1. Introduction
Since the 19th century, intensive forest management has been applied in many parts of Europe by replacing native European beech (Fagus sylvatica) with fast-growing coniferous tree species such as Norway spruce (Picea abies) [1,2,3,4]. The replacement of the original broad-leaved forests with spruce monocultures still has a number of problems, such as extensive bark beetle calamities and the breakdown of spruce grown outside their ecological optimum [5,6]. The replacement of forest tree species, on the other hand, affects the composition of soil organic matter and soil organic carbon dynamics due to changes in understory vegetation, canopy closure, soil acidification, and litter structure [7,8,9,10].
Soil organic matter (SOM) is the primary component of soil and plays essential roles in regulating the nutrient cycle, adsorption and desorption processes, and C stabilization [11,12]. SOM is a mixture of components with different molecular weights, polarities, and functional groups that can maintain the mobility of contaminants in the soil [13]. Forest tree species play essential roles in SOM stability and store approximately 40% of the global total organic carbon [14,15]. Forest tree species, however, can affect the SOM in various ways, such as bulk deposition, interception, canopy uptake and leaching, stem flow, nutrient uptake, and organic acid exudation [16,17]. The quality and quantity of SOM differ depending on the surrounding environmental conditions, especially the decomposition rate of the plant residues. For instance, the residues found in spruce forests tend to decompose slowly, resulting in SOM stabilization, while the residues found in beech forests decompose rapidly, resulting in the availability of nutrients for the plants [18,19,20].
Recently, the stable part of SOM has been described as a supramolecular aggregate that bridges the functional groups of the molecule and can protect the high quality of organic compounds via the strong bond between metals and clay [21,22]. Low molecular mass organic acids (LMMOAs), which are derived mainly from root exudation, microbial activities, and the decomposition of SOM, are part of the C cycle and are also characterized as labile, variable, and soluble components of the SOM [23,24,25].
The stable part, often called humic substances (HSs), forms roughly 80% of the SOM and behaves differently in the terrestrial ecosystem depending on the parent material, vegetation type, climate condition, land use, and topography [13,26,27]. Humic substances significantly affect the chemical sorption capacity of soil buffering, micronutrient availability, the level of trace element toxicity, and metal deficiency in soil [28,29,30]. In the early concept, the HS structure was described as a polymer system of various molecular weights that is relatively similar to other natural biological macromolecules (e.g., lignin, proteins, and carbohydrates) [31,32]. On the contrary, Piccolo [33] stated that HSs can be better described as a supramolecular association as opposed to constituting macromolecular polymers, as the traditional concept believed. A new view of HSs as supramolecular associations can be interpreted as relatively small humic and chemically diverse organic molecules linked together by hydrogen bonds and hydrophobic interactions [22,34]. On the other hand, Lehmann and Kleber [35] argued that the HS terminology in soil science has led to misinterpretations or varying definitions by researchers. Therefore, the HS in our study was interpreted according to Piccolo’s review. For a similar reason, we used the description of alkaline-extractable organic substance (AEOS) for a mixture or association of compounds extractable with alkaline solutions. This is especially important in surface horizons, where these compounds are not present in the classical concept of humification processes. Extracts from L and F horizons contain a mixture of organic compounds such as lignin, carbohydrates, proteins, lipids, and carbonyl due to the fresh and non-decayed materials.
Our study benefits from a known study site history. The planted spruce monoculture is almost 100 years old and replaced previously planted or naturally growing beech forests, which are still found in the vicinity. A comparison of the soil properties of these two stands thus gives information about the influence of spruce cultivation, i.e., the effects of a qualitatively different organic material, a different distribution of precipitation, or perhaps a different distribution of roots on soil conditions with detailed consideration of the qualitative parameters of the SOM. Moreover, there are few studies that address the qualitative changes in SOM within the entire soil profile, including both surface organic and mineral horizons.
To fill this lacuna, this study aims to (1) determine the various organic components throughout the forest soil profile, (2) evaluate the changes in chemical soil components and compositions (aliphatic, aromatic, and other functional groups presence) of the extracted AEOS from beech and spruce forest soil horizons using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTs), and (3) evaluate the effect of spruce planting on organic matter compositions in whole soil profiles. We hypothesized that the various organic compounds (AEOS, LMMOAs, and DOC), derived from the acidic forest with contrasting vegetation covers and similar bedrock and soil types, incorporate and transform differently across the forest soil profiles (e.g., from the litter horizon to the subsurface mineral horizons).
2. Materials and Methods
2.1. Study Area and Soil Sampling
The research was conducted in the Jizera Mountains in the northern part of the Czech Republic. The area was adversely affected by atmospheric acid deposits during the 1980s and 1990s due to a nearby coal-fired power station. Several previous studies performed observations in these mountains [36,37], and based on them, one specific area was determined to be suitable for long-term monitoring of the development of soil properties in acidic forest soils. The study area is called Paličník (50.8683900′ N, 15.2527000′ E). The mean annual precipitation and temperature are roughly 1200 mm and 4–7 °C, respectively. This study focuses on two specific mono-forest species: European beech (Fagus sylvatica L.) and Norway spruce (Picea abies L. Karst.). The soil types are Entic Podzols under the spruce and Dystric Cambisol under the beech forest; both are strongly acidic soils [38]. The canopy closure of the spruce (40%) is lower than that of the beech forests (87%). The ages of the spruce and beech forests are roughly 100 and 180 years, respectively [16].
At intervals of several years (e.g., from 2008 to 2020), soil samples were taken in the studied areas to monitor the basic soil characteristics [39]. For the specific purpose of this research, additional soil samples were taken beyond the scope of monitoring to study the qualitative parameters of soil organic matter. Thirty soil samples were collected from five different soil horizons (L: litter horizon; F: fermentation horizon; H: humified horizon; A: organo-mineral horizon; B: subsurface mineral horizon (cambic horizon under beech, spodic humusosesquioxidic horizon and cambic horizon enriched with iron oxides under spruce)). Three individual soil pits (approximately 50 × 50 cm) were randomly selected and dug from each forest for soil description and sample collection. The distance between the soil pits was at least 15 m. Each soil sample was divided into two parts. The first part was analyzed in a “fresh” state, representing actual soil moisture, and was used to measure dissolved organic carbon (DOC) and low molecular mass organic acid (LMMOA) contents. The second part was air-dried and passed through a 2 mm sieve. Notably, the air-dried soil samples of the L horizon were blended to obtain fine particles and sieved to 2 mm.
2.2. Soil Analysis
The active pH (pHH2O) was determined in water extract (soil/water (w:v) ratio: 1:4 for organic horizons due to the low density of samples from the organic horizons and 1:2 for mineral horizons) and measured using the SenTix 21 pH electrode (Inolab pH level 21, WTW, Berlin, Germany). A thermal gradient with continued heating (up to 900 °C) and with a soliTOC cube (elementar, Lanenselbold, Germany) was used to evaluate the stability and quality of the SOM, according to Rennert and Herrmann [40]. The cation exchange capacity (CEC) was determined in a 0.1 M BaCl2 extract of the soil following the standard ICP Forest methods [41]. The SOC content was determined by rapid dichromate oxidation techniques according to Tyurin’s method [42]. The DOC and LMMOA contents were determined with the fresh soil samples extracted by deionized water (soil/water ratio: 1:10, w:v). The DOC was measured at 340 nm using a spectrophotometer after dichromate oxidation, according to Tejnecký et al. [43]. The content of water-extractable LMMOAs was determined using ion chromatography (IC) in conjunction with suppressed conductivity (capillary high-pressure ion chromatography—HPIC). Dionex ICS 4000 and ICS 6000 (Thermo Scientific, Waltham, MA, USA) systems equipped with a Dionex IonPac AS11-HC 4 µm (Thermo Scientific, Waltham, MA, USA) guard and analytical columns were used [44].
