Screening Dominant Species and Exploring Heavy Metals Repair Ability of Wild Vegetation for Phytoremediation in Copper Mine

Abstract

Phytoremediation, a sustainable approach, is a hot topic, particularly for harsh mining environments. The Baiyin copper mine, a typical example of massive sulfide deposits, retains value as a national park after closure. Our research on it aimed to explore phytoremediation. By studying the plant community’s phyto-sociological attributes, we found that plants maintained long-term stability, with restoration potential. And the top-level dominant species, Lycium chinense and Nitraria tangutorum, were selected as candidate repair plants based on importance value. Then, we assessed soil heavy metals using pollution indices and found that Pb, As, and Cd were the primary contributors, along with Cu and Zn, causing pollution. Next, we determined the repair ability of two candidate repair plants through their accumulation effect and transport efficiency, finding that both had strong tolerance to these heavy metals and accumulated similar amounts, except for Cu, which was slightly lower than expected; however, Lycium compensated for this with its higher Cu conversion rate, leading to its final recommendation. Lycium has an uncommon advantage: during extraction of active ingredients, it can remove heavy metals as impurities, preserving economic value. This discovery provides the idea, theoretical basis, and pioneer plant for the phytoremediation of sulfide deposits like the Baiyin copper mine, particularly in northwestern China’s mining regions.

1. Introduction

Mining inevitably results in heavy metal leakage [1]. Heavy metals usually damage the physicochemical properties of soil, leading to environmental degradation, and they can even be transported and accumulated in plants and animals, causing chain hazards [2]. The repair of heavy metal contamination has been widely researched up to now [3].

There are chemical, physical, and biological methods for repairing soil from heavy metals [4]. Between them, the chemical repair methods involve secondary pollution and are environmentally unfriendly; physical repair methods involve breaking the ground, with high costs; so, still now, biological repair methods are the best way for repairing soil contaminated by heavy metals, with advantages such as environmental protection and low costs [4]. Phytoremediation, a mainstream biological repair method, uses the ability of plants to optimize soil conditions, thereby improving the soil environment [5].

Phytoremediation has identified many hyperaccumulators capable of absorbing and accumulating large amounts of heavy metals, but they are not suitable for use in all environments [6]. In particular, the soil of mining areas usually has many issues, such as nutrient deficiency, extreme pH, poor fertilizer and water-holding capacity, and excessive heavy metals, which make it difficult for plants to survive [7]. The solution found by scientists is selecting dominant species from native plants [8]. Only a few plants are able to survive in the harsh environment, and the best of them are able to occupy an advantage in the community and then become the native dominant species [9]. Domestication in harsh environments enables them to better resist stress, and they can absorb and accumulate heavy metals in themselves, thereby removing heavy metals from contaminated soil [10]. In addition, they can reduce the risk of heavy metals leaching into the adjacent environment by stabilizing soil and water through their roots [9]. At the same time, they can also improve environmental conditions through secreting compounds to regulate soil pH, increase essential nutrients for soil biota, and promote the survival of microorganisms beneficial to plant growth [8]. Nowadays, native dominant plants are considered keys to the phytoremediation of soil with heavy metals, especially in mining areas [11], and are often used as pioneer plants [12].

In this study, we selected the Baiyin copper mine as the object of investigation, aiming to analyze the plant community and identify pioneer species for the phytoremediation of mines with similar situations. The Baiyin copper mine represents a typical massive sulfide deposit [13,14], characterized by high Cu content and the co-occurrence of economically valuable elements such as Pb, Zn, Au, and Ag alongside other elements with limited economic value such as As and Cd [13,14,15]. This type of deposit holds significant industrial importance for Cu production and is one of the four major deposit types serving as primary sources of Cu globally, with a wide distribution [13,14,15]. For example, in the northwestern provinces of China, in addition to the Baiyin copper mine in Gansu, there are the Ashele deposit in Xinjiang [16], the Xitieshan deposit in Qinghai [17], the Erlihe deposit in Shaanxi [18], and others. The mining and processing of such deposits pose significant environmental challenges. S from the ore readily oxidizes to produce acidic conditions [19], and acid leaching during ore beneficiation exacerbates environmental acidification [20]. Extreme pH makes the phytoremediation of heavy metals in this type of deposit extremely challenging. The Baiyin copper mine, with a long history of exploitation, exemplifies these challenges. Its mining for Ag began as early as the Han dynasty, with the “Baiyin” part of its name derived from the Chinese pronunciation of Ag, and mining for Cu started after the establishment of the People’s Republic of China, with the “copper” part of its name referring its status as the largest Cu-producing mine in China at the time [13,21]. During production, the mining operation employed open-pit mining and acid leaching processes [12,20]. The mining environment is acidic [20], with heavy metals which even disperse into the surrounding areas. Existing studies have conducted tests for Pb, Cu, Zn, and Cd in the water and sediments of rivers surrounding this mine, revealing that their concentrations exceed standard limits [22]. And existing studies have also conducted tests for Pb, As, Cu, Zn, and Cd in the plough layers and the cultivated crops surrounding this mine, revealing that their concentrations exceed standard limits [21,23,24]. Next to it, Baiyin city (also known as the copper city), which developed from the miners’ settlement of this mine, also revealed excessive levels of Pb, As, Cu, Zn, and Cd [25,26]; part of their sources pointing to this mine [26]. These contaminants have been linked to changes in sperm motility and genetic characteristics in local animals [27,28], as well as an increased cancer risk among local children [29]. However, most existing research related to the Baiyin copper mine or other massive sulfide deposits has focused on contaminants and their impact on the environment or organisms, with a lack of studies on phytoremediation. The main objectives of this study are: (1) to assess the heavy metals and physicochemical properties of the soil; (2) to research the composition, structure, and diversity of the plant community; (3) to screen top-level dominant species with the greatest potential for repair; (4) to select the best plant as a pioneer plant with a good heavy-metals accumulation effect and transport efficiency suitable for phytoremediation. The findings are expected to provide a reliable idea, theoretical basis, and plant resource for phytoremediation of this mine and other massive sulfide deposits with similar climate and soil conditions, such as those located in the northwestern provinces of China.

