J Soils Sediments (2017) 17:2066–2079 DOI 10.1007/s11368-017-1678-4
SOILS, SEC 2 • GLOBAL CHANGE, ENVIRON RISK ASSESS, SUSTAINABLE LAND USE • RESEARCH ARTICLE
Organic matter transformation and porosity development in non-reclaimed mining soils of different ages and vegetation covers: a field study of soils of the zinc and lead ore area in SE Poland Krystyna Ciarkowska 1
Received: 26 June 2016 / Accepted: 9 February 2017 / Published online: 24 February 2017 # Springer-Verlag Berlin Heidelberg 2017
Abstract Purpose Plant residue decomposition, porosity status and biological activity in heavily polluted with Zn, Pb and Cd postmining soils were investigated in relation to natural soil in the area. The study was carried out on soils from different ages and vegetation cover. This work aimed at studying the influence of heavy metal concentration on the humus layer formation with the help of micromorphological methods. Materials and methods Soil samples were collected from 5 sites situated in the Zn and Pb mining area and from one site located in the vicinity but unchanged by mining works. In each site, a representative area of about 100 m2 was selected and soil samples from 5 randomly selected plots were taken from surface and subsurface layers. Chemical, micromorphological and biological analyses were conducted in order to evaluate humus transformations occurring in studied soils and to establish the main factors affecting these processes. In images taken from thin sections, we separated and measured areas covered by decomposed organic matter, plant residues and pores. Results and discussion Mine soils had similar pH soil values (6.7–7.1); only one natural soil was moderately acid (pH = 5.6). The soils differed in SOM content, from 30.84 to 168 g kg−1. Mine soils were contaminated with heavy metals up to 10,980 mg Zn, 5436 mg Pb and 95.2 mg Cd· kg−1. The largest amount of the medium-sized and large plant residues (18.4 and 20.5%) were found in post-mining soil Responsible editor: Jean Louis Morel * Krystyna Ciarkowska
[email protected] 1
Soil Science and Soil Protection Department, University of Agriculture, Aleja Mickiewicza 21, 31-120 Krakow, Poland
covered with xerothermic flora typical of metalliferous areas. The lowest amount of small residues was found in postmining forest soil. The diversified accumulation of plant residues reflected the organic matter decomposition ratio varying from 1.64 (post-mining soil 15% covered with calamine flora) to 62.7% (natural soil covered with forest). In the natural soil, rounded pores prevailed, while in post-mining soils, planar pores dominated. Invertase activity ranged from 1.64 to 154.2 mg of inverted sugar, and carbon of microbial biomass ranged from 5.94 to 731.2 μg g−1. Both characteristics were related to the amount of organic matter regardless of the heavy-metal pollution. Conclusions The results showed that a decomposition ratio was lower in mining soils than in the natural soil, and large plant residues were accumulated in surface layers. Microbial activity was more influenced by plant cover density and diversity than by heavy metal concentration. The evolution in the organic matter form and pore shapes with the soil age and the vegetation cover was observed. Keywords Chronosequence . Heavy metal pollution . Micromorphological analysis . Plant residues decomposition . Porosity . Post-mining soils
1 Introduction Zinc and lead mining activities in the Olkusz district (SE Poland) that started centuries ago have left behind areas with mine wastes composed of overburdened rocks and tailings without vegetation. Moreover, during the last decades, the flotation of zinc and lead ores, introduced as a method of metal recovery, resulted in the formation of settling ponds. All these waste materials, containing high amounts of zinc, lead and
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cadmium, were left to the spontaneous restoration of soils (Pająk et al. 2015; Ciarkowska et al. 2016). Studies on the development of plant cover and soil formation processes occurring on mine waste deposits are of great importance because their results may suggest measures to counteract threats of heavy metal leaching to the surrounding environment (Pellegrini et al. 2016). Accumulation, decomposition and humus formation are the major processes in the soil rehabilitation on post-mining sites, where, as a result of mining activities, upper humus horizons have been destroyed and have to be reconstructed (Frouz et al. 2006). Decomposition and transformation of organic matter, soil structure formation and flow of energy are mainly carried out by soil microorganisms. Therefore, the estimation of microbial biomass may serve as an ecological marker, which is especially useful in the evolution of reconstructing ecosystems (Voroney et al. 2008; Józefowska et al. 2016). Soil enzymes play an important role in the breakdown of organic matter. They also stimulate the processes connected with the formation of soil humus. The activity of the enzyme invertase reflects the rate of organic matter transformation as it takes part in the decomposition of carbon compounds (Yang et al. 2007; Li et al. 2012; Ciarkowska et al. 2014). Soil organic matter (SOM) accumulation also affects the soil pore architecture, which in turn influences water movement, infiltration and retention, hence the development of vegetation cover. On the other hand, diversified vegetation increases pore complexity (Bottinelli et al. 2010; Jangorzo et al. 2013). Soils developed on post-mining sites are good subjects for studying processes related to organic matter accumulation and transformation, because they present different stages of paedogenesis: from almost bare, soil-less lands to afforested areas with soil profiles that have developed over centuries. Moreover, specific humus layer formation and soil restoration can be observed in soils derived from technogenic materials, characterized by unfavourable conditions for plant growth, such as high amounts of heavy metals and scarcity of water and nutrients (Frouz et al. 2008; Jangorzo et al. 2013; Ciarkowska et al. 2016; Żołnierz et al. 2016). SOM formation influenced by plant residue quality was studied in reclaimed and non-reclaimed post-mining sites in a laboratory-created microcosmos (Frouz et al. 2008). There were also studies on soil microbial parameters during spontaneous succession, on post-mining sites in coal-mining areas (Frouz and Nováková 2005). The relationship between vegetation restoration and the pores’ complexity in areas degraded by heavy erosion was also examined (Zhou et al. 2012). To our knowledge, there is still scarce information on the selfrestoration of soil of Zn-Pb post-mining areas, in relation to plant residue decomposition, humus formation processes and porosity development. Our work will provide new insight into the use of combined chemical, biological and
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micromorphological analyses for monitoring the soil rehabilitation processes under specific conditions that include chronic pollution with Zn, Pb and Cd; soils of different age and with a diversified vegetation cover. The innovative aspect will be to consider the role of native vegetation appearing on postmining sites in the formation of humus layers in mining soils. Evaluating the level of self-restoration processes may help in planning for post-mining areas management. In our work, we hypothesise that differences in humus layer formation between post-mining soils and natural soil were caused mainly by the input of variously decomposable plant residues and low biological activity resulting from heavy-metal contamination. Our aims were (i) to investigate by micromorphological means the amount and size of plant residues and porosity structure; (ii) to evaluate SOM susceptibility towards microbial decomposition, based on the determination of microbial biomass and invertase activity and (iii) to estimate interactions among plant residues, microbial biomass, invertase activity and porosity structure. More specifically, we investigated how much post-mining soils differ in properties from a natural soil in the area studied and which factors are responsible for these differences.
