Spatio-Temporal Variation and Its Driving Forces of Soil Organic Carbon along an Urban–Rural Gradient: A Case Study of Beijing
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources and Processing
2.2.1. Data Sources
2.2.2. Explanatory Variable Selection
2.3. Methods
2.3.1. Methodological Flowchart
2.3.2. Analysis of Land-Use Changes
2.3.3. Analysis of Changes in SOC Stock
Sen & Mann–Kendall Trend Test
Hurst Index Analysis
2.3.4. Multicollinearity
2.3.5. Regression Models
OLS and GWR Models
GTWR Model
2.3.6. Urban–Rural Gradient Construction
3. Results
3.1. Spatio-Temporal Characteristics of Land-Use Change
3.2. Spatio-Temporal Variation Characteristics of SOC Stock
3.3. Driving Factors Analysis of SOC Stock
3.3.1. Comparison of Model Performance
3.3.2. Analysis of Drivers Using GTWR Model
4. Discussion and Impact
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Dataset | Year | Spatial Solution | Source |
---|---|---|---|
Land use data | 2001–2015 | 30 × 30 m | Xie et al. (2022) |
SOC stock data | 2001–2015 | 250 × 250 m | Wheeler and Hengl (2018) |
DEM | 2009 | 30 × 30 m | The United States Geological Survey |
Soil data | 2017 | 250 × 250 m | SoilGrid |
Population | 2001–2015 | 1 × 1 km | WorldPop |
GDP | 2000–2015 | 1 × 1 km | Chinese Academy of Sciences |
NDVI | 2001–2015 | 1 × 1 km | Chinese Academy of Sciences |
Temperature | 2001–2015 | 1 × 1 km | Chinese Academy of Sciences |
Precipitation | 2001–2015 | 1 × 1 km | Chinese Academy of Sciences |
Variables | Indicators | Describe | Is It Dynamic |
---|---|---|---|
Topography | Elevation | Average elevation, m | No |
Slope | Average slope, degree | No | |
Climate | Tem | Average annual temperature, °C | Yes |
Per | Average annual precipitation, mm | Yes | |
Soil property | CEC | Cation exchangeable capacity, cmol/kg | No |
SILT | Silt content, % | No | |
CLAY | Clay content, % | No | |
pH | Soil pH | No | |
Land-use type | Cultivated land | Cultivated land rate, % | Yes |
Grassland | Grassland rate, % | Yes | |
Artificial surface | Artificial surface rate, % | Yes | |
Forest | Forest rate, % | Yes | |
Shrubland | Shrubland rate, % | Yes | |
Wetland | Wetland rate, % | Yes | |
Barren land | Barren land rate, % | Yes | |
Water | Water rate, % | Yes | |
Vegetation | NDVI | Annual Normalized Difference Vegetation Index | Yes |
Socio-economics | Distance | Euclidean Distance to the urban center, km | No |
POP | Annual population density, person km−2 | Yes | |
GDP | Annual Gross Domestic Product, yuan km−2 | Yes |
Year | Cultivated Land | Forest | Grassland | Shrubland | Wetland | Water | Artificial Surface | Barren Land |
---|---|---|---|---|---|---|---|---|
2001 | 4156.89 | 4756.36 | 1822.83 | 2993.84 | 2.38 | 206.90 | 2464.11 | 8.60 |
2005 | 4021.72 | 4815.89 | 1836.58 | 2993.47 | 2.92 | 173.41 | 2556.30 | 11.61 |
2010 | 3881.10 | 4826.72 | 1855.40 | 2997.46 | 5.02 | 182.09 | 2650.25 | 13.88 |
2015 | 3717.62 | 4853.48 | 1872.08 | 2999.60 | 5.66 | 205.10 | 2743.02 | 15.35 |
2001–2005 | −135.17 | 59.53 | 13.75 | −0.37 | 0.54 | −33.49 | 92.19 | 3.01 |
2005–2010 | −140.62 | 10.83 | 18.82 | 3.99 | 2.10 | 8.69 | 93.95 | 2.27 |
2010–2015 | −163.48 | 26.76 | 16.68 | 2.14 | 0.64 | 23.00 | 92.77 | 1.48 |
2001–2015 | −439.27 | 97.12 | 49.25 | 5.76 | 3.27 | −1.80 | 278.91 | 6.76 |
Model | R2 | Adjusted R2 | AICc | Bandwidth | Residual Sum of Squares |
---|---|---|---|---|---|
OLS | 0.635 | 0.635 | 253,079.66 | - | - |
GWR | 0.948 | 0.931 | 156,289.41 | 17 | 28,686.46 |
GTWR | 0.963 | 0.951 | 135,475.98 | 17 | 20,871.31 |
Variables | 2001 | 2005 | 2010 | 2015 |
---|---|---|---|---|
Forest | 76.94% | 85.47% | 86.23% | 87.29% |
Grassland | 45.84% | 48.55% | 49.00% | 51.46% |
Per | 78.58% | 75.73% | 82.20% | 78.31% |
Slope | 75.43% | 68.86% | 67.65% | 70.31% |
POP | 36.19% | 36.80% | 39.32% | 40.46% |
Distance | 44.30% | 46.61% | 43.77% | 55.51% |
SILT | 73.27% | 71.87% | 72.36% | 74.19% |
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Liu, B.; Qian, J.; Zhao, R.; Yang, Q.; Wu, K.; Zhao, H.; Feng, Z.; Dong, J. Spatio-Temporal Variation and Its Driving Forces of Soil Organic Carbon along an Urban–Rural Gradient: A Case Study of Beijing. Int. J. Environ. Res. Public Health 2022, 19, 15201. https://doi.org/10.3390/ijerph192215201
Liu B, Qian J, Zhao R, Yang Q, Wu K, Zhao H, Feng Z, Dong J. Spatio-Temporal Variation and Its Driving Forces of Soil Organic Carbon along an Urban–Rural Gradient: A Case Study of Beijing. International Journal of Environmental Research and Public Health. 2022; 19(22):15201. https://doi.org/10.3390/ijerph192215201
Chicago/Turabian StyleLiu, Bingrui, Jiacheng Qian, Ran Zhao, Qijun Yang, Kening Wu, Huafu Zhao, Zhe Feng, and Jianhui Dong. 2022. "Spatio-Temporal Variation and Its Driving Forces of Soil Organic Carbon along an Urban–Rural Gradient: A Case Study of Beijing" International Journal of Environmental Research and Public Health 19, no. 22: 15201. https://doi.org/10.3390/ijerph192215201