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Article

Reforestation Impacted Soil Heavy Metal Fractionation and Related Risk Assessment in the Karst Area, Southwest China

by
Qian Zhang
1,
Guilin Han
2,* and
Xingliang Xu
1
1
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2
Institute of Earth Sciences, China University of Geosciences (Beijing), Beijing 100083, China
*
Author to whom correspondence should be addressed.
Forests 2021, 12(7), 891; https://doi.org/10.3390/f12070891
Submission received: 6 June 2021 / Revised: 28 June 2021 / Accepted: 6 July 2021 / Published: 8 July 2021
(This article belongs to the Special Issue Biogeochemical Cycling in Forest Ecosystems)
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Abstract

:
Human agricultural activities have resulted in widespread land degradation and soil contamination in the karst areas. However, the effects of reforestation after agricultural abandonment on the mobility risks and contamination of heavy metals have been rarely reported. In the present study, six soil profiles were selected from cropland and abandoned cropland with reforestation in the Puding karst regions of Southwest China. The Community Bureau of Reference (BCR) sequential extraction method was used to evaluate the compositions of different chemical fractions of soil heavy metals, including Fe, Mn, Cr, Zn, Ni, and Cd. The total contents of Cr, Ni, Zn, Cd, and Mn in the croplands were significantly higher than those in the abandoned croplands. For all soils, Cr, Ni, Zn, and Fe were mainly concentrated in the residual fractions (>85%), whereas Mn and Cd were mostly observed in the non-residual fractions (>65%). The non-residual fractions of Cd, Cr, Ni, and Zn in the croplands were higher than those in the abandoned croplands. These results indicated that the content and mobility of soil heavy metals decreased after reforestation. The individual contamination factor (ICF) and risk assessment code (RAC) showed that Cd contributed to considerable contamination of karst soils. The global contamination factor (GCF) and potential ecological risk index (RI) suggested low contamination and ecological risk of the investigated heavy metals in the croplands, moreover they can be further reduced after reforestation.

1. Introduction

Land degradation is a consequence of natural processes or human activities in the ecosystems [1]. Land resource is rare throughout the world, however nearly 25% surface area of the earth is influenced by land degradation [2]. Heavy metal pollution is an important anthropogenic factor that causes soil degradation [3]. Because of the difficulty of removing heavy metals from soils, some polluted soils cannot be used for cultivation, and this will aggravate land shortage [4,5]. To solve the soil loss, desertification, and adverse effects of cultivation, reforestation has been implemented by the Chinese government under the Grain for Green Project (GGP), which is the largest forest ecological construction project in the world [6,7,8]. In the southwest of China, particularly the karst region, the severe soil erosion and nutrient loss has extensively occurred with the continuous cultivation of steeply sloping farmlands. As a result, a large area of low-yielding farmlands has been abandoned and returned to forests with the implementation of GGP [9,10].
Karst landform shaped by carbonate weathering accounts for 15% area of the Earth’s land surface [11,12]. The karst areas are characterized by high ecological fragility and vulnerability to anthropogenic activities [13,14,15]. Poor quality of karst soils is mainly reflected in thin regolith, high porosity, and uneven distribution, resulting in their weak carrying capacity, flexible migration, and wide distribution of heavy metal pollution [16,17]. Because of the importance of agricultural production to the local area, environmental pollution and assessment have attracted great attention from scientific research and soil management. However, heavy metal behaviors have limited understanding in these regions [16].
Moreover, soil is usually considered as a main cluster of various pollutants in various ecosystems [18]. Human health is easily threatened by heavy metal contamination in soils, especially in agricultural soils, which has aroused an increasing concern in recent years [19,20,21]. For example, Cd has been listed as a carcinogenic metal [3,22], because it can enter the brain neurons and parenchyma through food chains, and cause malfunction of the nervous system, finally affecting memory, attention, and olfactory function [23,24,25]. Agricultural activity is an essential source of heavy metals in soils, not only causing metal enrichment in cropland soils, but also directly influencing the soil physicochemical properties due to the long-term application of chemical fertilizers or manure [17]. Exploring heavy metal behaviors of soils is an essential prerequisite to prevent heavy metals from entering the human body through food chains.
Total metal content is generally used as an indicator for soil pollution, but it cannot reflect the extent of toxicity, mobility, and bioavailability of various metals [26,27]. These characteristics are mainly dependent on the different chemical speciations related to binding between metals and solid phases [28]. Sequential extraction methods can obtain additional and accurate information on metals bound to soil particulates [29]. Both binding sites and binding strength are identified to fully evaluate the ecological risks associated with metals [30,31]. Several sequential extraction methods such as the Community Bureau of Reference (BCR) and Tessier methods have been developed and are mostly employed [32,33]. The BCR method is a more general method for speciation classification of heavy metals, in which heavy metals in soils are divided into residual, acid extractable/exchangeable, reducible, and oxidizable fractions [33], while these fractions can directly reflect the bioavailability and mobility of metals in soils. The modified BCR method has extensive application in sequential extraction of metals from soils, sediment, and sludge samples due to its reliability [34,35,36].
Puding County, a typical karst agricultural area, is located in the center of Guizhou Province in southwest China, with 84% karst area distributed in the county (the area of karst rocky desertification is more than 35%) [12]. Since 2002, many croplands have been abandoned under the GGP to prevent further soil erosion and control desertification [10]. This has provided a unique chance to compare the metal speciation between cropland and abandoned cropland soils and evaluate tillage management effects and the food security crisis. The BCR procedure was performed to research Cr, Ni, Zn, Cd, Fe, and Mn contents and speciation distribution. This work is aimed at understanding the existing forms of metals, assessing the potential risks related to these metals, and evaluating the GGP effects in soil metals. The influence of soil organic carbon (SOC) and total phosphorus (TP) on total metals and their speciation were also investigated to provide fundamental knowledge for ecological environmental protection and land management in the karst regions. We aimed to test the following hypotheses: (1) Cropland and abandoned cropland soils contain a similar total content of heavy metals, but abandoned cropland could have lower bioavailable heavy metals because agricultural activities improve metal mobility in soils, and (2) High SOC content could lead to lower bioavailable heavy metals due to the high absorbability of soil organic matter.