2. Materials and Methods

2.1. Study Area and Quadrat Setting

The Baiyin copper mine belongs to the metamorphic volcanic rock series in the eastern part of the North Qilian Caledonian fold belt [14]. It is a polymetallic sulfide deposit, which is also a typical example of a massive sulfide deposit on a global scale [13,14]. This mine began extraction in 1956 and closed in 1988. During production, the mining operation employed open-pit mining and acid leaching processes [13,20]. These processes, along with the associated sites and solid waste, were distributed around the mine pit, leading to severe environmental degradation in the surrounding area. And, after its closure, this abandoned copper mine was set by China as one of the first national mining parks for decades. However, due to pollution, the vegetation in this area is sparse compared to the situation recorded in the “Flora of Gansu” [30] and the “Baiyin City Territorial Spatial Master Plan (2021–2035)” [31], with no invasive species present.

We conducted a study on this abandoned mine. The site is 104°12′54″ E–104°14′10″ E, 36°38′11″ N–37°39′54″ N; its area is 10.95 km², altitude is 1800–2000 m, average annual temperature is 8.5 °C, average annual precipitation is 204.3 mm, average annual sunshine hours are 2537.2 h, and average annual frost-free period is 183.8 d. It belongs to the narrow temperate continental climate, and its typical communities are herbs and shrubs [32,33].

This study was conducted in early September to facilitate the collection of fruits. As there are no trees, only shrubs and herbs grow there. So, 15 quadrats (see Figure 1) were set for both shrubs and herbs. And the quadrats were kept at 3.15 m × 3.15 m and randomly selected and evenly distributed. Plant community in each sample was measured based on composition (of family, genus, and species) and structure (which included quantity, cover, height, and frequency) [34].

2.2. Collection and Processing of Soil and Plants

Each quadrat collected 5–20 cm of soil with the five-point method. The soil was dried naturally. The dried soil was sieved to remove stones, plant remains, and animal debris. The fraction passing through a 60-mesh sieve was used for pH determination, while the fraction passing through a 200-mesh sieve was used for the determination of the total amount of C, N, Na, K, Ca, and heavy metals (Pb, As, Cu, Zn, Cd). And each quadrat collected fruits of every plant species, and the fruits were washed with distilled water, then dried naturally and crushed, for determination of the total amount of heavy metals (the elements being the same as for the soil).

Soil pH was measured at the soil–water interface using a pH meter (PH400, Alalis, China) after mixing the soil and water at a ratio of 2.5:1, followed by stirring and settling [35]. The assay of the total C and total N in the soil was by elemental analyzer (Elementar vario EL cube, Elementar, Germany) [36]. The assay of the total amount of Na, K, Ca in the soil and heavy metals in the soil and fruits was by microwave digestion instrument (MD, ETHOS UP, Milestone, Italy) and inductively coupled plasma optical emission spectrometer (ICP-OES, PE Avio 500, PerkinElmer, America) [37]. In MD, the soil was digested with a HNO₃-H₂O₂-HF system at a ratio of 1:4:2; the fruits were digested with a HNO₃-H2O₂ system at a ratio of 1:4. The digestion procedure was as follows: the temperature was increased to 140 °C over 5 min and held for 2 min, then increased to 190 °C over 8 min and held for 2.5 min, followed by an increase to 220 °C over 8 min and maintained for 20 min. Prior to analysis of ICP-OES, the digestion solutions were evaporated to 1 mL at high temperature to remove the acid and then diluted to a constant volume.

2.3. Plant Community Status and Dominant Species Analysis

In stressful environment, when the plant community was stable, top-level dominant species would be the most stable and have environmental resistibility which could be used for environmental repair [33]. By combining the structure and diversity (Margalef index, Shannon–Wiener index, Simpson index, Pielou index) of the plant community, the community status of the plants would be understood [34]. The structure of the plant community was counted in the sample. The diversity of the plant community was obtained through statistical analysis.

