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牛鸿波,田少国,祖鹏举,等. 神东矿区煤炭开采对植被净初级生产力的影响[J]. 煤炭科学技术,2024,52(7):267−277. doi: 10.12438/cst.2023-1026
引用本文: 牛鸿波,田少国,祖鹏举,等. 神东矿区煤炭开采对植被净初级生产力的影响[J]. 煤炭科学技术,2024,52(7):267−277. doi: 10.12438/cst.2023-1026
NIU Hongbo,TIAN Shaoguo,ZU Pengju,et al. Effect of coal mining on net primary productivity of vegetation in Shendong Mining Area[J]. Coal Science and Technology,2024,52(7):267−277. doi: 10.12438/cst.2023-1026
Citation: NIU Hongbo,TIAN Shaoguo,ZU Pengju,et al. Effect of coal mining on net primary productivity of vegetation in Shendong Mining Area[J]. Coal Science and Technology,2024,52(7):267−277. doi: 10.12438/cst.2023-1026

神东矿区煤炭开采对植被净初级生产力的影响

Effect of coal mining on net primary productivity of vegetation in Shendong Mining Area

  • 摘要: 神东矿区煤炭开采对当地生态环境,特别是植被生长,产生了重要影响。为了定量描述这种影响,该研究利用区域蒸散模型,计算神东矿区潜在净初级生产力(Potential Net Primary Productivity,NPPp),并利用MODIS17A3数据集(2001—2022年)表征实际净初级生产力(Actual Net Primary Productivity,NPPa),同时结合中国陆地生态系统逐月净初级生产力栅格数据集(NPPa1,1988—2015年),采用地理加权回归(Geographically weighted regression, GWR)模型构建校正方法,对NPPa1进行校正获取1988—2000年的NPPa数据,以二者之差(Human Net Primary Productivity)NPPh表征煤炭开采的影响,评估了神东矿区煤炭开采对植被NPP的影响。结果表明:①利用GWR模型校正的NPPa1数据精度约为0.76,校正后的NPPa1数据与MODIS17A3数据集具有较强的空间相关性,说明了校正模型精度的可靠性;②神东矿区的整体上NPPa和NPPh表现为先下降后逐渐恢复的趋势,但植被NPP并未恢复至采矿前水平。采矿前NPPh均值和采矿后NPPh均值分别为21.50 g/m2、−60.20 g/m2,NPPh<0表明矿区NPP植被生长受到采矿活动的干扰,发生退化的矿井主要分布在高强度开采区域(以C计,下同);③1996—2022年神东矿区NPP值的变化主要受气候变化和人类活动的共同影响,人类活动和气候变化对生态退化的占比分别为35.7%、8.2%, 1996—2015年人类活动贡献率指数(Relative Contribution Index, I_\mathrmR\mathrmC )主要集中在0.5左右,表明煤炭开采对植被退化占主导作用,2016年后光伏电站建设对NPP的影响表现出促进作用。该研究有助于理解煤炭开采对植被净初级生产力动态变化的影响,并为神东矿区的植被恢复和高质量发展提供科学依据。

     

    Abstract: Coal mining in Shendong Mining area has an important impact on the local ecological environment, especially the growth of vegetation. In order to describe this effect quantitatively, this study uses a regional evapotranspiration model to calculate the Potential Net Primary Productivity (NPPp) of the Shendong mining area. MODIS17A3 dataset (2001—2022) was used to characterize the Actual Net Primary Productivity (NPPa), and combined with the monthly net primary productivity raster dataset of terrestrial ecosystems in China (NPPa1, 1988—2015), using GWR model construction correction method to correct NPPa1 to obtain 1988—2000 NPPa data, and using the difference between the two (Human Net Primary Productivity) NPPh to characterize the impact of coal mining. The effect of coal mining on vegetation NPP in Shendong mining area was evaluated. The results show that: ① the accuracy of NPPa1 data corrected by GWR model is about 0.76, and the corrected NPPa1 data has a strong spatial correlation with the MODIS17A3 dataset, which indicates the reliability of the accuracy of the corrected model; ② The overall NPPa and NPPh of Shendong mining area showed a trend of decreasing first and then recovering gradually, but the NPP of vegetation did not recover to the pre-mining level. The mean values of NPPh before mining and NPPh after mining are 21.50 g/m2 and −60.20 g/m2, respectively. NPPh<0 indicates that NPP vegetation growth in mining areas is disturbed by mining activities, and the degraded mines are mainly distributed in high-intensity mining areas (calculated in C, the same below). ③ The change of NPP value in Shendong mining area from 1996 to 2022 is mainly influenced by climate change and human activities. The proportion of human activities and climate change to ecological degradation is 35.7% and 8.2%, respectively. The I_\mathrmR\mathrmC from 1996 to 2015 is mainly about 0.5, indicating that coal mining plays a leading role in vegetation degradation. After 2016, the impact of photovoltaic power plant construction on NPP showed a promoting effect. This study is helpful to understand the impact of coal mining on the dynamic change of net primary productivity of vegetation, and provides scientific basis for vegetation restoration and high-quality development in Shendong mining area.

     

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