2. Materials and Methods

2.1. Study Area

The study site is located within Chenqi catchment, Puding (26°15′–26°16′ N, 105°46′–105°47′ E, Figure 1), Guizhou province, southwest China. Puding belongs to the subtropical monsoon climate zone with an average precipitation of 1400 mm and a mean annual temperature of 15 °C over the past 20 years [9]. In Chenqi catchment, the dryland covers more than 50%, shrub land covers more than 20%, and paddy land is about 15% [12]. Although the area of cropland in Chenqi catchment is small, it is the typical land use type for agriculture which reflects the basic information of the karst area in southern China. The croplands in Chenqi catchments have been mainly converted from dryland and shrubland [12], but some croplands were abandoned due to the GGP 10 years ago. Soil thickness in this catchment is in the range of 10–160 cm.

2.2. Sampling and Analysis

The selections of cropland (CL) and abandoned cropland (ACL) are shown in the Chenqi catchment (Figure 1) in June 2016. The land-use types, land cover change, and dominant plant species of sampling sites are described in Table 1. Three soil profiles were selected for each land-use type (Figure 1). Soil samples were collected at intervals of 10 cm in the upper 30 cm depth and with intervals of 20 cm from 30 cm depth to the bottom.
An amount of 50 mg soil was weighed in a PTFE jar, and digested using mixed acids (HCIO4, HNO3, and HF) and then heated to dissolve at 120 °C for 24 h [37]. Six metals in the dissolved samples were analyzed on an inductively coupled plasma-atomic emission spectrometer (Optima, Perkin Elmer, Waltham, MA, USA) and with inductively coupled plasma-mass spectrometry (Elan DRC-e, Perkin Elmer, Waltham, MA, USA). The limit of detection was 0.02–0.05 ppb, and the relative standard deviations were lower than 5%. A standard reference substance (GBW07427, the Natural Research Center for Certified Reference Materials, Beijing, China) and procedural blanks were treated to verify the accuracy of analytical procedures [38,39]. The range of recoveries was from 95.8% to 103.3% for the analytes (Cd: 103.3%, Cr: 95.3%, Ni: 95.8%, Zn: 95.6%, Fe: 96.3%, Mn: 98.3%). Soil physicochemical properties including SOC and total phosphorus (TP) were determined according to the methods in our previous study [37,40,41].