Generally, all the analytical procedures were secure from a point of view of quality assurance and quality control (QA and QC). The procedures ensuring laboratory QC and QA were performed according to the standard laboratory practices, including repeated measurements, processed blanks, fortified standards, spiked samples, and certified reference materials.
2.3. Alkaline-Extractable Organic Substances
Alkaline-extractable organic substances (AEOSs) were isolated from soil samples (L, F, H, A, and B horizons) and were determined according to the International Humic Substance Society (IHSS) fractionation method, modified by Piccolo et al. [45]. Notably, AEOSs can be subcategorized as less soluble (soluble only in alkaline and in mineral horizons, also called humic acids (HAs)) and soluble (soluble across the whole pH scale and mineral horizons, also called fulvic acids (FAs)). Sixty grams of soil was extracted by adding 300 mL of a mixture of 0.5 M NaOH and 0.1 M Na4P2O7 and then shaken for 24 h. The dissolved AEOS was separated by centrifugation at 4000 rpm for 15 min and then transferred into beakers. This extraction was repeated three times. The solution was acidified to pH 1.0 using HCl and left overnight in the refrigerator for precipitation and separation of the AEOS into low-solubility (insoluble in acid nature) and soluble (soluble in whole pH scale) AEOSs, which were finally separated by centrifugation. The low-solubility AEOS was redissolved with 1 M NaOH and reprecipitated with HCl. To purify the co-extracted clay, the precipitates were shaken with 300 mL of a mixed solution of 0.5% HCl and 0.5% HF (v/v) for two days. The suspension was centrifuged at 4000 rpm for 10 min and neutralized. They were then transferred into a dialysis bag and soaked with distilled water in a cylinder to free chlorine. Finally, they were frozen and freeze-dried. The soluble AEOS was purified using the hydrophobic resin in the column. A 0.5 M NaOH solution was used to release the soluble AEOS sorbed in the resin. Finally, they were neutralized, then dialyzed, frozen, and freeze-dried.
2.4. Diffuse Reflectance Infrared Fourier Transform Spectroscopy
The freeze-dried AEOS powders were measured using an infrared spectrometer (Nicolet IS10) and OMNIC 9.8.372 software (Thermo Fisher Scientific Inc., Madison, WI, USA). The samples were recorded over 120 scans with wavenumbers ranging from 4000 to 400 cm−1 at a resolution of 4 cm−1 using a gold mirror as the background. The unit of the reflectance was converted to Kubelka–Munk. However, to determine relative changes of the reflectance bands in DRIFT spectra and for spectrum percentage comparisons, the relative reflectance (rR) of a selected band was calculated by dividing the sum of all selected band heights (2929, 1724, 1633, 1517, 1447, 1403, 1280, and 1045 cm−1) and multiplying it by 100 (e.g., rR1724 = R1724/∑R(2929–1050) × 100) [46,47].
2.5. Statistical Analysis
Mean comparisons of the chemical compositions among the soil horizons under beech and spruce were statistically analyzed using a one-way analysis of variance (ANOVA) at an error level of 0.05 (confidence level of 95%). The t-test was also used to compare the chemical compositions and chemical soil structures between beech and spruce stands using IBM SPSS software (version 29, New York, NY, USA). To analyze the data distribution, the homogeneity of variances was applied to check its normality (Kolmogorov–Smirnov test for normality). The statistical differences between horizons and vegetation covers are presented with letters (a, b, c, and d) and were determined using the Tukey test. A correlation coefficient matrix was also assessed to evaluate the relationship among the chemical compositions under both forest species.
3. Results and Discussion
3.1. Basic Soil Characteristics
The pH values within the soil profiles were similar for both forest stands (Figure 1). From the soil surface (L horizon), the pH gradually decreased to the A horizon and then increased to the B horizon. Comparing between forest species, we found that the pH values in both stands were similar in the mineral horizons (A and B), while in the surface organic horizons, the spruce had higher pH values than the beech forests. This indicated the acidifying influence of the spruce forests, which was mainly caused by the litter residues. This difference was also demonstrated at the studied site in previous studies working with longer time series of sampling and larger sets of samples [38,48]. The CEC decreased significantly from the L to B horizons, ranging from 51.9 ± 2.2 to 7.2 ± 2.2 cmol kg−1 under beech and from 29.7 ± 2.7 to 7.0 ± 1.6 cmol kg−1 under spruce (Table S1). It was similar to the tendency of the soil organic carbon (SOC) content, which had been stored more in the uppermost layer than in the deeper soil horizons (L > F > H > A > B) under both stands. When comparing between forest species, a higher CEC was shown in the beech stands than in the spruce stands (Table S1). Generally, the CEC increases with increasing SOC [49], and a further discussion has been presented in Thai et al. [39].
The decrease in pH and CEC after replacing the natural beech stands with a spruce monoculture can subsequently lead to the leaching of nutrients [50,51] and an increase in the content of some potentially toxic elements (Al, Fe, and Mn) not only in the soil environment [52,53] but also in surface water [54]. This can also be said to have resulted from anthropogenic acidification during the 1980s and 1990s [37,55], but similar problems can arise in areas with large-scale cultivation of conifer plantations in areas of original broad-leaved forests, e.g., in developing countries [56,57].
The thermal gradient with continued heating was used as the first parameter focusing on organic matter quality. We evaluated at least two maxima of the temperature (Tmax, Tmax2) depending on CO2 evolution (Figure S1). Under the beech forest, the position and temperature of the first Tmax was ≥ 400 °C, and the second local maximum (Tmax2) was Tmax2 ≥ 500 °C (Figure 1). A significant difference among the soil horizons under the beech forest was observed through the whole soil profile (L > F > H < A < B). Under the spruce stands, the values of Tmax and Tmax2 were similar to the values found in the beech forest (Tmax ≥ 400 °C and Tmax2 ≥ 500 °C), and no significant difference was observed between the forest stands in most of the horizons except for the L horizon, where under the spruce forest, there were higher values than under the beech forest. The distribution of the Tmax values within the soil profile under spruce gradually decreased from the L to H horizons and then rose again from the A to B horizons, while the Tmax2 decreased with increasing depth (L > F > H, A, B). Generally, Tmax values ranging from 300 to 350 °C indicate the dominance of labile SOM and a lack of interaction with minerals, while Tmax values ranging from 350 to 400 °C demonstrate the loss of aromatic compounds such as lignin and other polyphenols and highly recalcitrant organic matter [8,58]. In our results, the Tmax value exceeded 400 °C in the forest soil profiles, which indicated the dominance of poorly degraded SOM and highly recalcitrant materials rich in aromatic components [59] and revealed the stability of the SOM in the soil profiles or the presence of black C [8]. The increase in Tmax values from the H to B horizons under both forest stands also demonstrated the interactions of the SOM with the mineral surfaces [40].
3.2. Dissolved Organic Carbon and Low Molecular Mass Organic Acids
The dissolved organic carbon (DOC) was more abundant in the F and H horizons than in the L, A, and B horizons under both forest stands (Figure 1). Under beech, the total content of LMMOAs decreased with depth, ranging from 104 ± 67.2 to 1.1 ± 0.7 mmol kg−1, while under spruce, the highest concentration of total LMMOAs was found higher in the F and H horizons (15.4 ± 18.9 and 10.4 ± 7.42 mmol kg−1, respectively), followed by the L, A, and B horizons (7.80 ± 0.2, 6.70 ± 5.4, and 0.90 ± 0.7 mmol kg−1, respectively) (Figure 2, Table S2). Specifically, the most frequent LMMOAs under both forest species were citrate, lactate, oxalate, and quinate, mostly observed in the organic horizons (L, F, and H). This indicated that there was greater litter, root materials, and biological activity occurring in the organic horizon, which led to an increased rate of SOM decomposition and both directly and indirectly increased LMMOA production [44]. The release of a wide range of organic acids that were produced by microorganisms was observed by Adeleke et al. [24] during the decomposition of forest litter. Other reasons for the increased concentration of LMMOAs in the upper horizons are soil acidity and plant root exudates [60,61].
