Assessing the Effectiveness of Turf Transplantation and Artificial Replanting in Restoring Abandoned Mining Areas

Abstract

Long-term and extensive mineral mining in the Kuermutu mine section of the Two Rivers Nature Reserve in the Altai region has disrupted the ecological balance between soil and vegetation. To assess the effectiveness of various restoration measures in this abandoned mine area, we compared two restoration approaches—natural turf transplantation (NTT) and replanted economic crop grassland (ARGC)—against an unaltered control (original grassland). We employed 11 evaluation indices to conduct soil and vegetation surveys. We developed a comprehensive evaluation model using the Analytic Hierarchy Process (AHP) to assess restoration outcomes for each grassland type. Our findings indicate that both NTT and ARGC significantly improved ecological conditions, such as reducing soil fine particulate matter loss and restoring vegetation cover. This brought these areas closer to their original grassland state. The species composition and community structure of the NTT and ARGC vegetation communities improved relative to the original grassland. This was due to a noticeable increase in dominant species’ importance value. Vegetation cover averaged higher scores in NTT, while the average height was greater in ARGC. The soil water content and soil organic carbon (SOC) varied significantly with depth (p < 0.05), following a general ‘V’ pattern. NTT positively impacted soil moisture content (SMC) at the surface, whereas ARGC influenced SMC in deeper layers, with the 40–50 cm soil layer achieving 48.13% of the original grassland’s SMC. SOC levels were highest in the control (original grassland), followed by ARGC and NTT, with ARGC showing the greatest organic carbon content at 20–30 cm depths. A comprehensive AHP ecological-economic evaluation revealed that restoration effectiveness scores were 0.594 for NTT and 0.669 for ARGC, translating to 59.4% and 66.9%, respectively. ARGC restoration was found to be more effective than NTT. These results provide valuable insights into ecological restoration practices for abandoned mines in Xinjiang and can guide future effectiveness evaluations.

1. Introduction

Mineral resource mining, though a significant contributor to local economic growth, has far-reaching consequences for ecosystem integrity, particularly in vulnerable regions like the Kuermutu mine section of the Two Rivers Nature Reserve in the Altai Mountains. Decades of extensive mining have severely degraded the local ecosystem. Soil–vegetation dynamics have been profoundly disrupted, with topsoil being stripped away, subsurface soil layers compacted, and natural habitats fragmented. These disturbances have led to significant vegetation loss, biodiversity decline, and the destabilization of the local ecological balance [1,2]. Additionally, the accumulation of mining byproducts, such as tailings, has further contaminated the soil, increased salinity levels, and degraded water systems, aggravating the already fragile ecological state.

Vegetation restoration in mining areas has progressed significantly over recent years, driven by the urgent need to restore the ecosystem structure and function in regions impacted by mining. Globally, restoration practices focus on rehabilitating vegetation, soil properties, and biodiversity, aiming to bring disturbed areas closer to their pre-mining ecological conditions [3]. In the Kuermutu region, successful vegetation restoration faces multiple challenges: altered topography and geomorphology, soil degradation, and biodiversity loss [4]. Key strategies such as terrain reshaping, soil reconstruction, and vegetation reestablishment have emerged as essential components of ecological rehabilitation in mining regions. A review of restoration efforts in comparable mining areas worldwide reveals that comprehensive and tailored approaches—specific to local climatic and ecological conditions—are needed to achieve sustainable restoration outcomes.

Various restoration frameworks have been proposed, but their effectiveness is context-dependent. Hou [5] advocate for multi-factor risk assessments, which are essential for understanding complex interactions between degradation factors in mining areas. In Kazakhstan, Toktar [6] achieved successful restoration by experimenting with locally adapted soil and vegetation restoration techniques. These studies emphasize the importance of site-specific assessment frameworks that address local environmental conditions, restoration requirements, and ecological priorities.