2.3. Sequential Extraction

Optimized BCR procedure was applied for the sequential extraction of soil metals [42]. The chemical fractions of heavy metals were classified into acid extractable/exchangeable (F1), reducible (F2), oxidizable (F3), and residual fractions (F4). Method accuracy of the BCR procedure was checked by total concentration of four metal fractions, and the recovery of sequential extraction was calculated with the following equation [43].
Recovery (%) = (CF1 + CF2 + CF3 + CF4)/(C total concentration) × 100
The standard reference substances (GBW07427) were used, with method blanks and duplicate standard reference material performed in the same manner as the samples to verify the accuracy of the BCR procedure. The relative standard deviations of all the metals were less than 10%. Recoveries of the targeted metals were 113.1% for Cd, 102.9% for Cr, 103.1% for Ni, 95.3% for Zn, 91.6% for Fe, and 88.2% for Mn.

2.4. Assessment of Heavy Metal Contamination

2.4.1. Potential Ecological Risk Index

The potential ecological risk index (RI) developed by Hakanson was selected to evaluate the risk of heavy metals [44]. It is an extremely useful and comprehensive approach to evaluate the combined pollution risk in sediments and soils [45,46]. The RI of metals determined in the studied soils was calculated as follows:
R I = ∑ E r i = ∑ T r i C f = ∑ ( T r i × C n B n i )
where E r i represents the monomial potential ecological risk factor, and Cf represents the contamination factor; where Cn is the metal concentration and B n i is the background value of the heavy elements in the soils, respectively. B n i denotes the background value of heavy metals in Cuizhou province (Table S1) [47]. T r i is the biological toxicity factor (i.e., Cd = 30, Ni = 5, Cr = 2, and Zn = 1) [44]. Classifications for RI and E r i are described in Table S2 [46].

2.4.2. Risk Assessment Code

Speciation distribution of heavy metals is an important factor to assess the potential mobility and bioavailability in soils [48]. The risk assessment code (RAC) is one of the widely used indexes [49], which is defined as the exchangeable fraction (F1) related to carbonate fractions. Classifications of RAC are shown in Table S3 [50].

2.4.3. Individual and Global Contamination Factor

The evaluation of the contamination factor of metals is significant in determining the risk degree of these metals to the ecological environment [51]. The individual contamination factors (ICF) were applied to assess the pollution level of a single metal to the ecological environment [52]. The ICF of each sample was calculated as the non-residual fraction divided by the residual fraction, and the non-residual fraction was the sum of F1, F2, and F3. The global contamination factor (GCF) for each sampling site was defined as the total ICF of all the different heavy metals [52]. The GCF represents the comprehensive potential risks bound to the complex influence of metals to the environment. These assessment strategies associated with contamination factors have been used in many studies [30,53]. The classifications of ICF and GCF are described in Table S3 [50].

2.5. Statistics Analysis

The standard deviations of means are presented in some figures as a variability parameter. The cultivation effect on the six targeted heavy metals was compared by one-way ANOVA using the spss 16.0 software package (SPSS Inc., Chicago, IL, USA). Pearson correlation analysis was used to assess the relationship between heavy metals and SOC or TP.

3. Results and Discussion

3.1. Total Soil Heavy Metals

The total concentrations of Cd, Mn, and Fe in surface (0–10 cm) soils of cropland and abandoned cropland exceeded their background values, while Ni and Cr contents were close to their background values, with Zn lower than its background value (Figure 2a). The lower content of Zn may be related to the absorption of plants. Both Fe and Mn, primarily from natural weathering under different land-use types are the major elements in soils [37]. Higher Cd content may be related to heavy metal atmospheric deposition [34].
A distinct pattern of the relative contents for the six heavy metals was observed between cropland and abandoned cropland soils (Figure 2b). The contents of Zn, Cr, Cd, and Mn in cropland soils were significantly higher than those in the soils of abandoned croplands (p < 0.05). Agricultural activity, including chemical usage like fertilization, is likely to cause metal input to the soils because these metals are mainly concentrated in the cultivated layer (0–20 cm). No significant difference was observed in the concentrations of Fe and Ni between the two land-use types (Figure 2b).
Among the soil profiles, Zn, Cr, Cd, Mn, the metals Fe and Ni demonstrated various patterns in both cropland and abandoned cropland (Figure 3). The concentrations of most metals were enriched in the surface soils, and decreased slightly with increasing soil depth at 0–30 cm. The metal contents increased slightly or remained stable with increasing depth beyond 30 cm. The difference of these metal contents between cropland and abandoned cropland was obvious in the upper layer soils, and intensity was not significant in the deeper layers. Surface enrichment is probably derived from deposited atmospheric contamination. Moreover, contaminations are mainly absorbed on the top soils, and then through chemical exchange as well as various disturbances, they are transferred into deeper layers.

