Ecological Security Pattern Construction and Multi-Scenario Risk Early Warning (2020–2035) in the Guangdong–Hong Kong–Macao Greater Bay Area, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources and Processing
2.3. Delineation of Ecological Security Risk Zones
2.3.1. Habitat Quality Assessment
2.3.2. Landscape Ecological Risk Model
2.4. Identifying Ecological Security Patterns
2.4.1. Identify Ecological Sources
- (1)
- Ecosystem service value assessment
- (2)
- Ecosystem sensitivity assessment
- (3)
- Landscape connectivity evaluation
2.4.2. Resistance Surface Construction
2.4.3. Corridors and Pinch Points Extraction
2.5. Multi-Scenario Risk Early Warning of Ecological Security Patterns
- (1)
- The NDS analyzes the land use change trend in the study area from 2000 to 2020 using the Markov model, without considering various macro-policy regulation requirements, to predict the future demand for each land type.
- (2)
- The EPS considers the environmental carrying capacity and ensures ecological benefits, building on the natural development scenario. Specific settings: grassland and forestland to built-up land is reduced by 30%, arable land and waters to built-up land by 20%, and built-up land to forestland is increased by 10%.
- (3)
- The EDS prioritizes economic benefits, aiming to boost economic output and urbanization rates, based on the natural development scenario. Specific settings: arable land, forestland, and grassland to built-up land increase by 20%, while built-up land to non-arable landscape types decreases by 30%.
3. Results
3.1. Results of Ecological Security Risk Zones Division
3.2. Ecological Security Patterns
3.2.1. Ecological Source and Resistance Surface
3.2.2. Ecological Security Patterns
3.2.3. Multi-Level Ecological Security Patterns
3.3. Early Warning of Ecological Security Pattern Risk
- (1)
- Under the NDS, the warning level is between the EPS and EDS. The ecological source warning level is relatively good, and the number of severe and extreme warnings is at a low level. The number of severe and extreme warnings in ecological corridors is relatively large, mainly distributed in the center of the study area, connecting all parts of the area. The situation of ecological sources is slightly serious and needs to be addressed. In pinch points, there are many severe warnings, mainly in ecological corridors on both sides of the Pearl River Estuary.
- (2)
- Under the EPS, the regional ecological security situation is obviously optimized. All ecological sources are in a state of no warning, which is conducive to ensuring regional ecological security. Most ecological corridors are kept in a state of no warning or mild warning to ensure the connectivity of regional landscape. There is no moderate warning alarm or above for pinch points, which can ensure the stability of key nodes. It shows that under the policy guidance of ecological priority, ESP is well maintained, and biodiversity and ecosystem service functions are maintained at a healthy level.
- (3)
- Under the EDS, the ecological pressure faced by the study area suddenly increases, and the total area of regional early warning is as high as 358.17 km2. The total number of severe and extreme warnings in ecological sources, corridors, and pinch points is as high as 101, seven times that of NDS. Among them, pinch points are in an all-round alert state, and the migration and diffusion of ecological flow will be hindered. This indicates that under the influence of rapid economic growth, if appropriate ecological protection measures are not taken, the integrity of regional ecological sources and ecological networks will be seriously threatened.
