Seasonal changes of principal anions con

Science of the Total Environment 442 (2013) 165–171

Contents lists available at SciVerse ScienceDirect

Science of the Total Environment
journal homepage: www.elsevier.com/locate/scitotenv

Profile distribution and temporal changes of sulphate and nitrate contents and
related soil properties under beech and spruce forests
Václav Tejnecký a,⁎, Monika Bradová a, Luboš Borůvka a, Karel Němeček a, Ondřej Šebek b,
Antonín Nikodem a, Jitka Zenáhlíková c, Jan Rejzek c, Ondřej Drábek a
a
b
c

Department of Soil Science and Soil Protection, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Kamýcká 129, 165 21 Prague 6, Czech Republic
Laboratories of the Geological Institutes, Faculty of Science, Charles University in Prague, Albertov 6, 128 43 Prague 2, Czech Republic
Department of Silviculture, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 21 Prague 6, Czech Republic

H I G H L I G H T S
► Distribution of sulphate and nitrate in the soil profile

► Sulphate and nitrate in acid forest soil under different vegetation covers
► Soil properties influencing the distribution of inorganic anions.

a r t i c l e

i n f o

Article history:
Received 18 June 2012
Received in revised form 11 October 2012
Accepted 12 October 2012
Available online xxxx
Keywords:
Soil acidification
Vegetation cover
Forest soils
Anions
Sulphate
Nitrate

a b s t r a c t
The behaviour of principal inorganic anions in forest soils, originating mainly from acid deposition, strongly
influences the forest ecosystem response on acidification. The aim of this study was to describe seasonal and
temporal changes of sulphate and nitrate contents and related soil properties under beech and spruce forests
in a region heavily impacted by acidification. The Jizera Mountains area (Czech Republic) was chosen as such
a representative mountainous soil ecosystem. Soil samples were collected at monthly intervals from April to
October during the years 2008–2010 under both beech and spruce stands. Soil samples were collected from
surface fermentation (F) and humified (H) organic horizons, humic (A) organo-mineral horizons and subsurface mineral (B) horizons (cambic or spodic). A deionised water extract was applied to unsieved fresh samples
and the content of anions in these extracts was determined by ion chromatography (IC).
In the studied soil profiles, the lowest amount of SO42− was found in the organo-mineral A horizons under both
types of vegetation. Under spruce the highest amount of SO42− was determined in mineral spodic (B) horizons,
where a strong sorption influence of Fe and Al oxy-hydroxides is expected. Under beech the highest amount was
observed in the surface organic F horizons (forest floor). The amount of NO3− is highest in the F horizons and decreases with increasing soil profile depth under both types of vegetation. A significantly higher amount of NO3−
was determined in soils under the beech stand compared to spruce. For both soil environments – under beech
and also spruce stands – we have determined a general increase of water-extractable SO42− and NO3− during the
whole monitoring period. The behaviour of SO42− and NO3− in the soils is strongly related to the dynamics of soil
organic matter and particularly to the DOC.
© 2012 Elsevier B.V. All rights reserved.

1. Introduction

Principal inorganic anions (Cl −, SO42− and NO3−) are introduced
into the environment mainly by dry and wet depositions. These anions
have a major impact on soil chemical and biological processes, forest
health status and quality of surface waters (DeHayes et al., 1999; Krug
and Frink, 1983; Puhe and Ulrich, 2001).
Deposition of SO42− and NO3− is significantly affected by anthropogenic emissions of SO2 and NOx. Since 1985 there was a significant decrease
⁎ Corresponding author. Tel.: +420 224382759.
E-mail address: tejnecky@af.czu.cz (V. Tejnecký).
0048-9697/$ – see front matter © 2012 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.scitotenv.2012.10.053

in the deposition of SO2 and NOx in the Czech and Slovak Republics. By
the year 2000 the deposition of SO2 had decreased by about 87% and deposition of NOx had decreased by about 51% (Kopáček and Veselý, 2005).
The decrease of SO42− deposition has been observed since 1990. Prechtel
et al. (2001) report the decrease by about 38–82% on a European scale.
However, pools of organically bound S (originating from the years of
high S depositions) represent an internal source of SO42− in the soil environment. Thus, this SO42− source can strongly affect the recovery of anthropogenically acidified soil environments (Mitchell et al., 2011). A
faster degradation rate of soil organic matter (SOM) is attributed to the
decreased deposition of SO42− and NO3−. In the same time, the amount
of dissolved organic carbon (DOC), observed in surface waters of North

166

V. Tejnecký et al. / Science of the Total Environment 442 (2013) 165–171

The aim of this work is to i) monitor the amount of water-extractable
anions, namely SO42− and NO3−, in soils under beech and spruce forests affected by anthropogenic acidification and ii) assess seasonal and annual
trends in the distribution and behaviour of these anions.