In China, restoration practices differ markedly across regions due to distinct climatic, edaphic, and ecological conditions. Liu [7] introduced a cubic ecological restoration framework optimized using an entropy-weighted TOPSIS model. This framework integrates soil improvement and vegetation reestablishment. However, restoration in arid regions like Xinjiang presents unique challenges, with low precipitation, extreme temperatures, and fragile ecosystems complicating restoration efforts [8]. The extreme environmental conditions of Xinjiang underscore the need for scientific, tailored restoration strategies to balance ecological sustainability with economic feasibility in mining-affected regions.

This study investigates the Kuermutu abandoned mine area within the Altai Mountains and the Two Rivers Nature Reserve. The region, rich in mineral resources, has suffered significant ecological degradation due to mining activities, including deforestation, vegetation loss, soil erosion, and habitat destruction. Since 2010, various ecological restoration initiatives have focused on improving topography, soil structure, and biodiversity through artificial replanting and natural turf transplantation (NTT). This research provides a comprehensive evaluation of these restoration methods using 11 key ecological-economic indicators, including topography, soil characteristics, vegetation growth, and biodiversity. By identifying effective, scientifically grounded restoration strategies, this study aims to contribute to the global knowledge base on ecosystem restoration in mining-affected areas, offering replicable models for similar ecological challenges.

2. Materials and Methods

2.1. Overview of the Study Area

The study area is situated in the Two Rivers Nature Reserve within the Altai Mountains. We focus on the section from Kuermutu mine to Akesala. This region lies in the central and southern Altai Mountains, encompassing Qinghe, Fuyun, and Fuhai counties, with geographical coordinates ranging from 87°30′ to 91°00′ E longitude and 46°30′ to 48°10′ N latitude [9]. The Altai Mountains exhibit quasi-planar uplift and well-developed glacial landforms, characterized by numerous intermountain and pre-mountain basins and extensive river terraces. The climate is continental and cold-temperate, with average annual temperatures below −2 °C in the higher elevations (1400–2600 m) and below 4 °C in the lower elevations [10]. The region is well-watered, with five large rivers with annual runoff exceeding 1 × 10⁸ m³, and a total catchment area of 5280 km². Annual precipitation is 296.3 mm, with a surface runoff of 11.2 × 10⁸ m³ and annual production of 8.17 × 10⁸ m³ [11]. The area’s biodiversity includes over 1400 vascular plant species, along with more than 200 Bryophyta, Lichenes, and Macrofungi. In addition, there are over 60 species of wild oleaginous plants and more than 100 species of wildflowers.

However, the mining investigation area has been heavily impacted by long-term mining activities, resulting in significant land degradation, including large pits, altered topographic relief, and severely damaged soils [12]. By 2006, the ground surface was densely covered with rocks approximately 10 cm thick, due to mining operations. The site was bulldozed and backfilled in 2010, with no vegetation present between 2010 and 2012. Restoration measures began in 2012. The turf transplantation restoration site spans 10 acres in the Akesala section (center coordinates 47°55′43″ N, 89°23′39″ E), and the artificial replanting site, including blackcurrant cultivation, covers 50 acres in the Kuermutu section (center coordinates 47°54′4″ N, 89°18′40″ E). A wire fence was constructed around the experimental sites to prevent external disturbances during restoration (Figure 1).

2.2. Experimental Design

This study involved three types of sample plots: original natural grassland, turf transplantation grassland, and artificial replanting grassland, all established within the Kuermutu abandoned mine area to assess different restoration strategies. The original natural grassland served as a control, representing undisturbed conditions. In the turf transplantation and artificial replanting plots, we applied active restoration techniques to the degraded landscape.

Prior to restoration, the site was prepared through bulldozing and a 5–8 cm mulch layer. This preparation was performed to stabilize the soil, retain moisture, and reduce erosion, creating a suitable foundation for vegetation recovery. The turf transplantation method involved transplanting an 8 cm thick layer of mixed grasses (Poa annua, Festuca valesiaca, and Carex L.) selected for their adaptability to arid conditions and ability to quickly establish ground cover, thereby stabilizing the soil and promoting ecosystem function. In the artificial replanting plot, native plant species such as Helictotrichon schellianum, Oxalis, Trifolium lupinaster, and blackcurrant (Ribes nigrum) were manually replanted. This method focused on fostering plant growth from seeds and young plants, without fertilizers, to simulate natural regeneration and evaluate long-term ecosystem resilience.

