Study on Ecosystem Service Value (ESV) Spatial Transfer in the Central Plains Urban Agglomeration in the Yellow River Basin, China
Abstract
:1. Introduction
2. Overview of Study Area
3. Data and Methods
3.1. Data Sources and Processing
3.2. ESV Calculation Method
3.2.1. Unit Equivalent Value
3.2.2. Amount Calculation
3.3. ESV Spatial Transfer Calculation Method
3.3.1. Spatial Transfer Radius
3.3.2. Spatial Transfer Intensity
3.3.3. Spatial Transfer Amount
4. Results
4.1. ESV Amount and Distribution
4.1.1. Amounts and Changes
4.1.2. Density Distribution
4.2. ESV Spatial Transfer Intensity and Amount
4.2.1. Spatial Transfer Intensity
4.2.2. Spatial Transfer Amount
4.3. ESV Spatial Transfer Radius and Radiation Range
4.3.1. Spatial Transfer Radius
4.3.2. Spatial Radiation Range
5. Discussion
5.1. Implications
5.2. Contributions and Limitations
6. Conclusions
- (1)
- The ESV distributions presented a trend of hinterland > metropolitan area > central city due to the spatial heterogeneity of natural resource endowment and socioeconomic development level in the Central Plains Urban Agglomeration. Additionally, the ESV could naturally be transferred from the hinterland, the main ESV transferred-out area showing increases, and the metropolitan area to the central city. The distributions of transferred ESV presented a trend of hinterland > metropolitan area.
- (2)
- The spatial transfer intensity of ESV from the hinterland to the central city was reduced, indicating a “weakening” ecological correlation between the hinterland and the central city. The spatial transfer intensity of ESV from the metropolitan area to the central city was increased due to the preliminary integration of ecological protection and governance among cities in the metropolitan area, which could ensure the central city benefit from cities in this region in terms of ES.
- (3)
- Spatial transfer was a pathway of ES delivery from the hinterland and the metropolitan area to the central city. But only very small part of ESV was delivered under natural conditions in this paper. There is still great potential for strengthening all-round intercity cooperation at the ecological protection and governance among the hinterland, the metropolitan area, and the central city, to achieve sustainable development of the urban agglomeration area.
- (4)
- The ESV spatial transfer radius and the radiation range of each city was tended to shrink. The ESV spatial transfer radius of most cities in the hinterland and the metropolitan area could not reach the central city, resulting in the inefficiency of the ESV spatial integration within the Central Plains Urban Agglomeration.
- (5)
- According to the characteristics of ESV spatial transfer, some works could be suggested to accelerate the spatial movement of ESV as well as the ecosystem-derived material and energy to provide an ecological path, solving the transboundary problems and increasing the development momentum of the Central Plains Urban Agglomeration: Firstly, the concepts of a “big region” and a “big environment” view should be established. Secondly, the intercity integration of ecological protection and governance should be promoted, especially a long-run administrative mechanism should be promoted to strengthen all-round cooperation among cities. Thirdly, an ecosystem network consisting of high-quality ES “production base” system, well connected “ecological corridor” system and feasible ES “consumption” infrastructures should be built based on current “conservation land” system and ecological infrastructures in prospective to provide carrier for ESV transfer.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Ecosystems | Land Use Types of the Original Land Use Data |