4. Discussion
4.1. Feasibility Analysis of Risk Early Warning Methods for Ecological Security Patterns
4.2. Implications of Ecological Security Pattern Risk Assessment and Multi-Scenario Risk Early Warning
4.3. Limitations and Future Research Prospects
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Data Category | Data Name | Time | Resolution | Data Source |
---|---|---|---|---|
Land use | Land use data of GHKMGBA | 2000, 2010, 2020 | 30 m | National Ecological Science Data Center https://www.resdc.cn (accessed on 3 May 2023) |
Meteorological data | Annual average temperature | 2020 | 1 km | |
Annual average precipitation | 2020 | 1 km | ||
Socioeconomic data | Population density | 2019 | 1 km | |
GDP | 2020 | 1 km | ||
Nighttime light | 2020 | 1 km | ||
Road | 2020 | - | OpenStreetMap https://www.openstreetmap.org (accessed on 3 May 2023) | |
Natural environment data | River | 2020 | - | |
Potential evapotranspiration | 2020 | 1 km | National Tibetan Plateau https://data.tpdc.ac.cn (accessed on 3 May 2023) | |
Vegetation cover | 2020 | 250 m | ||
Soil data | 2013 | 1 km | Harmonized World Soil Database from FAO (https://www.fao.org/) (accessed on 23 May 2024) | |
DEM | 2020 | 30 m | Geospatial Data Cloud (www.gscloud.cn) (accessed on 3 May 2023) | |
Slope/relief degree of land surface data | 2020 | 30 m | Based on DEM calculation |
Habitat Quality Level | Landscape Ecological Risk Level | ||
---|---|---|---|
Low | Medium | High | |
Poor | III | III | III |
Moderate | II | II | III |
Good | I | II | III |
Ecosytem Service Index | Calculation Formula | Explanation | Reference |
---|---|---|---|
Soil conservation | SC represents the soil conservation capacity of unit i, R is the rainfall erosivity factor, K is the soil erodibility factor, LS is the topographic factor, C is the vegetation coverage factor, and P is the factor of soil and water conservation measures. Among them, the K factor is calculated based on the world soil database, R is calculated based on the annual rainfall data, LS is calculated based on DEM, and C and P are set according to the existing related research. | [7,56,57] | |
Water yield | WY(x) represents the annual water supply of unit x, AET(x) is the annual actual evapotranspiration of unit x, PET(x) is the annual potential evapotranspiration of unit x, and PRE(x) is the annual precipitation of unit x. | [58] | |
Carbon sequestration | Ci is the total carbon storage of type i, Ci-above and Ci-below are the aboveground and underground carbon densities of type i, Ci-soil is the soil organic carbon density of type i, Ci-dead is the dead organic carbon density of type i, Ctotal is the regional total carbon storage, and Si is the area of type i. Concerning A dataset of carbon density in Chinese terrestrial ecosystems (2010s) and related research is used. | [25,59] |
Land Use Class I | Land Use Class II | Resistance Value |
---|---|---|
Arable land | paddy field | 10 |
Dryland | 15 | |
Forestland | Shrubland | 10 |
Forestland | 5 | |
Other forestland | 8 | |
Grassland | High-cover grassland | 10 |
Medium-cover grassland | 8 | |
Low-cover grassland | 5 | |
Water area | Canals | 10 |
Rivers | 20 | |
Reservoirs | 15 | |
Mudflats | 20 | |
Built-up land | Urban built-up land | 50 |
Rural built-up land | 40 | |
Other built-up land | 45 | |
Unused land | sandy land | 30 |
marshland | 35 | |
bare ground | 20 | |
Other unused land | 15 |
Buffer Zone Level | |||
---|---|---|---|
Buffer Type | I | II | III |
Ecological corridor buffer zone | 1 km | 2 km | 3 km |
Pinch point buffer zone | 3 km | 4 km | 5 km |
Area of Encroachment on Ecological Sources (km2) | Area of Encroachment on Ecological Corridor Buffer Zones (km2) | Area of Encroachment on the Buffer Zone of Pinch Points (km2) | Warning Level | Warning Situation |
---|---|---|---|---|
0 ≤ area < 0.21 | 0 ≤ area < 0.09 | 0 ≤ area < 0.05 | V | No warning |
0.21 ≤ area < 0.66 | 0.09 ≤ area < 0.78 | 0.05 ≤ area < 1.15 | IV | Light warning |
0.66 ≤ area < 1.71 | 0.78 ≤ area < 4.27 | 1.15 ≤ area < 3.51 | III | Medium warning |
1.71 ≤ area < 5.76 | 4.27 ≤ area < 14.81 | 3.51 ≤ area < 5.6 | II | Severe warning |
5.76 ≤ area < 61.73 | 14.81 ≤ area < 110.61 | 5.6 ≤ area < 17.36 | I | Extreme Warning |
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Ma, J.; Mei, Z.; Wang, X.; Li, S.; Liang, J. Ecological Security Pattern Construction and Multi-Scenario Risk Early Warning (2020–2035) in the Guangdong–Hong Kong–Macao Greater Bay Area, China. Land 2024, 13, 1267. https://doi.org/10.3390/land13081267
Ma J, Mei Z, Wang X, Li S, Liang J. Ecological Security Pattern Construction and Multi-Scenario Risk Early Warning (2020–2035) in the Guangdong–Hong Kong–Macao Greater Bay Area, China. Land. 2024; 13(8):1267. https://doi.org/10.3390/land13081267
Chicago/Turabian StyleMa, Junjie, Zhixiong Mei, Xinyu Wang, Sichen Li, and Jiangsen Liang. 2024. "Ecological Security Pattern Construction and Multi-Scenario Risk Early Warning (2020–2035) in the Guangdong–Hong Kong–Macao Greater Bay Area, China" Land 13, no. 8: 1267. https://doi.org/10.3390/land13081267