When comparing between forest species, the results showed that the DOC content was higher in the L, F, and H horizons under the beech forest than under the spruce forest (Figure 1). This is similar to the LMMOA concentrations (almost all the organic acids, except for quinate), which were higher in the L and F horizons under beech than under the spruce forest (Figure 2). The lower contents of DOC and LMMOAs in the organic horizon of the spruce forest compared to the beech forest (Table S2) indicated that there were more recalcitrant residues (slowly decomposable). With that being said, the higher biological activity and decomposable litter under the beech compared to the spruce forest, which were observed in the locality by Buresova et al. [48], produced more organic acids. Interestingly, despite the lower concentration in the surface horizons of the spruce forest, quinate, lactate, formate, and oxalate as well as DOC and SOC contents were higher in the A horizon in comparison to the beech forest (Tables S1 and S2). The results showed higher mobility of the organic compounds in the deeper horizons, indicating the initial process of podzolization under the spruce forest and the association among SOC, DOC, and LMMOAs. A positive correlation of SOC content with LMMOAs (p < 0.01, r = 0.45 *) and DOC (p < 0.001, r = 0.55 **) was also identified in the study (Figure 3).
3.3. The Spectroscopic Characterization of Alkaline-Extractable Organic Substances
The DRIFT spectra of alkaline-extractable organic substances (AEOSs) extracted from the soil under the beech and spruce forests are shown in Figure 4 and Figure 5. The major reflectance bands of the soluble AEOS spectra under both forest species were in the regions at 3400–3300 cm−1 (H-bonded OH groups), 2950–2800 cm−1 (aliphatic C-H stretching), 1724 cm−1 (C=O stretching of COOH and ketones), 1633 cm−1 (C=O stretching of amide I, quinone, and H-bonded conjugated ketones), 1517 cm−1 (N-H bending and C=N stretching), 1477 cm−1 (OH deformation and C-H stretching of phenolic OH), 1403 cm−1 (OH deformation of CH2 and CH3), 1280 cm−1 (C-O stretching and OH deformation of COOH), and 1045 cm−1 (polysaccharides).
Generally, the soluble and low-solubility AEOS spectra were clearly distinguished in each soil horizon for both forest species. In the soluble AEOS spectra, it was observed that more peaks were visible in the L, A, and B horizons than in the F and H horizons. In the soluble AEOS spectra under both forest species, the peak of aliphatic C-H stretching was less visible with increasing depth. This indicates the preferential biological degradation of carbohydrates, which are the main parts of the O-Alky C fraction [47]. However, the band at 1724 cm−1, described as carboxylic groups, was more visible in the A horizon compared to the L, F, H, and B horizons under beech. In contrast, the band at 1724 cm−1 was more apparent in the A and B horizons than in the L, F, and H horizons under the spruce forest (Figure 4). Additionally, the band at 1724 cm−1 in the B horizon under spruce had the same peak height as the peak of the shoulder reflectance band at 1633 cm−1. This indicates that the C=O stretch of COOH and ketones was present in the deeper soil profiles and resulted from the oxidative cleavage of lignin side-chain and aromatic rings during the degradation [47]. The higher abundance of DOC in the F and H horizons (Figure 1) was an indicator of carboxylic groups becoming more soluble and transported into deeper soil horizons. It was noticed that there were opposite intensities of bands (1633 ≥ 1280 cm−1) in most of the soil horizons, except for the F horizon (1633 ≤ 1280 cm−1), under both forest species. This result could be due to the initiated decomposition of OM and more abundant organic acids, which promoted more OH deformation of COOH in the F horizon. On the other hand, it suggested that increasing the degree of decomposition and maturity of OM enhanced higher aromatic components in the deeper soil horizons (H, A, and B horizons) [62,63]. The band at 1517 cm−1 representing N-H bending and C=N stretching was more intense in the L horizon, followed by the F, H, A, and B horizons. A similar result was also found by Leinweber et al. [64]. The bands at 1447 cm−1 and 1403 cm−1 were more intense through the soil horizons (Figure 4). This revealed the presence of lignin structures at this amplitude, thus eliminating the amplitude of the band at 1447 cm−1, exposing organic compounds, and increasing decomposition, and the humification rate could cause the peaks to be lower for some soil horizons (L and F horizons) [65]. However, the disappearance of the polysaccharide chains through the soil profiles (Figure 4) signified that the polysaccharides had been used or decomposed by soil microorganisms [64].
The major bands of the low-solubility AEOS were 3400–3300, 2950–2800, 1724, 1633, 1517, 1403, 1280, and 1045 cm−1. The low-solubility AEOS spectrum peaks were more visible in the L, F, and H horizons than in the A and B horizons under both forest species (Figure 4). The peaks of aliphatic groups (2950–2800 cm−1) increased relatively with increasing depth under the beech forest, while the peaks under spruce had a higher intensity in the A horizon (Figure 4 and Figure 5). This result could be explained by the amount of aliphatic groups within the low-solubility AEOS having increased during decomposition and the formation of the micelles of the low-solubility AEOS [66]. The bands of C=O stretching of COOH and ketones (1724 cm−1) were visible at a high intensity with increasing depth under both forest species. The aromatic C=C stretching (1633 cm−1) increased with depth under the beech, while under the spruce stands, it was relatively constant through the soil horizons. A similar finding was documented by Tatzber et al. [67]. Interestingly, the peaks between 1724 and 1633 cm−1 showed that the peak at 1724 cm−1 was lower (1724 < 1633 cm−1) in the F, A, and B horizons, while in the H horizon, it had a similar height under the beech forest. Under the spruce forest, the peak at 1724 cm−1 was similar in height to the shoulder peaks at 1633 cm−1 in the L and F horizons, but it had a higher intensity (1724 > 1633 cm−1) in the H, A, and B horizons. The higher peak of 1724 cm−1 than that of 1633 cm−1 in the subsoil horizon was likely due to ester formation and the elimination of the stretching mode of COO− ions [68]. Additionally, this phenomenon explained how the 1724 cm−1 band became progressively weaker with an increase in color intensity, indicating a progressive decrease in COOH content with increasing molecular weight. These systematic changes occurred in the intensities and positions of bands in the 1660–1600 cm−1 region [68]. Besides that, these results revealed that the structures of organic matter were more stable under beech than under spruce [69]. The gradual disappearance of N-H bending and C=N stretching (1517 cm−1) with increasing depth under both forest stands (Figure 4) indicated that the N was being decomposed by soil microorganisms and resulted from the degradation of various moieties of forest litter substances from L to B horizons [70]. In addition, the peak of N-H bending and C=N stretching under the beech forest was higher in the L and F horizons compared to the spruce forest (Table S3). Similarly, Mládková et al. [71] reported that low-solubility AEOSs originating from the organic horizons under the beech forest were relatively richer in nitrogen functional groups than substances originating from the spruce stands. The band of the OH deformation and C-H stretching of phenolic OH was visible in all horizons under both forests. The band at 1280 cm−1 (C-O stretching and OH deformation of COOH) was lower at deeper soil depths. This pointed to the higher maturity of low-solubility AEOSs in the uppermost soil layer [69]. It showed a similar tendency to the polysaccharides bands, which had lower intensities at deeper soil horizons. However, it was observed that the band at 1280 cm−1 was higher than the other neighboring peaks, such as those at 1447, 1403, and 1280 cm−1, in most of the soil horizons under the spruce forest, while in the beech forest, it was observed only in the F horizon and had lower peaks with depth.