2 Materials and methods 2.1 Study area The study was performed in SE Poland in the KrakowSilesian Upland (N50°17′E19°29′), on the post-mining area of zinc and lead ores, during 2013–2014. The climate of the area is moderate humid (mean annual precipitation is 700 mm, mean annual temperature 7.2 °C). Six sites located in the Silesia-Cracow region, which rich silver, lead and zinc deposits supported one of Europe’s oldest mining areas, were investigated. Opencast mining started in this area during the twelfth and thirteenth centuries, when rich silver, lead and zinc deposits, occurring in Triassic dolomites covered with Pleistocene sand, were discovered. In the history of ore mining of this region, three main stages connected with the different methods of metal extraction and recovery can be distinguished. The first period up to the sixteenth century was associated with manual mining of surface metal deposits in which fire-heated rocks were broken or crushed with pickaxes or hammers, and metals were recovered by simple sieving and washing methods. From that period, the oldest heaps remained formed of dolomite waste rock pieces, metal residues with sand (site in Bukowo—W, 400 years old). The next stage (from the sixteenth century till about 50 years ago) covered time period of mechanized opencast mining of ores located a few meters under the surface. From this long lasting period, a lot of tailings remained composed of the similar material as the oldest ones. On these dumps soils from sites, Ujkow
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Stary—U (100 years old), Tarnowskie Góry—TG and Żabie Doły—ZD (both about 70 years old) are located. The last stage started about 50 years ago with the development of new drainage techniques that allowed deeper deposits of metals to be exploited by underground mining technique. The technology for metal recovery was changed to flotation method, and since that time, sludges after flotation processes have been collected on a settler (site SP, 30 years old). The bedrock of site SP comprised the post-flotation sludge originated due to grinding of dolomitic Zn-Pb ores, sand and fragments of dolomite rock. All investigated sites were located on flat areas, at a distance 5–20 km from each other. They have never been reclaimed and left to natural plant succession. As a reference model, a natural soil, derived from the Triassic dolomite and Pleistocene sand, unchanged by mining activities, located in the vicinity was included. A natural soil has a similar bedrock to post-mining soils and a climax plant community. It was meant to represent the final stage of the development of soils of the studied area. The studied sites differed in age, type of vegetation cover and its density. The first site (SP) was 15% covered, with calamine flora species, such as: Armeria marritima Mill. Willd, Silene vulgaris (Moench) Garcke and Gypsophila fastigiata L., with some Betula pendula Roth trees. The two next sites (TG and ZD) were both covered by grassland vegetation, with rare species characteristic of calamine flora (listed for previous site), and numerous species typical of xerothermic meadow, such as Plantago media L., Ajuga genevensis L., Asperula cynanchica L., and Euphorbia cyparissias L. The TG site surface was 40% covered with vegetation while the ZD site was 80% covered. The U site was 100% covered with calamine flora, composed of the calamine flora species listed above, as well as Biscutella laevigata L., Carlina acaulis L., Gentianella germanica (Willd.) Börner, Alyssum montanum L. and Epipactis atrorubens (Hoffm.) Besler. The W site was overgrown by a forest ecosystem, which had developed by natural colonization (Pinus silvestris L. and Betula pendula Roth as dominant trees, with flora similar to Festuco-Brometea as undergrowth). The reference, natural soil (F), presented a site of conifers with some deciduous trees (P. silvestris L., B. pendula Roth, Fagus silvatica L.), with the undergrowth composed of Vaccinium myrtillus L., V. vitis-idaea L., Deschampsia flexuosa (L.) Trin, D. caespitosa (L.) P. Beauv., Calamagrostis arundinacea (L.) Roth and Pleurosium scheberi Wildt.