3.2. Fractionation of Soil Heavy Metals

A similar pattern of the average percentages of chemical fractions for the six metals was observed in the surface (0–10 cm) soils in both cropland and abandoned cropland (Figure 4). However, the distribution among various metals varied widely. The percentages of residual fractions (F4) for Cr, Ni, Zn, and Fe were the highest fraction and more than 85%, suggesting Cr, Ni, Zn and Fe were bound in a mineral lattice. Mn and Cd were predominantly in non-residual fractions (F1, F2, plus F3), showing these metals were associated with high potential mobility and bioavailability. The average non-residual fractions of Cr, Ni, Zn, and Cd from croplands were slightly higher (<8%) than those from abandoned croplands (Figure 4), suggesting that agricultural activities possibly cause the mobility of metals in soils.
The acid extractable/exchangeable fraction contained more Fe, Mn, and Zn in abandoned cropland and more Ni, Cr, and Cd in cropland (Figure 5a), but it contained relatively little Cr, Fe, Ni, and Zn (less than 2%). This indicates these metals were poorly available in both cropland and abandoned cropland soils. The higher acid extractable/exchangeable Cd in cropland soil was dependent on the current agricultural activity because the accumulation of Cd occurred in cropland soil. Oxidizable heavy metal contents were generally positively related to soil organic matter [20]. Because the SOM in cropland soil was higher than in abandoned cropland, the oxidizable fractions of the six metals were higher in cropland soil. The reducible fraction of the six metal contents was also higher in cropland soil than in abandoned cropland (Figure 5b,c), which was attributed to the higher total metal contents in cropland because of a significant positive relationship between non-residual fraction and total metal content [34].

3.2.1. Cadmium

Cd was predominantly in the non-residual fraction, with 83.6% in cropland soils and 78.1% in abandoned cropland soil. The Cd concentrations in exchangeable fractions of cropland and abandoned cropland soils were 29.9% and 31.1% of the total, respectively. This indicates that the Cd in soils is labile and could be easily absorbed and taken up by living organisms. About one fifth of the Cd was found in oxidizable fraction in both cropland and abandoned cropland soils, which is due to the affinity of Cd for organic matter [37,54]. The dominant fractions were labile or reducible in karst soils, demonstrating potential releasing of Cd under soil pH change or reducing environmental conditions [36].

3.2.2. Iron

Fe is abundant in karst soils, having higher concentrations than the local background value. The residual fraction of Fe in soil was the highest, with about 98% in cropland soil and abandoned cropland soils, suggesting that Fe might have a lower ecological risk due to its low potential mobility compared with the other metals. After the residual fraction, the reducible fraction of Fe was higher than the other fractions, with 1.4% and 1.9% of the total in cropland and abandoned cropland soils, respectively.
Fe oxide is the predominant mineral in karst soils, and Fe is separated from the original minerals and Fe oxide minerals during the weathering process. Fe oxides can be divided into amorphous and crystalline iron oxides, which are released from silicate crystalline minerals, and attributed to karst weathering and soil formation. A previous study showed that Fe plays a dominant role in the geochemical transformation in acid sulfate soils of southern China [17]. However, Fe oxides have low mobility and are not inclined to transform into other speciations in the karst soils of southwest China. This is related to the soil pH with nearly neutral status [37].

3.2.3. Manganese

The distribution of Mn in soils followed a decreasing order of reducible fraction > acid extractable/exchangeable fraction > residual fraction > oxidizable fraction. Mn was found at the highest concentration in the reducible fraction (65.9% in cropland soils and 64.4% in abandoned cropland) than in the other fractions. As a result, Mn in soils was more likely to be released as reducible fraction because the dissolution of Fe-Mn oxides and oxyhydroxides bacterially catalyzed below the surface of sediment leads to the increase of more mobile reduced forms (i.e., Mn2+ and Fe2+) in interstitial waters [55].

3.2.4. Chromium

A large proportion of Cr was found in the residual fractions, with 87.7% in cropland and 90.6% in abandoned cropland. The result indicates that the Cr in the soils was likely immobilized as aluminosilicate minerals and reduced the bioavailability [35]. After the residual fractions, higher concentrations of Cr were found in the oxidizable fractions in cropland and abandoned cropland soils, which could be related to the adsorption of organic matter.