America and Europe, exhibited an increasing trend (De Wit et al., 2007;
Monteith et al., 2007). Nowadays, the deposition of N compounds remains on a constant level. Nevertheless, a decrease of dissolved inorganic
nitrogen forms (DIN) in surface waters has been reported. It was shown
that the distribution and movement of DIN are significantly influenced
by S deposition, depth of surface organic horizons and C/N ratios in forest
floors (Oulehle et al., 2008).
The type of vegetation cover strongly affects not only soil characteristics but also the amount of deposited S and N compounds. The difference
between deposition caused by coniferous and broad-leaved species is apparent in basic soil characteristics, mainly in soil pH (De Schrijver et al.,
2007; Rothe et al., 2002). Whilst studying clear-cut areas, Drábek et al.
(2007) observed changes in Al speciation and pH in soils under different
vegetation covers. Generally, it is coniferous vegetation cover that catches

more of the dry deposition as opposed to broad leaved vegetation cover
or clear cut-areas. The difference is caused by the higher specific surface
of needles compared to leaves or grass and by the fact that needles are
present the whole year, unlike leaves of deciduous species. Thus,
the coniferous forests have higher interception of dust and gases. These
deposits are consequently washed by precipitation into the soil environment (Augusto et al., 2002; Berger et al., 2008; Rothe et al., 2002; Vannier
et al., 1993).
Mayer et al. (1995) and Zhang et al. (1998) concluded that the
mineralization of carbon-bound S was a considerable source of SO42−
in soil solutions of acidic forest soils. Alewell et al. (1999) also identified
that the organic S was determined as the main S pool in forest soils;
moreover, they claimed that adsorption/desoption of SO42− plays an important role in the retention of S in forest watershed ecosystems.
Ukonmaanaho and Starr (2002) studied an acidified watershed and
they found that organic soil layers are particularly important for N
retention and in contrast, deeper soil mineral layers (containing S
sorbents — Al and Fe hydroxide) are crucial for S retention.
Seasonal trends of SO42− and NO3− contents in stream waters have
been reported (Likens et al., 2002; Oulehle et al., 2008). The accumulation
of snow and its subsequent melting plays a major role in the dynamic of
SO42− output from soils and their input into stream flows during the year

(Likens et al., 2002). Tree uptake was identified as the main mechanism
that controls the amount of NO3− in watershed ecosystems during the
year (low values in midsummer and high values in winter) (Oulehle
et al., 2008).

2. Materials and methods
2.1. Site description
The principal part of the study was carried out on the locality Paličník
in the Jizera Mountains located in the north of the Czech Republic (Fig. 1).
The altitude of both studied plots ranges from 635 (bottom edge) to 680
(upper edge) m a.s.l. Annual precipitation is approximately 1200 mm
and the annual mean temperature 4–7°°C (Balcar et al., 2012; Remrova
and Císlerová, 2010). The climate is strictly identical between sites. Vegetation cover is formed mainly by acidophilic beechwood (forest dominated by Fagus sylvatica L.) and spruce monoculture (forest dominated
by Picea abies [L.] Karst.) with a dominance of Calamagrostis arundinacea
(L.) Roth and Calamagrostis villosa (Chaix ex Vill.) J. F. Gmel. in the herbal
layer; the clear-cut area is predominantly covered by C. villosa (Chaix ex
Vill.) J. F. Gmel. (Tejnecký et al., 2010). The average stand height is 28.6 m
in the spruce forest and 32.4 m in the beech forest. Average crown area is
14.7 m2 (spruce forest) and 32.4 m2 (beech forest). Soils are developed
from medium-grained porphyric granite to granodiorite of the Upper

Carboniferous age (Cháb et al., 2007). The soils were classified according
to the World Reference Base for Soil Resources (WRB, 2006). The prevailing soil types are Entic and Haplic Podzols (et PZ, ha PZ) under spruce forest and Aluminic Cambisols (au CM) under beech forest.
The water regime of the studied area was previously described by
(Batysta et al., 2010).
2.2. Soil sampling and sample treatment
Soil samples were collected on two adjacent areas; one covered
with beech forest and one with spruce forest (Tejnecký et al., 2010).
Sampling was carried out monthly in the period from April to October
2008–2010 (from April to November in 2009). Each time, three new soil
pits were dug on each area, with two pits closer to the opposite edges
and one close to the centre of the area. Following this rule, the particular
place for each pit was selected randomly. The distance between pits was

SPRUCE

BEECH

Beech forest

.

Jizera Mts.

.

N

.

Legend

.
..
. .
. .. .
. . . . . .. .
.
.
. .
.

.
.
.
.
.
.
.
. .
.
. .
.
. .
.
.
.
. .
.
.
.
.

.. . .
. . . ..
..
. .
.
.
.
.
.
.
.
. .
.
.
. . . . .
.. . .
.. . . . .
.
.
.

. . . . .
... .
. .. . . . .
. ..
.

.
.

60 Meters

.
.. . .
.

0

..

N

.
.

.

.
.

.

.

Clear-cut area
Sampling area

.
.
. .
.
.
.
.
. .
.
. .
.
.
. .
.
.
.
.
.
.
.
.
.
..
.
. .
. . ..
.
.
.
.

Spruce forest

Living tree

Crown projection 0

Border area

Rock

10

20

Prague

Czech Republic

Fig. 1. Sampling locality in the Czech Republic and permanent research plots (PRP) in the spruce and beech forests.

