Institute of Loess Plateau, Shanxi University, Taiyuan 030006, China.
College of Resource and Environment, Shanxi University, Taiyuan 030006, China.
Ying Yong Sheng Tai Xue Bao. 2021 Nov 15;32(11):3923-3932. doi: 10.13287/j.1001-9332.202111.004.
Although coal has made a huge contribution to the development of the economy and socie-ty and its economic benefits have often attracted much attention, little research has focused on the ecosystem services of coalfields. Based on remote sensing data, meteorological data, and soil data in Shanxi coalfields during 1986, 2000, and 2015, we estimated soil conservation and water yield using the InVEST model, assessed the net primary productivity of vegetation using the CASA mo-del, and estimated sand fixation using the RWEQ model. Further, we simulated the spatial patterns of ecosystem services (ESs) using the k-means cluster analysis method and analyzed the influence factors of ESs using the Geodetector model in Shanxi coalfield areas. The results showed that soil conservation service, water yield service, and sand fixation service increased continuously. The high-value area of soil conservation service was mainly concentrated in the north of Hedong coalfield and the northeast of Qinshui coalfield, while the low-value area was distributed in the southwestern edge of Datong coalfield. The high-value area of water yield service was mainly concentrated in the northeast of Qinshui coalfield, while the low-value area was distributed in the northeast of Qinshui coalfield, Xishan coalfield and northwestern Qinshui coalfield. The high-value area for vegetation production service was mainly concentrated in the southeast of Qinshui coalfield, while the low-value area was distributed in Datong coalfield, Ningwu coalfield, Xishan coalfield, and northern Hedong coalfield. The distribution of low- and high-value areas of sand fixation service was unfixed. Ecosystem service bundles could be divided into four categories. The first category belonged to soil conservation service bundle, mainly distributed in the northern Ningwu coalfield, the northern Hedong coalfield, and the northern Qinshui coalfield. The second was water yield service bundle, mainly distributed in Huoxi coalfield and southern Qinshui coalfield. The third category belonged to vegetation production service bundle, mainly distributed in parts of Qinshui coalfield. The fourth category belonged to sand fixation service bundle, mainly distributed in the southern part of Hedong coalfield and Qinshui coalfield. Soil conservation service was greatly affected by temperature, digital elevation model (DEM), and industrial output value, with q values of 0.5, 0.3, and 0.2, respectively. Water yield service was greatly affected by precipitation, temperature, and DEM, with q values of 0.8, 0.3, and 0.2, respectively. The industrial output value, precipitation, and temperature q values of vegetation production service were 0.7, 0.6, and 0.2, respectively. The main influen-cing factors of sand fixation service were precipitation, temperature, and DEM, while the q values were 0.7, 0.3, and 0.3, respectively. The spatial distribution of coalfields ESs and the relationship between multiple ESs were closely related to natural and human factors. Therefore, maintaining the coordination relationship between natural-human factors and ecological services would be helpful to the management of the land reclamation, ecological reconstruction, and the sustainable development of coalfields ecosystem.
虽然煤炭在经济和社会发展方面做出了巨大贡献，其经济效益也常常备受关注，但针对煤矿区生态系统服务的研究却相对较少。本研究基于 1986 年、2000 年和 2015 年的遥感数据、气象数据和土壤数据，利用 InVEST 模型估算了土壤保持和水源涵养服务，利用 CASA 模型评估了植被净初级生产力，利用 RWEQ 模型估算了防风固沙服务，并采用 k-均值聚类分析方法模拟了生态系统服务（ESs）的空间格局，利用地理探测器模型分析了 ESs 的影响因素。结果表明：土壤保持服务、水源涵养服务和防风固沙服务持续增加。土壤保持服务的高值区主要集中在河东煤田北部和沁水煤田东北部，低值区分布在大同煤田西南部边缘。水源涵养服务的高值区主要集中在沁水煤田东北部，低值区分布在沁水煤田、西山煤田和沁水煤田西北部。植被生产服务的高值区主要集中在沁水煤田东南部，低值区分布在大同煤田、宁武煤田、西山煤田和河东煤田北部。防风固沙服务的低、高值区分布不稳定。生态系统服务束可分为四类。第一类属于土壤保持服务束，主要分布在北部宁武煤田、北部河东煤田和北部沁水煤田。第二类是水源涵养服务束，主要分布在霍西煤田和南部沁水煤田。第三类属于植被生产服务束，主要分布在沁水煤田的部分地区。第四类属于防风固沙服务束，主要分布在河东煤田南部和沁水煤田。土壤保持服务主要受温度、数字高程模型（DEM）和工业产值的影响，q 值分别为 0.5、0.3 和 0.2。水源涵养服务主要受降水、温度和 DEM 的影响，q 值分别为 0.8、0.3 和 0.2。植被生产服务的工业产值、降水和温度 q 值分别为 0.7、0.6 和 0.2。防风固沙服务的主要影响因素是降水、温度和 DEM，q 值分别为 0.7、0.3 和 0.3。煤矿区生态系统服务的空间分布和多种生态系统服务之间的关系与自然和人为因素密切相关。因此，维护自然-人为因素与生态服务之间的协调关系，将有助于矿区土地复垦、生态重建和矿区生态系统的可持续发展的管理。
