect except qCO2, relative water
content, and Cmic-to-Nmic ratio (Fig. 1). Ctot, Ntot, Navail,
microbial respiration and Cmic-to-Nmic and Ctot-to-Ntot
ratios were 2, 2, 4, 4, 3, 3 times and 30% greater,
respectively, in the forest floor than in the mineral soil
(Tables 3 and 4).
For the forest floor, no effect of harvesting was found for
any of the studied variables (data not shown). The PCA of
the 10 variables under study yielded biological-PCs that
explained 31%, 20% and 19.5% of the total variation, for
the first, second and third PC, respectively (data not
shown). The discriminant analysis with these 3 biologicalPCs as independent variables and HARVEST as dependant variable explained 41% of the variability of two
grouping variables and was not significant (F ¼ 3:5,
P ¼ 0:502; data not shown). In the ordination plot, the
samples from the mature forest were mixed with the heavy
compaction-forest floor intact plots (graph not shown).
For the mineral soil, no effect of harvesting was found
either (Table 4). The PCA of the 10 variables under study
yielded PCs that explained 37%, 24%, 14% and 12% of
the total variation, for the first, second, third and fourth
biological-PC, respectively (data not shown). The discriminant analysis with these 4 biological-PCs as the
independent variable and HARVEST, as dependant
variable explained 43% of the variability of the two
grouping variables and was not significant (F ¼ 1:9,
P ¼ 0:175; data not shown). In the ordination plot, the
samples from the mature forest were mixed with all the
other groups of samples (data not shown).
3.3. Effects of compaction and forest floor removal in the
LTSP experiment
The time since installation had no effect on the 10
variables under study in the forest floor and the mineral
soil: it explained 17% and 3% of the total variations for the
forest floor and the mineral soil, respectively (Table 5).
For the forest floor, the multivariate analysis did not
detect a significant effect of the compaction treatment or
year since installation on the 10 variables under study
(Table 5). The proportion of the variance explained by soil
compaction (23%) was less than half of the fraction
Table 2
Spearmann R rank correlation coefficients among the 10 studied variables for two depths, including both the mature forest and LTSP plots (n ¼ 24)
Ntot
a
Resp.
Ntot
Ctot
Cmic
Nmic
Navail
Ctot:Ntot
Cmic:Nmic
qCO2
#
#
0.566
Ctot
Cmic
Nmic
Navail
Ctot:Ntot
Cmic:Nmic
qCO2
WC
0.749***
0.903***
0.923***
0.641*
0.750***
0.762***
0.577#
0.707**
0.750***
0.740***
0.564#
0.529 ns
0.784***
0.563#
0.698**
0.523 ns
0.578#
0.666*
0.563#
0.642*
0.026 ns
0.067 ns
0.146 ns
0.060 ns
0.566#
0.175 ns
0.105 ns
0.790***
0.300 ns
0.486 ns
0.533 ns
0.562#
0.566#
0.580#
0.136 ns
0.431 ns
0.220 ns
0.220 ns
0.377 ns
0.364 ns
0.506 ns
0.772***
0.058 ns
0.449 ns
Test significant at 10%; *test significant at 5%; **test significant at 1%; ***test significant at p0.5%; ns, test non-significant at 10%.
a
Cmic, microbial biomass C; Nmic, microbial biomass N; Cmic:Nmic, microbial biomass C:N ratio; Ctot, soil C; Ntot, total soil N; Ctot:Ntot, soil C:N ratio;
Navail, available N; Resp., microbial respiration; qCO2, specific microbial respiration; WC, water content.
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Axis 2: non constraint (PC1)
1.0
1.0
LFH
Cmic:Nmic
qCO2 Ctot Resp.
LFH
Cmic and Ctot: Ntot
Ntot
Navail
LFH
LFH
LFH
LFH
MIN
LFH
LFH
LFH
WC
Nmic
LFH
(a)
-1.0
-1.5
(b)
-1.0
1.5
-1.0
Canonical axis 1:Layer effect, 60% of total variation
1.0
Fig. 1. Differences between forest floor and mineral soil layers for the 9 plots where the 2 layers were present (RDA on raw data centred and
standardized). (a) RDA ordination plot representing the soil samples (coordinates are linear combination of the dependent variables). (b) RDA ordination
plot. Variables underlined contributed more than the mean to canonical axis 1. The canonical analysis yielded only one canonical axis because there is only
one independent variable.
Table 3
Means and coefficients of variation in percent (in parentheses) of the
measured parameters in the forest floor (n ¼ 3)
Measurement
MFa
NcFi
HcFi
Bulk density (g cm3)
Ctotb (g kg1)
(kg ha1)
Ntot (g kg1)
(kg ha1)
Ctot:Ntot
Navail (mg kg1)
(kg ha1)
WC (as a % of WHC)
Resp. (mg CO2–C kg1 d1)
(kg CO2 ha1 d1)
qCO2 (g CO2–C kg1 Cmic d1)
Cmic (mg kg1)
(kg ha1)
Nmic (mg kg1)
(kg ha1)
Cmic:Nmic
0.24 (17)
366 (8)
4815 (21)
17.0 (7)
220 (17)
21.6 (4)
61 (9)
8 (6)
25 (2)
451 (7)
58 (15)
40 (4)
9639 (13)
1460 (14)
896 (10)
118 (23)
12.8 (8)
0.16 (15)
403 (2)
3424 (12)
19.3 (4)
165 (15)
20.9 (5)
70 (8)
6 (10)
26 (2)
374 (3)
32 (16)
30 (5)
12074 (5)
1085 (12)
1300 (15)
109 (13)
10.1 (10)
0.22 (21)
367 (6)
4278 (21)
17.6 (6)
205 (20)
20.8 (2)
50 (7)
6 (21)
26 (5)
505 (8)
59 (23)
48 (4)
13057 (10)
1243 (24)
1128 (21)
128 (28)
11.1 (38)
a
MF, mature forest; NcFi, no compaction with forest floor intact;
HcFi, heavy compaction with forest floor intact.
b
Cmic, Microbial biomass C; Nmic, Microbial biomass N; Cmic:Nmic,
microbial biomass C:N ratio; Ctot, soil C; Ntot, total soil N; Ctot:Ntot,
soil C:N ratio; Navail, Available N; Resp., microbial respiration; qCO2,
specific microbial respiration; WC, water content; WHC, water-holding
capacity.
extracted by the first 2 PCs of the related PCA (64%, data
not shown). Therefore, we did not look further at the forest
floor results.
In contrast, for the mineral soil, the full model (Soil
compaction+OM removal+Interaction) significantly ex-
plained 41% of the variability of the 10 variables under
study in the experimental plots, after removing the effect of
the covariate (Table 5). This is a substantial fraction (63%)
of the total variability (66%) extracted by the first 2 PCs of
the related PCA (data not shown). Soil compaction was the
only factor significant in the RDA, explaining 20% of the
total variability of the data (Table 5).
The mineral soil had higher Ctot, Ntot, Nmic, and water
content, but a lower Cmic-to-Nmic ratio in the compacted
than in the non-compacted plots; Cmic and qCO2 were only
slightly higher in the compacted plots and did not
contribute meaningfully to the treatment effect (only
10% of the total variability for Cmic and 6% for qCO2
were explained by the compaction factor; data not shown);
Navail and Ctot-to-Ntot ratio were not affected by compaction (Fig. 2, Table 4).
3.4. Bulk density
For bulk density, the only significant difference was
between the forest floor and the uppermost mineral soil
(91% of the total variability explained by the layer effect,
F ¼ 145, P ¼ 0:005). For the uppermost mineral soil, the
tests were non-significant, with 3% (F ¼ 0:4, P ¼ 0:533)
and 24% (F ¼ 2:2, P ¼ 0:578), respectively, of variability
explained by harvesting, and the treatments in the LTSP
experiment, i.e., compaction+forest floor removal+interaction term). For the forest floor, similarly, the effects of
harvesting and compaction were non-significant, with 39%
(F ¼ 11:2, P ¼ 0:107) and 21% (F ¼ 1:8, P ¼ 0:236) of
variability explained, respectively.