40 Meters

167

V. Tejnecký et al. / Science of the Total Environment 442 (2013) 165–171

at least 20 m. Soil samples were collected from all horizons with sufficient thickness. In all cases, samples were collected from surface fermentation (F) and humified (H) organic horizons and subsurface B
horizons (cambic or spodic). Where possible, samples from the surface
organo-mineral (humic, A) horizon were also collected. In total, 132 soil
pits were described and sampled during the sampling period and 492
samples were collected.
Two permanent research plots (PRP) in the spruce stand (60×55 m)
and in the beech stand (65×45 m) have been created in the investigated
area since 2010 (Fig. 1).
Collected samples were immediately treated and analysed in the
laboratory. Each sample was thoroughly mixed and then divided into
two parts. The first part was analysed in a “fresh” state representing
actual soil moisture. The moisture was determined gravimetrically.
The second part of each soil sample was air dried and sieved through
a 2 mm sieve.

of the anion determination was based on the application manual of
the IC instrument producer (Dionex, 2000; Dionex, 2003) and the US
EPA methodology for water analysis (US EPA, 1993). Standards were
prepared by dilution from 1 g L −1 anion concentrates (Analytika, CZ)
and deionised water (conductivity b 0.055 μS cm−1; Millipore, USA) in
the range of 0.1–50 mg L −1. The following determination limits were
calculated according to Cerjan Stefanović et al. (2001): Cl− 0.19, SO42−
0.56, NO3− 0.56 mg L −1.
The concentration of extracted Al was determined on an iCAP 6500
Radial ICP Emission spectrometer (Thermo Scientific, UK) equipped
with a concentric nebulizer and cyclonic spray chamber. The radial plasma instrument was chosen to reduce matrix interference. Standard reference materials NIST 1640 and NIST 1643d were used to check the
quality of the element determination in the aqueous extract. Aluminium
concentration was determined at the wavelength 167.079 nm, determination limit=0.05 mg Al L−1.

2.3. Sample analyses

2.4. Statistical analyses

2.3.1. Analysed soil characteristics
Fresh samples were subjected to a deionised water extracting
agent (ratio soil/water 1:10 w/v, 24 h extraction on a reciprocal shaker
at a stable laboratory temperature). The suspension was then centrifuged
at 4000 rpm for 15 min; finally, extracts were filtrated through a 0.45 μm
nylon membrane filter (Cronus Membrane Filter Nylon, GB). In aqueous
extracts the following chemical parameters were analysed: selected
inorganic anions (F−, SO42−, NO3− and Cl−) with ion chromatography
(IC) with suppressed conductivity, Al content with inductively coupled
plasma–optical emission spectrometer (see details below). Dissolved organic carbon (DOC) content was determined by a modified wet dichromate oxidation method according to Yakovchenko and Sikora (1998)
and Zbíral (2004). Results were compared for selected soil samples
with results of TOC Analyser (Apollo 9000HS, Central Laboratory of the
Czech Geological Survey) (Tejnecký et al., in preparation). A significant
correlation between results by the two methods was obtained (data not
shown). All results were recalculated to soil dry weight.
Active and exchangeable pH (pHH2O and pHKCl) were determined
on dried and sieved soil samples potentiometrically (pH metre inoLab
pH level 1 WTW, Germany); ratio soil/water or 0.2 M KCl was 1:10 w/v.

Stratigraphics XVI.I Centurion was used for statistical analyses.
Basic statistical analyses such as simple and multiple regression and
correlation and multivariate analysis of variance (MANOVA) were used.

2.3.2. Analytical equipment
The IC method for determination of inorganic anions was performed
by means of the ion chromatograph ICS 90 (Dionex, USA) equipped
with IonPac AS14A (Dionex, USA) guard and analytical columns were
used. The eluent composition was 8.0 mM Na2CO3/1.0 mM NaHCO3
and flow rate was set to 1 mL min−1. To suppress eluent conductivity
an AMMS 300 — 4 mm suppressor (Dionex, USA) and 25 mM H2SO4 reagent was used. The eluent conductivity was even further suppressed
by the carbon removal device CRD 300 — 4 mm (Dionex, USA) and
0.2 M NaOH solution. Samples were introduced by the autosampler
AS-DV (Dionex, USA). Chromatograms were processed and evaluated
using the software Chromeleon 6.80 (Dionex, USA). The methodology

3. Results and discussion
3.1. Basic soil characteristics
Tables 1 and 2 summarise the basic soil properties and their statistical parameters for soils under beech and spruce vegetation cover. All
sampled forest soils were strongly acidic. Under beech, active pH
(pHH2O) ranged from 3.45 to 5.00, and exchangeable pH (pHKCl) values
ranged from 2.80 to 4.07 (Table 1). Under spruce, pHH2O ranged from
3.17 to 4.64, and pHKCl values ranged from 2.55 to 4.17 (Table 2). In
comparison, soils under spruce forest were more acidic (3.82± 0.29)
than beech forest (4.08 ±0.27).
3.2. Water extractable anions in soil
The period under consideration was 3 years–22 months of sampling. Sampling month, vegetation cover, and soil horizons were considered by means of MANOVA as the main factors influencing SO42−
and NO3− content in soil. The main factors influencing SO42− were determined to be the sampled horizon (F-ratio = 12.33, p b 0.001) and
month of sampling (F-ratio= 3.52, p b 0.001). The least important factor
for all samples was soil vegetation cover (F-ratio = 0.01, p = 0.906). The
amount of water extractable NO3− was also mainly influenced by the
sampled horizon (F-ratio = 30.97, p b 0.001) and month of sampling
(F-ratio = 12.05, p b 0.001). However, the influence of soil vegetation
cover was also significant in the case of nitrates (F-ratio = 9.57, p =
0.002). The various influences on the amount of SO42− and NO3− are
discussed separately in the following section.

