Assessment of Regional Ecosystem Health—A Case Study of the Golden Triangle of Southern Fujian Province, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources
2.3. Analysis of Landscape Pattern
2.3.1. Shannon’s Diversity Index
2.3.2. Shannon’s Evenness Index (SHEI)
2.3.3. Landscape Fragmentation Index (FN)
2.4. Evaluation Indexes Used in the PSR Model and Determination of Index Weight
2.4.1. PSR Model
2.4.2. Evaluation of Indexes
2.4.3. Determination of Index Weight
- , Element and element j are of the same importance to the upper level
- , Element is slightly more important than element j
- , Element is more important than element j
- , Element is much more important than element j
- , Element is of even greater importance than element j
- , n = 1, 2, 3, 4… The importance of elements i and j are between and
2.5. Evaluation Method
2.5.1. Standardization of Indexes
2.5.2. Comprehensive Evaluation of Ecosystem Health
3. Results
3.1. Landscape Pattern Analysis
3.1.1. Shannon’s Diversity Index (H)
3.1.2. Shannon’s Evenness Index (SHEI)
3.1.3. FN
3.2. Evaluation of Ecosystem Health
3.3. Analysis of Regional Ecosystem Health Elements in the Study Areas
3.3.1. Pressure
3.3.2. State
3.3.3. Response
4. Discussion
4.1. Identification of Main Controlling Factors
4.2. Spatial Correlation between Ecological Health and Urbanization
4.3. Sensitivity of the Indexes Used to Evaluate Ecological Health
4.4. Innovation and Prospect
4.4.1. Innovation Compared with Other Authors’ Previous Works
4.4.2. Future Work Prospect
5. Conclusions
- (1)
- There is a wide variation in the ecosystem health of different cities; this is primarily due to the extremely low ecosystem health status of Xiamen compared with Zhangzhou and Quanzhou. The poor ecosystem health of Xiamen is primarily due to its development as the political, economic, and cultural center of Fujian. In Xiamen, economic development, urban infrastructure, and environmental facilities are superior to those in in Zhangzhou and Quanzhou.
- (2)
- Ecosystem health is determined by the interactions between numerous ecological factors. In order to understand the influence of these factors on the ecological health of the area, we calculated the main factors affecting ecosystem health. Ecosystem health states were calculated using the mean values of the primary ecological factors influencing the ecosystem and by determining the main control factors in different ecosystems.
- (3)
- Ecological health exhibits a significant negative correlation with the urbanization rate, GDP, and development in Southern Fujian. This suggests that urbanization and industrialization contribute to a decline in the ecosystem health.
- (4)
- Because of the gaps in the available data, we were unable to perform a longitudinal study assessing changes in ecosystem health in the study region over time. We will attempt to address this issue in future research.
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Elements | Index Type | Index Name | Weight [36,37,38,39,40] |
---|---|---|---|
Pressure | Land | Land reclamation (−) C1 | 0.0678 |
Population | Human interference index (−) C2 | 0.0661 | |
State | Vitality | Average carbon density (−) C3 | 0.0501 |
Per capita GDP (+) C4 | 0.0596 | ||
Comprehensive industrial economic benefits (−) C5 | 0.0617 | ||
Organization structure | Landscape fragmentation index (−) C6 | 0.0612 | |
Shannon‘s evenness index (+) C7 | 0.0665 | ||
Shannon‘s diversity index (+) C8 | 0.0625 | ||
Vegetation cover index (+) C9 | 0.0549 | ||
