Prediction and Evaluation of Ecosystem Service Value Based on Land Use of the Yellow River Source Area
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources
2.3. Land Use Transfer Matrix Model
2.4. Ecosystem Service Value Model
2.5. PLUS Model
- (1)
- Natural development scenario (NDS): Ruling out the influences arising from policy and regional planning, the land use in 2030 was simulated according to the rate of land use change in the YRSA in 2000, 2010 and 2020. In this scenario, the transfer direction of land use types is not limited in the transfer matrix when the transfer direction is in order;
- (2)
- Ecological protection scenario (EPS): Based on the NDS, this scenario is aimed at ecological protection where the probability of the ecological land (e.g., forest, water area) transferring to anthropogenic land (e.g., farmland, construction land) shall be reduced and the probability of grassland transferring to ecological land (e.g., forest, wetland) shall be increased while the rapid expansion of construction land shall be slowed. In addition, the large water area is considered a restricted development area in this scenario;
- (3)
- Carbon neutral scenario (CNS): The goal of this scenario is to respond to the call of carbon neutral plans proposed by China. Based on EPS, the probability of construction land used for solar and water facilities in the YRSA shall be increased and the transferring probability that certain land use types (e.g., forest, water area) could contribute to the goal of carbon neutrality shall be increased to a lesser extent. In addition, the forest is considered a restricted development area in this scenario;
- (4)
- Production priority scenario (PPS): This scenario is aimed for food security. Based on EPS, the retention of farmland in the YRSA is guaranteed and the amount of farmland replenishment is increased. The probability of transferring grassland to farmland is increased while the probability that farmland transferring to other land use types is reduced. Meanwhile, the probability of transferring to farmland is increased with the intact wetland and water area. In this scenario, the water area and wetland that supply water resources for farmland are considered restricted development areas.
3. Results and Analysis
3.1. Land Use Change from 2000 to 2020
3.2. Change in the Ecosystem Services Value from 2000 to 2020
3.3. Changes in the Ecosystem Services Value by Function
3.4. Future Changes in Land Use and Ecosystem Service Value under Different Scenarios
3.4.1. Land Use Changes in 2030
3.4.2. Changes in ESV under Different Scenarios in 2030
3.5. Discussion
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Macro LULC Classes | Micro LULC Classes Information | Level of Intensity |
---|---|---|
Construction land | Surface formed by man-made construction activities, including various residential areas, industrial mines and transportation facilities in towns. | 7 |
Farmland | Land used for growing crops, including paddy fields, dry land, vegetable fields, pastureland, orchards. | 6 |
Forest | The land covered by trees with crown coverage over 30% and the land covered by shrubs with shrub coverage over 30% are forest, shrub land, open forest land and immature forest land. | 5 |
Grassland | The land covered by natural herbaceous vegetation with coverage higher than 10% includes grassland, meadow, savanna and desert grassland. | 4 |
Wetland | Land with shallow water or over-wet soil, including inland marshes, lake marshes and shrub wetlands. | 3 |
Water area | Liquid water covered areas and ice-covered areas, including rivers, lakes, glaciers, beaches. | 2 |
Unused land | Naturally covered land with less than 10% vegetation cover, including saline, sandy, bare rock and bare tundra. | 1 |
Driving Factors | Data Source |
---|---|
Precipitation | NOAA (https://www.noaa.gov/, accessed on 1 October 2021) |
Temperature | |
DEM | Geospatial Data Cloud (www.gscloud.cn, accessed on 1 October 2021) |
Slope | |
Aspect | |
Soil type | Harmonized World Soil Database v 1.2 [51] (https://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/harmonized-world-soil-database-v12/en/, accessed on 1 October 2021) |
Distance from senior roads | OpenStreetMap (https://www.openstreetmap.org/, accessed on 1 October 2021) |
Distance from minor roads | |
Distance from the river |
Ecosystem Services | Land Use Types | |||||||
---|---|---|---|---|---|---|---|---|
Primary Classification | Secondary Classification | Farmland | Forest | Grassland | Wetland | Water Area | Construction Land | Unused Land |
Provisioning services | Food supply | 777.98 | 231.11 | 213.56 | 466.79 | 366.11 | 0.00 | 4.58 |
raw material supply | 366.11 | 530.86 | 314.24 | 457.64 | 105.26 | 0.00 | 13.73 | |