Table 1
Basic statistical parameters of soil properties for the total set of soil beech samples.
Cl−
mg kg
Count
Average
Median
Standard deviation
Coeff. of variation
Minimum
Maximum

NO3−

SO42−

DOC

Al

−1

232
10.2
6.72
14.4
141%
b0.19a
156

232
108
22.2
203
189%
b0.56a
1204

Recalculations to dry sample weight.
a
Determination limits of the used analytical methods (mg L−1).

232
33.7
24.0
42.9
127%
b0.56a
526

232
135
73.6
164
121%
b0.5a
910

231
12.5
9.02
13.6
109%
b0.05a
105

pHH2O

pHKCl

Moisture

–

–

g.g−1

224
4.08
4.08
0.27
6.60%
3.45
5

224
3.54
3.57
0.25
7.16%
2.8
4.07

232
0.42
0.39
0.15
34.9%
0.17
0.76

168

V. Tejnecký et al. / Science of the Total Environment 442 (2013) 165–171

Table 2
Basic statistical parameters of soil properties for the total set of soil spruce samples.
SO42−

NO3−

Cl−

DOC

Al

mg kg−1
Count
Average
Median
Standard deviation
Coeff. of variation
Minimum
Maximum

260
9.98
6.26
15.4
154%
b0.19a
196

260
66.8
25.3
115
172%
b0.56a
867

260
32.6
27.0
22.0
67.5%
b0.56a
155

262
200
134
192
96.1%
b0.5a
792

261
9.45
7.58
7.94
84.0%
b0.05a
64.9

pHH2O

pHKCl

Moisture

–

–

g.g−1

260
3.82
3.79
0.29
7.7%
3.17
4.64

260
3.22
3.05
0.45
14.0%
2.55
4.17

262
0.37
0.32
0.15
38.8%
0.05
0.69

Recalculations to dry sample weight.
a
Determination limits of the used analytical methods (mg L−1).

3.3. Distribution of anions in the soil profile
We have observed significant differences in anion distribution
within soil profiles during the investigated period of time. The largest
amount of SO42− under beech stands was identified in the organic F
horizon (55.5 ±4.84 mg kg−1). The determined amount subsequently
decreases with depth to the lowest average value which was observed
in the A organo-mineral horizon (17.2±7.59 mg kg−1). The deepest B
horizons exhibit a significantly higher amount of SO42−, compared to A
horizons (Table 3). In the case of the spruce stand, we have observed
that the amount of SO42− follows the pattern: F>H>Ab B. Thus, a high
amount was found in F, less in H and the lowest amount was determined
in the A horizons. However, the largest amount of SO42− (40.2±
2.11 mg kg−1) was determined for the mineral B horizon (Table 3).
Non-silicate Al and Fe forms and soil organic matter are very important
soil constituents which significantly influence SO42− sorption (Sokolova
and Alekseeva, 2008). The proportional share of Fe oxy-hydroxides can
be roughly estimated from the soil colour determined by means of
Munsell's colour scale (Scheinost and Schwertmann, 1999). We have observed differences in colour between cambic and spodic horizons for the
studied soil environment. The cambic horizons have generally darker
colours: brown–dark brown (7.5 YR, 4/4 value/chroma). The spodic horizons are brighter in colour: light brown (7.5–10 YR, 5/6 value/chroma)
and it can be expected that they have a higher content of Fe and Al
oxy-hydroxides. It suggests that there is a higher amount of positively charged sorption sites in spodic horizons leading to a stronger
ability to bind sulphate anions. Another factor contributing to the
release of SO42 − can be the decomposition of S containing organic
matter (Mitchell et al., 2011). Kaiser et al. (2002) reported that in
acidic soils only about 40–50% of organic carbon (OC) is contained
in subsurface horizons, so the rest of the OC is located in mineral
horizons — such as B horizons. The amount of soil water extractable OC
was found to be significantly (p=0.005) higher for the spruce stand
(62.8±7.32 mg kg−1) compared to the value determined for the beech
stand (32.1±7.72 mg kg−1), which could imply a stronger organic S
pool in soils under spruce.
The amount of NO3− (Table 4) determined in F and H horizons of
the beech forest stand was the highest and it was decreasing with increasing depth. The lowest NO3− content (26.1 ± 18.4 mg kg −1) was
determined in the B horizons. A similar trend of NO3− was also

Table 3
Mean and 95% LSD interval of water extractable SO42− in beech and spruce forests
(mg kg−1).
Horizon

F
H
A
B

Beech SO42− (mg kg−1)

Spruce SO42− (mg kg−1)

3.4. The relationship of water extractable sulphates and nitrates with
other soil characteristics
Table 5 shows correlations of SO42− and NO3− contents with other
soil characteristics in the F and B horizons under spruce and beech
forests. A fairly close and significant correlation between the content
of SO42 − and NO3− was found in the F horizons under both forest types
(r = 0.444, at p b 0.001 for F horizon under beech forest and r = 0.579,
at p b 0.001 for F horizon under spruce forest). A similar correlation
was also reported in stream waters e.g., by Likens et al. (2002). The
content of SO42− in the F horizon is not significantly related to pH. Sulphates in the F horizons show positive correlations with DOC content.
The release of SO42− from decomposed soil organic matter was recently reported by Mitchell et al. (2011). Soil organic matter mineralization thus yields not only S, but also DOC (Kalbitz et al., 2000). Under

Table 4
Mean and 95% LSD interval of water extractable NO3− in beech and spruce forests
(mg kg−1).
Horizon

Count

LS mean

LS sigma

H.G.