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L. Mariani et al. / Soil Biology & Biochemistry 38 (2006) 1734–1744
Table 4
Means and coefficients of variation in percent (in parentheses) of the measured parameters in the 0–3 cm deep mineral soil (n ¼ 3)
Measurement
MFa
NcFr
NcFi
HcFr
HcFi
Bulk density (g cm3)
Ctotb (g kg1)
(kg ha1)
Ntot (g kg1)
(kg ha1)
Ctot:Ntot
Navail (mg kg1)
(kg ha1)
WC (as a % of WHC)
Resp. (mg CO2–C kg1 d1)
(kg ha1 d1)
qCO2 (g CO2–C kg1 Cmic d1)
Cmic (mg kg1)
(kg ha1)
Nmic (mg kg1)
(kg ha1)
Cmic:Nmic
0.83 (11)
43.8 (21)
1044 (10)
2.8 (25)
66 (15)
16.0 (7)
5 (19)
1 (7)
37 (12)
33 (1)
8 (6)
33 (20)
1207 (21)
262 (14)
84 (27)
20 (26)
13.9 (16)
0.98 (3)
26.4 (21)
770 (20)
1.8 (19)
54 (19)
14.3 (8)
3 (4)
1 (4)
55 (6)
29 (7)
8 (6)
25 (14)
896 (13)
327 (10)
94 (16)
27 (17)
12.3 (14)
0.82 (5)
35.7 (5)
874 (0)
2.2 (12)
53 (8)
16.6 (8)
4 (16)
1 (12)
41 (2)
23 (21)
6 (17)
21 (3)
784 (23)
268 (12)
80 (20)
19 (16)
14.3 (8)
0.85 (11)
49.6 (26)
1289 (21)
3.1 (22)
81 (17)
15.9 (5)
4 (11)
1 (6)
36 (8)
33 (10)
9 (7)
24 (4)
2025 (15)
372 (15)
147 (27)
40 (29)
11.2 (33)
0.86 (15)
41.1 (8)
1091 (5)
2.6 (10)
70 (6)
15.7 (1)
4 (13)
1 (7)
28 (12)
31 (2)
8 (14)
26 (6)
1364 (5)
305 (10)
176 (26)
41 (11)
7.8 (18)
a
NcFi, no compaction with forest floor intact; HcFi, heavy compaction with forest floor intact; NcFr, no compaction with forest floor removed; HcFr,
heavy compaction with forest floor removed.
b
Cmic, microbial biomass C; Nmic, microbial biomass N; Cmic:Nmic, microbial biomass C:N ratio; Ctot, total soil C; Ntot, total soil N; Ctot:Ntot, soil C:N
ratio; Navail, available N; Resp., microbial respiration; qCO2, specific microbial respiration; WC, water content; WHC, water-holding capacity.
Table 5
Variance decomposition of the effect of the treatments and the covariate on the measured variables in the forest floor and mineral soil layers. RDA on raw
data centred and standardized (multivariate analyses)
Source
Data analysis
Variance %
DF
F
P
Forest floor
Installation year (covariate)
Soil compaction
Unexplained
Partial RDA
Simple RDA
By difference
17.1
23.1
59.8
1
1
4
0.86
1.16
—
0.551 ns
0.456 ns
—
Mineral soil
Installation year (covariate)
Explained (A+B+A B)
Interaction (A B)
Soil compaction (A)
Organic matter removal (B)
Unexplained
Partial RDA
Simple RDA
Partial RDA
Partial RDA
Partial RDA
By difference
3.2
40.9
7.6
20.2
13.1
55.9
1
3
1
1
1
8
0.37
1.63
0.88
2.85
1.15
—
0.868 ns
0.088 #
0.510 ns
0.048 *
0.3480 ns
—
ns: Test non-significant at the 10% level. #Test significant at the 10% level;*test significant at the 5% level.
4. Discussion
4.1. Forest floor and mineral soil properties
Cmic and Nmic contents, Cmic-to-Nmic, Cmic-to-Corg (total
soil organic C content) and Nmic-to-Ntot ratios, and
microbial specific respiration rates (qCO2) were all within
the range reported for boreal forest soils (Smolander et al.,
1994; Pietikainen and Fritze, 1995; Scheu and Parkinson,
1995; Bauhus et al., 1998; Startsev et al., 1998). Navail was
also within the range of reported values for forest soils
(Corns and Maynard, 1998; Maynard and MacIsaac, 1998;
Li et al., 2003), with extractable N values averaging around
0.3% and 0.2% of Ntot in the forest floor and the
uppermost mineral soil, respectively. The Cmic-to-Corg
ratios averaged 3.%1 and 3.2% and the Nmic-to-Ntot ratios
averaged 6.2% and 4.7% in the forest floor and the mineral
soil, respectively.
The fact that Cmic-to-Nmic ratio was not correlated with
any of the other variables measured except Nmic implies
that there was no causal link between bacteria:fungi ratio
and indices of microbial activity, OM characteristics and N
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L. Mariani et al. / Soil Biology & Biochemistry 38 (2006) 1734–1744
4.2. Effects of forest harvesting and soil compaction
1.0
Cmic
Cmic :Nmic
Axis 2: non constraint (PC1)
1741
Ntot
Ctot
Navail
Ctot:Ntot
Resp.
WC
Soil
compaction
Nmic
qCO2
-1.0
-1.0
1.0
Canonical axis 1: 20% of total variation
Fig. 2. RDA ordination plot of soil total C and N contents, microbial
biomass C and N contents, microbial respiration, and available N content
for the mineral soil, with compaction used as independent variable and
forest floor removal, the interaction term and the year of installation of the
plots as a covariates. Variables underlined contributed more than the
mean to the effect of compaction.
availability. Li et al. (2004) also found that Cmic-to-Nmic
ratio was not correlated with Ctot, Ntot, or Ctot-to-Ntot
ratio, while Srivastava and Singh (1991) reported that Cmicto-Nmic ratio was only negatively correlated with mineral N
content. On the contrary, the significant correlations
between microbial respiration, Ctot, Ntot, Ctot-to-Ntot ratio,
Cmic, Nmic, and Navail reflect that microbial activity, OM
quantity and quality, and available N are linked in the soil
nutrient cycle.
The forest floor has a microbial population that was
50% less efficient than the mineral soil (as the qCO2 data
shows), perhaps as a consequence of the abundance of food
that decreased competition among microbial populations
in the forest floor, allowing microbes to be less efficient. It
is to be noted however that the differences in microbial
efficiency did not contribute meaningfully to the difference
between the forest floor and mineral soil layers in the
multivariate analysis. In addition, the similarity in Cmic-toNmic ratio between the forest floor and the mineral soil
suggests that the fungi:bacteria ratio (Marumoto et al.,
1982) were very similar in those two soil material types.
Even though the plots were installed over a 4-year
period, the plots installed in 1995 did not differ from these
installed in 1998 or 1999 for the 10 chemical variables
measured in this study. At the study site, others reported as
well no effect of the age of the plots, on numerous
parameters, i.e., bulk density, nitrogen mineralization
and nitrification of 0–10 cm mineral soil and forest
floor, air porosity of the 0–2 cm mineral soil, tree growth
and tree regeneration (Kabzems and Haeussler, 2005;
Tan et al., 2005).
We found no significant effects of forest harvesting on
the studied parameters in the forest floor and the surface
mineral soil 3–7 years after the treatments were applied.
Harvesting was conducted in winter on frozen ground,
which is reported to have little effect on soil physical and
biological properties within one (Bock and Van Rees, 2002)
or 3–5 years after harvesting (Stone and Elioff, 1998; Block
et al., 2002). Harvesting clearly has been shown to have
immediate impacts on water evaporation at the soil
surface, soil temperature and its diurnal fluctuations, and
the size of easily decomposable OM pool (Greacen and
Sands, 1980; Lenhard, 1986; Williamson and Neilsen,
2000). However, our results suggest that 3–7 years after
harvesting various impacts on the soil ecosystem either
compensated each other, subsided, or were not yet noticeable on the measured parameters.