The calculation method for diversity was as follows [38,39,40,41]:

$$\mathrm{M}\mathrm{a}\mathrm{r}\mathrm{g}\mathrm{a}\mathrm{l}\mathrm{e}\mathrm{f} \mathrm{i}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{x}=(\mathrm{S}-1)/\mathrm{l}\mathrm{n}\mathrm{N}$$

(1)

$$\mathrm{S}\mathrm{h}\mathrm{a}\mathrm{n}\mathrm{n}\mathrm{o}\mathrm{n}–\mathrm{W}\mathrm{i}\mathrm{e}\mathrm{n}\mathrm{e}\mathrm{r} \mathrm{i}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{x}=-{\sum }_{\mathrm{i}=1}^{\mathrm{S}}\left({\mathrm{P}}_{\mathrm{i}}\mathrm{l}\mathrm{n}{\mathrm{P}}_{\mathrm{i}}\right)$$

(2)

$$\mathrm{S}\mathrm{i}\mathrm{m}\mathrm{p}\mathrm{s}\mathrm{o}\mathrm{n} \mathrm{i}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{x}=1-{\sum }_{\mathrm{i}=1}^{\mathrm{s}}{\displaystyle \frac{{\mathrm{N}}_{\mathrm{i}}\left({\mathrm{N}}_{\mathrm{i}}-1\right)}{\mathrm{N}\left(\mathrm{N}-1\right)}}$$

(3)

$$\mathrm{P}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{o}\mathrm{u} \mathrm{i}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{x}=-{\sum }_{\mathrm{i}=1}^{\mathrm{S}}\left({\mathrm{P}}_{\mathrm{i}}\mathrm{l}\mathrm{n}{\mathrm{P}}_{\mathrm{i}}\right)/\mathrm{l}\mathrm{n}\mathrm{S}$$

(4)

where S is the number of species; N_i is the individual number of i species; N is the total individual number of all species; P_i = N_i/N is proportion of individual numbers for i species.

Then, the importance value could be used for selecting the top-level dominant species when the plant community was stable.

The calculation method for importance value was as follows [42]:

$$\mathrm{P}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{t} \mathrm{i}\mathrm{m}\mathrm{p}\mathrm{o}\mathrm{r}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{c}\mathrm{e} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e}={\displaystyle \frac{\mathrm{R}\mathrm{e}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{e} \mathrm{a}\mathrm{b}\mathrm{u}\mathrm{n}\mathrm{d}\mathrm{a}\mathrm{n}\mathrm{c}\mathrm{e}+\mathrm{R}\mathrm{e}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{e} \mathrm{f}\mathrm{r}\mathrm{e}\mathrm{q}\mathrm{u}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{y}+\mathrm{R}\mathrm{e}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{e} \mathrm{d}\mathrm{o}\mathrm{m}\mathrm{i}\mathrm{n}\mathrm{a}\mathrm{n}\mathrm{c}\mathrm{e}}{3}}$$

(5)

where relative abundance is the percentage of a species’ individual number to the total species number; relative frequency is the percentage of a species’ quadrat number to the total quadrat number; relative dominance, which is replaced by relative cover, is the percentage of a species’ cover to the total species cover.

2.4. Heavy Metals Status Analysis

Existing studies had shown that the heavy metals pollution released from this mine were primarily Pb, As, Cu, Zn, and Cd [21,22,23,24,25,26]. Their concentrations in the soil were directly compared with national standards to determine whether they exceed the limits. Furthermore, pollution indices (Nemerow integrated pollution index and single-factor pollution index) were calculated to assess their environmental impact. They collectively illustrated the situation of heavy metals in the environment.

The Nemerow integrated pollution index method could be used for evaluating the overall environmental pollution situation.

The calculation method for the Nemerow integrated pollution index was as follows [43]:

$$\mathrm{N}\mathrm{e}\mathrm{m}\mathrm{e}\mathrm{r}\mathrm{o}\mathrm{w} \mathrm{i}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{g}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{d} \mathrm{p}\mathrm{o}\mathrm{l}\mathrm{l}\mathrm{u}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n} \mathrm{i}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{x}=\sqrt{\left({\mathrm{P}}_{\mathrm{m}\mathrm{a}\mathrm{x}}^2{+\mathrm{P}}_{\mathrm{a}\mathrm{v}\mathrm{g}}^2\right)/2}$$

(6)

where P_max is the maximum value among the individual pollution indices of all the pollutants; P_avg is the average value of the individual pollution indices of all the pollutants; and the individual pollution index is obtained by dividing the measured concentration of the pollutant by its environmental background concentration. If the value is greater than 3, the environment is classified as severe pollution; if the value is between 2 and 3, it is classified as moderate pollution; if the value is between 1 and 2, it is classified as light pollution; if the value is between 0.7 and 1, it is classified as a warning level; and if the value is below 0.7, it is classified as safe.

The single-factor pollution index method could be used for evaluating the contribution of a single heavy metal element to the overall environmental pollution situation.