By comparing these approaches, the study aimed to identify the most effective strategy for restoring ecosystem function and biodiversity in mining-affected areas, offering valuable insights into restoration in similar environments globally.

2.3. Experimental Program

On 15 August 2023, a comprehensive vegetation survey and soil sampling were conducted in the abandoned mine area of Kuermutu. Three types of sample plots were established: original grassland, natural turf-transplanted grassland, and artificially planted economic crop plots. Each plot comprised three 1 m × 1 m herbaceous sample areas, with three replicates per plot. Field investigations focused on assessing vegetation height, species number, and vegetation cover. These variables were used to determine the significance, density, and species diversity of vegetation. Vegetation cover (VC) was estimated visually, vegetation height (VH) was measured using a ruler, and vegetation density (VD) was determined by counting the individual plants.

Soil samples were collected at five different depths: 0–10 cm, 10–20 cm, 20–30 cm, 30–40 cm, and 40–50 cm, with three replicates per depth at each plot. The selection of these specific depth intervals was based on established methodologies in soil science. These depths are commonly used to assess variations in soil properties related to moisture content and organic carbon across the soil profile. These intervals also allow for a detailed understanding of root distribution, nutrient availability, and soil structure at various depths. These are key factors influencing vegetation growth. After collection, soil samples were cleaned of impurities, weighed, dried, and analyzed to determine the soil moisture content and soil organic carbon (SOC) [1].

2.4. Indicator Selection and Measurement Methods

The assessment of ecological restoration effectiveness focused on both soil and vegetation indicators [13], chosen based on pre-restoration ecological conditions and the specific goals of the restoration measures. Vegetation indicators included growth changes and species diversity, with vegetation cover and diversity indices used for evaluation. Soil indicators, such as soil water content (SWC) and soil organic carbon (SOC), were measured to assess the restoration of soil conditions necessary for vegetation recovery. Economic costs (CNY/acre) were also incorporated into the assessment to provide a comprehensive ecological–economic evaluation.

The soil water content was determined using the standard drying method, where soil samples were dried at 105 °C to a constant weight, following established protocols (Li, 2019 [14]). The soil organic carbon content was measured based on soil organic carbon density and soil bulk weight. Carbon storage was calculated using methods described by Li (2019) [14]. These indicators provide a holistic understanding of restoration efforts and their impact on soil health and vegetation recovery.

2.5. Data Analysis

Based on vegetation survey data, several indices were used to assess species diversity and community structure. The Margalef richness index was employed to evaluate species richness, while species diversity was measured through the Shannon–Wiener index (H′), which incorporates both the number of species and their distribution. The Pielou index (J_s) was applied to determine species evenness, and the Simpson index (D) was used to assess community dominance [15].

Relative abundance was classified into three categories: dominant species (>15%), common species (1–15%), and rare species (<1%). These indices provide insight into restoration’s impact on vegetation composition and structure, facilitating a comprehensive understanding of species recovery in restored areas.

The formula for carrying out the eco-efficiency assessment was first derived:

$$EO={\displaystyle \sum }_{i=1}^n{\partial }_R{\displaystyle \frac{H_R}{H_{R}max}}\left(R=1···n\right)$$

(1)

where H_R is the Rth indicator of the Hth restoration measure, and ∂_R is the weight of the Rth indicator. Referring to the AHP analysis method and the comprehensive indicator method, the formula for calculating the ecological–economic comprehensive benefit indicator was as follows:

$$(EQI)={\partial }_{g}EO-{\partial }_p{\displaystyle \frac{C_P}{C_{P}max}}$$

(2)

In the formula, ${\partial }_{\mathrm{g}}EO$ is the product of the ecological benefit and weight, $C_P$ is the pth indicator of $C$ cost, and ${\partial }_{\mathrm{p}}$ is the weight of the pth indicator.