Severe soil compaction had no effect on any of the 10
measured chemical properties in the forest floor. In
addition, the bulk density of the forest floor was the same
in the LTSP experiment and the mature forest. These
results probably indicate that physical and biological
properties of the forest floor recovered from effects of
compaction 3–7 years after the treatment.
In the surface mineral soil, heavy compaction increased
Ctot and Ntot by 45% and 40%, Nmic by 72% and relative
water content by 34% and decreased Cmic-to-Nmic ratio by
29%. Changes in both the plant community composition
and in soil physical properties may be contributing to these
responses. The rhizomatous grass Calamagrostis canadensis
expanded to 4–6 times its original cover on compacted
plots where the forest floor was retained (Haeussler and
Kabzems, 2005). Severe compaction decreased significantly
the aeration porosity in the 0–2 cm deep mineral soil at the
study site (Kabzems and Haeussler, 2005) which reflect the
increase of volume of small pores at the expense of large
pores (Greacen and Sands, 1980; Shestak and Busse, 2005).
Thus, increases in soil C and N contents may be due to the
increase of small pores that protect the OM and bacteria
from protozoa grazing (Hassink et al., 1993; Shestak and
Busse, 2005). This should have reduced microbial activities
and hence the rates of mineralization and microbial
respiration (Elliott et al., 1980). The increased microbial
respiration rates were probably an artefact due to sieving
that disturbed the soil and caused more soil C to become
accessible to micro-organisms.
4.3. Effects of forest floor removal on mineral soil properties
Forest floor removal caused no significant effects on any
of the parameters measured in this study. A detailed survey
of the literature shows that forest floor removal has been
reported to cause no effect as frequently as negative effects
on these parameters (Table 1). In contrast, SOM quantity
and soil microbial activity of the surface mineral soil were
increased by compaction but were not affected by scalping.
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L. Mariani et al. / Soil Biology & Biochemistry 38 (2006) 1734–1744
Moreover, stem only harvesting did not affect SOM
quantity and soil microbial activity. In contrast with these
findings, forest floor removal and soil compaction on the
studied site have been shown to reduce white spruce and
aspen growth which will likely delay future stand development and reduce site productivity (Stone and Kabzems,
2002; Kabzems and Haeussler, 2005).
Differences between plant communities in the different
treatment plots were clear (Haeussler and Kabzems, 2005).
The forest floor removal plots had the greatest change in
vegetation composition and structure, featuring a prominent moss layer and reduced abundance of herbs and
shrubs. In contrast, Calamagrostis canadensis dominated
heavily compacted plots where the forest floor had been
retained (Haeussler and Kabzems, 2005). Competition
between tree seedlings and early successional understory
species is of main concern for forest regeneration (Steijlen
et al., 1995; Robinson et al., 2002; Hangs et al., 2003). Due
to the seasonal dynamic of N cycling (Li et al., 2003), a lack
of synchronicity between soil N availability and the N
needs of regenerating trees could also impact the relationships between the studied ecosystem properties.
Most importantly, large quantities of biomass and
nutrients were exported in the forest floor removal plots,
with the forest floor containing 1350 kg ha1 of N
(Kabzems, pers. comm.). In the stem only harvested
treatment 9% less wood biomass were exported as wood
residues (Kabzems, pers. comm.). The forest floor in boreal
forests is generally a thick layer of partially decomposed
recalcitrant OM which immobilizes nutrients and its
removal is expected to promote short-term site productivity by changing the site’s biophysical conditions and
encouraging decomposition but has the potential to
compromise long-term site productivity (Prescott et al.,
2000). At the study site, we observed little mixing of the
forest floor with the surface mineral soil in the forest floor
removal plots. We suggest that the effects of forest floor
removal on the uppermost layer of mineral soil were
partially compensated for by the changes in the composition of the plant community which regenerated in the short
period (3–7 years) after disturbance.
5. Conclusions
At 3–7 years after treatment application, biological
activities, Ctot and Ntot in the uppermost mineral soil were
significantly increased by compaction but not affected by
harvesting or forest floor removal; biological activities, Ctot
and Ntot in the forest floor were neither affected by
compaction nor by harvesting. Our results contrast with
other studies that reported negative impacts of forest
harvesting, soil compaction and forest floor removal on
tree regeneration at the study site. Further studies are
needed to determine if these contradictions resulted from
an incomplete picture of the interactions between the soil
environment, plant communities and tree species or if they
describe the reality of soil microbial communities being
more resistant than trees to changes imposed by the
treatments.
Acknowledgements
We thank Tony Hunt, Brian Farwell and Todd
Thomson, foresters and coop student, respectively, British
Columbia Ministry of Forests, for their help with field
sampling, and Monica Molina and Miwa Matsushima for
valuable technical help in the laboratory. We are also
grateful to Drs. Pierre Legendre (Universite´ de Montre´al,
Canada), Marti J. Anderson (University of Auckland, New
Zealand), and Y. Feng (University of Alberta), for help
with statistical analysis and to Dr. Robert F. Powers, PSW
Research Station, USDA Forest Service, for providing
information on LTSP experiments. Lucero Mariani was
funded by a research grant and a postdoctoral fellowship
from the Alberta Ingenuity Fund.
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Soil Biology & Biochemistry 38 (2006) 1734–1744
www.elsevier.com/locate/soilbio
Effects of tree harvesting, forest floor removal, and compaction on
soil microbial biomass, microbial respiration, and N availability
in a boreal aspen forest in British Columbia
Lucero Mariania,, Scott X. Changa, Richard Kabzemsb
a
Department of Renewable Resources, 442 Earth Sciences Building, University of Alberta, Edmonton, Alta., Canada T6G 2E3
b
Ministry of Forests, 9000–17th St., Dawson Creek, BC, Canada V1G 4A4
Received 30 May 2005; received in revised form 27 November 2005; accepted 29 November 2005
Available online 17 February 2006
Abstract
The effects of timber harvesting and the resultant soil disturbances (compaction and forest floor removal) on relative soil water
content, microbial biomass C and N contents (Cmic and Nmic), microbial biomass C:N ratio (Cmic-to-Nmic), microbial respiration,
metabolic quotient (qCO2), and available N content in the forest floor and the uppermost mineral soil (0–3 cm) were assessed in a longterm soil productivity (LTSP) site and adjacent mature forest stands in northeastern British Columbia (Canada). A combination of
principal component analysis and redundancy analysis was used to test the effects of stem-only harvest, whole tree harvest plus forest
floor removal, and soil compaction on the studied variables. Those properties in the forest floor were not affected by timber harvesting or
soil compaction. In the mineral soil, compaction increased soil total C and N contents, relative water content, and Nmic by 45%, 40%,
34% and 72%, respectively, and decreased Cmic-to-Nmic ratio by 29%. However, these parameters were not affected by stem only
harvesting or whole tree harvesting plus forest floor removal, contrasting the reduction of white spruce and aspen growth following forest
floor removal and soil compaction reported in an earlier study. Those results suggest that at the study site the short-term effects of timber
harvesting, forest floor removal, and soil compaction are rather complex and that microbial populations might not be affected by the
perturbations in the same way as trees, at least not in the short term.
r 2006 Elsevier Ltd. All rights reserved.
Keywords: Available N; Boreal forest; Long-term soil productivity (LTSP); Microbial respiration; Microbial biomass; qCO2; Redundancy analysis
1. Introduction
Forest harvesting has been reported to decrease soil
evapotranspiration, increase soil temperature and its
diurnal fluctuations, and create a large amount of debris
and dead roots that are easily decomposed by soil biota
(Greacen and Sands, 1980; Lenhard, 1986; Williamson and
Neilsen, 2000). In addition, forest-harvesting machinery
may cause soil compaction and uneven forest floor
displacement or disturbance, and common site preparation
practices such as harvest residue removal and forest floor
Corresponding author. Present address: Muse´um National d’Histoire
Naturelle, 4 avenue du Petit Chaˆteau, 91 800 Brunoy, France.