Count

LS mean

LS sigma

H.G.

66
66
29
72

55.5
28.4
17.2
25.8

4.84
4.84
7.59
4.68

b
a
a
a

63
66
53
79

37.7
30.8
17.6
40.2

2.33
2.28
2.59
2.11

b
b
a
c

H.G. homogeneous groups.

noted for the spruce stand. The highest NO3− amount was observed
in the F horizon, a significantly decreasing amount was further determined for H, A and B horizons. The lowest amounts were determined
in organo-mineral (15.0 ± 11.8 mg kg −1) and mineral B (15.4 ±
9.61 mg kg −1) (Table 4) horizons. The distribution of NO3− in the
soil profile is significantly influenced by i) the continuous supply of
NO3− by means of dry and wet deposition (Aber et al., 1989) and
ii) decomposition of soil organic matter and litter fall (Prescott,
2002). Albers et al. (2004) describe faster decomposition of litter
fall in the environment under beech stands in comparison to that
under spruce stands. Moreover, they claim that beech litter is a
more favourable source of N for microorganisms, compared to spruce
litter (Albers et al., 2004).
A significantly higher amount of NO3− was determined in the surface horizons of the beech stand compared to the spruce stand
(Table 4). Christiansen et al. (2006) also described higher soil saturation by NO3− and elevated NO3− leaching under beech stands compared to spruce stands. The principal source of NO3−, utilised by
microorganisms and vegetation in the environment of the beech
stand, seems to be from the decomposition of soil organic matter.
According to Christiansen et al. (2006), this phenomenon is caused
by the fact that the soils under beech stands have a higher nutrient
content and a more favourable C:N ratio, in comparison to the conditions under spruce stands.

F
H
A
B

Beech NO3− (mg kg−1)

Spruce NO3− (mg kg−1)

Count

LS mean

LS sigma

H.G.

Count

LS mean

LS sigma

H.G.

66
66
29
71

191
147
37.2
26.1

19.0
19.0
29.8
18.4

b
b
a
a

63
66
53
79

142
91.5
15.0
15.4

10.7
10.4
11.8
9.61

c
b
a
a

H.G. homogeneous groups.

169

V. Tejnecký et al. / Science of the Total Environment 442 (2013) 165–171
Table 5
Correlation coefficients of the relationships between SO42−, NO3− and other soil characteristics in F and B horizons under spruce and beech forests.
F horizon
Beech

Spruce

SO42−
0.444⁎⁎⁎

NO3−
pHH2O
DOC
Al
Moisture

−0.078
0.274⁎
0.752⁎⁎⁎

NO3−

SO42−

NO3−

–
0.298⁎

0.579⁎⁎⁎
−0.002
0.547⁎⁎⁎

–
0.348⁎⁎

3.5. Temporal variations of the content of water extractable anions

−0.008
−0.303⁎
0.207

Short-term temporal and also seasonal variations in the forest
ecosystem influence the soil vegetation cover, soil fauna and soil
chemical and biological processes. The seasonality itself is pronounced
in a scale of weeks or months. The main seasonal changes are the vegetation growth, and the composition and activity of populations of organisms. All of these changes also strongly influence the soil environment
(Puhe and Ulrich, 2001). During three years (2008–2010) the changes
in the amount of water extractable SO42− and NO3− were recorded. The
seasonal changes in organic F and mineral B horizons are shown in
Figs. 2 and 3. It is apparent that for the time period of concern, the
amount of SO42− is increasing in F and B soil horizons under both
beech and spruce stands, though the rate of S deposition in Central
Europe is decreasing or at least constant (CHMI, 2009; Kopáček and
Veselý, 2005). We can easily explain this slight increasing trend of
SO42−. Generally, the majority – around 95% – of total soil S is bound in
the structure of soil organic matter (Scherer, 2009), which seems to be
increasingly decomposing and transforming. These changes of organic
matter were reported e.g., by Hruška et al. (2009). These authors have
found an increasing release of DOC to surface water streams in the
mountainous regions of the Czech Republic. The close correlation of the
amount of aqueous extractable DOC and SO42− in soil F horizons was
discussed in Section 3.3.
The temporal variation of anion content under the beech stand is
wider in F horizons compared to B horizons. A similar phenomenon
was also observed in soils under spruce stands. However, the variability
of SO42− in the B horizons was still quite strong under spruce. This is

0.022
0.338⁎⁎

0.228

0.225
−0.210

0.216

B horizon
Beech

NO3−
pHH2O
DOC
Al
Moisture

been reported by numerous authors (e.g. Drábek et al., 2005; Norton
and Veselý, 2003).
Little to no effect of other determined soil characteristics on the
content of SO42− and NO3− could be determined in the B horizons
(Table 5).