Water supply | 18.31 | 274.58 | 173.90 | 2370.57 | 4782.32 | 0.00 | 9.15 | |
Regulating services | Gas regulation | 613.24 | 1745.89 | 1104.43 | 1739.02 | 434.76 | 0.00 | 59.49 |
Climate regulation | 329.50 | 5223.94 | 2919.73 | 3294.99 | 1295.12 | 0.00 | 45.76 | |
Purify environment | 91.53 | 1530.80 | 964.09 | 3294.99 | 2613.11 | 0.00 | 187.63 | |
Hydrological regulation | 247.12 | 3418.56 | 2138.70 | 22,177.14 | 50,051.88 | 0.00 | 109.83 | |
Supporting services | Soil formation and retention | 942.73 | 2125.73 | 1345.46 | 2114.29 | 425.60 | 0.00 | 68.65 |
Maintain nutrient cycling | 109.83 | 162.46 | 103.73 | 164.75 | 32.03 | 0.00 | 4.58 | |
Biodiversity protection | 118.99 | 1935.81 | 1223.42 | 7203.22 | 1171.55 | 0.00 | 64.07 | |
Cultural services | Recreation and culture | 54.92 | 848.92 | 540.01 | 4329.26 | 906.12 | 0.00 | 27.46 |
Total | 3670.26 | 18,028.65 | 11,041.28 | 47,612.67 | 62,183.86 | 0.00 | 594.93 |
Year | Farmland | Forest | Grassland | Wetland | Water Area | Construction Land | Unused Land | Total | |
---|---|---|---|---|---|---|---|---|---|
2000 | ESV | 5.8 | 6.13 | 1283.73 | 263.1 | 132.96 | 0 | 2.95 | 1694.66 |
Proportion (%) | 0.34% | 0.36% | 75.75% | 15.53% | 7.85% | 0.00% | 0.17% | ||
2010 | ESV | 7.72 | 4.56 | 1261.59 | 296.21 | 146.98 | 0 | 3.31 | 1720.38 |
Proportion (%) | 0.45% | 0.27% | 73.33% | 17.22% | 8.54% | 0.00% | 0.19% | ||
2020 | ESV | 12.08 | 4.93 | 1215.7 | 315.23 | 149.24 | 0 | 4.69 | 1701.87 |
Proportion (%) | 0.71% | 0.29% | 71.43% | 18.52% | 8.77% | 0.00% | 0.28% |
Primary Classification | Secondary Classification | 2000 | 2010 | 2020 | |
---|---|---|---|---|---|
Provisioning services | Food supply | 29.52 | 29.89 | 30.14 | |
Raw material supply | 40.12 | 39.98 | 39.34 | ||
Water supply | 43.71 | 46.08 | 46.53 | ||
Regulating services | Gas regulation | 140.80 | 140.10 | 137.13 | |
Climate regulation | 362.97 | 359.44 | 349.27 | ||
Purify environment | 137.48 | 138.46 | 136.44 | ||
Hydrological regulation | 480.32 | 502.64 | 505.05 | ||
Supporting services | Soil formation and retention | 171.58 | 170.80 | 167.39 | |
Maintain nutrient cycling | 13.29 | 13.25 | 13.03 | ||
Biodiversity protection | 185.71 | 188.47 | 186.63 | ||
Cultural services | Recreation and culture | 89.16 | 91.26 | 90.92 | |
Total | 1694.66 | 1720.38 | 1701.87 |
LULC | Area (km2) | ||||
---|---|---|---|---|---|
NDS | EPS | CNS | PPS | ||
Farmland | 4398.39 | 3254.30 | 3723.96 | 4798.71 | |
Forest | 287.39 | 473.55 | 297.00 | 285.50 | |
Grassland | 106,383.85 | 108,890.31 | 110,199.61 | 108,593.89 | |
Wetland | 7011.14 | 7062.83 | 6266.29 | 6931.61 | |
Water area | 2444.72 | 2480.58 | 2496.06 | 2439.40 | |
Construction land | 477.89 | 366.41 | 443.75 | 441.84 | |
Unused land | 9885.73 | 8361.13 | 7462.44 | 7398.14 | |
Total | 130,889.11 | 130,889.11 | 130,889.11 | 130,889.11 |
Primary Classification | Secondary Classification | 2020 | NDS | EPS | CNS | PPS |
---|---|---|---|---|---|---|
Provisioning services | Food supply | 30.14 | 30.42 | 30.14 | 30.37 | 31.15 |
Raw material supply | 39.34 | 38.80 | 39.27 | 39.38 | 39.56 | |
Water supply | 46.53 | 47.06 | 47.81 | 46.17 | 47.22 | |
Total | 116.01 | 116.28 | 117.22 | 115.93 | 117.93 | |
Regulating services | Gas regulation | 137.13 | 134.54 | 136.94 | 136.94 | 136.93 |
Climate regulation | 349.27 | 340.28 | 348.34 | 348.75 | 346.48 | |
Purify environment | 136.44 | 134.75 | 137.33 | 135.61 | 136.17 | |
Hydrological regulation | 505.05 | 508.53 | 517.02 | 502.34 | 511.04 | |
Total | 1127.88 | 1118.10 | 1139.63 | 1123.64 | 1130.62 | |
Supporting services | Soil formation and retention | 167.39 | 164.43 | 167.14 | 167.23 | 167.44 |
Maintain nutrient cycling | 13.03 | 12.84 | 13.01 | 13.03 | 13.09 | |
Biodiversity protection | 186.63 | 185.23 | 188.84 | 184.38 | 187.24 | |
Total | 367.05 | 362.51 | 368.99 | 364.65 | 367.77 | |
Cultural services | Recreation and culture | 90.92 | 90.77 | 92.44 | 89.56 | 91.57 |
Total | 90.92 | 90.77 | 92.44 | 89.56 | 91.57 | |
Total | 1701.87 | 1687.66 | 1718.28 | 1693.78 | 1707.90 |
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Lu, Z.; Song, Q.; Zhao, J.; Wang, S. Prediction and Evaluation of Ecosystem Service Value Based on Land Use of the Yellow River Source Area. Sustainability 2023, 15, 687. https://doi.org/10.3390/su15010687
Lu Z, Song Q, Zhao J, Wang S. Prediction and Evaluation of Ecosystem Service Value Based on Land Use of the Yellow River Source Area. Sustainability. 2023; 15(1):687. https://doi.org/10.3390/su15010687
Chicago/Turabian StyleLu, Zhibo, Qian Song, Jianyun Zhao, and Shiru Wang. 2023. "Prediction and Evaluation of Ecosystem Service Value Based on Land Use of the Yellow River Source Area" Sustainability 15, no. 1: 687. https://doi.org/10.3390/su15010687