On comparing the spectra of AEOSs, we found that the soluble AEOS spectra had three dominant peaks (1633, 1403, and 1280 cm−1), while the low-solubility AEOS spectra had more well-separated peaks (2950–2800, 1724, 1517, 1403, and 1280 cm−1). Generally, the soluble AEOS was readily affected by the degree of humification and easily translocated in the soil solution through the soil profiles, whereas the low-solubility AEOS indicated impurities associated with minerals or water or had complex chains and showed high humification of organic compounds that were insusceptible to degradation, thus tending to persist for longer [11,65]. However, there was a higher saturation degree of the low-solubility AEOS than the soluble AEOS, which was confirmed by the reflectance bands between 2932 and 2853 cm−1. The low-solubility AEOS spectra appeared at two peaks (2932 and 2853 cm−1) in the aliphatic C-H stretching group region in each horizon, while the soluble AEOS spectra appeared at only one peak and had lower intensities than those of the low-solubility AEOS under both forest stands. This result showed a similar finding to Giovanela et al. [72], and it could be attributed to the asymmetrical and symmetrical stretching of methylene (-CH2-) groups in the low-solubility AEOS and the asymmetrical C-H stretching of methyl (-CH3-) groups in the soluble AEOS. Remarkably, the peaks of the low-solubility AEOS in the region of the C=O stretch of COOH and ketones were more intense and visible compared to the soluble AEOS spectra in most soil horizons. The band at 1633 cm−1 appeared similar in height and was visible under both AEOS spectra. The higher intensity of the peaks of N-H bending and C=N stretching (1517 cm−1) in low-solubility AEOS spectra than soluble AEOS spectra under both forest tree species was likely due to the less labile structure in the low-solubility AEOS and exposure to enzymatic attack, leading to increased humification; therefore, more molecular structures can be seen [73]. The percentage of N was generally higher in the low-solubility AEOS, which reflected the presence of protein or peptide fragments [47,74]. It was consistent with the finding of Ussiri and Johnson [26] that the low-solubility AEOS maintained a higher proportion of N than soil organic matter, while the soluble AEOS was depleted of N. Another difference between the AEOS spectra was that the intensity peaks at 1403 cm−1 were more intense in the soluble AEOS compared to the low-solubility AEOS under both forest species. The band of the C-O stretching and OH deformation of COOH observed at 1280 cm−1 was sharper and had a higher intensity in soluble than low-solubility AEOS spectra. The peaks of polysaccharides at 1045 cm−1 were more visible under the low-solubility AEOS in most of the soil horizons. In this case, it could be due to the lower stability of the soluble AEOS. Therefore, it showed a low incidence in the region of polysaccharides, possibly due to aluminosilicate impurities (Si-O stretch) [61,75]. However, ascribing these bands to aluminosilicate impurities depended on some factors, including the additional presence of bands at 980 cm−1 (AlAlOH stretch) and 530 cm−1 (Al-O-Si stretch) [65].
3.4. The Effect of Forest Tree Conversion on Soil Organic Matter and Soil Development through Forest Soil Profile
It is presumed that the SOM, which consists of mainly humus substances, behaves differently through the beech and spruce forest soil profiles. In our results, the SOM had been stabilized under the beech and spruce forests by changing from available or reactive substances to more stable forms in forest soil profiles (beech and spruce), as we observed increases in aliphatic and carboxylic groups within the low-solubility AEOS in deeper soil horizons and a relative increase in aromatic groups under the beech stands. It was also confirmed by the thermal analysis, which showed Tmax values ranging between 400 and 500 °C (Figure 1). After clear cutting forests for spruce plantation to investigate soil development for a century, the content of SOM was rapidly reduced and lost in the uppermost layers due to the humification process and organic matter decomposition for the first few years and then started to stabilize with time [14]. It was noticed that the SOM structures, such as aliphatic CH groups, which were evaluated using DRIFT, were more frequent in the A horizon under spruce, and the content of carboxylic groups increased in deeper soil horizons. It is consistent with previous research [39] showing that the SOC content increased in each horizon under beech, while under spruce, it increased with time only in the A horizon after long-term observation from 2008 to 2020. It explained that the SOC content under spruce increased after plantation but decreased in 2015 due to the dry climate condition (low precipitation and high temperature), which directly affected the SOC in the organic horizons (L, F, and H horizons). Our study also found that some organic acids were more represented in the A horizon and some carboxylic groups within the soluble AEOS were more prevalent in deeper soil horizons (A and B horizons), which resulted in the soil development and acceleration of podzolization [76]. Generally, the formation and downward transport of organic acid complexes with Al and Fe are some of the processes indicating the podzol formation, and the quality and mobility of SOM play an essential role in it [76]. Podzolization, on the other hand, is a long-term natural process that is also conditioned by low soil pH and base saturation. The formation of a well differentiated soil profile takes approximately 300–3000 years, depending on climate conditions [77]. Chemical changes conditioned, for example, by vegetation cover changes are faster [76,78]. Under the beech forest, the SOM structure, such as aliphatic CH group representation, increased relatively with depth compared to the spruce forest. This resulted from the age of the forest tree species, the canopy closure, and the organic matter input. Studies by Yuan et al. [79] and Bradová et al. [16] revealed that older beech forests typically had larger canopy closure, resulting in a reduced SOM decomposition rate, while an open canopy closure led to SOM loss due to more favorable soil microclimates, higher exposure to throughfall, and the warmer condition, which accelerated the decomposition rate of the SOM [80,81,82,83]. Ohno et al. [84] indicated that older deciduous forests had a high amount of organic inputs, such as litterfall, root dead mass, and root mortality, thus enhancing the high amount of aliphatic CH groups within the forest soil profiles. This phenomenon can lead to lower soil wettability and improve long-term SOC storage by adsorption onto the mineral surface under beech forests and can protect SOM within the aggregate, and vice versa [85]. Additionally, climatic conditions can alter the microbial activities and low molecular weight fractions to be more depolymerized by-products under spruce, and they can be easily lost and transported into deeper soil horizons or leach into the groundwater [14,86,87].
Besides that, the results also showed some negative consequences of vegetation change, specifically on the border of organic and mineral horizons. The higher proportion of mobile components of SOM and acidic COOH groups under the spruce stands compared to the beech stands, together with the lower pH and CEC in spruce forest soil, can lead to the leaching of nutrients and the release of risk elements into the soil solution. On a broader scale, the shift towards fast-growing coniferous plantations has relevant consequences on fundamental soil functions and services such as biogeochemical nutrient cycling, including the mentioned changes in exchangeable cations and differences in organic matter composition, C, and nutrient stocks. Given that natural temperate broadleaf stands are among the highly threatened ecosystems requiring effective protection (the studied locality is part of a protected area included in the UNESCO World Heritage List), it is important to understand the conversion to cultural conifer stands is inappropriate.
4. Conclusions
This study agreed with the hypothesis that the change in vegetation cover caused changes not only in basic soil conditions, as found in previous studies, but also in the qualitative composition of soil organic matter. It can be stated that the various organic components were translocated differently through the forest soil profiles. The content of DOC was higher in the F and H horizons compared to other horizons under both forest tree species. A higher content of LMMOAs, on the other hand, was found in the L and F horizons under beech, and in the F and H horizons under spruce. When comparing both forest stands, the beech forest soil had a higher DOC concentration in the organic horizons and a higher abundance of LMMOAs than the spruce forest soil did. The spectroscopic characterization of AEOSs differed between organic and mineral horizons under both forests. The most obvious difference was that the aliphatic groups in the soluble AEOS spectra disappeared in deeper soil horizons under both forest species. On the contrary, the aliphatic groups in the low-solubility AEOS spectra were intense in the A horizon in the spruce, and their intensity relatively increased with depth under the beech stands. This indicated the maturity of the organic matter in the beech forest and the formation of micelles of the low-solubility AEOS. Nonetheless, it can suggest that the soil under the spruce has undergone podzolization and the SOM has stabilized after the replacement of natural beech stands with the spruce monoculture.
Conceptualization, S.T., L.P., and V.T.; methodology, S.T., L.P., and V.T.; investigation, P.V., B.T., K.V., and O.D.; writing—original draft preparation, S.T., L.P., and V.T.; writing—review and editing, S.T., L.P., O.D., and V.T.; visualization, S.T., L.P., O.D., and V.T. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Not applicable.
