| Autor: |
Xupu Li, Shuangshuang Li, Yufeng Zhang, Patrick J. O’Connor, Liwei Zhang, Junping Yan |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Land, Vol 10, Iss 7, p 739 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2073-445X |
| DOI: |
10.3390/land10070739 |
| Popis: |
Rapid urbanization and intensification of human activities increases the risk of disturbance of ecological systems via multiple sources, with consequences for regional ecological security and health. Landscape ecological risk assessment (LERA) is an effective way to identify and allocate risk to resources. We used the north and south Qinling Mountain area as a case study to analyze the spatial heterogeneity of landscape ecological risk using a potential- connectedness-resilience three-dimensional (PCR 3D) framework based on an integrated and dynamic risk assessment concept from adaptive cycle theory. We explored factors driving the risks with a spatial model GeoDetector. The results show that the comprehensive landscape ecological risk was north–south polarized and dominated by low and moderate risk levels (90.13% of total risk) across the whole study area. The high-risk area was centered on the Weihe plain north of the Qinling Mountains (NQL), while low-risk areas accounted for 86.87% of the total area and were prevalent across the south of the study area. The areas with high potential and connectedness risks were centered in the Xi’an–Xianyang urban agglomeration and those with high-resilience risk were in the upper reaches of the Hanjiang River. The vast majority of the area to the south of the Qinling Mountains (SQL) is at low risk. In terms of driving forces, population density and vegetation coverage (NDVI) are the primary factors affecting landscape ecological risk. Our findings suggest that anthropogenic activity is the primary cause of landscape ecological risks in the study area and regional socioeconomic exploitation and environmental conservation need to be rebalanced to achieve sustainability for the social ecosystem. The PCR 3D LERA framework employed in this study can be used to inform landscape ecological health and security and to optimize socioeconomic progress at regional scales. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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