Trade-Offs and Synergies in the Species–Carbon–Water–Food–Economy Functional Nexus in China’s Provinces from a Socio-Ecological System Perspective
Abstract
1. Introduction
2. Materials and Methods
2.1. Functional Nexus Linkage Mechanisms
2.2. Ecosystem Functions Evaluation
2.3. Economic Development Functions Evaluation
2.3.1. Evaluation Indicator System
2.3.2. Measurement of Economic Development Functions
2.4. Functional Nexus Trade-Offs and Synergies
2.5. Redundancy Analysis
2.6. Functional Policy Goals
2.7. Data Sources
3. Results
3.1. Temporal Variation
3.2. Spatio-Temporal Patterns
3.2.1. Spatio-Temporal Patterns of Ecosystem Functions
3.2.2. Spatio-Temporal Patterns of Economic Development Functions
3.3. Trade-Offs and Synergies Among Different Functions
3.4. Redundancy Analysis of SES
3.5. Trade-Offs and Synergies Among Policy Goals
4. Discussion
4.1. Functional Evolution Characteristics
4.2. Functional Trade-Offs and Synergies
4.3. Coordinate the Five-Pool Functional Nexus of SES
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
| Functions | Dimensions | Policy Goals |
|---|---|---|
| Species protection | S1 | Improve biodiversity monitoring and establish the regulatory system |
| S2 | Protect wild, rare, and endangered species | |
| S3 | Enhance the management and control of invasive alien species | |
| S4 | Improve the biotechnological level of germplasm resource variety improvement | |
| S5 | Protect natural resources, reduce environmental pollution, and enhance ecosystem quality and stability | |
| Carbon sink | C1 | Promote clean production and the transformation of traditional energy industries |
| C2 | Significant improvement in utilization efficiency | |
| C3 | Promote green and low-carbon consumption patterns | |
| C4 | Enhance the carbon sequestration capacity of ecosystems | |
| Water conservation | W1 | Ensure the safety of centralized drinking water sources |
| W2 | Optimize the water resource allocation pattern and improve allocation efficiency | |
| W3 | Control the total water resource utilization and development intensity | |
| W4 | Improve the utilization efficiency | |
| W5 | Strengthen water pollution prevention and control | |
| Food supply | F1 | Strictly adhere to the farmland red line and build high-standard farmland |
| F2 | Convert farmland back to forests and grasslands | |
| F3 | Ensure stable food supply and prices | |
| F4 | Implement the “Technology-Driven Grain” initiative | |
| F5 | Enhance the capacity for agricultural waste recycling | |
| Economic development | E1 | Increase fiscal and tax support and develop green finance |
| E2 | Develop smart tourism | |
| E3 | Strengthen the management of natural resource assets and improve the mechanism for realizing the value of ecological products | |
| E4 | Vigorously develop the new energy industry | |
| E5 | Increase the added value of agricultural products |
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| Ecosystem Functions | Assessment Method | Computational Formula | Variable |
|---|---|---|---|
| Species protection | Invest model habitat quality module | Where represents the habitat maintenance dimension of land use type j raster x, represents the degree of habitat degradation for land use type j raster x, and represents the degree of habitat suitability of land use type j. | |
| Carbon sink | Estimated as a function of Net Primary Production (NPP) | Where represents the amount of oxygen sequestered by image , and represents the value of NPP of image . | |
| Water conservation | Water balance equation | Where represents water yield, represents flow-producing rainfall, represents surface runoff, represents evapotranspiration, represents ecosystem area, represents ecosystem type, and represents total number of ecosystem types. | |
| Food supply | NDVI estimation method | Where and represent the output of material products of image , the total output of material products (grain, meat, vegetables) of each county, and represent the NDVI of farmland (or grassland) of image , and the total value of farmland (or grassland) of the whole county. |
| Economic Development Functions | Indicator | Unit | Causality | Weights |
|---|---|---|---|---|
| Ecological investments | Investment in ecological construction and protection | 104 yuan | + | 0.2554 |
| Expenditure on energy conservation and environmental protection | 108 yuan | + | 0.3471 | |
| Investment in drainage and pollution control | 104 yuan | + | 0.3875 | |
| Growth rate of investment in agriculture, forestry, animal husbandry and fishery | % | + | 0.0099 | |
| Environmental outputs | Forest and grass cover | % | + | 0.3769 |
| Carbon emission intensity | t/104 yuan | − | 0.0876 | |
| Proportion of Classes I-III water quality sections | % | − | 0.3615 | |
| Growth rate of primary industry output | % | + | 0.1740 | |
| Social benefits | per capita GDP | yuan | + | 0.3538 |
| per capita disposable income | yuan | + | 0.4008 | |
| Gini coefficient | - | − | 0.2077 | |
| Urban-rural consumption ratio | - | − | 0.0377 |
| Data | Description | Source |
|---|---|---|
| Land use data | Land use types | Resource and Environmental Science Data Platform (http://www.resdc.cn/ (accessed on 8 July 2024)) (2000–2020) |
| Vegetation data | NDVI data and NPP data | National Ecosystem Science Data Center (http://www.nesdc.org.cn/ (accessed on 8 July 2024)) (2000–2020) Earth Resources Data Cloud Platform (http://www.gis5g.com/ (accessed on 9 July 2024)) (2000) MODIS_MOD17A3 on Google Earth Engine (GEE) (https://lpdaac.usgs.gov/products/mod17a3hgfv061/ (accessed on 9 July 2024)) (2001–2020) |
| Meteorological data | Rainfall data and evapotranspiration data | National Earth System Science Data Center (https://www.geodata.cn/ (accessed on 10 July 2024)) (2000–2020) National Tibetan Plateau Data Center (https://data.tpdc.ac.cn/ (accessed on 10 July 2024)) (2000–2020) |
| Soil data | World soil dataset | International Institute for Applied Systems Analysis (IIASA) and the Food and Agriculture Organization (FAO) of the United Nations (https://iiasa.ac.at/models-tools-data/hwsd (accessed on 10 July 2024)) |
| Statistical data | Food production, ecological investments, environmental outputs, and social benefits | China County Statistical Yearbook, China Environmental Statistical Yearbook, China Ecological and Environmental Status Bulletin, and so on (2000–2020) |
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Liu, Y.; Wang, Y.; Long, P. Trade-Offs and Synergies in the Species–Carbon–Water–Food–Economy Functional Nexus in China’s Provinces from a Socio-Ecological System Perspective. Land 2025, 14, 2336. https://doi.org/10.3390/land14122336
Liu Y, Wang Y, Long P. Trade-Offs and Synergies in the Species–Carbon–Water–Food–Economy Functional Nexus in China’s Provinces from a Socio-Ecological System Perspective. Land. 2025; 14(12):2336. https://doi.org/10.3390/land14122336
Chicago/Turabian StyleLiu, Yuhan, Yongsheng Wang, and Pei Long. 2025. "Trade-Offs and Synergies in the Species–Carbon–Water–Food–Economy Functional Nexus in China’s Provinces from a Socio-Ecological System Perspective" Land 14, no. 12: 2336. https://doi.org/10.3390/land14122336
APA StyleLiu, Y., Wang, Y., & Long, P. (2025). Trade-Offs and Synergies in the Species–Carbon–Water–Food–Economy Functional Nexus in China’s Provinces from a Socio-Ecological System Perspective. Land, 14(12), 2336. https://doi.org/10.3390/land14122336