The datasets used and analyzed during the study are available from the corresponding author upon reasonable request.
We thank Thilo Rennert for valuable help with providing and consulting about lab experiments.
The authors declare that they have no conflicts of interest.
Footnotes
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Enlarge this image.Figure 1. The distribution of basic soil characteristics in the litter horizon (L), fermentation horizon (F), humified horizon (H), organo-mineral horizon (A), and subsurface mineral horizon (B—spodic or cambic) of the soil profile dug under beech and spruce at Jizera Mountains (Czech Republic) (mean and standard deviation). Cation exchange capacity, CEC (cmol kg−1); soil organic carbon, SOC (%); dissolved organic carbon, DOC (mg kg−1); maximal temperatures, Tmax and Tmax2 (°C).
Enlarge this image.Figure 2. The concentration of low molecular mass organic acids under beech and spruce forests. (A) Comparison of the low molecular mass organic acids between beech and spruce forests, expressed in mmol kg−1. (B) The translocation of low molecular mass organic acids expressed as a percentage (%) through the whole soil profile in each forest stand (mean value). Litter horizon (L), fermentation horizon (F), humified horizon (H), organo-mineral horizon (A), and subsurface mineral horizon (B—spodic or cambic).
Enlarge this image.Figure 3. Correlation matrix plot of all data among the soil properties under forest tree species: cation exchange capacity (CEC), soil organic carbon (SOC), dissolved organic carbon (DOC), thermal analysis presented as maximum temperatures (Tmax and Tmax2), amount of relative reflectance of soluble alkaline-extractable organic substance (sAEOS), low-solubility alkaline-extractable organic substance (lAEOS), and low molecule mass organic acids (LMMOAs).
Enlarge this image.Figure 4. The spectra of soluble and low-solubility alkaline-extractable organic substances in each horizon under beech and spruce forests (mean spectra from three individual samples). Litter horizon (L), fermentation horizon (F), humified horizon (H), organo-mineral horizon (A), and subsurface mineral horizon (B−spodic or cambic).
Enlarge this image.Figure 5. The reflectance bands of soluble alkaline-extractable organic substances (sAEOSs) and low-solubility alkaline-extractable organic substances (lAEOSs), expressed as %, in each horizon under beech and spruce forests. Litter horizon (L), fermentation horizon (F), humified horizon (H), organo-mineral horizon (A), and subsurface mineral horizon (B−spodic or cambic).
Supplementary Materials
The following supporting information can be downloaded at:
References
1. Budde, S.; Schmidt, W.; Weckesser, M. Impact of the admixture of European beech (Fagus sylvatica L.) on plant species diversity and naturalness of conifer stands in Lower Saxony. Wald. Online; 2011; 11, pp. 49-61.
2. Spiecker, H.; Hansen, J.; Klimo, E.; Skovsgaard, J.P.; Sterba, H.; von Teuffel, K. Norway Spruce Conversion–Options and Consequences; EFI Research Report 18 Brill: Leiden, The Netherlands, Boston, MA, USA, Köln, Germany, 2004; ISBN 90-04-13728-9
3. Verstraeten, G. Conversion of Deciduous Forests to Spruce Plantations and Back: Evaluation of Interacting Effects on Soil, Forest Floor, Earthworm and Understorey Communities. Ph.D. Thesis; Ghent University: Ghent, Belgium, 2013.
4. Achilles, F.; Tischer, A.; Bernhardt-Römermann, M.; Heinze, M.; Reinhardt, F.; Makeschin, F.; Michalzik, B. European beech leads to more bioactive humus forms but stronger mineral soil acidification as Norway spruce and Scots pine–Results of a repeated site assessment after 63 and 82 years of forest conversion in Central Germany. For. Ecol. Manag.; 2021; 483, 118769. [DOI: https://dx.doi.org/10.1016/j.foreco.2020.118769]
5. Klimo, E.; Hager, H.; Kulhavý, J. Spruce Monocultures in Central Europe–Problems and Prospects. Spruce Monocultures in Central Europe-Problems and Prospects; Proceedings 33 European Forest Institute: Joensuu, Finland, 2000; ISBN 952-9844-76-X
6. Seliger, A.; Ammer, C.; Kreft, H.; Zerbe, S. Changes of vegetation in coniferous monocultures in the context of conversion to mixed forests in 30 years–Implications for biodiversity restoration. J. Environ. Manag.; 2023; 343, 118199. [DOI: https://dx.doi.org/10.1016/j.jenvman.2023.118199]
7. Heine, P.; Hausen, J.; Ottermanns, R.; Schäffer, A.; Roß-Nickoll, M. Forest conversion from Norway spruce to European beech increases species richness and functional structure of aboveground macrofungal communities. For. Ecol. Manag.; 2019; 432, pp. 522-533. [DOI: https://dx.doi.org/10.1016/j.foreco.2018.09.012]
8. Fernández, J.M.; Plante, A.F.; Leifeld, J.; Rasmussen, C. Methodological considerations for using thermal analysis in the characterization of soil organic matter. J. Therm. Anal. Calorim.; 2011; 104, pp. 389-398. [DOI: https://dx.doi.org/10.1007/s10973-010-1145-6]
9. Lal, R. Soil organic matter and water retention. Agron. J.; 2020; 112, pp. 3265-3277. [DOI: https://dx.doi.org/10.1002/agj2.20282]
10. Ahmad, B.; Wang, Y.; Hao, J.; Liu, Y.; Bohnett, E.; Zhang, K. Variation of carbon density components with overstory structure of larch plantations in northwest China and its implication for optimal forest management. For. Ecol. Manag.; 2021; 496, 119399. [DOI: https://dx.doi.org/10.1016/j.foreco.2021.119399]
11. Ohno, T.; He, Z.; Tazisong, I.A.; Senwo, Z.N. Influence of tillage, cropping, and nitrogen source on the chemical characteristics of humic acid, fulvic acid, and water-soluble soil organic matter fractions of a long-term cropping system study. Soil Sci.; 2009; 174, pp. 652-660. [DOI: https://dx.doi.org/10.1097/SS.0b013e3181c30808]
12. Li, Q.; Wang, L.; Fu, Y.; Lin, D.; Hou, M.; Li, X.; Hu, D.; Wang, Z. Transformation of soil organic matter subjected to environmental disturbance and preservation of organic matter bound to soil minerals: A review. J. Soils. Sediments; 2023; 23, pp. 1485-1500. [DOI: https://dx.doi.org/10.1007/s11368-022-03381-y]
13. Ukalska-Jaruga, A.; Smreczak, B.; Klimkowicz-Pawlas, A. Soil organic matter composition as a factor affecting the accumulation of polycyclic aromatic hydrocarbons. J. Soils. Sediments; 2019; 19, pp. 1890-1900. [DOI: https://dx.doi.org/10.1007/s11368-018-2214-x]
14. Jamroz, E.; Jerzykiewicz, M. Humic fractions as indicators of soil organic matter responses to clear-cutting in mountain and lowland conditions of southwestern Poland. Land. Degrad. Dev.; 2022; 33, pp. 368-378. [DOI: https://dx.doi.org/10.1002/ldr.4158]
15. Kooch, Y.; Samadzadeh, B.; Hosseini, S.M. The effects of broad-leaved tree species on litter quality and soil properties in a plain forest stand. Catena; 2017; 150, pp. 223-229. [DOI: https://dx.doi.org/10.1016/j.catena.2016.11.023]
