Abstract
Understanding how the variations in vegetation in vulnerable ecosystems such as mining areas are affected by human-induced landscapes is essential to environmental and resource management for achieving sustainable development goals (SDGs). However, in the existing literature, most of the vegetation monitoring in mining areas has mainly focused on coverage while lacking attention to the spatial structure of vegetation. This study developed a framework to identify the spatiotemporal variation and heterogeneity of plant functional types (PFTs) in the restored mining areas integrating indicators selection, satellite imagery analysis, and field survey. The framework was applied and monitor the restoration in the Shendong mining area, one of the most typical mining areas in China. The functional traits of the study area were characterized by having moderately low canopy cover, productivity, and water content. During the study period (from 1990 to 2020), the local PFTs were affected by the comprehensive impact of coal mining and ecological restoration, with only a small proportion of the PFTs degraded into less-desirable types or even deserts. The original PFTs with Salix as the dominant species gradually changed to that with planted Artemisia as the dominant species; some plant functional types appeared with clumps of Artemisia annua L. and pure Pinus sylvestris L. forests. It indicates that coal mining in the study area might not drive more extensive vegetation degradation, and ecological restoration could achieve a shift in plant functional types. Nevertheless, the transformed plant functional types are less resistant to disturbance than the original vegetation, so they will require further management and maintenance. Our methodological framework and findings can provide information on vegetation structural changes in response to disturbance and facilitate the assessment of the effects of the ecological restoration project in mining areas, which can guide regional sustainable development in the Shendong mining area and other large mining areas in China, and will be valuable for policy and planning purposes to the pursuance of SDGs.
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The authors confirm that the data supporting the findings of this study are available within the article and its supplementary material. Raw data that support the findings of this study area available from the corresponding author upon responsible request.
Notes
Google Earth V 6.2.2.6613. (September 30, 2020). Shaanxi China. 39° 28′ 19.76″S, 151° 45′ 15.01″W, Eye alt 77.15 km. DigitalGlobe 2012. http://www.earth.google.com [April 26, 2012].
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We thank LetPub (http://www.letpub.com) for its linguistic assistance during the preparation of this manuscript.
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This work was supported by the National Social Science Fund of China (grand number 22BJY064).
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In this study, QW, HX, YY, HH, XW, YP and SZ, JX performed all the data collection and drafted the manuscript. All authors participated in the design of the study and analysis of results. The specific division of work is as follows: YY: conceptualization, methodology. QW: software, data curation, formal analysis and writing—original draft. HX: visualization, investigation. XW and JM: validation. YP: resources. SZ: supervision. HH: funding acquisition.
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Wu, Q., Xu, H., Yang, Y. et al. Identifying structure change of vegetation under long-term disturbance in the Shendong mining area. Environ Earth Sci 82, 450 (2023). https://doi.org/10.1007/s12665-023-11005-y
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DOI: https://doi.org/10.1007/s12665-023-11005-y