The calculation method for the single-factor index was as follows [43]:

$$\mathrm{S}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{l}\mathrm{e}-\mathrm{f}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{o}\mathrm{r} \mathrm{p}\mathrm{o}\mathrm{l}\mathrm{l}\mathrm{u}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n} \mathrm{i}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{x}={\displaystyle \frac{\mathrm{m}\mathrm{e}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{c}\mathrm{o}\mathrm{n}\mathrm{c}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n} \mathrm{i}\mathrm{n} \mathrm{s}\mathrm{o}\mathrm{i}\mathrm{l} \mathrm{o}\mathrm{f} \mathrm{s}\mathrm{t}\mathrm{u}\mathrm{d}\mathrm{y} \mathrm{a}\mathrm{r}\mathrm{e}\mathrm{a}}{\mathrm{m}\mathrm{e}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{c}\mathrm{o}\mathrm{n}\mathrm{c}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n} \mathrm{i}\mathrm{n} \mathrm{s}\mathrm{o}\mathrm{i}\mathrm{l} \mathrm{o}\mathrm{f} \mathrm{e}\mathrm{n}\mathrm{v}\mathrm{i}\mathrm{r}\mathrm{o}\mathrm{n}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{b}\mathrm{a}\mathrm{c}\mathrm{k}\mathrm{g}\mathrm{r}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{d}}}$$

(7)

where if the value is greater than 3, this factor is classified as severe pollution; if the value is between 2 and 3, it is classified as moderate pollution; if the value is between 1 and 2, it is classified as light pollution; and if the value is below 1, it is classified as safe.

The results of the survey conducted by China’s Environmental Protection Agency in 1990 showed that the soil environmental background values of Pb, As, Cu, Zn, and Cd in Gansu Province were 18.8, 12.6, 24.1, 68.5, and 0.116 mg/kg, respectively [44].

2.5. Plant Repair Ability Analysis

Fruit, one of the annual organs of plant, was used to reflect the status of plant in the current year. The accumulation effect and transport efficiency of heavy metals in fruits of plants were used to set out the relationship between plants and soil and measure plants heavy metals repair ability [45].

The accumulation effect of heavy metals in plants, representing the aggregation degree of heavy metals in plants, was measured by the concentrations of heavy metals in the fruits [45].

The transport efficiency of heavy metals in plants, representing the conversion rate to heavy metal in plants, was measured by the fruits’ transfer coefficient of heavy metals [46].

The calculation method for the transfer coefficient was as follows [46]:

$$\mathrm{T}\mathrm{r}\mathrm{a}\mathrm{n}\mathrm{s}\mathrm{f}\mathrm{e}\mathrm{r} \mathrm{c}\mathrm{o}\mathrm{e}\mathrm{f}\mathrm{f}\mathrm{i}\mathrm{c}\mathrm{i}\mathrm{e}\mathrm{n}\mathrm{t}={\displaystyle \frac{\mathrm{m}\mathrm{e}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{c}\mathrm{o}\mathrm{n}\mathrm{c}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n} \mathrm{i}\mathrm{n} \mathrm{f}\mathrm{r}\mathrm{u}\mathrm{i}\mathrm{t}}{\mathrm{m}\mathrm{e}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{c}\mathrm{o}\mathrm{n}\mathrm{c}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n} \mathrm{i}\mathrm{n} \mathrm{s}\mathrm{o}\mathrm{i}\mathrm{l}}}$$

(8)

2.6. Data Processing and Statistical Analyses

Mapping was performed through AcrGIS 10.8. Analyses of the data were performed through Excel 2019 (means and analysis of variance). The generation of graphs was performed through Origin 2019.

Before proceeding with the statistical analysis, an outlier analysis was conducted on the samples. Each quadrat value was within the range of the mean ± three times the standard deviation, and no samples were removed.

3. Results

3.1. Plant Community’s Phyto-Sociological Attributes (Composition, Structure, and Diversity)

To obtain a preliminary understanding of the plant community situation, the composition of the plant community was analyzed from the perspectives of morphology and taxonomy.

In relation to morphology, the plants belonged to nine families, eleven genera, and eleven species (see Figure 2). They were all recorded in the “Flora of Gansu” [30]. So, all species were local plants, with no exotic plants. As the mine closed in 1988, plants freely grew there for several decades. The absence of exotic plants after such a long time meant that the plant community in the study area had strong exclusivity, leading to a stable localization. At the same time, we also found that, except for Reaumuria and Tamarix, which belonged to Tamaricaceae, and Kochia and Halogeton, which belonged to Chenopodiaceae, other genera belonged to separate families. Even so, there were only nine families, eleven genera. The Baiyin municipal government clearly stated that the city is home to hundreds of species of wild plants, including 115 species with medicinal properties which belong to 39 families and 92 genera [31]. Compared with the natural vegetation in Baiyin City, the species of the plants in the study area were fewer. This indicated that the environment of the study area was not suitable for exotic plants, and there were few local plants that could adapt to it, which ultimately led to sparse vegetation.

In relation to taxonomy, there were four shrubs and seven herbs among the plants (see Figure 2). The climate of Baiyin only supported the growth of herbs and shrubs. The presence of shrubs suggested that the growth of plants at the top level was still supported. This indicated that the scarcity of plant species did not originate from the uniqueness of the region’s climate, given that any climatic changes would initially impact the survival of plants at the top level, but was instead attributed to the pollution caused by mining.

All these results indicated that the climate inherently restricted plant growth, leading to the elimination of trees, while pollution further exacerbated this situation, making it impossible for exotic plants to colonize and limiting the number of native plant species that could colonize. We all know that the harsh environmental conditions make repair plants sourced from this environment more likely to successfully adapt to this environment after replanting, compared to those sourced through other means. Therefore, it was suitable to try screening plants for repair from within the environment in this study. Meanwhile, because there were only shrubs and herbs, the data of plants were integrated by community level, such as shrubs and herbs, in this study.

