Profile distribution and temporal changes of sulphate and nitrate contents and related soil properties under beech and spruce forests

Profile distribution and temporal changes of sulphate and nitrate contents and related soil properties under beech and spruce forests

Science of the Total Environment 442 (2013) 165–171 Contents lists available at SciVerse ScienceDirect Science of the Total Environment journal home...

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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 22 November 2012 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: [email protected] (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

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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).

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. 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

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Jizera Mts.

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Living tree

Crown projection 0

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Rock

10

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Czech Republic

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

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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

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

NO3−

SO42−

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.

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−

−0.078 0.274⁎ 0.752⁎⁎⁎

pHH2O DOC Al Moisture

0.228

NO3−

SO42−

NO3−

– 0.298⁎ 0.022 0.338⁎⁎

0.579⁎⁎⁎ −0.002 0.547⁎⁎⁎

– 0.348⁎⁎ −0.008 −0.303⁎ 0.207

0.225 −0.210

0.216

B horizon Beech

NO3− pHH2O DOC Al Moisture

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

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).

3.5. Temporal variations of the content of water extractable anions 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

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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).

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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

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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

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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

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