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description. Soil samples were taken from 0 to 10-cm and from 10 to 20-cm layers. Un-decomposed needles and leaves accumulated on the surface, 1–2 cm thick, were removed. Undisturbed soil samples were collected in Kubiena boxes and impregnated with Araldite epoxy resin in a vacuum for thin-section preparation. There were five Kubiena boxes collected from the 0–5-cm depth (corresponding to O and a part of A soil horizons) and five from the 15–20-cm depth (corresponding to A and AB soil horizons) for each site as the organic horizons were of varied thickness, from 5 cm (SP) to 15 cm (W and F). In the oldest post-mining soil (W) and a natural soil (F), humus horizons were of similar thickness, composed of L (about 2 cm), O (about 3 cm) and A (about 12 cm). In soils of sites U, TG, ZD and SP only, A horizons occurred with maximum thickness of 10 cm (U), 8 cm (TG, ZD) and 5 cm (SP). In sites TG and ZD, soil samples for micromorphological analysis were taken only from the surface layers, because in the subsurface layers, there were too many pieces of dolomite rocks to take undisturbed soil sample. Around each point of soil sampling, a number of plant species was counted in spring and autumn. In the laboratory, each sample was divided into two parts: one part was designed for chemical and physical analyses and was air-dried and sieved by a 2-mm sieve while the other was designed for microbial analysis and kept at a temperature of 4 °C for 2 weeks before analysis. 2.3 Analyses of physical, chemical and biological soil properties Disturbed soil samples were analysed using the following methods: & & &
2.2 Sampling & Soil samples were collected in October 2013. Sampling design consisted in choosing a representative area of 100 m2 in each investigated site. In each area, five plots of about 4 m2 were randomly selected to collect samples for chemical, biological and micromorphological analyses as well as for plant
Soil texture was determined by the densimetric-sieve method and classified according to WRB 2014 recommendations (WRB 2014) pH values were determined potentiometrically in H2O suspension, with soil-to-water ratio 1:2.5 (Tan 2005). Total and inorganic carbon concentrations were determined using an automatic carbon analyser (Elementar Vario MAX CUBE), with sulphanilic acid as the reference material and with detection limits of 0.001% for C. Organic carbon concentrations were calculated as the difference between the total and the inorganic carbon concentrations. Soil organic matter (SOM) was computed by multiplying organic carbon content by the Van Bemmelen factor equal to 1.724 (Tan 2005). Total Zn, Pb and Cd concentrations were measured after digestion in HNO3 and HClO4 acids (Hendershof et al. 2006), and their soluble forms were extracted with 0.01 M CaCl2 at pH = 7 (Houba et al. 1994). Total and soluble metals were assessed with a PerkinElmer atomic emission spectrometer ICP-OES Optima 7300 DV and
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&
&
multi-element ICP-IV Merck standard solution. The accuracy of the analytical methods was verified using GSS-8 certificated reference material (GBW 07408, State Bureau of Metrology, Beijing, China). Invertase activity was established colorimetrically after incubating the samples for 24 h at 37 °C, with a saccharose solution used as the substrate. The intensity of coloration was measured with a Beckman DU 600 spectrophotometer, at a wavelength of 540 nm (Frankenberger and Johanson 1983). In order to eliminate seasonal fluctuations in the determination of enzyme activity, soil samples were collected twice, once in May and once in October (Włodarczyk 2000). The results presented in the table are the arithmetic means of the spring and autumn enzyme activity. Microbial biomass (MBC) was determined by the fumigation-extraction method. MBC was calculated from the difference between the amount of total carbon extracted with 0.5 M potassium sulphate from fresh soil fumigated with chloroform and the amount extracted from nonfumigated soil samples (Voroney et al. 2008). Carbon dissolved in the soil extracts was measured by the dry combustion method using TOC analyser.
2.4 Image analysis Images of thin sections were taken using a Nikon D200 (3872 × 2592 pixel) camera with an AF Micro Nikkor 60 mm lens, with circular polarized light (CPL) and transmitted light (TL), in a way which was described precisely by Ciarkowska et al. (2016). In the images, porosity and organic matter were assessed with two different software programs. Images of the soil thin sections were segmented using a ‘thresholding’ technique of Corel Photo-Paint X5, in order to obtain binary images. The total porosity was determined using Micromorph 1.4 software (TRANSVALOR 2000). The total soil pore area (AP) was grouped into rounded (APr), planar (APp) and intermediate (APi) pores, which were separated according to a shape factor (SF) relating the shape of an object to that of a circle: SF ¼ 4Π⋅ area=perimeter2 For planar pores, the SF is less than 0.2; for intermediate pores, the SF is between 0.2 and 0.5 and for rounded pores, the SF is larger than 0.5 (Głąb and Kulig 2008). The pore area was computed for each pore category. Organic matter was assessed in plane light using Aphelion ADCIS S.A. Aai. Inc. software. For the identification of selected objects image processing was performed (Jangorzo et al. 2014). A colour histogram was used as a thresholding method to divide organic matter
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into a well-decomposed and aggregated part (AM) and plant residues as a non-decomposed part (AR). The total area of aggregates (AM) was calculated. Plant residues (roots or leaves) were divided into three classes, based on their diameter—small 50–300 μm (ARs), mediumsized 300–2000 μm (ARm) and large above 2000 μm (ARl). Their areas (ARs, ARm, ARl) were measured. The mean and standard deviations of these properties were calculated in each size class and for each sample. The organic matter decomposition ratio (DR) was calculated as a share of decomposed organic matter in the whole organic matter area (AM/(AM + AR)) multiplied by 100 to report in percent.
2.5 Statistics In order to present the general characteristics of the selected parameters of the studied soils, the arithmetic means and standard deviations (SD) were calculated. Analysis of variance (one-way ANOVA) was used to study the differences in examined parameters regarding the amount and size of plant residues, pores of different shapes, amount and decomposition of organic matter and microbial activity between soils of different age and plant cover. Prior to the variance analysis, it was checked whether the tested variables were normally distributed (Shapiro-Wilk test), and whether there was homogeneity of variance (Levene test). Owing to the presence of normal distribution, the parametric variance analysis was applied. In order to estimate the least significant differences between the mean values of homogenous groups, the post hoc test, by means of the Bonferroni correction (at P < 0.05), was used. To evaluate interactions among plant residues, microbial biomass, invertase activity and porosity structure, a Pearson’s linear correlation coefficient values were calculated. Factor analysis (FA) was applied to specify groups of variables (soil parameters) influenced by the main factors. In order to make the factors more easily interpretable, the Varimax rotation was performed. Principal component analysis (PCA) showed the relationship between the examined variables (selected soil parameters) and soils of different sites. Plotting of soil parameters in the PC1-PC2 plan allowed us to select groups of parameters correlated with each other and specify which parameters affected development of the surface layer of each soil (ter Braak and Smilauer 2012). In order to depict the increasing dissimilarity among the soils studied, and especially, the difference between mining soils of different age and plant cover and a natural soil, a hierarchical cluster diagram after Ward’s method was produced. Statistical analyses were conducted using Statistica PL v 12 packet (StatSoft Inc. 2014) and Canoco 5 (ter Braak and Smilauer 2012).
