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Zhu C, Chen Y, Wan Z, Chen Z, Lin J, Chen P, Sun W, Yuan H, Zhang Y. Cross-sensitivity analysis of land use transition and ecological service values in rare earth mining areas in southern China. Sci Rep 2023; 13:22817. [PMID: 38129431 PMCID: PMC10739947 DOI: 10.1038/s41598-023-49015-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 12/02/2023] [Indexed: 12/23/2023] Open
Abstract
Exploring the cross-sensitivity between land use transformation and ecological service values in rare earth mining areas is of great significance for the development of ecological protection and restoration in rare earth mining areas. To study the impact of land use changes on ecosystem service functions in rare earth mining areas, firstly, the land use change trends in the study area from 2009 to 2019 were analyzed using the land transfer matrix; then the distribution of ecosystem service values and the flow direction of ecosystem service values in the study area were measured based on the ecosystem service value equivalents; a spatial autocorrelation analysis was done on the ecosystem service values to explore their spatial distribution patterns; and finally, the cross-sensitivity coefficient was used to quantitatively assess the extent and direction of the impact of land use change on ecosystem service values. The results show that the land use types in the study area are mainly forest land and farmland, with woodland accounting for the highest proportion of the study area. The ESV changes in the study area are consistent with the trend of land use transformation, with the overall increase and decrease being comparable, and the decrease in ESV is mainly concentrated in the areas with a large increase in mining land and construction land; during the study period, the study area was significantly reduced with low-low cluster areas and the ecological environment was improved; from 2009 to 2014, the ecological sensitivity coefficient is more variable, and is more sensitive to the net conversion between water and desert, from 2014 to 2019, the ecological sensitivity coefficient is less variable, and the most sensitive is the net conversion between cultivated land and water. The study area should be reasonably developed for rare earth resources and the ecological environment around the mining area should be reasonably protected to build an ecological security pattern.
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Affiliation(s)
- Chenhui Zhu
- School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China
| | - Yonglin Chen
- School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China.
| | - Zhiwei Wan
- School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China
| | - Zebin Chen
- School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China
| | - Jianping Lin
- School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China
| | - Peiru Chen
- School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China
| | - Weiwei Sun
- School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China
| | - Hao Yuan
- School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China
| | - Yunping Zhang
- School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, 341000, China
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Wang J, Chen G, Yuan Y, Fei Y, Xiong J, Yang J, Yang Y, Li H. Spatiotemporal changes of ecological environment quality and climate drivers in Zoige Plateau. ENVIRONMENTAL MONITORING AND ASSESSMENT 2023; 195:912. [PMID: 37392290 DOI: 10.1007/s10661-023-11506-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 06/10/2023] [Indexed: 07/03/2023]
Abstract
Ecological environment is the essential material basis of human survival and connects regional economy with socially sustainable development. However, climate changes characterized by global climate warming have caused a series of ecological environmental problems in recent years. Few studies have discussed various climate factors affecting the ecological environment, and the spatial non-stationary effects of different climate factors on the ecological environment are still unclear. Dynamically monitoring ecological environment changes in fragile areas and identifying its climate-driving mechanism are essential for ecological protection and environmental repair. Taking Zoige Plateau as a case, this paper simulated the eco-environmental quality during 1987-2020 using remote sensing data, utilized Geodetector method to identify the contributions of various climate drivers to ecological environment quality, and then adopted the Geographically Weighted Regression model to explore the spatial non-stationary impacts of climate factors on ecological environment quality. The results showed that the ecological quality in the middle regions of the Zoige Plateau was slightly better than in the surrounding marginal areas. For the whole area of Zoige Plateau, the average ecological environment quality index was 54.92, 53.99, 56.17, 57.88, 63.44, 56.93, 59.43, and 59.76 in 1987, 1992, 1997, 2001, 2006, 2013, 2016 and 2020, respectively, which indicated that eco-environmental quality witnessed several fluctuations during the study period but showed a generally increasing trend. Among five climate factors, the temperature was the dominant climate factor affecting the ecological environment quality (q value: 0.11-0.19), sunshine duration (0.03-0.17), wind speed (0.03-0.11), and precipitation (0.03-0.08) were the main climate drivers, while the explanatory power of relative humidity to ecological environment quality was relatively small. Such various climate factors impacting the ecological environment quality demonstrated distinct spatial non-stationary and the range of driving impact varied with time. Temperature, sunshine duration, wind speed, and relative humidity promoted ecological environment quality in most regions (regression coefficients > 0), while precipitation mainly had a negative inhibitory impact (regression coefficients < 0). Meanwhile, the greater impacts of these five climate factors were concentrated in high-elevation regions of the south and west or the northern areas. The appropriate enhancement of climate warming and air humidity was beneficial to the improvement of the ecological environment, but the excessive precipitation would result in landslides and exhibit inhibition of vegetation growth. Therefore, selecting cold-tolerant herbs and shrubs, and strengthening climate monitoring and early warning systems (such as drought and excessive precipitation) are essential for ecological restoration.
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Affiliation(s)
- Jiyan Wang
- School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, 610500, China
| | - Guo Chen
- School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, 610500, China
| | - Yirong Yuan
- School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, 610500, China
| | - Yi Fei
- Sichuan Water Resources and Hydroelectric Investigation & Design Institute Co.Ltd, Chengdu, 610500, China
| | - Junnan Xiong
- School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, 610500, China.
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Jiawei Yang
- School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, 610500, China
| | - Yanmei Yang
- School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, 610500, China
| | - Hao Li
- School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu, 610500, China
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