Tel.: +33 1 60 47 92 14; fax: +33 1 60 46 57 19.
E-mail address: lucero.mariani@wanadoo.fr (L. Mariani).
0038-0717/$ - see front matter r 2006 Elsevier Ltd. All rights reserved.
doi:10.1016/j.soilbio.2005.11.029
scalping can affect site organic matter (OM) content and
soil porosity, the two ecosystem properties most likely to
impact long-term soil productivity (Powers et al., 2005).
Assessing the effects of forest harvesting and site
preparation practices on soil biological properties and
processes is a crucial step towards the conservation of
forest ecosystem functions and productivity (Li et al.,
2004). Soil organic matter (SOM) content and quality, soil
microbial biomass, microbial respiration, and N availability have been used as indices to assess soil biological
activity and health (Nambiar, 1996; Burger and Kelting,
1999; Schoenholtz et al., 2000). SOM content and quality
are generally considered as key indicators of forest soil
quality and sustainability because SOM is linked to the
fundamental attributes of the soil: water-holding capacity,
nutrient availability, soil buffering capacity, rates of gas
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L. Mariani et al. / Soil Biology & Biochemistry 38 (2006) 1734–1744
exchange, and soil biological activities (Powers et al., 2005;
Nambiar, 1996). Soil microbial biomass is a small but very
active part of the SOM and has frequently been suggested
as a sensitive indicator of change, whereas total SOM
content appears to be quite resilient to soil disturbance
(Johnson et al., 1991; Bauhus et al., 1998; Stone and Elioff,
1998; Piatek and Allen, 1999; Li et al., 2004). Microbial
respiration is a measure of soil biological activity that can
be combined with microbial biomass to derive specific
microbial respiration (qCO2) that can be used to assess the
efficiency of soil micro-organisms in utilizing C substrates
(Insam, 1990; Pietikainen and Fritze, 1995; Bauhus et al.,
1998). Being at the core of plant nutrition, soil N
availability is also a critical index for evaluating the
sustainability of soil productivity (Marshall, 2000; Li et al.,
2003).
Reports on the impact of forest harvesting, soil
compaction, and forest floor removal on biological properties of forest soils are still scarce and some experiments
were designed in such a way that compaction and forest
floor removal treatments are confounded (i.e., Dick et al.,
1988; Pietikainen and Fritze, 1995; Corns and Maynard,
1998). In addition, some published studies report contradictory results, such as those summarized in Table 1. Table
1 indicates that stem only harvest and forest floor removal
either cause no effect or decrease the parameters listed;
while whole tree harvest and soil compaction can cause no
effect, increase, or decrease the measured properties. A
most recent publication reports that compaction alters soil
physical properties and tree growth but not the biological
indices of soil health, indicating a strong resilience of the
microbial communities (Shestak and Busse, 2005). While
tree growth can be impaired by the decrease of large pores
due to compaction, microbes were found to take advantage
of the increased volume of small pores (Shestak and Busse,
2005). Forest floor removal could also alter mineral soil
properties in a contrasting way for plants and microbes.
Therefore, no definitive conclusions can be made regarding
the impact of forest harvesting and soil disturbances on soil
biological properties, particularly in the boreal region in
North America.
The objective of this study was to investigate the effects
of soil compaction and forest floor removal on microbial
biomass C and N contents (Cmic and Nmic), microbial
respiration, and soil N availability in a long-term soil
productivity (LTSP) experiment established in a representative mesic aspen ecosystem in northeastern British
Columbia, Canada. Under boreal aspen forests, SOM
contents, total soil N and S contents, available N and P,
and other nutrients are significantly higher in the forest
floor and the first few centimetres of the mineral soil than
in deeper horizons (Neville et al., 2002) and the highest
concentration of roots are at the organic/mineral–soil
interface (Strong and La Roi, 1985). We therefore sampled
the forest floor and the uppermost mineral soil (0–3 cm) in
order to study the most biologically active soil horizons.
Forest floor removal and soil compaction on the studied
site have been shown to reduce white spruce and aspen
Table 1
A summary of published studies on the effects of timber harvest, soil compaction, and forest floor removal on soil biological properties
Forest floor
Cmicb
Resp.
qCO2
Corg
Navail
Ntot
Stem only harvest
Whole tree harvest
No effect
No effect
Decrease
Decrease
No effect
Increase
Forest floor removala
Decrease
No effect
Decrease
9c
9
5
5
Surface mineral soil (0–15 cm)
Cmic
Nmic
Cmic:Nmic
Resp.
5
Corg
Navail
8
Ntot
8
WC
8
a
Increase
Soil compactiona
9
5
9
5; 12d
5
1; 9
1
1
1
12
2; 4; 7; 10
4
11
5
8
8
5
8
11; 10
2; 6
4; 6
6
4; 12; 3
6
6; 3
7
7
6
2
5; 12
8; 6
8; 12
8
4
4; 7
8; 6
4
6
4
Additional effects over timber harvest.
Cmic, microbial biomass C; Nmic, microbial biomass N; Resp., microbial respiration; qCO2, specific microbial respiration; Corg, soil organic C; Navail,
available N; Ntot, total soil N; WC, water content.
c
References: (1) Corns and Maynard (1998), (2) Dick et al. (1988), (3) Gomez et al. (2002), (4) Jordan et al. (2000), (5) Laiho et al. (2003), (6) Li et al.
(2003), (7) Li et al. (2004), (8) Piatek and Allen (1999), (9) Pietikainen and Fritze (1995), (10) Shestak and Busse (2005), (11) Startsev et al. (1998), (12)
Stone and Elioff (1998).
d
Forest floor removal effects on properties of the newly accumulated forest floor.
b
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growth which will likely delay future stand development
and reduce site productivity (Stone and Kabzems, 2002).
However we expected contrasting results between tree
growth and soil processes (Shestak and Busse, 2005).
Consequently, we hypothesized that tree harvesting, soil
compaction, and forest floor removal do not change
mineral soil microbial biomass, microbial respiration and
N availability, and that tree harvesting and soil compaction
do not affect these properties in the forest floor.
2. Materials and methods
2.1. Study site
The research site is located about 40 km northeast of
Dawson Creek (551580 N, 1201280 W; 720 masl) in the Peace
Forest District, in northeastern British Columbia. The site
is representative of mesic aspen (Populus tremuloides
Michx.) ecosystems in the moist, warm subzone of the
Boreal White and Black Spruce (BWBS) biogeoclimatic
zone (DeLong et al., 1990, 1991). The site has a south
aspect and a 4% slope gradient. The overstory tree species
were dominated by aspen, with small amounts of white
spruce (Picea glauca (Moench) Voss), cottonwood (Populus
balsamifera L.) and lodgepole pine (Pinus contorta ex
Loud. var. latifolia Engelm.). Soils on the study site have
20–30 cm of silt loam veneer over clay loam and are
dominated by Luvic Gleysols (Soil Classification Working
Group, 1998). The pre-treatment forest floor thickness
averaged 7.5 cm (Kabzems, unpublished data) and the
humus form was classified as a Lamimoder (Fons et al.,
1998). The pre-treatment forest floor contained
1350 kg ha1 of total N (SE of the mean: 71 kg ha1;
Kabzems, unpublished data). Annual precipitation ranges
between 395 and 660 mm, with 33–63% of this falls as
snow, mean annual temperature is 1.1 1C, and mean frost
free period is 150 days (DeLong et al., 1990).