According to the experts’ opinions and reviewed information, combined with the actual ecological restoration site investigation data in the study area, the values of each index of natural turf transplantation grassland and replanting economic crop grassland were obtained.

3. Results

3.1. Vegetation Community Species Composition

Field surveys of the plant communities at the abandoned mine site revealed distinct differences in species composition among the original grassland, turf-transplanted grassland, and artificially replanted cash crop grassland (

Table 1. Species composition and importance values of plant communities in different types of grasslands.

			Importance Value/%
No.	Family	Plant Species	NG	NTT	ARCG
1	Gramineae	Bromus inermis Leyss.	14.67	2.78	—
2		Festuca valesiaca	18.06 △	18.99 ▲	13.74
3		Poa annua	0.99 ▼	—	12.86
4	Compositae	Artemisiakas chgaria	0.94 ▼	—	—
5		Trifolium lupinaster	—	—	1.43
6		Vicia sepium	—	—	2.61
7		Sonchus oleraceus	—	—	3.31
8		Taraxacum mongolicum Hand.-Mazz.	4.51	15.23	3.5
9		Achillea millefolium L.	16.92	3.999	9.95
10	Cyperaceae	Carex L.	24.96 ▲	—	6.95
11	Salicaceae	Salix cupularis	—	3.51	—
12	Rosaceae	Alchemilla japonica	14.93	—	—
13		Potentilla bifurca	9.04	11.37	15.78 ▲
14	Polygonaceae	Medicago falcate	7.03	8.59	—
15	Leguminosae	Melilotus officinalis (L.) Pall.	6.62	18.88 △	1.04 ▼
16		Oxytropis ochrocephala Bunge	—	—	9.19
17	Rubiaceae	Galium Linn.	—	1.87 ▼	—
18	Pinaceae	Picea asperata Mast.	—	7.84	—
19	Labiatae	Salvia japonica Thunb.	—	—	6.28
20		Phlomis oreophila	—	0.66 ▼	—
21	Pinaceae	Larix sibirica Ledeb.	—	—	13.35
22			—	—	15.16 △
23	Boraginaceae	Echium vulgare L.	—	—	2.23
24	Ranunculaceae	Ranunculus monophyllus	3.87	—	7.69
25	Chenopodiaceae	Suaeda glauca (Bunge) Bunge	—	—	0.96 ▼

Note: ▲ Stands for dominant species in sample site; △ stands for subdominant species in sample site; ▼ stands for occasional species in sample site; — stands for none present in sample site.

).

In the original grassland, 12 herbaceous species from 7 families were identified. Key species included Bromus inermis, Festuca valesiaca, Poa annua, Artemisia kaschgarica, Taraxacum mongolicum, Achillea millefolium, Carex, Alchemilla japonica, Potentilla bifurca, Medicago falcata, Melilotus officinalis, and Ranunculus. Among these, Carex (Cyperaceae) was the dominant constructive species, while Festuca valesiaca (Poaceae) was the auxiliary species. Festuca valesiaca and Poa annua were occasional species.

In natural turf-transplanted grassland (NTT), 11 herbaceous species from 9 families were recorded. These included Bromus inermis, Festuca valesiaca, Taraxacum mongolicum, Achillea millefolium, Salix cupularis, Potentilla bifurca, Medicago falcata, Melilotus officinalis, Galium, and Picea asperata. Festuca valesiaca emerged as the constructive species, and Melilotus officinalis was identified as the auxiliary species.

The artificially replanted cash crop grassland (ARCG) featured 17 herbaceous species from 10 families. This community included Festuca valesiaca, Poa annua, Trifolium lupinaster, Vicia sepium, Sonchus oleraceus, Taraxacum mongolicum, Achillea millefolium, Carex, Potentilla bifurca, Melilotus officinalis, Oxytropis ochrocephala, Salvia japonica, Larix sibirica, Ribes nigrum, Echium vulgare, Ranunculus monophyllus, and Suaeda glauca. Ribes nigrum was identified as the constructive species, with Potentilla bifurca as the auxiliary species. Melilotus officinalis and Suaeda glauca were occasional species.