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3 Results 3.1 Physical and chemical soil properties All studied soils had similar textures, with a high content of sand ranging from 60 to 85% and a low amount of clay (2– 13%). Soil reaction varied between slightly acid and neutral, with pH values, measured in H2O, ranging from 5.6 (site F, covered with forest) to 7.3 (site TG, covered with grassland vegetation) (Table 1). All post-mining soils derived from waste ores bearing rocks (sites: W, U, ZD, TG and SP) contained very high amounts of Zn, Pb and Cd. However, the levels of heavy metal concentration varied in wide range. TG soil contained the largest total concentrations of each metal which exceeded 10,000 mg Zn· kg−1, 5350 mg Pb·kg−1 and 89 mg Cd·kg−1 in the surface layer. Still high but significantly lower amounts of these metals than in TG occurred in the youngest SP soil (Table 2). Such distribution was related to the modernization of technology of recovering the metals from ores. Old technology based on washing and sieving of ores left higher concentration of metals in wastes, compared to modern flotation method. A natural soil from the F site had, on average, 375.5 mg Zn·kg−1; 407.7 mg Pb·kg−1 and 7.62 mg Cd·kg−1 in the surface layers. In the subsurface layers, the total concentrations of heavy metals were lower than in surface layers, due to atmospheric deposits. Total amounts of metals are not a direct indicator of their bioavailability as they are comprised of forms with varying solubility. Therefore, soluble Zn, Pb and Cd concentrations were also estimated in the examined soil samples. The amount of soluble Zn accounted for 0.8–2.1% of its total concentration and ranged from 0.5 to 165.1 mg kg−1. The amount of soluble Pb
Table 1 Physical and chemical properties, means ± standard deviation
accounted for 0.01–0.04% of its total concentration and ranged from 0.01 to 0.73 mg kg−1. The soluble Cd concentration accounted for 1.1–3.58% of the total Cd concentration and ranged from 0.01 to 1.76 mg kg−1 (Table 2). These concentrations of CaCl2-extractable heavy metals were much below those obtained by Liu et al. (2016), which inhibit the enzyme activity in polluted soils. Studied sites varied in diversity of plant species (Table 3). The highest number of species was recorded from sites W and U (21 and 19 species, respectively), similar but significantly less species were found at site F, TG and ZD (12–14 species) and the least number of species was found at the site SP (3 species). Different vegetation cover resulted in significantly diversified quantities of organic matter (SOM) accumulated in the soils. In the surface layers, the lowest and significantly different quantity of SOM compared to the other soils was found in the SP site (30.84 g kg−1) and the highest amounting to 168 g kg−1 in site U. Lower quantities of SOM were accumulated in the subsurface layers compared to surface layers. They ranged from 11.41 g kg−1 in SP site to 88.63 g kg−1 in W site (Table 1). 3.2 Invertase activity (Inv) and microbial biomass (MBC) In the surface layers, the invertase activity differed significantly among studied soils and varied from 1.64 to 154.2 mg of inverted sugar. Similar, significantly higher levels, exceeding 150 mg of inverted sugar, were determined in the natural soil cover with forest (F) and in the two oldest soils on post-mining sites (W and U) that were fully covered with vegetation. The lowest value was determined in the youngest 30-year-old soil, which was 15% covered with vegetation. In subsurface layers,
Site
Sand (2–0.05 mm) %
Clay (>0.002 mm) %
pH H2O
SOM g·kg−1
F/0–10 F/10–20 W/0–10 W/10–20 U/0–10 U/10–20 TG/0–10 TG/10–20 ZD/0–10 ZD/10–20 SP/0–10 SP/10–20
78bc ± 2 68ab ± 3 74b ± 3 67ab ± 4 74b ± 4 75bc ± 3 67ab ± 4 60a ± 3 71b ± 2 68ab ± 4 85c ± 5 85c ± 3
8abc ± 3 8abc ± 2 13c ± 2 7abc ± 3 4ab ± 2 3ab ± 2 5ab ± 3 9abc ± 2 3ab ± 3 9abc ± 2 2a ± 2 2a ± 2
5.6a ± 0.3 5.6a ± 0.2 6.8bcd ± 0.1 6.7bcd ± 0.1 6.8bcd ± 0.2 7.1de ± 0.2 7.3e ± 0.2 7.3e ± 0.1 6.4b ± 0.2 6.5bc ± 0.1 6.9cde ± 0.2 6.9cde ± 0.1
42.79c ± 1.51 13.79a ± 1.43 148.8g ± 1.4 88.63e ± 1.39 168.0i ± 1.5 34.08b ± 0.21 122.1h ± 0.97 81.28d ± 1.17 111.3f ± 1.34 12.98a ± 0.16 30.84b ± 1.10 11.41a ± 0.74
F—natural, forest soil; W—post-mining 400-year-old soil, overgrown by forest; U—post-mining, about 100year-old soil, fully covered with calamine flora; TG—post-mining, about 70 years old, soil covered in 40% with grass and calamine flora; ZD—post-mining, about 70 years old, soil covered in 80%with grass and calamine flora; SP—flotation settler, 30-year-old soil, covered in 15% by calamine flora. Different letters show significant differences, p < 0.05
J Soils Sediments (2017) 17:2066–2079 Table 2 Site
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Contents of total and soluble forms of zinc, lead and cadmium (arithmetic mean ± standard deviation, n = 5) Total content of metals (mg·kg−1)