3.2.5. Nickel

Ni existed primarily in the residual fraction, with 91.4% of total fractions in cropland and 93.2% in abandoned cropland, respectively. Therefore, Ni contents in karst soils were primarily immobilized in minerals, and displayed low mobility. The distribution of Ni in the different fractions in karst soils followed the order residual fractions > reducible fraction > oxidizable fraction acid > extractable/exchangeable fraction. The higher reducible fraction of Ni was related to the amorphous Fe/Mn oxides and hydroxides in the soils.

3.2.6. Zinc

Zn was also predominantly in the residual fractions with more than 90% of the total fractions in soils. Accordingly, the mineral lattice of soil accounts for most Zn, indicating Zn is primarily a non-anthropogenic source in the studied areas [56]. After the residual fractions, the fractions of Zn in soils were as follows: reducible fraction > acid extractable/exchangeable fraction > oxidizable fraction. Organic matter could result in the low mobility potential in soil [36].

3.3. Relationship between Metal Content and SOC, TP

SOC and TP concentrations in cropland soils were much higher in abandoned cropland (Figure 6). SOC contents ranged from 14.7 to 37.5 g kg−1 in soil profiles, and decreased with soil depth. The SOC contents were significantly higher in croplands (37.5 ± 11.2 g kg−1) than in abandoned croplands (23.2 ± 6.2g kg−1) [9]. The higher SOC content was caused mainly by organic fertilization in cropland; therefore, the binding of heavy metals can be relatively strong under condition of high SOC content [57]. TP contents in the upper 30 soil depth of croplands were significantly higher than those in abandoned croplands (p < 0.05), which is related to soil management, e.g., application of P-containing fertilizers.
Pearson correlation analysis showed that SOC and TP were significantly positively correlated with Cd and Mn of all the fractions (p < 0.01, Figure 7), indicating that Cd and Mn were greatly influenced by soil nutrients. The exchangeable fraction and oxidizable fraction of Cr were significantly related to SOC and TP (p < 0.01, Figure 7). SOC is characterized by good capacity for metal adsorption, especially for the oxidizable fraction. The oxidizable fraction of Ni and Fe also has very positive relationships with SOC (p < 0.01). All of these relationships explain why the oxidizable fractions of the six metals in cropland soil were higher than those in the abandoned croplands.
Soil organic matter in soils is considered as one of the most important factors in the geochemical behavior of heavy metals. Soil organic matter with strong adsorption ability often significantly affects heavy metal activity by holding the heavy metals [58]. Because there are significant positive correlations between the SOC and the oxidizable fraction (F3) of all the metals (except for Zn), soil organic matter also influences the chemical fractions of heavy metals, especially for the oxidizable fraction. A previous study reported heavy metals in the oxidizable fraction closely related to organic matter could be released or mobilized when the soil environment was in a relative oxidizing condition [22]. The influence of total P on the chemical fractions of heavy metals is similar to SOC in karst soils, which is also related to organic matter. When the humus content in soil is high, and the soil nutrient content increases accordingly, the total phosphorus content is relatively high.

3.4. Assessment of Potential Ecological Risk

3.4.1. Potential Ecological Risk Index

The result of Eri for Cd, Cr, Zn, and Ni from cropland and abandoned cropland in surface soils showed that Eri of Cd, Cr, Ni, and Zn were low (Er < 40), and the Eri values suggested that the pollution degree of metals decreased as follows: Cd > Cr > Ni > Zn (Table 2). The Eri for Cd was the highest with the values ranging from 17.5 to 33.4, and the values in croplands (mean 28.4) were significantly higher (p < 0.05) than those in abandoned croplands (mean 20.7). This means that Cd is considered as a metal with higher potential risk compared to the other five metals. The RI is related to the level of anthropogenic disturbance, and can exhibit low ecological risk (RI < 150) in the studied soils (Table 2). The mean RI values were 33.7 in cropland soils and 25.6 in abandoned cropland, indicating the cropland has a higher potential ecological risk of heavy metals compared to abandoned cropland.