2.2. Experimental design and sample collection
Forest floor and 0–3 cm mineral soil samples were
collected with a Dutch auger in September 2002 from all
three replications (replicated at the plot level) of four
treatments of the LTSP experiment and adjacent mature
forests. The sampled four treatments in the LTSP
experiment were: (1) stem-only harvest (forest floor intact),
no compaction (treatment code: NcFi), with two of the
replications installed in 1995 and the other in 1999; (2)
stem-only harvest (forest floor intact), heavy compaction
(HcFi), with two of the replications installed in 1995 and
the other in 1999; (3) whole-tree harvest plus forest floor
removal, no compaction (NcFr), with one of the replications installed in 1995 and the other two in 1998; and (4)
whole-tree harvest plus forest floor removal, heavy
compaction (HcFr). One of the HcFr replications was
installed in 1995 and the other two in 1998. The treatment
plots are randomly arranged. Due to the installation of the
experiment over a 4 year period (1995–1999), as it was
impossible to have all the plots installed in one single year
for an experiment of this size, there is no blocking in the
design. The time since installation was used as a covariate
in the analysis to remove it as a confounding factor as in
Kabzems and Haeussler (2005) and Tan et al. (2005). It was
found that plots installed in 1995 did not differ from those
installed in 1998 or 1999 for a wide range of soil properties
measured (Kabzems and Haeussler, 2005; Tan et al., 2005).
In the mature forest stands adjacent to the LTSP plots,
three transects were randomly located and they represented
the 3 replications of the mature forest treatment. In each
plot or transect, we collected one composite sample that
consisted of 18 sub-samples collected around 3 randomly
selected trees (6 sub-samples around each tree). The
samples were placed on ice in a cooler and transported
back to the laboratory.
2.3. Laboratory analyses
Fresh soil samples were passed through a 4 mm sieve.
Cmic and Nmic were measured on fresh samples by the
fumigation–extraction method (Brookes et al., 1985; Vance
et al., 1987). Each sample (20 g fresh mineral soil and 5 g
fresh forest floor sample) was fumigated in duplicates for
24 h with alcohol-free chloroform and then extracted in
60 ml 0.5 m K2SO4. Extracts of the duplicates were
combined prior to the measurement of their C and N
concentrations. Total N concentrations in K2SO4 extracts
was determined by Kjeldahl digestion (Voroney et al.,
1993) followed by colorimetric determination of the
NH+
4 –N (industrial method 98–70 W) concentration on a
Technicon Autoanalyzer II (Tarrytown, New York). Total
soluble organic carbon concentration in extracts was
determined with an ASTRO 2001 system 2 (Leagne City,
Texas). Extractability factors of 0.38 for Cmic (Vance et al.,
1987) and 0.54 for Nmic (Brookes et al., 1985; Bauhus et al.,
1998) were used to calculate Cmic and Nmic, respectively.
Available N (Navail) was measured by determining the
NH+
4 and NO3 (industrial method 487–77 A) concentrations in K2SO4 extracts of the non-fumigated soil samples
colorimetrically on a Technicon Autoanalyzer II following
the method in Maynard and Kalra (1993).
To measure microbial respiration, fresh soil samples
were pre-incubated for 7 days in the dark at 25 1C in 1 L
mason jars fitted with butyl rubber septa on the lids. For
the mineral soil, 6–8.5 g dry soil equivalent (in triplicates)
was used and for the forest floor samples 0.8–1.4 g dry mass
equivalent (in triplicates) was used. After the pre-incubation period, we ventilated the jars, closed the lids tightly
and immediately measured the initial CO2 concentration in
the jars. Concentrations of CO2 in the headspace of each
jar were measured with an HP 5890-II gas chromatograph
(Zibilske, 1994); 1 ml of the gas sample from each jar was
removed with a Gastights glass syringe and injected into
the GC. Then, the soil samples were incubated in the dark
at 25 1C for 7 or 8 days and we measured the CO2
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concentration in the headspace again. The difference in
CO2 concentrations between the initial and the postincubation measurements was used to calculate microbial
respiration.
Fresh samples of mineral soil (20 g) and forest floor (5 g)
were dried for 24 h at 105 1C to determine soil moisture
content gravimetrically. The relative soil water content was
expressed as water content as a percent of water holding
capacity. The water-holding capacity of the soils was
determined by the wet funnel method (Jenkinson and
Powlson, 1976). A sub-set of soil samples was air-dried and
ground to pass a 40-mesh sieve. Total C and N contents
(Ctot and Ntot) were determined by dry combustion
(Tabatabai and Bremner, 1991) with a Costech ECS 4010
elemental combustion analyzer (Milan, Italy). Carbonates
are absent from the soil. The results for all the measurements were expressed on an oven-dry soil weight basis and
converted to kg ha1 for each cm of depth of the material
using soil bulk densities of forest floor and mineral soil.
Data analyses were performed on the values expressed in
kg ha1 cm1.
2.4. Data analyses
2.4.1. Redundancy analysis (RDA)and permutation tests
The aim of the data analysis was to test the effects of
merchantable bole harvest, forest floor removal, and soil
compaction on the quantity and quality of SOM, including
Ctot and Ntot, soil C:N ratio (Ctot-to-Ntot), Cmic and Nmic,
Cmic-to-Nmic ratio, Navail, rates of microbial respiration,
qCO2, and relative water content.
We chose to run multivariate analyses because of the
strong correlations between the variables. Analysis of the
data by parametric MANOVA was not possible because of
heterogeneity of within-group variance (tested by Bartlett’s, Log-ANOVA, Cochran’s C, and Box’s M univariate
tests) and a high ratio of the number of variables to the
number of objects. In this paper, if the lowest variance is
greater than 33% of the highest variance, within-group
variance was considered to be homogeneous. Data
transformations were not able to correct the heterogeneity
of variance (heteroscedasticity).
RDA associated with permutation testing is an appropriate non-parametrical alternative to MANOVA for
ecological multivariate data sets (Verdonschot and ter
Braak, 1994; Legendre and Anderson, 1999; Anderson,
2001). We ran RDA on the correlation matrix (obtained
from data centred and standardized) and calculated the
multivariate within-group variances from the coordinate of
the soil samples. Permutation testing is impaired by
heteroscedasticity (Hayes, 1996; Legendre and Legendre,
1998). In case of heteroscedasticity, we have a two-part null
hypothesis: the multivariate locations (means) do not differ
and the within group variances do not differ. Consequently, a significant test might mean that the within group
variances are different but that the means do not differ. In
presence of heteroscedasticity, we used the ordination
1737
biplots to check the cause of a significant test (M.J.
Anderson pers. comm.).
We performed 3 sets of analyses: (1) for the 9 plots
(including the three mature forest transects and six forest
floor intact harvested plots) where both the forest floor and
mineral soil layers were present, we compared the forest
floor and the mineral soil by RDA with a dummy variable
indicating the layer of the sample (LAYER) as an
independent variable and dummy variables indicating if
the sample has been harvested (HARVEST) or compacted
(COMPACTION) as covariates. The 2 layers from the
same plot, autocorrelated, were treated as repeated
measures in the analysis. As we found a significant
difference between the 2 layers, we performed the
subsequent analyses for each layer separately; (2) to
analyse the timber harvesting effect, we first reduced the
number of biological variables by principal component
analysis (PCA). Then we used RDA as a form of inverse
analysis related to discriminant analysis (Legendre and
Legendre, 1998; Lepsˇ and Sˇmilauer, 2003) with the
resulting principal components (biological-PCs) as explanatory variables and HARVEST as dependent variable;
and (3) within the LTSP experiment, we tested the effect of
COMPACTION and organic matter removal by RDA.
The effect of organic matter removal was tested with
OMR, a dummy variable indicating if the organic matter
removal is low or severe. The time since installation was
used as a covariate. These 3 analyses were performed
separately for bulk density, because it is a parameter of a
different kind. All these RDA were tested by 999
permutations under the reduced model.