Importance values, which reflect the ecological role of species within a community, were calculated to determine the dominant species. In the original grassland, Festuca valesiaca had the highest importance value at 24.96%, followed by Achillea millefolium at 16.92% and Alchemilla japonica at 14.93%. In the turf-transplanted grassland, Festuca valesiaca increased to an importance value of 18.99%, with Melilotus officinalis and Taraxacum mongolicum showing values of 18.88% and 15.23%, respectively. In the artificially replanted cash crop grassland, Potentilla bifurca and Ribes nigrum had importance values of 15.78%, representing 42.71% of the values observed in the original grassland.

3.2. Vegetation Community Structure

The effectiveness of vegetation restoration in a mining area is assessed using indicators such as vegetation cover and diversity indices. These indicators reflect dynamic changes before and after restoration (Figure 2).

The average vegetation cover in the original grassland was 43.67%. In comparison, the average cover levels for the turf transplantation site in Akesala and the replanted economic vegetation site were 24.82% and 41.67%, respectively. These values were significantly lower than that of the original grassland (p < 0.001), achieving 56.84% and 95.42% of the original grassland cover, respectively. The restoration effect of economic vegetation replanting was notably better than that of natural turf transplantation, as it approached the cover value of the original grassland more closely.

In terms of vegetation height, the average heights recorded were 5.14 cm for the original grassland, 15.79 cm for the turf-transplanted grassland, and 15.81 cm for the replanted economic vegetation grassland. The original grassland had been heavily grazed by cattle and sheep, resulting in a reduced vegetation height. The restored grasslands showed significant increases in height, with average values of 207.2% and 207.6% broader than those of the original grassland (p < 0.001).

Vegetation diversity is a crucial indicator of community stability, including metrics such as the Margalef richness index, Shannon–Wiener diversity index, Simpson community dominance index, and Pielou evenness index. After restoration, the number of species and herbaceous individuals in the turf-transplanted grassland decreased compared to the original grassland, while the replanting of economic crops, particularly blackcurrants, led to an increase in both species and individual counts.

Figure 3 illustrates the box plots for significant differences in the vegetation diversity indices among the original grassland, natural turf-replanted grassland, and replanted economic vegetation grassland. The results indicate no significant differences between the original grassland and the restored natural turf-transplanted and economic vegetation grasslands, suggesting effective restoration of vegetation diversity in the restored areas. However, the Margalef richness index, Shannon–Wiener diversity index, Simpson community dominance index, and Pielou evenness index were all higher in ARCG than natural turf-transplanted grassland, resulting in the order ARCG > NG > NTT. This demonstrates that the restoration effect of economic vegetation replanting measures was significantly more successful than that of natural turf transplantation.

3.3. Characteristics of Basic Soil Properties

Soil moisture and the organic carbon content are critical indicators for assessing soil quality and ecological restoration in mining areas. These parameters influence surface vegetation growth and provide valuable insights for optimizing irrigation methods and evaluating soil fertility. Soil moisture directly affects vegetation growth and serves as a key indicator of soil quality assessment. Soil organic carbon, a major component of soil organic matter, is essential for evaluating soil fertility and health, significantly impacting vegetation growth in mining areas.

Table 2. Changes in soil water content in different types of grasslands (%, ±standard error).

	Solum Type of	0~10	10~20	20~30	30~40	40~50
Grassland
NG		20.29 ± 0.05 a	18.33 ± 0.07 a	12.57 ± 0.05 a	6.68 ± 0.03 b	4.98 ± 0.03 b
NTT		3.95 ± 0.04 b	6.96 ± 0.04 b	4.95 ± 0.01 ab	6.2 ± 0.03 a	5.10 ± 0.02 b
ARGC		3.61 ± 0.01 b	6.21 ± 0.04 b	8.38 ± 0.03 b	7.95 ± 0.02 c	9.60 ± 0.08 a

Different lowercase letters within the same column indicate significant differences between the different types of grasslands at the 0.05 level.

and

Table 3. Changes in soil organic carbon content in different grassland types (g·kg⁻¹, ±standard error).