---|---|
Forest | Broad-leaved evergreen forests, deciduous broad-leaved forests, evergreen coniferous forests, deciduous coniferous forests, mixed coniferous and broad-leaved forests, evergreen broad-leaved shrub forests, deciduous broad-leaved shrub forests, evergreen coniferous shrub forests, arbor garden, shrubby garden, arbor green space, shrub green space, sparse forests, sparse shrubbery |
Grassland | Water meadow, grassland, thick growth of grass, herbaceous green space, sparse grassland |
Farmland | Paddy field, dry land |
Wetland | Wetland, forest swamp, shrub swamp, herbaceous swamp |
Rivers/lakes | Lake, reservoir/pond, rivers, canal/ditch |
Desert | Moss/lichen, bare rock, bare soil, desert/sand, saline alkali land |
Construction land | Residential land, industrial land, traffic land, mining area |
ES | Forest | Grassland | Farmland | Wetland | Rivers/Lakes | Desert | Construction Land | |
---|---|---|---|---|---|---|---|---|
Supply services | Food production | 0.33 | 0.43 | 1.00 | 0.36 | 0.53 | 0.02 | 0.00 |
Raw material production | 2.98 | 0.36 | 0.39 | 0.24 | 0.35 | 0.04 | 0.00 | |
Regulatory services | Gas regulation | 4.32 | 1.50 | 0.72 | 2.41 | 0.51 | 0.06 | 0.00 |
Climate regulation | 4.07 | 1.56 | 0.97 | 13.55 | 2.06 | 0.13 | 0.00 | |
Hydrological regulation | 4.09 | 1.52 | 0.77 | 13.44 | 18.77 | 0.07 | 0.00 | |
Waste disposal | 1.72 | 1.32 | 1.39 | 14.4 | 14.85 | 0.26 | 0.00 | |
Support services | Soil conservation | 4.02 | 2.24 | 1.47 | 1.99 | 0.41 | 0.17 | 0.00 |
Biodiversity | 4.51 | 1.87 | 1.02 | 3.69 | 3.43 | 0.40 | 0.00 | |
Culture services | Aesthetic landscape | 2.08 | 0.87 | 0.17 | 4.69 | 4.44 | 0.24 | 0.00 |
Ecosystems | Food Production | Raw Material Production | Gas Regulation | Climate Regulation | Hydrological Regulation | Waste Disposal | Soil Conservation | Biodiversity | Aesthetic Landscape |
---|---|---|---|---|---|---|---|---|---|
Forest | 625.22 | 5645.94 | 8184.72 | 7711.06 | 7748.95 | 3258.73 | 7616.33 | 8544.69 | 3940.79 |
Grassland | 814.68 | 682.06 | 2841.92 | 2955.59 | 2879.81 | 2500.89 | 4243.93 | 3542.92 | 1648.31 |
Farmland | 1894.61 | 738.90 | 1364.12 | 1837.77 | 1458.85 | 2633.51 | 2785.08 | 1932.50 | 322.08 |
Wetland | 682.06 | 454.71 | 4566.01 | 25,671.97 | 25,463.56 | 27,282.38 | 3770.27 | 6991.11 | 8885.72 |
Rivers/lakes | 1004.14 | 663.11 | 966.25 | 3902.90 | 35,561.83 | 28,134.96 | 776.79 | 6498.51 | 8412.07 |
Desert | 37.89 | 75.78 | 113.68 | 246.30 | 132.62 | 492.60 | 322.08 | 757.84 | 454.71 |
Construction land | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
Region | Cities | 2000 (RMB, Billion) | 2018 (RMB, Billion) | 2018–2000 (RMB, Billion) | Change Rate (%) |
---|---|---|---|---|---|
Central city | Zhengzhou | 9.816 | 19.346 | 9.531 | 97.097 |
Metropolitan area | Kaifeng | 7.626 | 12.206 | 4.580 | 60.058 |
Jiaozuo | 6.558 | 8.941 | 2.384 | 36.353 | |
Xuchang | 5.666 | 10.260 | 4.593 | 81.062 | |
Xinxiang | 10.947 | 17.655 | 6.708 | 61.277 | |
Hinterland | Anyang | 9.984 | 15.633 | 5.649 | 56.581 |
Bengbu | 7.586 | 11.969 | 4.382 | 57.764 | |
Bozhou | 10.660 | 16.878 | 6.217 | 58.321 | |
Fuyang | 13.179 | 20.493 | 7.315 | 55.505 | |
Handan | 13.909 | 27.222 | 13.313 | 95.715 | |