As RDA is a constraint PCA, we then used PCA to
evaluate the percentage of variation extracted by the RDA
by comparing it to the variation extracted by the first and
second principal components of the related PCA (Lepsˇ and
Sˇmilauer, 2003). We regard these variables that have a
correlation coefficient with the canonical axes greater than
the mean of all the correlation coefficients as making
meaningful contributions to the canonical axes (Heuer and
Smalla, 1997).
2.4.2. Spearmann R correlation coefficients
Spearmann’s R correlation coefficients represent the
proportion of common variation between the ranks of the 2
variables being compared. For the 10 variables under
study, 45 simultaneous correlation tests were performed.
We applied Hochberg’s method to correct for multiple
testing (Hochberg, 1988; Legendre and Legendre, 1998).
2.4.3. Statistical software
The Bartlett’s, Log-ANOVA, Cochran’s C, and Box’s M
tests for homogeneity of variances were performed by 999
permutations with the program Test_hv (Legendre, 2000);
PCA and RDA analyses were performed with CANOCO 4
for Windows (ter Braak, 1988) developed by Microcomputer Power (Ithaca, NY, USA); the Spearmann R
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correlation was analysed with the STATISTICA package
developed by StatSoft Inc. (Tulsa, OK, USA).
3. Results
3.1. Correlations between soil C and N contents and
microbial properties
When all 24 data points (five treatments with three
replications and one or two depths) were considered, soil
microbial respiration, Ctot, Ntot, Ctot-to-Ntot ratio, Cmic,
Nmic, and Navail were significantly and positively correlated
with each other, with 2 exceptions: between Navail and Ctot
and between Ctot-to-Ntot ratio and Ntot (Table 2). Cmic-toNmic ratio was not significantly correlated with any of the
other studied variables except for Nmic. Metabolic quotient
(qCO2) was significantly and positively correlated with
microbial respiration, Nmic and Navail, and Ctot-to-Ntot
ratio. Relative water content was significantly and negatively correlated only with Ctot-to-Ntot ratio (Table 2).
3.2. Soil biological activities in forest floor vs. mineral soil
and effects of timber harvesting
For the layer effect, the multivariate within-group
variances were heterogeneous with a variance for the
mineral samples reaching only 22% of the variance of the
forest floor samples. However, the plot of the samples in
the space of the dependant variables shows clearly that the
2 groups have different means (Fig. 1).
Reflecting the large differences between the forest floor
and mineral soil in the 10 studied variables (Tables 3 and
4), the difference between forest floor and mineral soil was
highly significant and explained 60% of the total variance
of the 10 variables under study (F ¼ 26:8, P ¼ 0:005; Fig.
1). This corresponds to 78% of the variance extracted by
the first 2 PCs of the related PCA. All the variables
contributed to the layer effect except qCO2, relative water
content, and Cmic-to-Nmic ratio (Fig. 1). Ctot, Ntot, Navail,
microbial respiration and Cmic-to-Nmic and Ctot-to-Ntot
ratios were 2, 2, 4, 4, 3, 3 times and 30% greater,
respectively, in the forest floor than in the mineral soil
(Tables 3 and 4).
For the forest floor, no effect of harvesting was found for
any of the studied variables (data not shown). The PCA of
the 10 variables under study yielded biological-PCs that
explained 31%, 20% and 19.5% of the total variation, for
the first, second and third PC, respectively (data not
shown). The discriminant analysis with these 3 biologicalPCs as independent variables and HARVEST as dependant variable explained 41% of the variability of two
grouping variables and was not significant (F ¼ 3:5,
P ¼ 0:502; data not shown). In the ordination plot, the
samples from the mature forest were mixed with the heavy
compaction-forest floor intact plots (graph not shown).
For the mineral soil, no effect of harvesting was found
either (Table 4). The PCA of the 10 variables under study
yielded PCs that explained 37%, 24%, 14% and 12% of
the total variation, for the first, second, third and fourth
biological-PC, respectively (data not shown). The discriminant analysis with these 4 biological-PCs as the
independent variable and HARVEST, as dependant
variable explained 43% of the variability of the two
grouping variables and was not significant (F ¼ 1:9,
P ¼ 0:175; data not shown). In the ordination plot, the
samples from the mature forest were mixed with all the
other groups of samples (data not shown).
3.3. Effects of compaction and forest floor removal in the
LTSP experiment
The time since installation had no effect on the 10
variables under study in the forest floor and the mineral
soil: it explained 17% and 3% of the total variations for the
forest floor and the mineral soil, respectively (Table 5).
For the forest floor, the multivariate analysis did not
detect a significant effect of the compaction treatment or
year since installation on the 10 variables under study
(Table 5). The proportion of the variance explained by soil
compaction (23%) was less than half of the fraction
Table 2
Spearmann R rank correlation coefficients among the 10 studied variables for two depths, including both the mature forest and LTSP plots (n ¼ 24)
Ntot
a
Resp.
Ntot
Ctot
Cmic
Nmic
Navail
Ctot:Ntot
Cmic:Nmic
qCO2
#
#
0.566
Ctot
Cmic
Nmic
Navail
Ctot:Ntot
Cmic:Nmic
qCO2
WC
0.749***
0.903***
0.923***
0.641*
0.750***
0.762***
0.577#
0.707**
0.750***
0.740***
0.564#
0.529 ns
0.784***
0.563#
0.698**
0.523 ns
0.578#
0.666*
0.563#
0.642*
0.026 ns
0.067 ns
0.146 ns
0.060 ns
0.566#
0.175 ns
0.105 ns
0.790***
0.300 ns
0.486 ns
0.533 ns
0.562#
0.566#
0.580#
0.136 ns
0.431 ns
0.220 ns
0.220 ns
0.377 ns
0.364 ns
0.506 ns
0.772***
0.058 ns
0.449 ns
Test significant at 10%; *test significant at 5%; **test significant at 1%; ***test significant at p0.5%; ns, test non-significant at 10%.
a
Cmic, microbial biomass C; Nmic, microbial biomass N; Cmic:Nmic, microbial biomass C:N ratio; Ctot, soil C; Ntot, total soil N; Ctot:Ntot, soil C:N ratio;
Navail, available N; Resp., microbial respiration; qCO2, specific microbial respiration; WC, water content.
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Axis 2: non constraint (PC1)
1.0
1.0
LFH
Cmic:Nmic
qCO2 Ctot Resp.
LFH
Cmic and Ctot: Ntot
Ntot
Navail
LFH
LFH
LFH
LFH
MIN
LFH
LFH
LFH
WC
Nmic
LFH
(a)
-1.0
-1.5
(b)
-1.0
1.5
-1.0
Canonical axis 1:Layer effect, 60% of total variation
1.0
Fig. 1. Differences between forest floor and mineral soil layers for the 9 plots where the 2 layers were present (RDA on raw data centred and
standardized). (a) RDA ordination plot representing the soil samples (coordinates are linear combination of the dependent variables). (b) RDA ordination
plot. Variables underlined contributed more than the mean to canonical axis 1. The canonical analysis yielded only one canonical axis because there is only
one independent variable.