Spruce

SO42−

NO3−

SO42−

NO3−

0.065
0.200
−0.034
0.114
0.283⁎

–
−0.223
−0.045
0.082
0.205

0.033
0.325⁎⁎
−0.292⁎⁎

–
−0.258⁎
0.117
0.110
−0.019

−0.010
−0.163

⁎ Significant at the probability level of 0.05.
⁎⁎ Significant at the probability level of 0.01.
⁎⁎⁎ Significant at the probability level of 0.001.

beech forest, the content of SO42− and NO3− in the F horizons is positively correlated with water extractable Al. In contrast, under spruce
forest the correlation between NO3− and Al is negative, and the correlation between SO42 − and Al is not significant. It suggests that sulphate anions play a more important role as ligands complexing Al
under beech than under spruce, where the Al complexing role is
played more by DOC (Tejnecký et al., 2010). This difference between
soils under spruce and beech forests is supported by a closer correlation between Al and DOC in the F horizons under spruce (r = 0.694, at
p b 0.001) than under beech (r= 0.270, at p = 0.03). The fact that DOC,
SO42− and NO3− are important factors of Al mobility and speciation has

Spruce forest
250

200

200

SO42- (mg kg-1)

F horizon
SO42- (mg kg-1)

Beech forest
250

150
100
50

150
100
50

0

0
A M

J

J

A

S

O N A M

J

2008

J

A

S

O N A M

J

2009

J

A

S

A M

O N

J

J

A

S

J

J

A

S

O N A M

J

J

2009

A

S

O N

2010

Years (months)

Years (months)
100

100

80

80

SO42- (mg kg-1)

B horizon
SO42- (mg kg-1)

O N A M

2008

2010

60
40
20

60
40
20

0

0
A M

J

J

A

2008

S

O N A M

J

J

A

S

O N A M

2009

Years (months)

J

J

A

2010

S

O N

A M

J

J

A

2008

S

O N A M

J

J

A

S

O N A M

2009

J

J

A

S

O N

2010

Years (months)

Fig. 2. Seasonal variation of water extractable SO42− in organic F (top) and mineral B (bottom) soil horizons under beech (left) and spruce (right) forests (mg kg−1; mean and 95%
LSD interval).

170

V. Tejnecký et al. / Science of the Total Environment 442 (2013) 165–171

Beech forest

1000

800

NO3- (mg kg-1)

800

F horizon
NO3- (mg kg-1)

Spruce forest

1000

600
400
200

600
400
200

0

0
A M

J

J

A

S

O N

A M

J

2008

J

A

S

O N

A M

J

2009

J

A

S

A M

O N

J

J

A

S

O N

60

60

NO3- (mg kg-1)

B horizon
NO3- (mg kg-1)

80

40

20

J

J

A

2008

S

O N

A M

J

J

A

S

O N

2009
Years (months)

J

A

S

O N

A M

J

J

A

S

O N

S

O N

2010

Years (months)

80

A M

J

2009

Years (months)

0

A M

2008

2010

A M

J

J

A

S

40

20

0

O N

A M

J

J

A

2008

2010

S

O N

A M

J

J

A

S

O N

2009

A M

J

J

A

2010

Years (months)

Fig. 3. Seasonal variation of water extractable NO3− in organic F (top) and mineral B (bottom) soil horizons under beech (left) and spruce (right) forests (mg kg−1; mean and 95%
LSD interval).

observed (e.g. Attiwill and Adams, 1993). The increased amount of available NO3− can influence the vegetation cover, accelerate the environmental acidification and indirectly increase Al toxicity (Bowman et al., 2008).

4. Conclusions
In soil profiles, the lowest amount of SO42− was found in the organomineral A horizons under both types of vegetation. However, while
under spruce stands the highest amount of SO42− was determined in
the mineral spodic (B) horizons (where a strong influence of Fe and Al
oxy-hydroxides is expected), under beech stands the highest amount
was observed in the surface organic F horizons (forest floor). The amount
of NO3− is highest in the F horizons and decreases with increasing soil profile depth under both types of vegetation. A significantly higher amount of
NO3− was determined in soils under the beech stand compared to spruce.

5.0

5.0

4.5

4.5

pHH20

pHH20

F horizon

caused by larger amounts of SO42− in the B horizon under the spruce
stand compared to the beech forest (Fig. 2).
The amount of water extractable NO3− had increased slightly during
the investigated time period (Fig. 3). This fact cannot be attributed to
the increased deposition of NO3− and NH4+. Nitrate deposition in Central
Europe and in the Czech Republic remains constant or exhibits a slightly
decreasing trend (CHMI, 2009; Kopáček and Veselý, 2005). The slightly
increasing annual temperature might be a possible explanation for the
increase of water extractable NO3− (Veselý et al., 2003) and thus accelerated nitrification processes. Moreover, nitrification processes are positively affected by increasing pH (Ste-Marie and Paré, 1999). In the
studied environment we have observed pH increases on both stands
(Fig. 4). A higher variability for the water extractable NO3− content can
be seen in organic F horizons compared to the mineral B horizons. The
influence of biota is apparent here and also a larger vulnerability of F
horizons to external factors (precipitation, temperature, etc.) can be

4.0

4.0

3.5

3.5

30

30

Years (months)

Years (months)

Fig. 4. Seasonal variation of active soil pH in organic F horizons under beech (left) and spruce (right) forests (mean and 95% LSD interval).

