Evaluation of ecosystem service function in Shendong mining area

被引:0
|
作者
Liu Y. [1 ]
Wei J. [1 ]
Bi Y. [2 ,3 ]
Yue H. [1 ]
He X. [1 ]
机构
[1] College of Geomatics, Xi'an University of Science and Technology, Xi'an
[2] College of Geology and Environment, Xi'an University of Science and Technology, Xi'an
[3] College of Geoscience and Surveying Engineering, China University of Mining Technology (Beijing), Beijing
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关键词
Comprehensive ecosystem service(CES); InVEST model; Mine scale; Mining area scale; Shendong mining area;
D O I
10.13225/j.cnki.jccs.ST21.0188
中图分类号
学科分类号
摘要
The Shendong mining area is an important coal production base in China, and the coal mining has caused strong disturbance to its fragile ecological environment.It is necessary to use scientific methods to reveal the evolution of the ecosystem service function of the Shendong mining area, and improve the management system of green mining and sustainable development in the mining area.To quantify the changes in ecosystem service functions in Shendong mining area, a Comprehensive Ecosystem Service (CES) evaluation model was constructed based on the InVEST model, which integrates three ecosystem services: water supply, soil conservation, and carbon storage, and measures the characteristics and patterns of changes in CES in the Shendong mining area from 1990 to 2018 in both the scale of mining area and mine.The results show that at the mining area scale, ① the SCE in Shendong mining area decreased from 0.448 6 (1990) to 0.382 5 (2000), and then continued to increase to 0.471 6 (2015) and then decreased to 0.453 2 (2018), showing an overall increasing trend at a rate of 0.009 a-1.Spatially, it was the weakest in the northwest and gradually strengthened from the northwest to the southeast.② The spatial variability of the CES in the Shendong mining area was obvious, and the contribution of the change in the low-variable area to the change in the CES was higher than that of the medium-variable area and the abrupt change area, and the CES spatial change was closely related to vegetation cover and land use types.③ The spatial clustering of CES in the Shendong mining area was obvious, showing a pattern of "weakest in the northwest, strongest along the rivers, and insignificant in the southeast".④ The driving factors of CES change in Shendong mining area were land use type, slope, elevation, rainfall and vegetation coverage in order.The synergy of two factors was higher than that of single factor, and the synergy between land use and other factors was the strongest.At the mine scale, ① the CES in the Shendong mine area was highest in the medium-intensity mining area (SCE=0.502 8) and lowest in the very high-intensity mining area (SCE=0.430 8).② The CES in the Bulianta mine area was positively influenced by ecological management measures, the CES in the Daliuta and Huojitu mine area had been negatively affected by mining since 2010, and the CES in the Shigetai, Wulanmulun, Halagou and Yujialiang mine area had continued to suffer negative impacts since mining.③ The CES in the Daliuta rec-lamation experimental area had developed in the direction of becoming stronger.The model's comprehensive as-sessment results can quantitatively reflect the changing pattern of the CES in the Shendong mining area.It is suggested that Shendong mining area should implement ecological management with the northwest as the key area, and focus on optimizing the land use structure by improving vegetation cover, and use scientific methods such as microbial reclamation in the mining area.In addition, the development and use of multi-scale integrated model for the optimization of multiple ecosystem services should be committed, with a view to providing more accurate and reliable decision support for the sustainable management of regional ecosystem services. ©2021, Editorial Office of Journal of China Coal Society. All right reserved.
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页码:1599 / 1613
页数:14
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  • [1] GOLDSTEIN J H, CALDARONE G, DUARTE T K, Et al., Integrating ecosystem-service tradeoffs into land-use decisions, Proceedings of the National Academy of Sciences of the United States of America, 109, 19, pp. 7565-7570, (2012)
  • [2] BASTOLA S, LEE S, SHIN Y, Et al., An assessment of environmental impacts on the ecosystem services: Study on the Bagmati Basin of Nepal, Sustainability, 12, 9, (2020)
  • [3] ASADOLAHI Z, SALMANMAHINY A, SAKIEH Y, Et al., Dynamic trade-off analysis of multiple ecosystem services under land use change scenarios: Towards putting ecosystem services into planning in Iran, Ecological Complexity, 36, pp. 250-260, (2018)
  • [4] DAI Erfu, WANG Yahui, Spatial heterogeneity and driving mechanisms of water yield service in the Hengduan Mountain region, Acta Geographic Sinica, 75, 3, pp. 607-619, (2020)
  • [5] WANG Xiuming, LIU Xudan, LONG Yingxian, Et al., Spatial-temporal changes and influencing factors of ecosystem services in Shaoguan city based on improved InVEST, Research of Soil and Water Conservation, 27, 5, pp. 381-388, (2020)
  • [6] LIU Dongqing, GONG Jie, ZHANG Jinqian, Et al., Spatiotemporal variation of soil conservation function and lts influencing factors in Bailongjiang watershed in Gansu Province, Research of Soil and Water Conservation, 25, 4, pp. 98-103, (2018)
  • [7] YANG Jie, XIE Baopeng, ZHANG Degang, Spatio-temporal variation of water yield and its response to precipitation and land use change in the Yellow River Basin based on InVEST model, Chinese Journal of Applied Ecology, 31, 8, pp. 2731-2739, (2020)
  • [8] CHEN Xinmeng, Spatiotemporal changes and trade-offs of ecosystem services in the Yellow River Basin, Agriculture and Technology, 40, 20, pp. 122-125, (2020)
  • [9] SHARP R, TALLIS H T, RICKETTS T, Et al., InVEST 3.7.0 user's guide, (2018)
  • [10] WU Fangfang, CAO Yuee, LU Gang, Et al., Impact factors of soil wind erosion and estimation of soil loss in Zhundong, Xinjiang, Journal of Soil and Water Conservation, 30, 6, pp. 56-60, (2016)