Before screening repair plants, it was necessary to understand the stability of the plant community. When the plant community is stable, the plants within the community could exist in the environment for a long time, thus exhibiting long-term repair effects after replanting. To analyze the stability of the plant community, the characteristics of the plant community were analyzed in terms of structure and diversity.

Structure, as part of sociological attributes of the plant community, was analyzed based on height, cover, occurrence frequency, and individual number. The results (see Figure 3a) showed that, in the study area, there were 133 plants with 44.91 m height and 61.66 m² cover; then, herbs had higher values in individual number and occurrence frequency than shrubs, but herbs had lower cover and height than shrubs.

Diversity, as part of ecological attributes of the plant community, was analyzed using the Margalef index, Shannon–Wiener index, Simpson index, and Pielou index. The results (see Figure 3b) showed the following: (1) The Margalef index measures species richness and is directly proportional to it [38]. The value of this item was greater for herbs than for shrubs, so the species richness of herbs was higher. (2) The Shannon–Wiener index measures species variety and is directly proportional to it [39]. It is sensitive to changes in species abundance, and even changes in the abundance of rare species can be reflected [39]. The value of this item was greater for herbs than for shrubs, so the species variety of herbs was higher, reflecting both greater species richness and more even distribution of species. (3) The Simpson index also measures species variety and is inversely proportional to it [40]. The abundance of dominant species has a greater impact on the Simpson index [40]. The value of this item was smaller for herbs than for shrubs, so the species variety of herbs was higher, reflecting the herb community was less dominated by a single species. (4) The Pielou index measures species evenness and is directly proportional to it [41]. The value of this item was greater for herbs than for shrubs, so the species evenness of herbs was higher. Summarizing the community diversity performance, the diversity of herbs was larger than that of shrubs.

All these results indicated the characteristics of the plant community in the study area. This indicated that, although shrubs, as the top-level plants, were relatively few in number, they have developed larger sizes capable of providing greater coverage than herbs, suggesting that the top-level plants had existed for a long time and the community had reached a stable state. Therefore, plants in the study area with stable stress-resistance could be used for repair.

3.2. Screening Dominant Species of the Top Level as Candidate Plants for Repair

Due to the fact that the top level had more advantages in succession and could exist for a long time, the dominant species were selected from the top level based on their importance values to obtain repair plants. The results (see Figure 4) showed that the values of importance value for Lycium and Nitraria were 20~30% higher than that of other species, so they were preliminarily screened as candidate plants for repair.

3.3. Verifying Repair Abilities of Candidate Plants for Further Screening

3.3.1. Heavy Metals Status

To understand the heavy metals that need to be repaired, we assessed the soil by measuring and evaluating their concentrations. And other related influencing factors in the soil were measured.

Heavy metals (Pb, As, Cu, Zn, and Cd) were measured in the mine soil. The result (see Figure 5) showed that concentrations of Pb, As, Cu, Zn, and Cd decreased sequentially, and concentrations of Pb and As exceeded the limits set by the Chinese government (GB 15618-1995 [47]). The specific stress caused by heavy metals required further calculation.

The concentrations of heavy metals in the soil from the study area, combined with the soil environmental background values, were used to assess heavy metal pollution in the environment through the Nemerow integrated pollution index method and the single-factor index method. The soil background values were based on the survey results conducted by the China Environmental Protection Agency in 1990 [44]. By calculation, the Nemerow integrated pollution index of the environment was 15.22, which was greater than 3, indicating an environment with severe heavy metals pollution. And the single-factor index of Pb was 20.574; As was 8.067; Cu was 0.389; Zn was 0.085; Cd was 2.500. All values of the single-factor index of Pb and As were greater than 3, indicating they were severe pollution factors for the environment. The values of the single-factor index in Cd were greater than 2, indicating it was moderate pollution factor for the environment. Therefore, the environment had suffered significant pressure from heavy metals. Although the concentrations of Pb and As were relatively high and exceeded national standards, the main pollution factors came not only from Pb and As but also from Cd.

Other related influencing factors were measured from soil physicochemical properties, and the results are shown in

Table 1. Physicochemical properties of soil.

	pH	Macronutrients Required for Biological Growth (%)
		Total C	Total N	Total Na	Total K	Total Ca
quadrat 1	2.11	0.221	0.015	0.378	0.862	1.998
quadrat 2	2.27	0.237	0.011	0.284	0.987	2.055
quadrat 3	2.24	0.219	0.023	0.321	0.793	1.947
quadrat 4	2.23	0.321	0.029	0.392	0.955	1.973
quadrat 5	2.29	0.219	0.021	0.276	0.996	2.131
quadrat 6	2.25	0.235	0.013	0.312	0.834	2.056
quadrat 7	2.22	0.231	0.007	0.345	0.902	2.089
quadrat 8	2.28	0.234	0.052	0.291	1.143	1.791
quadrat 9	2.35	0.228	0.012	0.303	0.812	1.984
quadrat 10	2.24	0.196	0.025	0.377	0.965	2.099
quadrat 11	2.26	0.239	0.038	0.349	0.708	1.926
quadrat 12	2.23	0.233	0.031	0.279	0.932	2.092
quadrat 13	2.37	0.233	0.002	0.354	0.875	1.858
quadrat 14	2.25	0.236	0.063	0.318	1.001	1.962
quadrat 15	2.11	0.133	0.006	0.301	0.844	1.808
mean value	2.25 ± 0.069	0.23 ± 0.037	0.02 ± 0.017	0.33 ± 0.038	0.91 ± 0.106	1.98 ± 0.106

. In comparison with the soil environmental background values of soil elements in Gansu [44], we found soil in the study area with an extreme pH and poor macronutrients required for biological growth, which would release higher levels of toxicity from heavy metals and hinder soil self-repair. Therefore, the danger of heavy metals had been amplified.