Third industry accounts for GDP (+) C10 | 0.0631 | ||
Restoring force | Ecological elasticity (+) C11 | 0.0674 | |
Support power | Per capita road area (+) C12 | 0.0631 | |
Per capita public green space area (+) C13 | 0.0516 | ||
Response | Natural response | Water and soil conservation (+) C14 | 0.0524 |
Social and economic response | Treatment rate of industrial waste waste (+) C15 | 0.0553 | |
Utilization of industrial solid waste (−) C16 | 0.0543 | ||
Environmental investment accounts for GDP (+) C17 | 0.0424 |
Health Levels | Health State | Assessment Value |
---|---|---|
1 | Very good | 8.0–10.0 |
2 | Good | 6.0–8.0 |
3 | Normal | 4.0–6.0 |
4 | Poor | 4.0–6.0 |
5 | Extremely poor | 0.0–2.0 |
Study Areas | SHEI | H | FN |
---|---|---|---|
Si’ming | 0.09 | 0.42 | 0.26 |
Haicang | 0.18 | 0.68 | 0.18 |
Huli | 0.12 | 0.53 | 0.23 |
Ji’mei | 0.28 | 0.71 | 0.18 |
Tong’an | 0.29 | 0.86 | 0.20 |
Xiang’an | 0.26 | 0.72 | 0.18 |
Licheng | 0.24 | 0.61 | 0.22 |
Fengze | 0.19 | 0.58 | 0.24 |
Luojiang | 0.25 | 0.62 | 0.22 |
Quangang | 0.27 | 0.72 | 0.19 |
Hui’an | 0.16 | 0.63 | 0.21 |
Anxi | 0.30 | 0.83 | 0.19 |
Yongchun | 0.31 | 0.98 | 0.17 |
Dehua | 0.38 | 1.23 | 0.05 |
Shishi | 0.21 | 0.69 | 0.11 |
Jinjiang | 0.17 | 0.62 | 0.13 |
Nan’an | 0.28 | 0.86 | 0.09 |
Xiangcheng | 0.26 | 0.84 | 0.10 |
Longwen | 0.18 | 0.78 | 0.16 |
Yunxiao | 0.28 | 0.92 | 0.09 |
Zhangpu | 0.29 | 0.96 | 0.08 |
Zhao’an | 0.25 | 0.91 | 0.09 |
Changtai | 0.24 | 0.81 | 0.12 |
Dongshan | 0.27 | 0.88 | 0.07 |
Nanjing | 0.36 | 1.08 | 0.04 |
Pinghe | 0.31 | 1.02 | 0.08 |
Hua’an | 0.33 | 1.06 | 0.07 |
Longhai | 0.26 | 0.83 | 0.11 |
Indexes Number | Ecosystem Health Levels | |||||
---|---|---|---|---|---|---|
Very Good | Good | Normal | Poor | Extremely Poor | Mean | |
C1 | −109.1 | −56.4 | −20.3 | −16.3 | −86.9 | −57.8 |
C2 | −14.7 | −80.6 | −150.9 | −46.3 | −102.8 | −79.06 |
C3 | 66.1 | 15.8 | 92.4 | 55.4 | 18.8 | 49.7 |
C4 | 2.4 | 5.8 | 10.1 | 19.4 | 22.5 | 12.04 |
C5 | −58.3 | −30.8 | −28.6 | −20.3 | −79.4 | −43.48 |
C6 | −99.3 | −48.1 | −140.2 | −30.4 | −109.5 | −85.5 |
C7 | 96.3 | 20.5 | 99.1 | 66.3 | 48.9 | 66.22 |
C8 | 102.8 | 45.5 | 102.5 | 142.5 | 38.4 | 86.3 |
C9 | 114.4 | 37.0 | 40.3 | 150.2 | 67.6 | 81.9 |
C10 | 61.0 | 152.4 | 26.3 | 62.1 | 56.1 | 71.6 |
C11 | 147.5 | 162.8 | 81.2 | 184.7 | 16.7 | 118.6 |
C12 | 64.3 | 139.9 | 67.6 | 109.5 | 68.4 | 89.9 |
C13 | 29.9 | 70.8 | 64.2 | 194.9 | 40.7 | 80.1 |
C14 | 21.3 | 18.1 | 77.4 | 175.5 | 8.7 | 60.2 |
C15 | 9.7 | 177.2 | 38.1 | 215.9 | 37.5 | 95.7 |
C16 | 29.6 | 125.2 | 60.2 | 117.9 | 65.6 | 79.7 |
C17 | 15.4 | 87.5 | 58.2 | 180.8 | 23.9 | 73.1 |
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Wang, Z.; Tang, L.; Qiu, Q.; Chen, H.; Wu, T.; Shao, G. Assessment of Regional Ecosystem Health—A Case Study of the Golden Triangle of Southern Fujian Province, China. Int. J. Environ. Res. Public Health 2018, 15, 802. https://doi.org/10.3390/ijerph15040802
Wang Z, Tang L, Qiu Q, Chen H, Wu T, Shao G. Assessment of Regional Ecosystem Health—A Case Study of the Golden Triangle of Southern Fujian Province, China. International Journal of Environmental Research and Public Health. 2018; 15(4):802. https://doi.org/10.3390/ijerph15040802
Chicago/Turabian StyleWang, Ziyan, Lina Tang, Quanyi Qiu, Huaxiang Chen, Tong Wu, and Guofan Shao. 2018. "Assessment of Regional Ecosystem Health—A Case Study of the Golden Triangle of Southern Fujian Province, China" International Journal of Environmental Research and Public Health 15, no. 4: 802. https://doi.org/10.3390/ijerph15040802