Heze | 14.437 | 25.341 | 10.904 | 75.528 | |
Hebi | 2.783 | 4.627 | 1.845 | 66.295 | |
Huaibei | 3.626 | 5.892 | 2.266 | 62.493 | |
Jiyuan | 4.462 | 4.276 | −0.186 | −4.169 | |
Jincheng | 25.239 | 19.377 | −5.863 | −23.230 | |
Liaocheng | 9.675 | 18.378 | 8.703 | 89.953 | |
Luoyang | 46.870 | 31.899 | −14.971 | −31.942 | |
Luohe | 3.160 | 5.500 | 2.340 | 74.051 | |
Nanyang | 64.349 | 52.009 | −12.341 | −19.178 | |
Pingdingshan | 13.685 | 16.445 | 2.760 | 20.168 | |
Puyang | 4.707 | 8.973 | 4.266 | 90.631 | |
Sanmenxia | 29.941 | 21.160 | −8.781 | −29.328 | |
Shangqiu | 12.729 | 21.940 | 9.211 | 72.362 | |
Xinyang | 44.566 | 35.267 | −9.299 | −20.866 | |
Xingtai | 16.427 | 26.594 | 10.167 | 61.892 | |
Suzhou | 12.390 | 19.797 | 7.407 | 59.782 | |
Yuncheng | 19.755 | 28.344 | 8.588 | 43.473 | |
Changzhi | 26.581 | 30.164 | 3.584 | 13.483 | |
Zhoukou | 14.816 | 24.220 | 9.404 | 63.472 | |
Zhumadian | 24.252 | 29.287 | 5.035 | 20.761 | |
Total | 490.380 | 590.091 | 99.711 | 20.333 |
Region | City | 2000 (RMB, 10,000/km2) | 2018 (RMB, 10,000/km2) | 2018–2000 (RMB, 10,000/km2) |
---|---|---|---|---|
Central city | Zhengzhou | / | / | / |
Metropolitan area | Kaifeng | 82.98 | 132.82 | 49.84 |
Jiaozuo | 165.61 | 225.80 | 60.20 | |
Xuchang | 129.89 | 235.18 | 105.30 | |
Xinxiang | 132.50 | 213.70 | 81.20 | |
Hinterland | Anyang | 49.97 | 78.24 | 28.27 |
Bengbu | 4.99 | 7.87 | 2.88 | |
Bozhou | 13.56 | 21.47 | 7.91 | |
Changzhi | 57.69 | 65.47 | 7.78 | |
Fuyang | 16.78 | 26.09 | 9.31 | |
Handan | 24.61 | 48.17 | 23.56 | |
Hebi | 14.41 | 23.96 | 9.55 | |
Heze | 33.35 | 58.54 | 25.19 | |
Huaibei | 3.8 | 6.17 | 2.37 | |
Jincheng | 147.85 | 113.51 | −34.34 | |
Jiyuan | 36.39 | 34.87 | −1.52 | |
Liaocheng | 10.9 | 20.7 | 9.8 | |
Luohe | 23.42 | 40.76 | 17.34 | |
Luoyang | 254.85 | 173.45 | −81.4 | |
Nanyang | 147.85 | 119.49 | −28.35 | |
Pingdingshan | 130.02 | 156.24 | 26.22 | |
Puyang | 11.43 | 21.79 | 10.36 | |
Sanmenxia | 47.89 | 33.84 | −14.05 | |
Shangqiu | 30.36 | 52.33 | 21.97 | |
Suzhou | 10.13 | 16.19 | 6.06 | |
Xingtai | 16.48 | 26.69 | 10.2 | |
Xinyang | 45 | 35.61 | −9.39 | |
Yuncheng | 38.86 | 55.75 | 16.89 | |
Zhoukou | 55.6 | 90.89 | 35.29 | |
Zhumadian | 59.55 | 71.92 | 12.37 |
Region | City | 2000 (RMB, Billion) | 2018 (RMB, Billion) | 2018–2000 (RMB, Billion) | Change Rate (%) |
---|---|---|---|---|---|
Central city | Zhengzhou | / | / | / | / |
Metropolitan area | Kaifeng | 3.153 | 4.507 | 1.354 | 42.943 |
Xinxiang | 5.441 | 7.94 | 2.499 | 45.929 | |
Jiaozuo | 2.499 | 2.759 | 0.26 | 10.404 | |
Xuchang | 1.99 | 3.432 | 1.442 | 72.462 | |
Subtotal | 13.083 | 18.638 | 5.555 | 42.460 | |
Hinterland | Hebi | 0.633 | 0.94 | 0.307 | 48.499 |
Luohe | 0.78 | 1.253 | 0.473 | 60.641 | |
Huaibei | 0.976 | 1.404 | 0.428 | 43.852 | |
Jiyuan | 1.363 | 0.824 | −0.539 | −39.545 | |
Puyang | 1.485 | 2.775 | 1.29 | 86.869 | |
Bengbu | 3.128 | 4.371 | 1.243 | 39.738 | |
Liaocheng | 4.524 | 8.435 | 3.911 | 86.450 | |
Anyang | 4.743 | 6.6 | 1.857 | 39.152 | |
Bozhou | 5.23 | 7.416 | 2.186 | 41.797 | |
Suzhou | 6.534 | 9.432 | 2.898 | 44.353 | |
Shangqiu | 6.798 | 10.993 | 4.195 | 61.709 | |
Fuyang | 7.153 | 9.932 | 2.779 | 38.851 | |
Pingdingshan | 7.558 | 7.129 | −0.429 | −5.676 | |
Handan | 7.74 | 15.098 | 7.358 | 95.065 | |
Heze | 8.171 | 13.598 | 5.427 | 66.418 | |
Zhoukou | 8.483 | 12.723 | 4.24 | 49.982 | |
Xingtai | 9.845 | 14.593 | 4.748 | 48.228 | |
Yuncheng | 12.805 | 16.012 | 3.207 | 25.045 | |