	Solum	0~10 cm	10~20 cm	20~30 cm	30~40 cm	40~50 cm
Type of Grassland
NG		62.63 ± 44.48 a	33.97 ± 13.36	51.87 ± 49.90	19.47 ± 6.45 ab	23.87 ± 8.01
NTT		15.64 ± 8.74 a	13.25 ± 9.44	12.80 ± 9.00	9.86 ± 6.58 a	11.25 ± 8.51
ARGC		25.70 ± 9.87 a	25.17 ± 15.46	32.30 ± 14.01	25.83 ± 11.21 b	25.57 ± 9.09

Different lowercase letters within the same column indicate significant differences between the different types of grasslands at the 0.05 level.

illustrate the variations in soil water content and soil organic carbon content with soil depth across different land uses: original grassland, natural turf-transplanted grassland, and replanting economic vegetation (blackcurrant) grassland. Both soil water content and soil organic carbon exhibited significant changes with soil depth (p < 0.05).

Table 2 shows that the soil water content in the original grassland was significantly higher than in both the natural turf-transplanted grassland and the replanted economic crop (blackcurrant) grassland (p < 0.001). In the original grassland, the soil water content decreased with an increasing soil depth. This was with the highest value of 20.29% in the 0–10 cm layer and the lowest value of 4.98% in the 40–50 cm layer.

Following restoration, natural turf-transplanted grassland exhibited notable soil quality improvements. This was characterized by an increase in fine soil particles and a rise in soil water content compared to the pre-restoration state. The highest soil water content in this category was 6.96% at the 10–20 cm depth.

In the replanting of economic crop (blackcurrant) grassland, the soil water content increased with depth, reaching 9.60% in the 40–50 cm layer. This trend indicates that the replanting approach provided better water retention in deeper soil layers than the original grassland and natural turf-transplanted grassland, with the order being ARCG > NTT > NG.

Table 3 reveals that the soil organic carbon (SOC) content in the original grassland varied significantly with soil depth (p < 0.05). The highest SOC content was observed in the surface layer, with a decreasing trend observed at increasing depths. It reached its lowest point in the 30–40 cm layer.

In natural turf-transplanted grassland, the SOC content also decreased with depth but was notably lower in the surface layer compared to the original grassland, with a reduction of 75.03% in the 0–10 cm layer. This decrease in SOC follows a similar trend to that of the original grassland.

In contrast, the replanted economic crop (blackcurrant) grassland showed minimal variation in SOC across different soil layers. The SOC levels in this grassland were generally higher than in the natural turf-transplanted grassland but lower than in the original grassland, which were in the following order: NG > ARCG > NTT. The highest SOC content was found in the 20–30 cm layer, which likely supports nutrient availability for blackcurrant roots. This nutrient availability is a key factor contributing to the higher biodiversity observed in the replanted economic crop grassland compared to turf-transplanted restoration.

3.4. Evaluation of Ecological Restoration Effectiveness in the Study Area

The effectiveness of ecological restoration in the study area was assessed using the Analytic Hierarchy Process (AHP). This method involves constructing a hierarchical model that represents the relationships between different evaluation indicators. By employing pairwise comparisons and applying a scale method, the AHP calculates the relative weight of each indicator based on its importance.

As a systematic and quantitative evaluation tool, the AHP is widely used in environmental assessments, including those in mining areas. It provides a comprehensive evaluation framework by integrating expert opinions with the specific conditions of the mining area.

In this study, the AHP was utilized to determine the relative importance of various indicators (

Table 4. Structure and weighting of indicators for evaluating the effectiveness of ecological restoration in mining areas.