All these results indicated that heavy metals needed to be repaired, especially Pb, As, and Cd. Then, the repair performance of Lycium and Nitraria for heavy metals in the environment needed to be quantified.

3.3.2. Accumulation Effect and Transport Efficiency for Verification

The heavy metals repair ability of plants has two parts: the amount and rate of accumulation of heavy metals. In this study, in order to assess the repair abilities of the screened plants, the accumulation effect and transport efficiency based on annual performance were utilized to explain the relationship between the plants and soil. Although the accumulation of the same heavy metal varies among different plant organs, the preference for different heavy metals was consistent across organs. An organ could reflect the overall accumulation characteristics of the plant. Therefore, selecting fruit from the annual organs as measurement site would reflect the plant’s annual performance.

The accumulation effect was measured by the concentrations of heavy metals in fruits. The results (see Figure 6) showed the following: (1) The concentrations of Pb and Cu in the fruits of Lycium were slightly higher than in Nitraria, while the concentration of As in the fruits of Lycium was slightly lower than in Nitraria, and the concentrations of Zn and Cd in the fruits of Lycium and Nitraria were basically the same. (2) The concentrations of Pb and As in the fruits of Lycium and Nitraria were both above the Chinese government limits (GB 2762-2012 [48]). And the concentrations of Cu, Zn, and Cd in the fruits of Lycium and Nitraria were all below the Chinese government limits (Gb 15199-1994 [49], GB 13106-1991 [50], GB 2762-2012 [48]) but higher than those grown in an uncontaminated environment. (3) In the fruits of both Lycium and Nitraria, the concentrations of Pb, As, Zn, Cu, and Cd decreased sequentially. Except for Cu, the trend in the content of these heavy metals in the fruits was the same as that in the soil.

Summarizing the results, we found the following: (1) Due to the limitation of soil heavy metal concentrations, we did not know the numerical values of the accumulation limits for heavy metals in Lycium and Nitraria. But we could observe that both Lycium and Nitraria demonstrated strong tolerance when exposed to a large amount of heavy metals, as evidenced by the higher accumulation of these heavy metals in them. So, the repair ability of Lycium and Nitraria met the requirements for remediation in the current soil. (2) Accumulations of heavy metals in Lycium and Nitraria were similar and roughly proportional to the abundance of heavy metals in the soil. This meant that, when the amounts of heavy metals had not reached their saturation in Lycium and Nitraria their removal amounts in Lycium and Nitraria were roughly proportional to their respective contents in the soil. And Lycium and Nitraria would yield similar repair performances if they were used for repairing the ruin of the Baiyin mine. (3) The concentrations of heavy metals in the soil followed the order Pb > As > Cu > Zn > Cd, whereas, in both Lycium and Nitraria, the order was Pb > As > Zn > Cu > Cd. So, the accumulation of Cu plants in was slightly lower than expected. And Cu is more difficult to repair than other heavy metal elements for both Lycium and Nitraria, thus requiring extra attention for its repair.

All these results indicated that the accumulation effects of Lycium and Nitraria were limited by the concentrations of heavy metals in the current soil; only the accumulations of Pb and As had to be seen as good, but the accumulations for Cu, Zn, and Cd still had room for development. So, both Lycium and Nitraria were tolerant to Pb, As, Cu, Zn, and Cd, and could be used for these heavy metals’ repair in this abandoned copper mine. And, if used, Lycium and Nitraria would have similar repair performances for these heavy metals. Moreover, in the study area, Cu was more difficult to repair in Lycium and Nitraria than expected, thus requiring extra attention for its repair.

Transport efficiency was used in further analysis to get more information on the repair abilities of the plants. Transport efficiency was measured by the concentration ratio of the heavy metals in the fruits to the soil. The results (see Figure 7) showed that the transfer efficiency in fruits of Lycium and Nitraria followed the order Zn > Cu > Cd > Pb ≈ As, and all remained above 0.01. Notably, the transfer efficiency of Lycium for Cu was significantly higher than that of Nitraria. We all know that fruits have the lowest accumulations of heavy metals among the various plant organs. In existing studies, a transfer efficiency of fruits higher than 0.01 indicated that heavy metals were easily accumulated from soil to plants. Despite this, we did not know the numerical values of the accumulation limits for heavy metals in Lycium and Nitraria; this excellent transfer efficiency indicated that, before these limits were reached, the accumulations of these heavy metals in Lycium and Nitraria would increase rapidly. All these results indicated that Lycium and Nitraria both had good efficiency in converting Pb, As, Cu, Zn, and Cd from the soil to themselves. Notably, the conversion rate of Cu in Lycium was better than Nitraria.

