| Literature DB >> 35559321 |
Yuhan Huang1, Xinyu Kuang1, Yingui Cao1,2, Zhongke Bai1,2.
Abstract
Opencast coal mining damages the land in arid grassland mining areas where topsoil is scarce. Restoration of the soil chemical properties is important for land reclamation and the rebuilding of vegetation. We studied a south dump after 4 years of reclamation, a north dump after 8 years of reclamation, and undamaged land to identify changes in the soil profile after mining and reclamation. Variance, correlation, and principal component analyses assessed spatial and temporal differences, and correlations between soil organic matter (SOM), total nitrogen (STN), available phosphorus (SAP), available potassium (SAK), and soil pH (pH) in the 0-40 cm layers. The soil chemical properties were evaluated to support the reconstructed soil profiles and guide soil reconstruction in grassland mining areas. SOM, STN, SAP, and SAK in the south dump were significantly lower than those in the undamaged land. SOM and STN levels in the north dump were lower than those in the undamaged land. SAP and SAK levels in the north dump were higher than those in the undamaged land. Therefore, land reclamation can improve the chemical properties of the reconstructed soil profile in grassland mining areas lacking SAP. Principal component analysis revealed that increasing reclamation years improved the soil chemical quality, and that of the surface soil was better than that of the lower layer. The chemical quality of the soil below 20 cm was consistent. At 0-40 cm, correlations between the soil chemical properties declined from top to bottom, and changed from interdependent to mutually independent; SOM was the core element. The use of topsoil and coal gangue to construct soil profiles can improve the soil chemical properties and resolve the difficulties of land reclamation caused by surface soil scarcity and droughts. This journal is © The Royal Society of Chemistry.Entities:
Year: 2018 PMID: 35559321 PMCID: PMC9091915 DOI: 10.1039/c8ra08002j
Source DB: PubMed Journal: RSC Adv ISSN: 2046-2069 Impact factor: 3.361
Fig. 1Location of the no. 1 opencast coal mine in the Shengli mining area.
List of sampling site profiles
| Number | Section name | Soil layer thickness (cm) | Reclamation year | Treatment rate (%) | Main plant species |
|---|---|---|---|---|---|
| 1 | Undamaged profile-1 | 20 | — | — |
|
| 2 | Undamaged profile-2 | 20 | — | ||
| 3 | Undamaged profile-3 | 25 | — | ||
| 4 | South dump profile-1 | 40 | 4 | 100 |
|
| 5 | South dump profile-2 | 30 | 4 | ||
| 6 | South dump profile-3 | 50 | 4 | ||
| 7 | North dump profile-1 | 30 | 8 | 100 |
|
| 8 | North dump profile-2 | 15 | 8 | ||
| 9 | North dump profile-3 | 20 | 8 |
Soil nutrient grading standardsa
| Level | Abundance and deficiency | SOM (g kg−1) | STN (g kg−1) | SAP (mg kg−1) | SAK (mg kg−1) |
|---|---|---|---|---|---|
| 1 | Very rich | >40 | >2.0 | >40 | >200 |
| 2 | Rich | 30–40 | 1.5–2.0 | 20–40 | 150–200 |
| 3 | Medium | 20–30 | 1.0–1.5 | 10–20 | 100–150 |
| 4 | Lacking | 10–20 | 0.75–1.0 | 5–10 | 50–100 |
| 5 | Very lacking | 6–10 | 0.5–0.75 | 3–5 | 30–50 |
| 6 | Totally lacking | <6 | <0.5 | <3 | <30 |
Quoted from The Second National Soil Census Technical Regulations. SOM, soil organic matter; STN, soil total nitrogen; SAP, soil available phosphorus; SAK, soil available potassium.
Fig. 2Overall differences in the soil chemical properties of the various plots: a and b indicate a significant difference between the two, and ab indicates no significant difference, P < 0.05.
Soil nutrient grading of the various plots
| Sample plot | Nutrient grading | |||
|---|---|---|---|---|
| SOM | STN | SAP | SAK | |
| Undamaged land | 3 | 2 | 5 | 3 |
| South dump | 4 | 5 | 6 | 4 |
| North dump | 3 | 5 | 5 | 1 |
Fig. 3Vertical differences in the soil chemical properties of the various plots.