Number		Elements	Weighting of Elements	Indices	Weighting of Indices/%
1	Ecological benefits	Terrain and landform restoration	25%	Elevation	12.5%
				Relief	12.5%
2		Degree of restoration of species composition in vegetation communities	6%	Regional importance values	6%
3		Restoration of vegetation community	25%	coverage	13%
				Margalef index	4%
				Shannon–Wiener diversity index	4%
				Simpson index	1%
				Pielou index	3%
4		Recovery of basic soil characteristics	25%	SMC	12.5%
				SOC	12.5%
5	Ecological and economic integration benefits	Economic costs	19%	Cost of restoration (CNY/acre)	19%

Note: Since measures such as bulldozing and mulching the topography before taking restoration measures for the soil and vegetation in the mining area achieved the restoration objectives and the restoration effect was ideal, the impact of topography in this restoration effectiveness assessment can be ignored.

). Based on expert judgment and the mining area context, we assigned scores to each indicator. This was carried out by determining a weight vector for the evaluation factors. This approach ensures a robust and informed assessment of ecological restoration efforts (

Table 5. Evaluation results for each evaluation indicator.

Elements	Terrain and Landform Restoration		DRSCVC	Restoration of Vegetation Community					Recovery of Basic Soil Characteristics		Economic Costs
Indexes	Elevation	Relief	Regional Importance Values	Coverage	Margalef Richness Index	Shannon–Wiener Diversity Index	Simpson Index	Pielou Index	SMC (%)	SOC (g·kg−1)	Cost of Restoration (CNY/acre)
NT	0.334	0.725	0.536	0.414	0.430	0.470	0.600	0.700	0.362	0.196	0.436
ARCG	0.395	0.774	0.720	0.695	0.605	0.745	0.875	0.963	0.477	0.673	0.889

DRSCVC: Degree of restoration of species composition in vegetation communities.

).

Using the ecological–economic comprehensive benefit calculation formula, data index values for topography and geomorphology, vegetation community species composition, vegetation community structure, soil basic characteristics, and financial cost were derived for both the natural NTT and the replanting economic vegetation blackcurrant grassland (ARCG). The calculated index values were 0.192, 0.032, 0.191, 0.072, and 0.107 for NTT, while they were 0.279, 0.043, 0.182, 0.144, and 0.021 for ARCG. The comprehensive evaluation scores, which measure the restoration’s effectiveness, were 59.4% for NTT and 66.9% for ARCG. These results demonstrate that restoration efforts achieved the target values, with greater ARCG restoration effectiveness compared to NTT (Figure 4).

4. Discussion

The mining operations conducted at the Kuermutu mine section within the Altai Mountains Two Rivers Nature Reserve have led to severe ecological disturbances, particularly in soil structure and vegetation cover. As indicated in previous studies [16], mechanical mining methods have drastically altered the region’s soil composition, causing the loss of fine granular materials and exposing large surface stones, which have significantly reduced vegetation cover to less than 1%. Such degradation presents substantial challenges for restoration, a common issue in regions severely impacted by mining. Natural recovery approaches, known for their prolonged timelines and limited efficacy in extreme degradation cases, often fail to restore ecosystem functionality in such areas [17,18]. Our study builds on these findings by exploring the effectiveness of active restoration measures to address these challenges.

The 14-year ecological restoration project initiated in 2010 represents a systematic approach to reversing the damage. Through the establishment of 13 model plots over an area of 113 × 10⁴ hm², the restoration has targeted soil erosion, vegetation loss, and ecosystem degradation. Our findings demonstrated a significant improvement in vegetation cover, which increased from under 1% pre-restoration to an average of 43.6%. This outcome aligns with similar studies demonstrating that well-planned, targeted restoration efforts can result in substantial ecological recovery [14,19,20]. However, the mechanisms driving this recovery require further exploration. While improvements in soil structure and vegetation cover are evident, the specific contributions of various restoration techniques to these changes remain unclear.