Table 3
Means and coefficients of variation in percent (in parentheses) of the
measured parameters in the forest floor (n ¼ 3)
Measurement
MFa
NcFi
HcFi
Bulk density (g cm3)
Ctotb (g kg1)
(kg ha1)
Ntot (g kg1)
(kg ha1)
Ctot:Ntot
Navail (mg kg1)
(kg ha1)
WC (as a % of WHC)
Resp. (mg CO2–C kg1 d1)
(kg CO2 ha1 d1)
qCO2 (g CO2–C kg1 Cmic d1)
Cmic (mg kg1)
(kg ha1)
Nmic (mg kg1)
(kg ha1)
Cmic:Nmic
0.24 (17)
366 (8)
4815 (21)
17.0 (7)
220 (17)
21.6 (4)
61 (9)
8 (6)
25 (2)
451 (7)
58 (15)
40 (4)
9639 (13)
1460 (14)
896 (10)
118 (23)
12.8 (8)
0.16 (15)
403 (2)
3424 (12)
19.3 (4)
165 (15)
20.9 (5)
70 (8)
6 (10)
26 (2)
374 (3)
32 (16)
30 (5)
12074 (5)
1085 (12)
1300 (15)
109 (13)
10.1 (10)
0.22 (21)
367 (6)
4278 (21)
17.6 (6)
205 (20)
20.8 (2)
50 (7)
6 (21)
26 (5)
505 (8)
59 (23)
48 (4)
13057 (10)
1243 (24)
1128 (21)
128 (28)
11.1 (38)
a
MF, mature forest; NcFi, no compaction with forest floor intact;
HcFi, heavy compaction with forest floor intact.
b
Cmic, Microbial biomass C; Nmic, Microbial biomass N; Cmic:Nmic,
microbial biomass C:N ratio; Ctot, soil C; Ntot, total soil N; Ctot:Ntot,
soil C:N ratio; Navail, Available N; Resp., microbial respiration; qCO2,
specific microbial respiration; WC, water content; WHC, water-holding
capacity.
extracted by the first 2 PCs of the related PCA (64%, data
not shown). Therefore, we did not look further at the forest
floor results.
In contrast, for the mineral soil, the full model (Soil
compaction+OM removal+Interaction) significantly ex-
plained 41% of the variability of the 10 variables under
study in the experimental plots, after removing the effect of
the covariate (Table 5). This is a substantial fraction (63%)
of the total variability (66%) extracted by the first 2 PCs of
the related PCA (data not shown). Soil compaction was the
only factor significant in the RDA, explaining 20% of the
total variability of the data (Table 5).
The mineral soil had higher Ctot, Ntot, Nmic, and water
content, but a lower Cmic-to-Nmic ratio in the compacted
than in the non-compacted plots; Cmic and qCO2 were only
slightly higher in the compacted plots and did not
contribute meaningfully to the treatment effect (only
10% of the total variability for Cmic and 6% for qCO2
were explained by the compaction factor; data not shown);
Navail and Ctot-to-Ntot ratio were not affected by compaction (Fig. 2, Table 4).
3.4. Bulk density
For bulk density, the only significant difference was
between the forest floor and the uppermost mineral soil
(91% of the total variability explained by the layer effect,
F ¼ 145, P ¼ 0:005). For the uppermost mineral soil, the
tests were non-significant, with 3% (F ¼ 0:4, P ¼ 0:533)
and 24% (F ¼ 2:2, P ¼ 0:578), respectively, of variability
explained by harvesting, and the treatments in the LTSP
experiment, i.e., compaction+forest floor removal+interaction term). For the forest floor, similarly, the effects of
harvesting and compaction were non-significant, with 39%
(F ¼ 11:2, P ¼ 0:107) and 21% (F ¼ 1:8, P ¼ 0:236) of
variability explained, respectively.
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Table 4
Means and coefficients of variation in percent (in parentheses) of the measured parameters in the 0–3 cm deep mineral soil (n ¼ 3)
Measurement
MFa
NcFr
NcFi
HcFr
HcFi
Bulk density (g cm3)
Ctotb (g kg1)
(kg ha1)
Ntot (g kg1)
(kg ha1)
Ctot:Ntot
Navail (mg kg1)
(kg ha1)
WC (as a % of WHC)
Resp. (mg CO2–C kg1 d1)
(kg ha1 d1)
qCO2 (g CO2–C kg1 Cmic d1)
Cmic (mg kg1)
(kg ha1)
Nmic (mg kg1)
(kg ha1)
Cmic:Nmic
0.83 (11)
43.8 (21)
1044 (10)
2.8 (25)
66 (15)
16.0 (7)
5 (19)
1 (7)
37 (12)
33 (1)
8 (6)
33 (20)
1207 (21)
262 (14)
84 (27)
20 (26)
13.9 (16)
0.98 (3)
26.4 (21)
770 (20)
1.8 (19)
54 (19)
14.3 (8)
3 (4)
1 (4)
55 (6)
29 (7)
8 (6)
25 (14)
896 (13)
327 (10)
94 (16)
27 (17)
12.3 (14)
0.82 (5)
35.7 (5)
874 (0)
2.2 (12)
53 (8)
16.6 (8)
4 (16)
1 (12)
41 (2)
23 (21)
6 (17)
21 (3)
784 (23)
268 (12)
80 (20)
19 (16)
14.3 (8)
0.85 (11)
49.6 (26)
1289 (21)
3.1 (22)
81 (17)
15.9 (5)
4 (11)
1 (6)
36 (8)
33 (10)
9 (7)
24 (4)
2025 (15)
372 (15)
147 (27)
40 (29)
11.2 (33)
0.86 (15)
41.1 (8)
1091 (5)
2.6 (10)
70 (6)
15.7 (1)
4 (13)
1 (7)
28 (12)
31 (2)
8 (14)
26 (6)
1364 (5)
305 (10)
176 (26)
41 (11)
7.8 (18)
a
NcFi, no compaction with forest floor intact; HcFi, heavy compaction with forest floor intact; NcFr, no compaction with forest floor removed; HcFr,
heavy compaction with forest floor removed.
b
Cmic, microbial biomass C; Nmic, microbial biomass N; Cmic:Nmic, microbial biomass C:N ratio; Ctot, total soil C; Ntot, total soil N; Ctot:Ntot, soil C:N
ratio; Navail, available N; Resp., microbial respiration; qCO2, specific microbial respiration; WC, water content; WHC, water-holding capacity.
Table 5
Variance decomposition of the effect of the treatments and the covariate on the measured variables in the forest floor and mineral soil layers. RDA on raw
data centred and standardized (multivariate analyses)
Source
Data analysis
Variance %
DF
F
P
Forest floor
Installation year (covariate)
Soil compaction
Unexplained
Partial RDA
Simple RDA
By difference
17.1
23.1
59.8
1
1
4
0.86
1.16
—
0.551 ns
0.456 ns
—
Mineral soil
Installation year (covariate)
Explained (A+B+A B)
Interaction (A B)
Soil compaction (A)
Organic matter removal (B)
Unexplained
Partial RDA
Simple RDA
Partial RDA
Partial RDA
Partial RDA
By difference
3.2
40.9
7.6
20.2
13.1
55.9
1
3
1
1
1
8
0.37
1.63
0.88
2.85
1.15
—
0.868 ns
0.088 #
0.510 ns
0.048 *
0.3480 ns
—
ns: Test non-significant at the 10% level. #Test significant at the 10% level;*test significant at the 5% level.
4. Discussion
4.1. Forest floor and mineral soil properties
Cmic and Nmic contents, Cmic-to-Nmic, Cmic-to-Corg (total
soil organic C content) and Nmic-to-Ntot ratios, and
microbial specific respiration rates (qCO2) were all within
the range reported for boreal forest soils (Smolander et al.,
1994; Pietikainen and Fritze, 1995; Scheu and Parkinson,
1995; Bauhus et al., 1998; Startsev et al., 1998). Navail was
also within the range of reported values for forest soils
(Corns and Maynard, 1998; Maynard and MacIsaac, 1998;
Li et al., 2003), with extractable N values averaging around
0.3% and 0.2% of Ntot in the forest floor and the
uppermost mineral soil, respectively. The Cmic-to-Corg
ratios averaged 3.%1 and 3.2% and the Nmic-to-Ntot ratios
averaged 6.2% and 4.7% in the forest floor and the mineral
soil, respectively.
The fact that Cmic-to-Nmic ratio was not correlated with
any of the other variables measured except Nmic implies
that there was no causal link between bacteria:fungi ratio
and indices of microbial activity, OM characteristics and N
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L. Mariani et al. / Soil Biology & Biochemistry 38 (2006) 1734–1744
4.2. Effects of forest harvesting and soil compaction
1.0
Cmic
Cmic :Nmic
Axis 2: non constraint (PC1)
1741
Ntot
Ctot
Navail
Ctot:Ntot
Resp.