Content of soluble metals (mg·kg−1)
Zn
Pb
Cd
Zn
Pb
Cd
F/0–10
375.5a ± 12.9
407.7ab ± 21.7
7.62b ± 0.97
7.8 ± 0.6
0.07 ± 0.02
0.22 ± 0.05
F/10–20 W/0–10
22.83a ± 4.67 8365f ± 410
19.37a ± 2.8 4459g ± 191
0.5a ± 0.1 63.1i ± 1.7
0.5 ± 0.1 109.1 ± 9.1
0.01 ± 0.01 0.66 ± 0.07
0.01 ± 0.01 1.63 ± 0.16
W/10–20 U/0–10
5390d ± 198 8398f ± 401
4096g ± 161 2631f ± 97
52.0g ± 0.59 57.8h ± 0.99
9.0 ± 0.3 63.9 ± 1.2
0.46 ± 0.02 0.34 ± 0.06
0.91 ± 0.03 0.62 ± 0.04
U/10–20 TG/0–10
7061e ± 301 10871g ± 298
1259d ± 61 5353h ± 221
43.4f ± 0.76 89.9j ± 1.1
11.3 ± 0.6 165.1 ± 8.0
0.22 ± 0.04 0.73 ± 0.11
1.14 ± 0.12 1.73 ± 0.63
TG/10–20
6052d ± 176
2629f ± 103
42.9f ± 1.5
14.9 ± 0.3
0.43 ± 0.08
0.63 ± 0.03
ZD/0–10 ZD/10–20
3961c ± 241 2901b ± 114
1959e ± 98 1198d ± 101
62.8i ± 0.9 32.6e ± 0.29
63.6 ± 5.6 28.6 ± 3.6
0.32 ± 0.06 0.27 ± 0.04
1.76 ± 0.11 1.07 ± 0.10
SP/0–10 SP/10–20
4049c ± 204 2479a ± 197
961.6cd ± 97 769.7bc ± 46
23.61d ± 0.31 17.9c ± 0.8
78.1 ± 1.2 25.3 ± 0.3
0.33 ± 0.01 0.22 ± 0.01
0.63 ± 0.06 0.53 ± 0.04
Different letters show significant differences, p < 0.05. Abbreviations for the sites are provided in Table 1
the invertase activity was about tenfold lower than in the surface layers (0.29–19.6 mg of inverted sugar) (Fig. 1a). Microbial biomass varied also widely in both layers of the studied soils. In surface layers, significantly higher values of MBC were estimated in W (731.2 μg g − 1 ) and U (570.5 μg g−1) soils than in F and ZD (about 450 μg g−1) while TG soil was characterized by significantly lower MBC (291.4 μg g−1). Thus, MBC in the surface layers of the older soils formed on mine tailings (W and U) was higher than in the natural soil (F). The lowest MBC was estimated in SP soil (85 μg g−1). In subsurface layers, the distribution of MBC was similar but the values were more than twofold smaller than in the 0–10-cm layers (Fig. 1b).
3.3 Results of image analysis 3.3.1 Pore shapes The results of the shape factor analysis indicated that, in both layers, the natural soil (F) was characterized by a statistically higher share of rounded pores (APR) than other soils, exceeding 60% and below 40%, of the total porosity in surface and subsurface layers, respectively. In the surface layer of F soil, there was a very small share of planar pores—APP (below 5%) and a bit more in the subsurface layer (about 30%). In soils derived from technogenic materials, the proportion of rounded (APR) and planar pores (APP) areas were inverted. Table 3 Diversity of plant species, mean ± SD, n = 30
APR amounted to 10% while APP represented above 70% of the total porosity. The area of intermediate pores (API) was similar in the surface layers of all studied soils, and diversifications were only seen in subsurface layers (Fig. 2). 3.3.2 Organic matter In Fig. 3, shares of total plant residues (AR), decomposed organic matter (AM) and pore (AP) areas are presented. In both layers, total area of plant residues (AR) was significantly higher in technogenic soils (besides W) than in a natural soil (F). Significant differences in decomposed organic matter area (AM) between soils were observed only in the 0–10-cm layer. In U, TG, ZD and SP soils differed significantly from the one in F soil and was arranged in the order SP < TG < ZD < U < W < F. Sum of ARs, ARm and AM was significantly positively correlated with SOM described by Pearson’s linear correlation coefficient amounting to 0.3911. In the top layer, the total area of pores (AP) was significantly different from F soil in U, ZD, TG and SP soils, while in 10–20 cm, AP area was significantly higher only in SP soil. 3.3.3 Microstructure and plant residues description In the surface layer of SP soil, planar pores occurred mainly, with large plant residues and few aggregates among mineral soil material of sludge origin (Fig. 4a). The 100-year-old soil
Site
F
W
U
TG
ZD
SP
Species number
13b ± 2
21c ± 4
19c ± 3
14b ± 2
12b ± 2
3a ± 1
Different letters show significant differences, p < 0.05. Abbreviations for the sites are provided in Table 1
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Fig. 1 Box and whisker diagram of the activity of invertase (a) and MBC (b) in surface (0–10 cm) and subsurface (10–20 cm) layers. The focal point—the mean value, the box—the standard error and the whisker—the
standard deviation. Statistically significant differences are marked with different letters (P < 0.05)
U, fully covered with calamine flora, accumulated a large amount of organic matter, which was mainly slightly decomposed and stored in horizontally arranged stripes, with some aggregates of well-decomposed organic matter (Fig. 4b), while soils W and F (the oldest, post-mining soil and a natural one, both covered with forest) were composed of well-aggregated material (Fig. 4c). In surface layers, the lowest and similar areas of small(AR s ) , and medium-sized (AR m ) plant residues were