Comparing our results with the existing literature highlights the importance of adopting a multifaceted approach that integrates both vegetation and soil restoration. Key metrics, such as species composition, community structure, SWC, and SOC, are crucial indicators of ecosystem recovery and are consistently used to evaluate restoration success. Studies by Wei [21] and Zhu [22] emphasize similar metrics, affirming that improvements in both soil and vegetation are essential for long-term ecosystem resilience. Our results indicated that both NTT and artificial replanting of cash crops significantly improved species diversity and vegetation cover. The latter showed an increase of more than 80% compared to the baseline condition. These findings underscore the importance of strategic interventions, particularly in heavily degraded ecosystems.

Our study observed substantial soil health improvements in both SWC and SOC following restoration efforts. These results are consistent with previous research [23] which emphasizes the critical role of soil moisture and organic matter in accelerating ecosystem recovery. The increase in SWC, particularly in deeper soil layers under economic crop replanting, suggests that root depth and plant type may influence soil–water dynamics. SOC levels also rose significantly, indicating enhanced nutrient cycling and carbon sequestration potential, which are vital for long-term vegetation growth. These findings highlight the interdependence of soil and vegetation restoration. They align with broader ecological restoration frameworks that emphasize soil as the foundation for ecosystem recovery.

To assess the relative effectiveness of restoration methods, we applied the Analytic Hierarchy Process (AHP), allowing us to integrate ecological and monetary factors into a comprehensive evaluation model. Our analysis showed that economic vegetation replanting, specifically blackcurrant, led to significantly better outcomes than NTT (p < 0.05), consistent with He, S [24]. This finding reflects the importance of selecting plant species not only for their ecological suitability but also for their commercial viability in restoration efforts. Cash crops improve vegetation cover and soil health, which highlights the potential for combining environmental and economic objectives in restoration projects. This is a strategy that can make large-scale restorations more sustainable.

Despite its strengths, the AHP method has limitations [25,26]. Evaluation results are influenced by both natural variability and human interventions, which may introduce biases in assessing restoration outcomes [27]. Additionally, while economic factors are valuable, it is imperative to acknowledge that ecological recovery may not always align with short-term financial gains. Future studies could benefit from more detailed long-term monitoring to assess how these ecological and economic benefits evolve over time, particularly in arid regions like Xinjiang, where environmental conditions pose unique challenges to restoration.

Overall, our study contributes to the growing body of literature on ecological restoration by providing a replicable model that integrates environmental and economic evaluations. The approach presented here offers practical insights into managing large-scale restoration projects, especially in mining-affected regions. By aligning restoration efforts with both ecological recovery goals and economic considerations, this model provides a comprehensive framework that can be applied to similar contexts globally. Future research should continue to refine these methods, particularly by exploring mechanisms of soil and vegetation recovery in more detail. In addition, it should assess the long-term sustainability of restoration interventions.

5. Conclusions

This study evaluated ecological restoration efforts implemented at an abandoned mining site in the Altai Mountains. By comparing NTT and ARCG, we assessed the effectiveness of these restoration methods using key environmental indicators such as vegetation cover, species diversity, SWC, and SOC. The results demonstrated that both NTT and ARCG significantly improved ecological conditions, with ARCG showing the greatest success in enhancing vegetation cover and soil quality.

Our findings highlight the value of integrating ecological and economic considerations into restoration projects. ARCG, in particular, proved to be a cost-effective and ecologically successful approach, achieving a higher comprehensive evaluation score than NTT. The combination of improved soil properties and vegetation recovery underscores the importance of addressing both biotic and abiotic factors in restoring degraded ecosystems.

Future restoration efforts should focus on scaling up successful strategies, such as blackcurrant replanting, while adapting them to local ecological conditions. Continuous monitoring and adaptive management will be essential to ensure long-term sustainability. Additionally, future research should explore the potential for integrating other plant species and soil amendments to further enhance restoration effectiveness.

By addressing these recommendations, future restoration projects can achieve even greater ecological and economic benefits, contributing to mining-affected landscapes’ long-term resilience.