16. Bradová, M.; Tejnecký, V.; Borůvka, L.; Němeček, K.; Ash, C.; Šebek, O.; Svoboda, M.; Zenáhlíková, J.; Drábek, O. The variations of aluminium species in mountainous forest soils and its implications to soil acidification. Environ. Sci. Pollut. Res.; 2015; 22, pp. 16676-16687. [DOI: https://dx.doi.org/10.1007/s11356-015-4855-2] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26084557]
17. Habumugisha, V.; Mourad, K.A.; Hashakimana, L. The Effects of Trees on Soil Chemistry. Curr. Environ. Eng.; 2018; 6, pp. 35-44. [DOI: https://dx.doi.org/10.2174/2212717806666181218141807]
18. Nacke, H.; Goldmann, K.; Schöning, I.; Pfeiffer, B.; Kaiser, K.; Villamizar, G.A.C.; Schrumpf, M.; Buscot, F.; Daniel, R.; Wubet, T. Fine spatial scale variation of soil microbial communities under European beech and Norway spruce. Front. Microbiol.; 2016; 7, 2067. [DOI: https://dx.doi.org/10.3389/fmicb.2016.02067]
19. Richardson, J.B.; Friedland, A.J. Influence of coniferous and deciduous vegetation on major and trace metals in forests of northern New England, USA. Plant. Soil.; 2016; 402, pp. 363-378. [DOI: https://dx.doi.org/10.1007/s11104-016-2805-5]
20. Campbell, E.E.; Paustian, K. Current developments in soil organic matter modeling and the expansion of model applications: A review. Environ. Res. Lett.; 2015; 10, 123004. [DOI: https://dx.doi.org/10.1088/1748-9326/10/12/123004]
21. Clarholm, M.; Skyllberg, U.; Rosling, A. Organic acid induced release of nutrients from metal-stabilized soil organic matter—The unbutton model. Soil Biol. Biochem.; 2015; 84, pp. 168-176. [DOI: https://dx.doi.org/10.1016/j.soilbio.2015.02.019]
22. Gerke, J. Concepts and misconceptions of humic substances as the stable part of soil organic matter: A review. Agronomy; 2018; 8, 76. [DOI: https://dx.doi.org/10.3390/agronomy8050076]
23. Hubova, P.; Tejnecky, V.; Ash, C.; Boruvka, L.; Drabek, O. Low-Molecular-Mass Organic Acids in the Forest Soil Environment. Mini. Rev. Org. Chem.; 2017; 14, pp. 75-84. [DOI: https://dx.doi.org/10.2174/1570193X14666161130163034]
24. Adeleke, R.; Nwangburuka, C.; Oboirien, B. Origins, roles and fate of organic acids in soils: A review. S. Afr. J. Bot.; 2017; 108, pp. 393-406. [DOI: https://dx.doi.org/10.1016/j.sajb.2016.09.002]
25. Xiao, M.; Wu, F.; Liao, H.; Li, W.; Lee, X.; Huang, R. Characteristics and distribution of low molecular weight organic acids in the sediment porewaters in Bosten Lake, China. J. Environ. Sci.; 2010; 22, pp. 328-337. [DOI: https://dx.doi.org/10.1016/S1001-0742(09)60112-1] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20614773]
26. Ussiri, D.A.N.; Johnson, C.E.; Johnson, C.E. Characterization of organic matter in a northern hardwood forest soil by 13 C NMR spectroscopy and chemical methods of organic matter could account for variations in the structure and chemistry of organic matter in these forest soils. Geoderma; 2003; 111, pp. 123-149. [DOI: https://dx.doi.org/10.1016/S0016-7061(02)00257-4]
27. Senesi, N.; D’Orazio, V.; Ricca, G. Humic acids in the first generation of EUROSOILS. Geoderma; 2003; 116, pp. 325-344. [DOI: https://dx.doi.org/10.1016/S0016-7061(03)00107-1]
28. Guimarães, D.V.; Gonzaga, M.I.S.; da Silva, T.O.; da Silva, T.L.; da Silva Dias, N.; Matias, M.I.S. Soil organic matter pools and carbon fractions in soil under different land uses. Soil Tillage Res.; 2013; 126, pp. 177-182. [DOI: https://dx.doi.org/10.1016/j.still.2012.07.010]
29. Tang, W.W.; Zeng, G.M.; Gong, J.L.; Liang, J.; Xu, P.; Zhang, C.; Huang, B.B. Impact of humic/fulvic acid on the removal of heavy metals from aqueous solutions using nanomaterials: A review. Sci. Total Environ.; 2014; 468–469, pp. 1014-1027. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2013.09.044] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24095965]
30. Tunega, D.; Gerzabek, M.H.; Haberhauer, G.; Lischka, H.; Solc, R.; Aquino, A.J.A. Adsorption process of polar and nonpolar compounds in a nanopore model of humic substances. Eur. J. Soil. Sci.; 2020; 71, pp. 845-855. [DOI: https://dx.doi.org/10.1111/ejss.12865]
31. Yang, C.M.; Wang, M.C.; Lu, Y.F.; Chang, I.F.; Chou, C.H. Humic substances affect the activity of chlorophyllase. J. Chem. Ecol.; 2004; 30, pp. 1057-1065. [DOI: https://dx.doi.org/10.1023/B:JOEC.0000028467.82191.f9]
32. Debska, B.; Drag, M.; Banach-Szott, M. Molecular size distribution and hydrophilic and hydrophobic properties of humic acids isolated from forest soil. Soil Water. Res.; 2007; 2, pp. 45-53. [DOI: https://dx.doi.org/10.17221/2113-SWR]
33. Piccolo, A. The supramolecular structure of humic substances: A novel understanding of humus chemistry and implications in soil science. Adv. Agron.; 2002; 75, pp. 57-134. [DOI: https://dx.doi.org/10.1016/s0065-2113(02)75003-7]
34. Sutton, R.; Sposito, G. Molecular structure in soil humic substances: The new view. Environ. Sci. Technol.; 2005; 39, pp. 9009-9015. [DOI: https://dx.doi.org/10.1021/es050778q] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16382919]
35. Lehmann, J.; Kleber, M. The contentious nature of soil organic matter. Nature; 2015; 528, pp. 60-68. [DOI: https://dx.doi.org/10.1038/nature16069] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26595271]
36. Borůvka, L.; Vacek, O.; Jehlička, J. Principal component analysis as a tool to indicate the origin of potentially toxic elements in soils. Geoderma; 2005; 128, pp. 289-300. [DOI: https://dx.doi.org/10.1016/j.geoderma.2005.04.010]
37. Pavlů, L.; Borůvka, L.; Drábek, O.; Nikodem, A. Effect of natural and anthropogenic acidification on aluminium distribution in forest soils of two regions in the Czech Republic. J. For. Res.; 2021; 32, pp. 363-370. [DOI: https://dx.doi.org/10.1007/s11676-019-01061-1]
38. Tejnecký, V.; Bradová, M.; Borůvka, L.; Němeček, K.; Šebek, O.; Nikodem, A.; Zenáhlíková, J.; Rejzek, J.; Drábek, O. Profile distribution and temporal changes of sulphate and nitrate contents and related soil properties under beech and spruce forests. Sci. Total Environ.; 2013; 442, pp. 165-171. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2012.10.053] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23178776]
39. Thai, S.; Pavlů, L.; Tejnecký, V.; Chovancová, S.; Hin, L.; Thet, B.; Němeček, K.; Drábek, O. Temporal changes in soil chemical compositions in acidified mountain forest soils of Czech Republic. Eur. J. For. Res.; 2023; 142, pp. 883-897. [DOI: https://dx.doi.org/10.1007/s10342-023-01564-x]
40. Rennert, T.; Herrmann, L. Thermal-gradient analysis of soil organic matter using an elemental analyser–A tool for qualitative characterization?. Geoderma; 2022; 425, 116085. [DOI: https://dx.doi.org/10.1016/j.geoderma.2022.116085]
41. Cools, N.; De Vos, B. Sampling and Analysis of Soil. Manual on Methods and Criteria for Harmonized Sampling, Assessment, Monitoring and Analysis of the Effects of Air Pollution on Forests; UNECE ICP Forests Programme Coordinating Centre. Thünen Institute of Forest Ecosystems: Eberswalde, Germany, 2016.