determined in F (natural soil) and W (mining soil), both covered with forests (1.71 and 1.92% for ARs, and 1.28 and 1.37% for ARm, respectively) (Table 4). The highest ARs (4.9%) was determined in U (mining soil fully covered with calamine flora), while the highest ARm (18.4%) was found in ZD (mining soil 80% covered with grassland species). Areas covered by large plant residues (ARl) differed among studied soils, being significantly lower in W (0.4%) and F (0.5%) than in ZD (20.5%). In the subsurface layers, the differences in
Fig. 2 Share of pores of different shapes in the image area. APR rounded pores, API intermediate pores, APP planar pores areas. Statistically significant differences within each soil parameters are marked with different letters (P < 0.05)
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Fig. 3 Share of total pore area (AP), plant residue area (AR) and decomposed organic matter area (AM) in the image area. Statistically significant differences within each soil parameters when compared to the parameter in natural soil are marked with asterisks (P < 0.05)
image areas covered by small (ARs), medium-sized (ARm) and large (ARl) plant residues among the soils studied were much smaller. The organic matter decomposition ratio (DR) varied significantly and ranged from 2.9 (SP) to 62.7% (F) in the surface layers. In the subsurface layers, DR values were much lower and less diversified than in the surface layers. Fig. 4 Humus layers of studied soils, plane polarized light, A SP soil, a plant residues, b cracks, c technogenic material remains, B U soil, d horizontally packed stripes of medium decomposed organic matter, C W soil, e aggregates of well-decomposed organic matter (similar structure to a natural soil)
4 Discussion 4.1 Contribution of plants, microorganisms and pores in humus layer formation The density of vegetation and the susceptibility to decomposition of residues produced by different plant species affect the
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Table 4 Plant residue areas and organic matter decomposition ratio, mean ± standard deviation Soil
ARs %
ARm %
ARl %
DR %
F/0–10
1.92ab ± 0.19
1.28b ± 0.1
0.5a ± 0.1
62.7c ± 3.7
F/10–20 W/0–10
0.87a ± 0.11 1.71ab ± 0.18
0.6a ± 0.06 0.0a ± 0 1.37b ± 0.16 0.4a ± 0.1
15.1b ± 7.0 61.9c ± 0.5 12.9b ± 0.3
W/10–20
0.62a ± 0.12
0.59a ± 0.09
0.0a ± 0
U/0–10
4.90d ± 0.10
6.47f ± 0.18
1.26b ± 0.20 3.3a ± 0.3
U/10–20 TG/0–10
3.00bcd ± 0.51 4.81d ± 0.12 1.75b ± 0.24 1.9a ± 0.4 4.44cd ± 0.21 5.67e ± 0.27 2.77c ± 0.22 16.8b ± 0.1
ZD/0–10
4.57cd ± 0.25
SP/0–10 3.51abc ± 0.88 SP/10–20 1.31ab ± 0.11
18.4h ± 0.69 20.5e ± 0.51
9.3ab ± 0.1
12.9g ± 0.24 9.01d ± 0.23 2.9a ± 0.1 3.51c ± 0.05 3.26c ± 0.28 2.3a ± 0.3
Different letters show significant differences, p < 0.05 ARs area covered by small plant residues (dia till 300 μm), ARm area covered by medium-sized plant residues (dia 300–2000 μm), ARl area covered by large plant residues (dia above 2000 μm), DR decomposition ratio—share of decomposed organic matter in the whole organic matter area
amount and transformation of the soil organic matter (Gaillard et al. 2003; Harris 2003; Frouz et al. 2006; Séré et al. 2010; Kriaučiūniené et al. 2012; Zhou et al. 2012). The studied soils differed in both density (from 15% to 100%) and type of plant cover (calamine flora, grassland or forest with P. silvestris as a dominating species). Although coniferous trees are known as the richest in lignin, tannins and cutins, which can limit processes of residue breakdown, in our study, ratios of organic matter decomposition (DR) were similar and with the highest values in two forest soils: a natural one and the 400-year-old post-mining site. This can be explained by multiple plant successions during which the organic matter entered the mineral soil. Microbial carbon values were the highest for the oldest in mine soils W, while in F (natural soil), MBC had only average values. There can be two reasons for that: firstly, the poor fluvioglacial sand bedrock of F soil which makes this site dryer than W, in which ore-bearing dolomites are mixed with sand, and secondly, the acid soil reaction of F soil resulted in a not much hospitable habitat for microorganisms. The diversity of plant species was also significantly lower on F than on W site. The results obtained in this work partially confirm the opinion of Fagotti et al. (2012), Frouz et al. (2006) and Zhou et al. (2012), who said that the incorporation of organic matter into mineral soil increases the water-holding capacity and the nutrient content, making the habitats more favourable for soil microorganisms, thus accelerating SOM decomposition. Microorganisms are the primary decomposers of the plant litter as they transform more than 90% of the plant litter carbon. Thus, the accumulation of organic matter usually results in higher microbial biomass and an increase in the enzyme’s activity (Frouz et al. 2006; Yang et al. 2007).