Zhumadian | 17.067 | 16.791 | −0.276 | −1.617 | |
Jincheng | 18.038 | 9.134 | −8.904 | −49.362 | |
Changzhi | 19.375 | 17.523 | −1.852 | −9.559 | |
Sanmenxia | 22.81 | 10.417 | −12.393 | −54.331 | |
Xinyang | 38.892 | 21.93 | −16.962 | −43.613 | |
Luoyang | 41.56 | 18.994 | −22.566 | −54.297 | |
Nanyang | 62.697 | 37.806 | −24.891 | −39.700 | |
Subtotal | 318.388 | 276.123 | −42.265 | −13.275 | |
Total | 331.471 | 294.763 | −36.71 | −11.075 |
Region | City | 2000 (RMB, Billion) | 2018 (RMB, Billion) | 2018–2000 (RMB, Billion) | 2000–2018 (%) |
---|---|---|---|---|---|
Metropolitan area | Kaifeng | 0.140 | 0.120 | −0.020 | −14.286 |
Xinxiang | 0.194 | 0.206 | 0.012 | 6.186 | |
Jiaozuo | 0.076 | 0.026 | −0.050 | −65.789 | |
Xuchang | 0.032 | 0.042 | 0.010 | 31.250 | |
Subtotal | 0.442 | 0.394 | −0.048 | −10.860 | |
Hinterland | Luoyang | 1.264 | 0.140 | −1.124 | −88.924 |
Pingdingshan | 0.010 | 0.000 | −0.010 | −100.000 | |
Subtotal | 1.274 | 0.140 | −1.134 | −89.011 | |
Total | 1.716 | 0.534 | −1.182 | −68.881 |
Region | City | 2000 (km) | 2018 (km) | 2018–2000 (km) | Change Rate (%) |
---|---|---|---|---|---|
Central city | Zhengzhou | / | / | / | / |
Metropolitan area | Jiaozuo | 28.30 | 25.47 | −2.83 | −10.02 |
Xuchang | 28.52 | 27.83 | −0.69 | −2.40 | |
Xinxiang | 46.69 | 44.41 | −2.28 | −4.88 | |
Kaifeng | 44.91 | 42.44 | −2.47 | −5.51 | |
Hinterland | Luohe | 42.05 | 40.40 | −1.65 | −3.93 |
Jiyuan | 44.59 | 35.41 | −9.18 | −20.59 | |
Hebi | 48.29 | 45.65 | −2.64 | −5.47 | |
Pingdingshan | 55.55 | 49.21 | −6.33 | −11.40 | |
Anyang | 70.98 | 66.91 | −4.06 | −5.72 | |
Jincheng | 80.47 | 65.35 | −15.12 | −18.79 | |
Puyang | 83.03 | 82.21 | −0.82 | −0.99 | |
Zhoukou | 89.99 | 86.20 | −3.79 | −4.21 | |
Luoyang | 93.04 | 76.24 | −16.80 | −18.05 | |
Shangqiu | 109.02 | 105.60 | −3.42 | −3.14 | |
Heze | 114.03 | 111.04 | −2.99 | −2.63 | |
Huaibei | 116.79 | 109.87 | −6.93 | −5.93 | |
Zhumadian | 123.33 | 111.32 | −12.01 | −9.74 | |
Handan | 129.19 | 128.98 | −0.21 | −0.16 | |
Yuncheng | 132.25 | 123.47 | −8.78 | −6.64 | |
Changzhi | 133.51 | 119.19 | −14.32 | −10.73 | |
Bozhou | 143.09 | 135.41 | −7.68 | −5.36 | |
Liaocheng | 148.45 | 147.07 | −1.37 | −0.93 | |
Nanyang | 150.03 | 129.59 | −20.44 | −13.62 | |
Fuyang | 150.43 | 142.15 | −8.28 | −5.51 | |
Sanmenxia | 159.00 | 127.82 | −31.18 | −19.61 | |
Xingtai | 178.05 | 170.37 | −7.68 | −4.31 | |
Bengbu | 182.45 | 171.70 | −10.76 | −5.89 | |
Suzhou | 184.99 | 175.83 | −9.16 | −4.95 | |
Xinyang | 214.17 | 180.79 | −33.39 | −15.59 |
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Liu, M.; Fan, J.; Wang, Y.; Hu, C. Study on Ecosystem Service Value (ESV) Spatial Transfer in the Central Plains Urban Agglomeration in the Yellow River Basin, China. Int. J. Environ. Res. Public Health 2021, 18, 9751. https://doi.org/10.3390/ijerph18189751
Liu M, Fan J, Wang Y, Hu C. Study on Ecosystem Service Value (ESV) Spatial Transfer in the Central Plains Urban Agglomeration in the Yellow River Basin, China. International Journal of Environmental Research and Public Health. 2021; 18(18):9751. https://doi.org/10.3390/ijerph18189751
Chicago/Turabian StyleLiu, Min, Jianpeng Fan, Yating Wang, and Chanjuan Hu. 2021. "Study on Ecosystem Service Value (ESV) Spatial Transfer in the Central Plains Urban Agglomeration in the Yellow River Basin, China" International Journal of Environmental Research and Public Health 18, no. 18: 9751. https://doi.org/10.3390/ijerph18189751