42. Sparks, D.L.; Page, A.; Helmke, P.; Loeppert, R.H. Methods of soil analysis part 3 Chemical Methods Soil Science Society of America Book Series. Methods of Soil Analysis; American Society of Agronomy, Inc.: Madison WI, USA, 1996.
43. Tejnecký, V.; Řeřichová, N.; Bradová, M.; Němeček, K.; Šantrůčková, H.; Ash, C.; Drábek, O. Litter Decomposition as a Source of Active Phosphates in Spruce and Beech Mountainous Forests Affected by Acidification. Procedia Earth Planet. Sci.; 2014; 10, pp. 130-132. [DOI: https://dx.doi.org/10.1016/j.proeps.2014.08.043]
44. Hubová, P.; Tejnecký, V.; Češková, M.; Borůvka, L.; Němeček, K.; Drábek, O. Behaviour of aluminium in forest soils with different lithology and herb vegetation cover. J. Inorg. Biochem.; 2018; 181, pp. 139-144. [DOI: https://dx.doi.org/10.1016/j.jinorgbio.2017.09.017]
45. Piccolo, A.; Celano, G.; Conte, P. Methods of isolation and characterization of humic substances to study their interactions with pesticides. Pesticides/Soil Interactions: Some Current Research Methods; INRA: Paris, France, 2000; pp. 103-116.
46. Haberhauer, G.; Gerzabek, M.H. Drift and transmission FT-IR spectroscopy of forest soils: An approach to determine decomposition processes of forest litter. Vib. Spectrosc.; 1999; 19, pp. 413-417. [DOI: https://dx.doi.org/10.1016/S0924-2031(98)00046-0]
47. López, R.; Gondar, D.; Iglesias, A.; Fiol, S.; Antelo, J.; Arce, F. Acid properties of fulvic and humic acids isolated from two acid forest soils under different vegetation cover and soil depth. Eur. J. Soil. Sci.; 2008; 59, pp. 892-899. [DOI: https://dx.doi.org/10.1111/j.1365-2389.2008.01048.x]
48. Buresova, A.; Tejnecky, V.; Kopecky, J.; Drabek, O.; Madrova, P.; Rerichova, N.; Omelka, M.; Krizova, P.; Nemecek, K.; Parr, T.B. et al. Litter chemical quality and bacterial community structure influenced decomposition in acidic forest soil. Eur. J. Soil. Biol.; 2021; 103, 103271. [DOI: https://dx.doi.org/10.1016/j.ejsobi.2020.103271]
49. Cremer, M.; Prietzel, J. Soil acidity and exchangeable base cation stocks under pure and mixed stands of European beech, Douglas fir and Norway spruce. Plant Soil.; 2017; 415, pp. 393-405. [DOI: https://dx.doi.org/10.1007/s11104-017-3177-1]
50. Berthrong, S.T.; Jobbágy, E.G.; Jackson, R.B. A global meta-analysis of soil exchangeable cations, pH, carbon, and nitrogen with afforestation. Ecol. Appl.; 2009; 19, pp. 2228-2241. [DOI: https://dx.doi.org/10.1890/08-1730.1] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20014590]
51. Gruba, P.; Mulder, J. Tree species affect cation exchange capacity (CEC) and cation binding properties of organic matter in acid forest soils. Sci. Total Environ.; 2015; 511, pp. 655-662. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2015.01.013] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25596350]
52. 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, pp. 233-253. [DOI: https://dx.doi.org/10.1051/forest:2002020]
53. De Schrijver, A.; Geudens, G.; Augusto, L.; Staelens, J.; Mertens, J.; Wuyts, K.; Gielis, L.; Verheyen, K. The effect of forest type on throughfall deposition and seepage flux: A review. Oecologia; 2007; 153, pp. 663-674. [DOI: https://dx.doi.org/10.1007/s00442-007-0776-1] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/17629749]
54. Kopáček, J.; Hejzlar, J.; Kaňa, J.; Norton, S.A.; Porcal, P.; Turek, J. Trends in aluminium export from a mountainous area to surface waters, from deglaciation to the recent: Effects of vegetation and soil development, atmospheric acidification, and nitrogen-saturation. J. Inorg. Biochem.; 2009; 103, pp. 1439-1448. [DOI: https://dx.doi.org/10.1016/j.jinorgbio.2009.07.019] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/19793616]
55. Kopáček, J.; Veselý, J. Sulfur and nitrogen emissions in the Czech Republic and Slovakia from 1850 till 2000. Atmos. Environ.; 2005; 39, pp. 2179-2188. [DOI: https://dx.doi.org/10.1016/j.atmosenv.2005.01.002]
56. Fagan, M.E.; Kim, D.H.; Settle, W.; Ferry, L.; Drew, J.; Carlson, H.; Slaughter, J.; Schaferbien, J.; Tyukavina, A.; Harris, N.L. et al. The expansion of tree plantations across tropical biomes. Nat. Sustain.; 2022; 5, pp. 681-688. [DOI: https://dx.doi.org/10.1038/s41893-022-00904-w]
57. Salas, C.; Donoso, P.J.; Vargas, R.; Arriagada, C.A.; Pedraza, R.; Soto, D.P. The forest sector in chile: An overview and current challenges. J. For.; 2016; 114, pp. 562-571. [DOI: https://dx.doi.org/10.5849/jof.14-062]
58. Barreto, M.S.C.; Ramlogan, M.; Oliveira, D.M.S.; Verburg, E.E.J.; Elzinga, E.J.; Rouff, A.A.; Jemo, M.; Alleoni, L.R.F. Thermal stability of soil organic carbon after long-term manure application across land uses and tillage systems in an oxisol. Catena; 2021; 200, 105164. [DOI: https://dx.doi.org/10.1016/j.catena.2021.105164]
59. Barreto, M.S.C.; Elzinga, E.J.; Ramlogan, M.; Rouff, A.A.; Alleoni, L.R.F. Calcium enhances adsorption and thermal stability of organic compounds on soil minerals. Chem. Geol.; 2021; 559, 119804. [DOI: https://dx.doi.org/10.1016/j.chemgeo.2020.119804]
60. Berg, B.; McClaugherty, C. Plant Litter: Decomposition, Humus Formation, Carbon Sequestration; Springer: Berlin/Heidelberg, Germany, 2008.