Correlation analysis of the soil chemical properties of the various plotsa
| Sample plot | Index | SOM | STN | SAP | SAK | pH |
|---|---|---|---|---|---|---|
| Undamaged land | SOM | 1.00 | ||||
| STN | 0.97 | 1.00 | ||||
| SAP | 0.41 | 0.23 | 1.00 | |||
| SAK | 0.50 | 0.30 | 0.91 | 1.00 | ||
| pH | −0.11 | −0.16 | 0.16 | 0.15 | 1.00 | |
| South dump | SOM | 1.00 | ||||
| STN | 0.76 | 1.00 | ||||
| SAP | −0.11 | −0.10 | 1.00 | |||
| SAK | 0.78 | 0.71 | 0.08 | 1.00 | ||
| pH | −0.29 | −0.55 | −0.45 | −0.35 | 1.00 | |
| North dump | SOM | 1.00 | ||||
| STN | 0.67 | 1.00 | ||||
| SAP | 0.26 | 0.22 | 1.00 | |||
| SAK | 0.51 | 0.72 | 0.13 | 1.00 | ||
| pH | −0.86 | −0.42 | −0.02 | −0.32 | 1.00 |
At the 0.01 level (two-tailed), the correlation is significant.
At the 0.05 level (two-tailed), the correlation is significant.
Correlation analysis between the soil chemical properties in the different soil layers of the various plots
| Soil depth (cm) | Index | SOM | STN | SAP | SAK | pH |
|---|---|---|---|---|---|---|
| 0–10 | SOM | 1.00 | ||||
| STN | 0.90** | 1.00 | ||||
| SAP | 0.69* | 0.75* | 1.00 | |||
| SAK | 0.88** | 0.68* | 0.73* | 1.00 | ||
| pH | −0.67* | −0.50 | −0.48 | −0.72* | 1.00 | |
| 10–20 | SOM | 1.00 | ||||
| STN | 0.71* | 1.00 | ||||
| SAP | 0.44 | 0.09 | 1.00 | |||
| SAK | 0.17 | 0.00 | 0.28 | 1.00 | ||
| pH | −0.73* | −0.42 | −0.44 | −0.30 | 1.00 | |
| 20–30 | SOM | 1.00 | ||||
| STN | 0.65 | 1.00 | ||||
| SAP | 0.05 | −0.23 | 1.00 | |||
| SAK | 0.75* | 0.00 | 0.35 | 1.00 | ||
| pH | −0.80** | −0.66 | −0.11 | −0.54 | 1.00 | |
| 30–40 | SOM | 1.00 | ||||
| STN | 0.45 | 1.00 | ||||
| SAP | 0.08 | −0.29 | 1.00 | |||
| SAK | 0.55 | −0.26 | 0.74* | 1.00 | ||
| pH | −0.38 | −0.57 | −0.49 | −0.42 | 1.00 |
Explanation of total variancea
| Component | Initial eigenvalue | Extract the sum of squares of loads | ||||
|---|---|---|---|---|---|---|
| Total | Variance percentage | Cumulative (%) | Total | Variance percentage | Cumulative (%) | |
| 1 | 2.676 | 53.514 | 53.514 | 2.676 | 53.514 | 53.514 |
| 2 | 1.088 | 21.760 | 75.274 | 1.088 | 21.760 | 75.274 |
| 3 | 0.526 | 10.519 | 85.793 | |||
| 4 | 0.476 | 9.523 | 95.316 | |||
| 5 | 0.234 | 4.684 | 100.000 | |||
Extraction method: principal component analysis. Extraction principle: when the eigenvalues ≥1, it corresponds to the first “n” principal components
Initial factor load matrixa
| Index | Component | |
|---|---|---|
| 1 | 2 | |
| SOM | 0.872 | −0.223 |
| STN | 0.737 | −0.422 |
| SAP | 0.564 | 0.687 |
| SAK | 0.708 | 0.522 |
| pH | −0.744 | 0.339 |
Two components were extracted.
Principal component load matrixa
| Index | Component | |
|---|---|---|
| 1 | 2 | |
| SOM | 0.533 | −0.214 |
| STN | 0.451 | −0.405 |
| SAP | 0.345 | 0.659 |
| SAK | 0.433 | 0.500 |
| pH | −0.455 | 0.325 |
Two components were extracted.
Comprehensive scores and rankings of the principal components of the soil chemical properties in the various plotsa
| Sample plot | Principal component 1 score | Principal component 2 score | Comprehensive score | Rank |
|---|---|---|---|---|
| Undamaged land | 0.907 | −0.667 | 0.453 | 2 |
| South dump | −1.363 | 0.143 | −0.927 | 3 |
| North dump | 0.453 | 0.524 | 0.475 | 1 |
Data in the table are the average of twelve replicates.
Comprehensive scores and rankings of the soil chemical properties in the different soil layers of the studied mining areaa
| Soil depth (cm) | Undamaged land | South dump | North dump | Comprehensive score | Rank |
|---|---|---|---|---|---|
| 0–10 | 1.897 | −0.614 | 1.225 | 0.836 | 1 |
| 10–20 | 0.570 | −1.240 | 0.155 | −0.172 | 2 |
| 20–30 | −0.115 | −1.274 | 0.367 | −0.340 | 4 |
| 30–40 | −0.542 | −0.581 | 0.153 | −0.323 | 3 |
Data in the table are the average of three replicates.