V. Tejnecký et al. / Science of the Total Environment 442 (2013) 165–171

Higher temporal variability in the investigated characteristics was
proven for organic horizons compared to mineral horizons. The behaviour of sulphates and nitrates in the soils is strongly related to the
dynamics of soil organic matter and particularly to the DOC. An important role of SO42 − in Al behaviour was shown in organic horizons
under beech forest, while under spruce forest the effect of DOC is more
prominent.
For both soil environments – under beech and also spruce stands –
we have determined a general increase of water-extractable SO42−
and NO3− contents during the whole monitoring period. It indicates
a long-lasting impact of these acidificants accumulated in soils, even
though the rate of acid deposition has decreased significantly in the
last decades.
Acknowledgements
This study was supported by the Czech University of Life Sciences
Prague (project no. CIGA 1313/213106), the Ministry of Agriculture of
the Czech Republic (project no. QI92A216) and the Ministry of Education, Youth and Sports (project no. MSM 6046070901 and project no.
MSM 0021620855). We would like to express our gratitude to Chris
Ash for editing the manuscript. The authors thank the associate editor
Dr. Charlotte Poschenrieder and anonymous reviewers for their valuable comments and suggestions to the manuscript.
References
Aber JD, Nadelhoffer KJ, Steudler P, Melillo JM. Nitrogen saturation in northern forest
ecosystems. Bioscience 1989;39:378–86.
Albers D, Migge S, Schaefer M, Scheu S. Decomposition of beech leaves (Fagus sylvatica)
and spruce needles (Picea abies) in pure and mixed stands of beech and spruce. Soil
Biol Biochem 2004;36:155–64.
Alewell C, Mitchell MJ, Likens GE, Krouse HR. Sources of stream sulfate at the Hubbard
Brook Experimental Forest: long-term analyses using stable isotopes. Biogeochemistry 1999;44:281–99.
Attiwill PM, Adams MA. Nutrient cycling in forests. New Phytol 1993;124:561–82.
Augusto L, Ranger J, Binkley D, Rothe A. Impact of several common tree species of European
temperate forests on soil fertility. Ann For Sci 2002;59:233–53.
Balcar V, Špulák O, Kacálek D, Kuneš I. Climatic conditions in the Jizerka experimental plot — I.
Precipitation and soil moisture. Zpravy Lesnickeho Vyzkumu 2012;57:74–81.
Batysta M, Borůvka L, Drábek O, Tejnecký V, Šebek O. Laboratory assay of aluminium
transport through intact soil sample under controlled conditions. Soil Water Res
2010;5:69–74.
Berger TW, Untersteiner H, Schume H, Jost G. Throughfall fluxes in a secondary spruce
(Picea abies), a beech (Fagus sylvatica) and a mixed spruce-beech stand. For Ecol
Manage 2008;255:605–18.
Bowman WD, Cleveland CC, Halada L, Hresko J, Baron JS. Negative impact of nitrogen
deposition on soil buffering capacity. Nat Geosci 2008;1:767–70.
Cerjan Stefanović Š, Bolanča T, Ćurković L. Simultaneous determination of six inorganic
anions in drinking water by non-suppressed ion chromatography. J Chromatogr A
2001;918:325–34.
Cháb J, Stráník Z, Eliáš M. Geological Map of the Czech Republic 1 : 500 000. Prague:
Czech Geological Survey; 2007.
CHMI. Air pollution on the Czech Republic territory in 2008 — yearbook. Prague: Czech
Hydrometeorological Institute; 2009.
Christiansen JR, Elberling B, Jansson PE. Modelling water balance and nitrate leaching
in temperate Norway spruce and beech forests located on the same soil type
with the CoupModel. For Ecol Manage 2006;237:545–56.
De Schrijver A, Geudens G, Augusto L, Staelens J, Mertens J, Wuyts K, et al. The effect of forest
type on throughfall deposition and seepage flux: a review. Oecologia 2007;153:663–74.
De Wit HA, Mulder J, Hindar A, Hole L. Long-term increase in dissolved organic carbon
in streamwaters in Norway is response to reduced acid deposition. Environ Sci
Technol 2007;41(22):7706–13.
DeHayes DH, Schaberg PG, Hawley GJ, Strimbeck GR. Acid rain impacts on calcium nutrition and forest health. Bioscience 1999;49:789–800.
Dionex. Application note 135: determination of inorganic anions in wastewater by ion
chromatography. Dionex Corporation; 2000.
Dionex. IonPac AS14 product manual, document no. 031199. Dionex Corporation; 2003.