61. Thai, S.; Pavlů, L.; Tejnecký, V.; Vokurková, P.; Nozari, S.; Borůvka, L. Comparison of soil organic matter composition under different land uses by DRIFT spectroscopy. Plant Soil. Environ.; 2021; 67, pp. 255-263. [DOI: https://dx.doi.org/10.17221/11/2021-PSE]
62. Margenot, A.J.; Calderón, F.J.; Bowles, T.M.; Parikh, S.J.; Jackson, L.E. Soil Organic Matter Functional Group Composition in Relation to Organic Carbon, Nitrogen, and Phosphorus Fractions in Organically Managed Tomato Fields. Soil Sci. Soc. Am. J.; 2015; 79, pp. 772-782. [DOI: https://dx.doi.org/10.2136/sssaj2015.02.0070]
63. Veum, K.S.; Goyne, K.W.; Kremer, R.J.; Miles, R.J.; Sudduth, K.A. Biological indicators of soil quality and soil organic matter characteristics in an agricultural management continuum. Biogeochemistry; 2014; 117, pp. 81-99. [DOI: https://dx.doi.org/10.1007/s10533-013-9868-7]
64. Leinweber, P.; Schulten, H.R.; Kalbitz, K.; Meißner, R.; Jancke, H. Fulvic acid composition in degraded fenlands. J. Plant Nutr. Soil Sci.; 2001; 164, pp. 371-379. [DOI: https://dx.doi.org/10.1002/1522-2624(200108)164:4<371::AID-JPLN371>3.0.CO;2-9]
65. Machado, W.; Franchini, J.C.; de Fátima Guimarães, M.; Filho, J.T. Spectroscopic characterization of humic and fulvic acids in soil aggregates, Brazil. Heliyon; 2020; 6, e04078. [DOI: https://dx.doi.org/10.1016/j.heliyon.2020.e04078] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32548320]
66. Sierra, M.M.D.; Rauen, T.G.; Tormen, L.; Debacher, N.A.; Soriano-Sierra, E.J. Evidence from surface tension and fluorescence data of a pyrene-assisted micelle-like assemblage of humic substances. Water Res.; 2005; 39, pp. 3811-3818. [DOI: https://dx.doi.org/10.1016/j.watres.2005.07.005]
67. Tatzber, M.; Stemmer, M.; Spiegel, H.; Katzlberger, C.; Haberhauer, G.; Mentler, A.; Gerzabek, M.H. FTIR-spectroscopic characterization of humic acids and humin fractions obtained by advanced NaOH, Na4P2O7, and Na2CO3 extraction procedures. J. Plant Nutr. Soil Sci.; 2007; 170, pp. 522-529. [DOI: https://dx.doi.org/10.1002/jpln.200622082]
68. Stevenson, F. Humus Chemistry: Genesis, Composition, Reactions. Humus Chemistry; 2nd ed. Wiley: Hoboken, NJ, USA, 1994; ISBN 978-0-471-59474-1
69. Pavlů, L.; Mühlhanselová, M. Differences in humic acids structure of various soil types studied by DRIFT spectroscopy. Soil Water Res.; 2017; 13, pp. 29-35. [DOI: https://dx.doi.org/10.17221/76/2017-SWR]
70. Haberhauer, G.; Rafferty, B.; Strebl, F.; Gerzabek, M.H. Comparison of the composition of forest soil litter derived from three different sites at various decompositional stages using FTIR spectroscopy. Geoderma; 1998; 83, pp. 331-342. [DOI: https://dx.doi.org/10.1016/S0016-7061(98)00008-1]
71. Mládková, L.; Rohošková, M.; Borůvka, L. Methods for the Assessment of Humic Substances Quality in Forest Soils. Soil Water Res.; 2006; 1, pp. 3-9. [DOI: https://dx.doi.org/10.17221/6499-SWR]
72. Giovanela, M.; Parlanti, E.; Soriano-Sierra, E.J.; Soldi, M.S.; Sierra, M.M.D. Elemental compositions, FT-IR spectral and thermal behavior of sedimentary fulvic and humic acids from aquatic and terrestrial environments. Geochem. J.; 2004; 38, pp. 255-264. [DOI: https://dx.doi.org/10.2343/geochemj.38.255]
73. Pospíšilová, L.; Komínková, M.; Zítka, O.; Kizek, R.; Barančíková, G.; Litavec, T.; Lošák, T.; Hlušek, J.; Martensson, A.; Liptaj, T. Fate of humic acids isolated from natural humic substances. Acta Agric. Scand. Sect. B Soil Plant Sci.; 2015; 65, pp. 517-528. [DOI: https://dx.doi.org/10.1080/09064710.2015.1030442]
74. Gaffney, J.S.; Marley, N.A.; Clark, S.B. Humic and Fulvic Acids and Organic Colloidal Materials in the Environment; ACS Symposium Series; American Chemical Society: Washington, DC, USA, 1996; Volume 651, [DOI: https://dx.doi.org/10.1021/bk-1996-0651.ch001]
75. Madejova, J.; Komadel, P. Baseline studies of the clay minerals society source clays: Infrared methods. Clays Clay Miner.; 2001; 49, pp. 410-432. [DOI: https://dx.doi.org/10.1346/CCMN.2001.0490508]
76. Lundström, U.S.; Van Breemen, N.; Bain, D. The podzolization process. A review. Geoderma; 2000; 94, pp. 91-107. [DOI: https://dx.doi.org/10.1016/S0016-7061(99)00036-1]
77. Sauer, D.; Sponagel, H.; Sommer, M.; Giani, L.; Jahn, R.; Stahr, K. Podzol: Soil of the year 2007. A review on its genesis, occurrence, and functions. J. Plant Nutr. Soil Sci.; 2007; 170, pp. 581-597. [DOI: https://dx.doi.org/10.1002/jpln.200700135]
78. Dlouhá, Š.; Borůvka, L.; Pavlů, L.; Tejnecký, V.; Drábek, O. Comparison of Al speciation and other soil characteristics between meadow, young forest and old forest stands. J. Inorg. Biochem.; 2009; 103, pp. 1459-1464. [DOI: https://dx.doi.org/10.1016/j.jinorgbio.2009.07.024]
79. Yuan, Z.; Gazol, A.; Lin, F.; Ye, J.; Shi, S.; Wang, X.; Wang, M.; Hao, Z. Soil organic carbon in an old-growth temperate forest: Spatial pattern, determinants and bias in its quantification. Geoderma; 2013; 195–196, pp. 48-55. [DOI: https://dx.doi.org/10.1016/j.geoderma.2012.11.008]
80. Zech, W.; Guggenberger, G.; Haumaier, L.; Pöhhacker, R.; Schäfer, D.; Amelung, W.; Miltner, A.; Kaiser, K.; Ziegler, F. Organic Matter Dynamics in Forest Soils of Temperate and Tropical Ecosystems. Humic Substances in Terrestrial Ecosystems; Elsevier: Amsterdam, The Netherlands, 1996; pp. 101-170. [DOI: https://dx.doi.org/10.1016/b978-044481516-3/50004-9]
81. Merabtene, M.D.; Faraoun, F.; Mlih, R.; Djellouli, R.; Latreche, A.; Bol, R. Forest Soil Organic Carbon Stocks of Tessala Mount in North-West Algeria-Preliminary Estimates. Front. Environ. Sci.; 2021; 8, 520284. [DOI: https://dx.doi.org/10.3389/fenvs.2020.520284]
82. Hanakova-Becvarova, P.; Horvath, M.; Sarapatka, B.; Zouhar, V. The effect of stand characteristics on soil organic carbon content in spruce and deciduous stands. For. Syst.; 2022; 31, e005. [DOI: https://dx.doi.org/10.5424/fs/2022311-18824]
83. Jandl, R.; Leitgeb, E.; Englisch, M. Decadal Changes of Organic Carbon, Nitrogen, and Acidity of Austrian Forest Soils. Soil Syst.; 2022; 6, 28. [DOI: https://dx.doi.org/10.3390/soilsystems6010028]
84. Ohno, T.; Parr, T.B.; Ce, M.; Gruselle, I.; Fernandez, I.J.; Sleighter, R.L.; Hatcher, P.G. Molecular Composition and Biodegradability of Soil Organic Matter: A Case Study Comparing Two New England Forest Types. Environ. Sci. Technol.; 2014; 48, pp. 7229-7236. [DOI: https://dx.doi.org/10.1021/es405570c] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24912044]
85. Thai, S.; Davídek, T.; Pavlů, L. Causes clarification of the soil aggregates stability on mulched soil. Soil Water Res.; 2022; 17, pp. 91-99. [DOI: https://dx.doi.org/10.17221/151/2021-SWR]
86. Lal, R. Digging deeper: A holistic perspective of factors affecting soil organic carbon sequestration in agroecosystems. Glob. Change Biol.; 2018; 24, pp. 3285-3301. [DOI: https://dx.doi.org/10.1111/gcb.14054]
87. Zosso, C.U.; Ofiti, N.O.E.; Torn, M.S.; Wiesenberg, G.L.B.; Schmidt, M.W.I. Rapid loss of complex polymers and pyrogenic carbon in subsoils under whole-soil warming. Nat. Geosci.; 2023; 16, pp. 344-348. [DOI: https://dx.doi.org/10.1038/s41561-023-01142-1]
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; Vejvodová, Kateřina
; Drábek, Ondřej
; Tejnecký, Václav