WC
Soil
compaction
Nmic
qCO2
-1.0
-1.0
1.0
Canonical axis 1: 20% of total variation
Fig. 2. RDA ordination plot of soil total C and N contents, microbial
biomass C and N contents, microbial respiration, and available N content
for the mineral soil, with compaction used as independent variable and
forest floor removal, the interaction term and the year of installation of the
plots as a covariates. Variables underlined contributed more than the
mean to the effect of compaction.
availability. Li et al. (2004) also found that Cmic-to-Nmic
ratio was not correlated with Ctot, Ntot, or Ctot-to-Ntot
ratio, while Srivastava and Singh (1991) reported that Cmicto-Nmic ratio was only negatively correlated with mineral N
content. On the contrary, the significant correlations
between microbial respiration, Ctot, Ntot, Ctot-to-Ntot ratio,
Cmic, Nmic, and Navail reflect that microbial activity, OM
quantity and quality, and available N are linked in the soil
nutrient cycle.
The forest floor has a microbial population that was
50% less efficient than the mineral soil (as the qCO2 data
shows), perhaps as a consequence of the abundance of food
that decreased competition among microbial populations
in the forest floor, allowing microbes to be less efficient. It
is to be noted however that the differences in microbial
efficiency did not contribute meaningfully to the difference
between the forest floor and mineral soil layers in the
multivariate analysis. In addition, the similarity in Cmic-toNmic ratio between the forest floor and the mineral soil
suggests that the fungi:bacteria ratio (Marumoto et al.,
1982) were very similar in those two soil material types.
Even though the plots were installed over a 4-year
period, the plots installed in 1995 did not differ from these
installed in 1998 or 1999 for the 10 chemical variables
measured in this study. At the study site, others reported as
well no effect of the age of the plots, on numerous
parameters, i.e., bulk density, nitrogen mineralization
and nitrification of 0–10 cm mineral soil and forest
floor, air porosity of the 0–2 cm mineral soil, tree growth
and tree regeneration (Kabzems and Haeussler, 2005;
Tan et al., 2005).
We found no significant effects of forest harvesting on
the studied parameters in the forest floor and the surface
mineral soil 3–7 years after the treatments were applied.
Harvesting was conducted in winter on frozen ground,
which is reported to have little effect on soil physical and
biological properties within one (Bock and Van Rees, 2002)
or 3–5 years after harvesting (Stone and Elioff, 1998; Block
et al., 2002). Harvesting clearly has been shown to have
immediate impacts on water evaporation at the soil
surface, soil temperature and its diurnal fluctuations, and
the size of easily decomposable OM pool (Greacen and
Sands, 1980; Lenhard, 1986; Williamson and Neilsen,
2000). However, our results suggest that 3–7 years after
harvesting various impacts on the soil ecosystem either
compensated each other, subsided, or were not yet noticeable on the measured parameters.
Severe soil compaction had no effect on any of the 10
measured chemical properties in the forest floor. In
addition, the bulk density of the forest floor was the same
in the LTSP experiment and the mature forest. These
results probably indicate that physical and biological
properties of the forest floor recovered from effects of
compaction 3–7 years after the treatment.
In the surface mineral soil, heavy compaction increased
Ctot and Ntot by 45% and 40%, Nmic by 72% and relative
water content by 34% and decreased Cmic-to-Nmic ratio by
29%. Changes in both the plant community composition
and in soil physical properties may be contributing to these
responses. The rhizomatous grass Calamagrostis canadensis
expanded to 4–6 times its original cover on compacted
plots where the forest floor was retained (Haeussler and
Kabzems, 2005). Severe compaction decreased significantly
the aeration porosity in the 0–2 cm deep mineral soil at the
study site (Kabzems and Haeussler, 2005) which reflect the
increase of volume of small pores at the expense of large
pores (Greacen and Sands, 1980; Shestak and Busse, 2005).
Thus, increases in soil C and N contents may be due to the
increase of small pores that protect the OM and bacteria
from protozoa grazing (Hassink et al., 1993; Shestak and
Busse, 2005). This should have reduced microbial activities
and hence the rates of mineralization and microbial
respiration (Elliott et al., 1980). The increased microbial
respiration rates were probably an artefact due to sieving
that disturbed the soil and caused more soil C to become
accessible to micro-organisms.
4.3. Effects of forest floor removal on mineral soil properties
Forest floor removal caused no significant effects on any
of the parameters measured in this study. A detailed survey
of the literature shows that forest floor removal has been
reported to cause no effect as frequently as negative effects
on these parameters (Table 1). In contrast, SOM quantity
and soil microbial activity of the surface mineral soil were
increased by compaction but were not affected by scalping.
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L. Mariani et al. / Soil Biology & Biochemistry 38 (2006) 1734–1744
Moreover, stem only harvesting did not affect SOM
quantity and soil microbial activity. In contrast with these
findings, forest floor removal and soil compaction on the
studied site have been shown to reduce white spruce and
aspen growth which will likely delay future stand development and reduce site productivity (Stone and Kabzems,
2002; Kabzems and Haeussler, 2005).
Differences between plant communities in the different
treatment plots were clear (Haeussler and Kabzems, 2005).
The forest floor removal plots had the greatest change in
vegetation composition and structure, featuring a prominent moss layer and reduced abundance of herbs and
shrubs. In contrast, Calamagrostis canadensis dominated
heavily compacted plots where the forest floor had been
retained (Haeussler and Kabzems, 2005). Competition
between tree seedlings and early successional understory
species is of main concern for forest regeneration (Steijlen
et al., 1995; Robinson et al., 2002; Hangs et al., 2003). Due
to the seasonal dynamic of N cycling (Li et al., 2003), a lack
of synchronicity between soil N availability and the N
needs of regenerating trees could also impact the relationships between the studied ecosystem properties.
Most importantly, large quantities of biomass and
nutrients were exported in the forest floor removal plots,
with the forest floor containing 1350 kg ha1 of N
(Kabzems, pers. comm.). In the stem only harvested
treatment 9% less wood biomass were exported as wood
residues (Kabzems, pers. comm.). The forest floor in boreal
forests is generally a thick layer of partially decomposed
recalcitrant OM which immobilizes nutrients and its
removal is expected to promote short-term site productivity by changing the site’s biophysical conditions and
encouraging decomposition but has the potential to
compromise long-term site productivity (Prescott et al.,
2000). At the study site, we observed little mixing of the
forest floor with the surface mineral soil in the forest floor
removal plots. We suggest that the effects of forest floor
removal on the uppermost layer of mineral soil were
partially compensated for by the changes in the composition of the plant community which regenerated in the short
period (3–7 years) after disturbance.
5. Conclusions
At 3–7 years after treatment application, biological
activities, Ctot and Ntot in the uppermost mineral soil were
significantly increased by compaction but not affected by
harvesting or forest floor removal; biological activities, Ctot
and Ntot in the forest floor were neither affected by
compaction nor by harvesting. Our results contrast with
other studies that reported negative impacts of forest
harvesting, soil compaction and forest floor removal on
tree regeneration at the study site. Further studies are
needed to determine if these contradictions resulted from
an incomplete picture of the interactions between the soil
environment, plant communities and tree species or if they
describe the reality of soil microbial communities being
more resistant than trees to changes imposed by the
treatments.
Acknowledgements
We thank Tony Hunt, Brian Farwell and Todd
Thomson, foresters and coop student, respectively, British
Columbia Ministry of Forests, for their help with field
sampling, and Monica Molina and Miwa Matsushima for
valuable technical help in the laboratory. We are also
grateful to Drs. Pierre Legendre (Universite´ de Montre´al,
Canada), Marti J. Anderson (University of Auckland, New
Zealand), and Y. Feng (University of Alberta), for help
with statistical analysis and to Dr. Robert F. Powers, PSW
Research Station, USDA Forest Service, for providing
information on LTSP experiments. Lucero Mariani was
funded by a research grant and a postdoctoral fellowship
from the Alberta Ingenuity Fund.
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