3.4.2. Risk Assessment Code

To better evaluate the mobility and bioavailability of heavy metals in the cropland and abandoned cropland from karst environment, RAC values were calculated for the selected metals (Zn, Cr, Cd, and Ni) in surface soils. Zn, Cr, Fe, and Ni posed no risk or low risk (RAC < 10%, Figure 8), indicating these metals had low bioavailability and mobility in cropland and abandoned cropland soils from the karst environment. It is worth noting Cd performed as a moderate or considerable risk to the environment in both types of soil, but there was no significant difference in risk level between cropland and abandoned cropland soils. The higher mobility of Cd increases the bioaccumulation through food chains, and could lead to potential risks to living organisms and even human health [59].

3.4.3. Individual and Global Contamination Factor

ICF values of Cr, Ni, and Zn were lower than 1 (Figure 9) due to poor mobility of these metals, representing a low environmental risk. By comparison, the Cd ICF values ranged from 2.8 to 6.3 in soils (Figure 9), indicating most soils were a considerable ecological risk for contamination.
GCF was calculated as the sum of the ICF of Zn, Cr, Cd, and Ni and is a speciation index to reflect the general environmental risks of a specific site [50]. GCF values showed low contamination (GCF from 3.2 to 4.3) in abandoned cropland soils, and low or moderate contamination (GCF from 4.6 to 6.7) in cropland soils (Figure 9), Combined with the potential ecological risk index (RI), the contamination and ecological risk of heavy metal in cropland soils was higher than in abandoned cropland.

4. Conclusions

Most heavy metal (i.e., Cr, Zn, Cd, and Mn) contents in cropland soils were significantly higher than those after agricultural abandonment, and these metals were mainly concentrated in the cultivated layer. Human agricultural activities are likely to cause metal inputs to agricultural soils in the karst region. The average non-residual fractions of Cr, Ni, Zn, and Cd from cropland soils were higher than those in abandoned croplands, suggesting that agricultural activities possibly cause the mobility of metals in soils. Soil organic matter greatly affected the mobility and fractionation of metals by facilitating the transfer to oxidizable fractions of metals. Low contamination and ecological risk were found in the Puding karst area, except for considerable Cd contamination in both croplands and abandoned croplands. Pollution risk decreased with agricultural abandonment in the karst region. Our findings suggest that reforestation has effectively alleviated the soil contamination and improved the ecological environment in karst areas. Future studies should focus on the behaviors of heavy metals in various land-use types in karst regions to clarify the evolution of these metals in the soils, and to prevent further contamination of the karst ecosystems.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/f12070891/s1, Table S1: Reference concentrations of heavy metals, Table S2: Grades of environment by potential ecological risk index, Table S3: Classification of contamination.

Author Contributions

Conceptualization, G.H.; methodology, G.H.; validation, writing—original draft preparation, Q.Z.; writing—review and editing, Q.Z.; visualization, X.X.; supervision, G.H.; funding acquisition, G.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Natural Science Foundation of China, grant number 41325010 and 41661144029.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

The authors gratefully acknowledge Man Liu for field sampling and laboratory assistance.

Conflicts of Interest

The authors declare no conflict of interest.