171

Drábek O, Mládková L, Borůvka L, Száková J, Nikodem A, Němeček K. Comparison of
water-soluble and exchangeable forms of Al in acid forest soils. J Inorg Biochem
2005;99:1788–95.
Drábek O, Borůvka L, Pavlů L, Nikodem A, Pírková I, Vacek O. Grass cover on forest clear-cut
areas ameliorates some soil chemical properties. J Inorg Biochem 2007;101:1224–33.
Hruška J, Krám P, McDowell WH, Oulehle F. Increased dissolved organic carbon (DOC)
in Central European streams is driven by reductions in ionic strength rather than
climate change or decreasing acidity. Environ Sci Technol 2009;43:4320–6.
Kaiser K, Eusterhues K, Rumpel C, Guggenberger G, Kögel-Knabner I. Stabilization of organic matter by soil minerals — investigations of density and particle-size fractions
from two acid forest soils. J Plant Nutr Soil Sci 2002;165:451–9.
Kalbitz K, Solinger S, Park JH, Michalzik B, Matzner E. Controls on the dynamics
dissolved organic matter in soils: a review. Soil Sci 2000;165:277–304.
Kopáček J, Veselý J. Sulfur and nitrogen emissions in the Czech Republic and Slovakia
from 1850 till 2000. Atmos Environ 2005;39:2179–88.
Krug EC, Frink CR. Acid rain on acid soil: a new perspective. Science 1983;221:520–5.
Likens GE, Driscoll CT, Buso DC, Mitchell MJ, Lovett GM, Bailey SW, et al. The biogeochemistry of sulfur at Hubbard Brook. Biogeochemistry 2002;60:235–316.
Mayer B, Feger K, Giesemann A, Jäger H-J. Interpretation of sulfur cycling in two catchments in the Black Forest (Germany) using stable sulfur and oxygen isotope data.
Biogeochemistry 1995;30:31–58.
Mitchell M, Lovett G, Bailey S, Beall F, Burns D, Buso D, et al. Comparisons of watershed
sulfur budgets in southeast Canada and northeast US: new approaches and implications. Biogeochemistry 2011;103:181–207.
Monteith DT, Stoddard JL, Evans CD, de Wit HA, Forsius M, Hogasen T, et al. Dissolved
organic carbon trends resulting from changes in atmospheric deposition chemistry.
Nature 2007;450:537–40.
Norton SA, Veselý J. Acidification and acid rain. In: Lollar BS, editor. Environmental geochemistry, treatise on geochemistry, vol. 9. Amsterdam: Elsevier; 2003. p. 367–406.
Oulehle F, McDowell WH, Aitkenhead-Peterson JA, Kram P, Hruska J, Navratil T, et al.
Long-term trends in stream nitrate concentrations and losses across watersheds undergoing recovery from acidification in the Czech Republic. Ecosystems 2008;11:
410–25.
Prechtel A, Alewell C, Armbruster M, Bittersohl J, Cullen JM, Evans CD, et al. Response of
sulphur dynamics in European catchments to decreasing sulphate deposition.
Hydrol Earth Syst Sci 2001;5:311–25.
Prescott CE. The influence of the forest canopy on nutrient cycling. Tree Physiol 2002;22:
1193–200.
Puhe J, Ulrich B. Global climate change and human impacts on forest ecosystems. Berlin:
Springer; 2001.
Remrova M, Císlerová M. Analysis of climate change effects on evapotranspiration in
the watershed uhlířská in the Jizera mountains. Soil Water Res 2010;5:28–38.
Rothe A, Huber C, Kreutzer K, Weis W. Deposition and soil leaching in stands of Norway
spruce and European Beech: results from the Höglwald research in comparison
with other European case studies. Plant Soil 2002;240:33–45.
Scheinost AC, Schwertmann U. Color identification of iron oxides and hydroxysulfates:
use and limitation. Soil Sci Soc Am J 1999;63:1463–71.
Scherer HW. Sulfur in soils. J Plant Nutr Soil Sci 2009;172:326–35.
Sokolova T, Alekseeva S. Adsorption of sulfate ions by soils (a review). Eurasian Soil Sci
2008;41:140–8.
Ste-Marie C, Paré D. Soil, pH and N availability effects on net nitrification in the forest
floors of a range of boreal forest stands. Soil Biol Biochem 1999;31:1579–89.
Tejnecký V, Drábek O, Borůvka L, Nikodem A, Kopáč J, Vokurková P, et al. Seasonal variation of water extractable aluminium forms in acidified forest organic soils under
different vegetation cover. Biogeochemistry 2010;101:151–63.
Tejnecký V, Drábek O, Nikodem A, Vokurková P, Němeček K, Borůvka L. Fast determination of water extractable organic carbon from forest soil. in preparation.
Ukonmaanaho L, Starr M. Major nutrients and acidity: budgets and trends at four remote boreal stands in Finland during the 1990s. Sci Total Environ 2002;297:21–41.
US EPA. The determination of inorganic anions in water by ion chromatography. U.S.
Environmental Protection Agency Method 300.0; 1993.
Vannier C, Didon-Lescot JF, Lelong F, Guillet B. Distribution of sulphur forms in soils from
beech and spruce forests of Mont Lozère (France). Plant Soil 1993;154:197–209.
Veselý J, Majer V, Kopáček J, Norton SA. Increasing temperature decreases aluminium
concentration in Central European lakes recovering from acidification. Limnol
Oceanogr 2003;48(6):2346–54.
WRB. World reference base for soil resources 2006 — a framework for international classification, correlation and communication. World Reference Base for Soil Resources;
2006.
Yakovchenko VP, Sikora LJ. Modified dichromate method for determining low concentrations of extractable organic carbon in soil. Commun Soil Sci Plant Anal 1998;29:
421–33.
Zbíral J. Analýza půd III-jednotné pracoví postupy, Brno: SKZÚZ; 2004 (in Czech).
Zhang Y, Mitchell MJ, Christ M, Likens GE, Krouse HR. Stable sulfur isotopic biogeochemistry of the Hubbard Brook Experimental Forest, New Hampshire. Biogeochemistry 1998;41:259–75.