Combining the accumulation effect and transport coefficient, we found that Lycium and Nitraria showed higher tolerance and similar repair performances for Pb, As, Cu, Zn, and Cd. Therefore, Lycium and Nitrarial could all be used for repair of the study area and would get similar repair performances. Nevertheless, their repair abilities were different. Although they all had good efficiency at converting these heavy metals from the soil to themselves, Lycium had a better conversion rate for Cu than Nitraria. And the location to be repaired was a copper mining area. So, Lycium was relatively a better option than Nitraria for the repair of heavy metals in this abandoned copper mine.

4. Discussion

The study area lacks plants due to pollution, which is consistent with existing studies. In existing studies, the insufficient variety and growth of plants in mines are influenced by heavy metals and other contaminants, such as the Pingle manganese mine in China, where a total of 13 plant species were found [51], the Tonglushan copper mine in China, where a total of 13 plant species were found [52], and the Pakhar aluminum mine in India, where a total of 21 plant species were found [53]. Although these insufficiencies in plant variety and growth are influenced by contaminant stress from the environment, scientists have found that, within this stress, plants develop tolerance and repair abilities for contaminants, which makes them usable as repair plants [10]. Scientists have recognized that plants from other environments, including hyperaccumulators, may not be able to adapt to the harsh environment of mines [6]. However, repair plants selected from harsh environments do not have this problem and are therefore widely used [54]. But it is necessary to determine the stability of the plant community before plant screening. Existing studies show that, when the plant community is stable, the plants from it have been screened by the environment and will slow down succession and then exist in the environment for a long time [55]. Once selected, repair plants will achieve long-term repair effects through their prolonged colonization after being replanted [55]. To understand the community status of plants, a study of the plant community’s structure and diversity is required [34]. In this study, the study area is located in a mid-temperate continental arid and semi-arid climate zone. Under these climatic conditions, scientists find herbs and shrubs are typical communities [32]. When the community is stable, shrubs have existed in the environment for a long time and have developed larger body sizes [32,33]. Herbs have higher values in individual number and occurrence frequency, and even community diversity, but lower values in cover and height than shrubs [32,33]. The plant community in quadrats has the same characteristics as these, so the plant community has passed the initial stage of succession and entered a stable period, and the plants in it are plants with resistance to the harsh environment of the mine. Additionally, the plant community in the study area has not been colonized by exotic plants brought by tourists, despite being part of a national park for several decades, once again confirming that the existing plant community is stable, which means it has passed the challenge of preventing exotic plants from invading for a long time.

Given that phytoremediation is applicable in this situation, we can proceed with the screening of repair plants. Repair plants are dominant species screened from the top level. The top level of the community usually crowds out other species and significantly occupies resource superiority [33,56]. Plants of lower levels will be replaced by plants of higher level in the plant community as much as possible when the soil-bearing capacity allows this [33]. So, the dominant species at the top level are stable, as they are the most adaptable and exclusive among all plants of the top level [9]. After replanting, they can successfully adapt and exist long-term in this environment, then dominate the environment [57]. The repair of heavy metals in the soil by plants is not only reflected in their adsorption but also in their ability to stabilize soil and reduce the migration risk of heavy metals, as well as in their secretions that improve soil conditions [8,9]. So, scientists believe that, in addition to the advantage of succession, higher level plants like trees or shrubs, which do not wither periodically or die regularly, can more stably store and fix contamination than herbs [56]. The importance value of a plant can reflect its importance [57]. The dominant species at the top level are screened by importance value [57]. In this study, Lycium and Nitraria are preliminarily screened as candidate plants for repair. They are all medicinal plants. After being used for heavy metals repair, the heavy metals in them can be eliminated as impurities when extracting major active ingredients like the Lycium barbarum polysaccharides in Lycium [58] and total alkaloids in Nitraria [59]. Therefore, Lycium and Nitraria can still be used as raw materials for production, even if they accumulate heavy metals in themselves. Typically, plants lose their value by being directly incinerated after heavy metals repair, due to the toxicity of the heavy metals [60]. The candidate plants we selected still retain economic value after completing heavy metals adsorption, which is very rare.

Candidate plants need to be compared for their ability to repair polluted soil in order to determine the most suitable one. The uptake of heavy metals from soil to plants is a way for plants to mitigate contamination of heavy metals in soil [5]. To determine the repair ability of the screened plants, the relationship between plants and soil with respect to heavy metals is usually quantified [45].

To achieve this goal, we measure and evaluate the heavy metal situation of the soil on the one hand. The heavy metal concentration, the Nemerow integrated pollution index method, and the single-factor index method are common evaluation approaches [43]. Through these analyses, Pb and As are found to exceed national standards and are identified, along with Cd, as the main pollution factors, while synergistically working with Cu and Zn to contribute to severe environmental pollution. Heavy metals pollution in local mining-related areas, specifically involving Pb, As, Cd, Cu, and Zn, has been confirmed in many studies [21,22,23,24,25,26]. In addition, we also found that the soil in the study area was poor in the macronutrients required for biological growth and had high acidity. This situation is quite common in mines [61]. It is well-known that being poor in the macronutrients required for biological growth affects the self-repair capabilities of soil [62]. And acid in soil increases the bioavailability of heavy metals and makes the heavy metals more damaging [62,63,64,65]. Therefore, this study is both urgent and necessary for repair.