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Forests 12 00891 g001 550
Figure 1. Location of Puding area and sampling sites. C1, C2, C3: cropland, A1, A2, A3: abandoned cropland with reforestation.
Figure 1. Location of Puding area and sampling sites. C1, C2, C3: cropland, A1, A2, A3: abandoned cropland with reforestation.
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Figure 2. Relative average content changes in 0–10 cm layer soils of cropland (CL) and abandoned cropland (ACL). (a) The six metals normalized to the reference soils (=1.0); (b) The six metals normalized to the mean contents (=1.0) of cropland and abandoned cropland. Reference: background value of Guizhou soil [47].
Figure 2. Relative average content changes in 0–10 cm layer soils of cropland (CL) and abandoned cropland (ACL). (a) The six metals normalized to the reference soils (=1.0); (b) The six metals normalized to the mean contents (=1.0) of cropland and abandoned cropland. Reference: background value of Guizhou soil [47].
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Figure 3. Vertical distribution of the six metals in soil profiles under croplands and abandoned croplands. The values are mean ± SD of three replicates.
Figure 3. Vertical distribution of the six metals in soil profiles under croplands and abandoned croplands. The values are mean ± SD of three replicates.
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Figure 4. The average percentage of metal speciation in surface (0–10 cm) soils from cropland (a) and abandoned cropland (b) using the BCR method.
Figure 4. The average percentage of metal speciation in surface (0–10 cm) soils from cropland (a) and abandoned cropland (b) using the BCR method.
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Figure 5. Relative metal speciation (F1, F2and F3) contents in 0–10 cm layer soils of cropland and abandoned cropland. (a): acid extractable/exchangeable fraction (F1), (b): reducible fraction (F2), (c): oxidizable fraction (F3). The six metals are normalized to the mean contents. Reference: the mean value of croplands and abandoned cropland soils.
Figure 5. Relative metal speciation (F1, F2and F3) contents in 0–10 cm layer soils of cropland and abandoned cropland. (a): acid extractable/exchangeable fraction (F1), (b): reducible fraction (F2), (c): oxidizable fraction (F3). The six metals are normalized to the mean contents. Reference: the mean value of croplands and abandoned cropland soils.
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Figure 6. The contents of SOC (a) and TP (b) in the soil profiles under croplands and abandoned croplands. The values are shown as mean ± SD of three replicates.
Figure 6. The contents of SOC (a) and TP (b) in the soil profiles under croplands and abandoned croplands. The values are shown as mean ± SD of three replicates.
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Figure 7. Pearson correlation between metal speciation and SOC or TP (n = 30); ** p < 0.01; * p < 0.05; F1, F2 and F3 represents the different metal fraction.
Figure 7. Pearson correlation between metal speciation and SOC or TP (n = 30); ** p < 0.01; * p < 0.05; F1, F2 and F3 represents the different metal fraction.
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Figure 8. The RAC of studied metals in soils from abandoned cropland (A1, A2, and A3) and cropland (C1, C2 and C3).
Figure 8. The RAC of studied metals in soils from abandoned cropland (A1, A2, and A3) and cropland (C1, C2 and C3).
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Figure 9. The individual (ICF) and global contamination factor (GCF) in the surface soils (0–10 cm) from abandoned cropland (A1, A2, and A3) and cropland (C1, C2, and C3).
Figure 9. The individual (ICF) and global contamination factor (GCF) in the surface soils (0–10 cm) from abandoned cropland (A1, A2, and A3) and cropland (C1, C2, and C3).
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Table
Table 1. The description of land cover changes and dominant plant species in cropland and abandoned cropland.
Table 1. The description of land cover changes and dominant plant species in cropland and abandoned cropland.
Land Use TypeLand Cover ChangeDominant Plant Species
Cropland (CL)Long-term cultivation and mixed application of compound fertilizer and manureZea mays; Houttuynia cordata; Allium fistulosum; Ipomoea batatas
Abandoned cropland (ACL)Abandoned cropland for over 5 years and evolving into grassland or shrublandChrysopogon aciculatus; Artemisia lavandulaefolia; Potentilla reptans
Table
Table 2. Heavy metal potential ecological risk indexes in surface (0–10 cm) soils of cropland and abandoned cropland.
Table 2. Heavy metal potential ecological risk indexes in surface (0–10 cm) soils of cropland and abandoned cropland.
Sampling SiteEr (Zn)Er (Ni)Er (Cr)Er (Cd)RI
A10.762.22.217.522.6
A20.792.11.924.429.2
A30.731.91.920.424.9
C10.911.92.033.438.2
C20.892.12.124.529.7
C30.922.52.527.433.3
A indicates abandoned cropland; C indicates cropland.
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Zhang, Q.; Han, G.; Xu, X. Reforestation Impacted Soil Heavy Metal Fractionation and Related Risk Assessment in the Karst Area, Southwest China. Forests 2021, 12, 891. https://doi.org/10.3390/f12070891

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Zhang Q, Han G, Xu X. Reforestation Impacted Soil Heavy Metal Fractionation and Related Risk Assessment in the Karst Area, Southwest China. Forests. 2021; 12(7):891. https://doi.org/10.3390/f12070891

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Zhang, Qian, Guilin Han, and Xingliang Xu. 2021. "Reforestation Impacted Soil Heavy Metal Fractionation and Related Risk Assessment in the Karst Area, Southwest China" Forests 12, no. 7: 891. https://doi.org/10.3390/f12070891

APA Style

Zhang, Q., Han, G., & Xu, X. (2021). Reforestation Impacted Soil Heavy Metal Fractionation and Related Risk Assessment in the Karst Area, Southwest China. Forests, 12(7), 891. https://doi.org/10.3390/f12070891

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