Invertase participates in the decay of plant tissues and transformations of soil organic matter by breaking down sucrose to glucose and fructose. Invertase activity was highly positively correlated with MBC. Pearson linear correlation coefficients calculated among Inv and MBC amounted to 0.869 (at P < 0.05). Both MBC and Inv were highly correlated with SOM, with Pearson’s coefficients of 0.694 and 0.834, respectively (at P < 0.05). The impact of both discussed soil microbial characteristics on humus layer formation was also shown by Pearson coefficients calculated among MBC and DR (0.532) as well as Inv and DR (0.454). The determination of enzyme activity is often used as an indicator of the degradation of ecosystems, as a result of excessive heavy-metal accumulation and its recovery (Schimann et al. 2012). In the studied soils, invertase activity was negatively correlated with total Zn, Pb and Cd, with the Pearson’s correlation coefficients of −0.496, −0.34 and −0.423, respectively. Negative correlation with total heavy metal concentrations and MBC was also observed with the Pearson’s correlation coefficients of −0.526, −0.395 and −0.495, respectively. Similarly, Ciarkowska et al. (2014) observed that that in postmining soils with the concentration of heavy metals at the level of about 4050 mg Zn, 950 mg Pb and 24 mg Cd·kg−1, the invertase activity amounted to 6.95 mg of inverted sugar, while in post-mining soils with Zn, Pb and Cd concentrations amounting to more than 10,000, 6000 and 80 mg kg−1 respectively, the invertase activity was lowered to 0.12 mg of inverted sugar. However, in the studied soils, the highest values of both microbial characteristics were determined in soils of the old post-mining sites that were strongly polluted with heavy metals and fully covered with vegetation, while low enzyme activity was observed in soils with poor vegetation cover. A relationship between microbial characteristics and vegetation cover density was proved by the high Pearson’s correlation coefficients between invertase activity and plant cover density (0.996) and MBC and plant cover density 0.785 (at P < 0.05). It seems that a positive influence of organic matter on the microbial activity was much stronger than that of the long-lasting heavy-metal pollution. This may be connected with the change in the microbial community structure after long-term exposure to a heavy metal contamination or/and a low concentration of soluble and directly toxic to microorganism forms of heavy metals, which under conditions of neutral pH values are bound to organic matter. Similar results were reported by Ram and Masto (2010), Finkenbein et al. (2013) and Liu et al. (2016) who observed that high pH values or/and a large amount of organic matter could immobilize heavy metals to a point where toxicity is significantly decreased or even eliminated. Doelman et al. (1994) observed that metal-contaminated soil contained metal-resistant microbes, even though these microbes often had a restricted ability to degrade organic compounds. It was noticed that enzyme activity decreased with increasing plant residue sizes (Fruit
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et al. 1999; Shi et al. 2002). Such a relationship also occurred in our studies and was expressed by a negative Pearson coefficient between invertase activity and area covered by large plant residues, whose value was −0.705 (at P < 0.05). Specific features distinguish calamine flora, composed of metallicolous plant species, which developed thick cuticles composed of cutins as a protection against loss of water and microbial attack (Frouz et al. 2007; Przedpełska and Wierzbicka 2007). Therefore, among soils contaminated with similar levels of heavy metals, the soil fully covered with calamine flora was characterized by a lower organic matter decomposition ratio than grassland soils. In strongly polluted areas close to zinc and lead smelters in France, it was found that the reduced decomposition of highly metal-enriched plant residues, lacking faunal homogenization activity, led to an accumulation of A. maritima and Arabidopsis halleri plant fragments in the surface layers (Escarré et al. 2011). Similar loosely arranged and mostly horizontal strips of partially humified organic matter, accumulated on the surface of the soil, were observed in soils of postmining sites covered with calamine flora. This partially decomposed organic matter was not mixed with mineral soil components. Such an establishment of the soil surface layer indicates low activity of earthworms bringing residues into the soil (Gillet and Ponge 2002; Ciarkowska and Gambus 2005; Fox et al. 2006; Kapur et al. 2007). Although not assessed in this study, an adverse impact on these organisms would also be expected, owing to the high metal contamination and the loss of habitat function. Dynamics of organic matter and soil development are connected with the changes in pore shapes (Gillet and Ponge 2002). Rounded pores are characteristic of soils with good water retention and undisturbed biological life. In such soils, organic matter is broken down quite quickly and small amounts of plant residues are accumulated (Vanden Bygaart et al. 2000). The relationship between rounded pores and decomposed organic matter areas was described by a Pearson linear coefficient, which amounted to 0.506 (at P < 0.05), while the accumulation of medium-sized and large plant residues contributed to the predominance of planar pores. This relationship was expressed by a Pearson linear coefficient amounting to 0.458 and 0.383, respectively (at P < 0.05). 4.2 Main factors shaping humus layers properties Factor analysis (FA) was performed in order to extract factors that cause the variables to vary. For the analysis, soil properties related to organic matter dynamics were chosen, such as areas of small, medium-sized and large plant residues (ARs, ARm, ARl); areas of rounded, intermediate and planar pores (APR, API, APP); organic matter content (SOM); decomposed organic matter area (AM); decomposition ratio (DR); invertase
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activity (Inv); microbial biomass (MBC) and also pH values and soluble forms of Zn, Pb and Cd. Principal components retained for rotation were selected based on the scree test and the Kaiser criterion (all factors with eigenvalues higher than one). FA analysis showed that all selected soil properties formed three distinct associations, with high loadings higher than 0.7 (Table 5). The first component (F1) represented planar pore (APP) and small plant residue (ARs) areas with high positive values as well as rounded pore area (AP R ), decomposed organic matter (AM) and organic matter decomposition ratio (DR) with high negative values. The positive values of APP and ARs and negative values of APR, AM and DR can be attributed to soils with a short paedogenesis, thus this factor could express temporal soil development. This was the most important factor, which explained 46.9% of the total variability. A second factor F2, covering 31.5% of the variability, included SOM, invertase activity (Inv), microbial biomass (MBC) and the area of intermediate pores (APi) with high positive loadings. It proved a relationship between these parameters, as the transformation of organic matter depends on the microorganisms and SOM content is regulated mainly Table 5 Matrix of rotation of standardized factor charges approached by the varimax method of parameters in surface layers Variable
ARs ARm ARl APr APi APp AM SOM DR Inv MBC Zns Pbs Cds pH Eigenvalues Cumulative variance (%)
Factor loadings (loadings in bold are >0.7 ) F1
F2
F3
0.722 - 0.429 0.173 - 0.880
0.031 -0.256 -0.180 -0.271
0.230 0.838 0.954 -0.326
-0.159 0.915 -0.912 0.246 -0.839 -0.553 -0.323 0.260 0.170 0.279 0.584 7.02 46.9