On the other hand, we measure the concentrations of heavy metals in the fruits of screened plants. The reason for selecting fruit as the measurement site is that it is an annual organ, which can better reflect the interaction between plant and soil with regard to heavy metals in the current year [66]. This non-destructive method is suitable since it is difficult for the plants in such polluted environments to recover once they are injured [67]. And this method has been adopted by other scientists [66]. Simultaneously, in line with other studies, the measurement methods focus on the accumulation effect and transport efficiency to evaluate the heavy metals repair ability of the plants [45]. The accumulation effect of heavy metals in plants represents the degree of heavy metal aggregation in plants, and the transport efficiency of heavy metals in plants represents the conversion rate of heavy metal in plants [45]. Together, they can indicate the status of heavy metals accumulation in the plants for the current year through fruits. Scientists have found that, even though plants generally cannot reach the accumulation limits of heavy metals due to the limited concentration of these metals in soil in the natural environment, the accumulation of heavy metals can still provide insights into the tolerance and repair ability of plants [68]. In this study, compared to Lycium and Nitraria grown in uncontaminated environments, Lycium and Nitraria in the study area contain significant amounts of heavy metals [69], with the levels of Pb and As even exceeding national standards. Thus, they are capable of withstanding environmental stress from heavy metals in the study area and can be used for repairing. Additionally, it is noteworthy that the accumulation effects in Lycium and Nitraria are similar and roughly proportional to the concentrations of heavy metals in the soil, except Cu. This proportional phenomenon is consistent with the pattern of heavy metals accumulation in plants observed in other phytoremediation studies [70]. So, we can reasonably speculate that when Pb, As, Cu, Zn, and Cd have not reached their saturation in Lycium and Nitraria, in the current environment their removal amounts are similar and roughly proportional to their respective contents in the soil. And the removing power of Lycium and Nitraria on Cu is relatively poor. But, through transport efficiency, we know that Lycium slightly compensated for this through its higher conversion rate for Cu. Existing research has shown that fruits are the organ with the lowest accumulation of heavy metals in the entire plant [71], and any increase in the transport coefficient is highly valuable. Accordingly, within the study area, both Lycium and Nitraria can not only be used for repair but also exhibit similar repair effects. However, due to Lycium having a better transport efficiency for Cu than Nitraria, Lycium will respond more quickly when there are significant fluctuations in Cu levels. In addition, as the location to be repaired is a copper mining area, Lycium is selected as the final repair species. Good tolerance and accumulation by Lycium of heavy metals like Pb, As, Cu, Zn, and Cd has been reported [72], but it is rarely used for repair. Our study provides additional options for repairing plants. Existing studies have shown that plants in soil not only adsorb heavy metals from the environment and stabilize soil and water through their roots to reduce the risk of heavy metals leaching into adjacent environments but also improve environmental conditions by secreting compounds to regulate soil pH, increasing essential nutrients for soil biota and promoting the survival of microorganisms beneficial to plant growth [8,9]. Therefore, once Lycium is introduced, it can adsorb heavy metals during its growth, reduce the risk of heavy metals leaching into adjacent environments through its roots, and act as a pioneer plant for improving the environment to create favorable conditions for subsequent phytoremediation like the planting of hyperaccumulators. Furthermore, its products, such as Lycium barbarum polysaccharides extracted from fruit, can be used to generate economic value [58]. We propose the idea of using Lycium as a pioneer plant in the heavy metals repair of the Baiyin copper mine and provide an idea, theoretical basis, and reliable plant resource for phytoremediation of this mine. These also apply to other sulfide deposits, particularly in northwestern China’s mining regions.

5. Conclusions

In the present study, we find the ruin of Baiyin copper mine is characterized by extreme pH (2.25), deficiency of the macronutrients required for biological growth (low content of total C, total N, Na, K, and Ca), and dangerous heavy metals pollution (the concentration is Pb > As > Cu > Zn > Cd; Pb and As exceed national standards and are identified, along with Cd, as the main pollution factors, while synergistically working with Cu and Zn to contribute to severe environmental pollution), and a plant community with few species but a stable structure (only 11 species but herbs with higher values in individual number and occurrence frequency, and even community diversity, but lower values incover and height than shrubs). This means that the dominant species among the shrubs, as the top level of plants, possess significant potential for phytoremediation. There are two dominant shrub species, Lycium and Nitraria, which have an absolute advantage (values of the importance value are 20~30% higher than the others). They have higher tolerance and similar repair performances in the heavy metals of the study area (repairing force Pb > As > Zn > Cu > Cd), could be used for repair of the study area, and would get similar repair performances, except that the Cu accumulation is slightly lower than expected. But the fact that Lycium has a better conversion rate for Cu than Nitraria slightly compensated for this, which makes Lycium more suited to the repair needs of a cooper mine. Finally, Lycium is screened as a pioneer plant. Once Lycium is introduced, it can adsorb heavy metals, reduce the risk of heavy metals leaching into adjacent other environments, and improve the environmental conditions. And its fruit can be used as a production material to create economic value. This discovery provides an idea, theoretical basis, and reliable plant resource for phytoremediation of this copper mine and other sulfide deposits, particularly in northwestern China’s mining regions.