0.927 0.078 0.359 0.937 0.196 0.749 0.852 0.423 0.639 0.573 0.349 4.72 78.4
-0.100 0.341 0.002 -0.091 -0.288 -0.109 0.361 0.858 0.623 0.442 0.679 1.65 89.4
Areas of image covered by ARs—small plant residues (dia till 300 μm), ARm—medium-sized plant residues (dia 300–2000 μm), ARl—large plant residues (dia above 2000 μm), APr rounded pores, APi—intermediate pores and App—planar pores. Zns, Pbs and Cds are soluble forms of Zn, Pb and Cd AM decomposed organic matter SOM soil organic matter, DR decomposition ratio—share of decomposed organic matter in the whole organic matter area, Inv invertase activity, MBC carbon of microbial biomass
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by their activity in the soil and the activity of microorganisms is higher in soils of good water-air properties which in turn are influenced by intermediate pores (Ciarkowska and SołekPodwika 2012). Thus, the transformation processes of organic matter regulated by MBC and enzymes also constituted an important ecological factor shaping post-mining humus layer properties. A third factor (F3; 11.0% of variability) included areas of medium (ARm) and large plant residues (ARl) as well as soluble Zn content (Zns) with high positive loadings. The first two parameters were related to the density and type of vegetation cover, which enabled us to define this factor as the one showing the impact of plant cover on the soil humus layer development. The presence of Zns together with large- and medium-sized plant residues indicates its inhibitory effect on the plant residue decomposition. 4.3 Evaluation of post-mining soil development Figure 5 displays both the variables and site plot in the projection of principal components PC1 and PC2. PC1 seems to represent the soil development as discussed for the factor F1 (from the younger soil SP in the right to the older soil F in the left). PC2 seems to distinguish the sites depending on the microbial abundance and activity in relation to the SOM concentration and the plant diversity (higher in mine soils except
Fig. 5 Principal component analysis (PCA) based on biotic soil properties in the investigated post-mining sites and a natural soil. Abbreviations for the soil properties and sites are provided in Table 1
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SP) and the decomposition of the organic matter (higher in F). The figure shows high positive correlations between close variables such as APi and Pl div and ARl and ARm. In the development of W and U soils, AM, Inv, APi, Pl div, MBC and SOM played an important role and the sites were characterized by large values of these parameters while SP soil was characterized by low values. F soil properties were dominated by high values of DR and APr. The plot shows also the highest difference between F and SP sites among studied soils. Both ZD and TG soil properties were shaped by ARs, APp, ARm, ARl as well as pH and soluble Zn, Pb and Cd although in ZD soil, these parameters had higher values than in TG. Relatively homogenous group of sites were identified in the tree-like diagram. Figure 6 shows a dendrogram of clusters using Euclidian distance. In the diagram, there are two clusters of the shortest Euclidean distance: the first one is composed of ZD and TG sites and the second of U and W sites. The sites of the two clusters display more similarity than F site while the SP site differed the most from other sites. Soil of SP site was characterized by the lowest development of the humus layer which was related to the relatively short time of paedogenesis (30 years), and poor vegetation cover (15%) composed of only three calamine flora species. A litter originating from calamine flora species, which is hard to decompose, is also not attractive to microorganisms and soil fauna. The high
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Fig. 6 Tree-like diagram. Agglomeration according to Ward method, including areas of image covered by small, mediumsized and large plant residues; areas of rounded, intermediate and planar pores; area of decomposed organic matter, invertase activity, carbon of microbial biomass, decomposition ratio of organic matter and soil organic matter content
proportion of planar pores and the low proportion of rounded pores, together with an accumulation of large plant residues in the surface layers, were the common features for all postmining soils studied, differentiating them from the natural soil. It is said that the cessation of mining disturbances generally leads to the long-term natural reconstitution of the ecosystem (Escarré et al. 2011). However, in the case of major disturbances and heavy-metal contamination, the return to the natural ecosystem may be very difficult, or even impossible. The possible reason for that is that heavy metal pollution hampered soil fauna activity, especially that of earthworms which are known to be very susceptible to chemical pollution (Frouz et al. 2006, 2007; Józefowska et al. 2016). Even though microorganisms and plants adapted to the contaminated environment, reduced fauna activity, which incorporate organic matter in depth and take part in humification processes, slowed down the decomposition of organic matter and disturbed the soil functioning. Results of this study complements research on the temporal development of technogenic soils of this area, considered on the basis of soil aggregation and porosity structure development (Ciarkowska et al. 2016). With the development of aggregate formation, from medium-sized aggregates, in young soils to small aggregates in old soils (Ciarkowska et al. 2016), the gradual decrease in sizes and accumulation of nondecomposed plant residues were observed in this work. Temporal changes in porosity structure noticed in studied soils can also be related to plant cover and organic matter transformation. In surface layers of young soils, with poor plant cover, large and planar pores occurred between a few strips of slightly decomposed organic matter while the higher amount of narrower pores were observed in old soils. A higher amount of smaller and rounded pores resulted in the higher water
retention ability and in consequence the denser and more diversified plant cover of old mining soils.
5 Conclusions In this work, we studied a development of heavy-metalpolluted post-mining soils of different age (from 30 to 400 years old) by comparing their properties with those of a natural soil in the area. We examined if the heavy metal contamination caused the differences observed in plant cover diversity and density, microbiological activity (invertase and MBC), pore shape distribution, and the organic matter decomposition. In surface layers of post-mining soils, a decomposition ratio of organic matter was lower than in natural soil, and large plant residues were accumulated. Another characteristic feature of post-mining soils was a predominance of planar pores related to the accumulation of horizontally arranged, slightly decomposed strips of organic matter in soils with a dense plant cover and/or fissures among mineral soil material of technogenic origin in soils with poor plant cover. Although invertase activity and MBC were both negatively correlated with heavy metal concentrations, their values were more affected by the density of vegetation cover and thus the amount of organic matter entering the soil. Therefore, they reached the highest values in soils that were fully covered with vegetation, regardless of heavy-metal contamination. The abovedescribed differences in parameters between mining soils and a natural one resulted from the negative impact of a strong and long-term pollution by heavy metals. However, neutral pH and a large concentration of organic matter reduced the metal mobility and their negative impact on soil microbiological life.
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