Abstract：[Background] Iron tailings wasteland is one of the most degraded site types caused by the violent disturbance of mining activities. Studies have shown that vegetation restoration can significantly improve soil properties and nutrient content as one of the effective methods for soil reclamation. It is of great significance for soil conservation to evaluate and study soil nutrients of vegetation restoration mode. At present, the sole use of the mainstream evaluation method cannot completely reflect the characteristics of the evaluation object, because the results are affected by the subjectivity of method and the error of the sample difference. This work is to explore the effects of different vegetation restoration modes on soil nutrient recovery in iron tailings wasteland.[Methods] The pH, organic matter, available nitrogen, available phosphorus and available potassium of 6 restoration modes (Castanea mollissima + Juglans regia, C. mollissima + Crataegus pinnatifida, C. mollissima, Pinus tabuliformis + Amygdalus persica, P. tabuliformis + Amorpha fruticosa, A. persica + A. fruticosa) and bare soil were evaluated by evaluation model which combined the weight of analytic hierarchy process (AHP) and principal component analysis (PCA). The above nutrient indexes were obtained by experiment from soil samples of different vegetation modes in the study area.[Results] 1) The trend of soil nutrient recovery in the 6 modes showed that the pH value was improved well, rich in available potassium, medium in available nitrogen, lacking in available phosphorus and organic matter. The nutrient score of the 6 modes was 2.66 -3.40 times higher than the soil of bare land, the highest score of C. mollissima + J. regia mode was 5.61 grade "Credit", in which the soil pH value and organic matter were significantly improved. However, there were significant differences in nutrients between different soil layers in this mode, which indicated the improvement of soil nutrient by vegetation restoration mode was achieved from the surface layer to the deep layer. The evaluation score of A. persica + A. fruticosa mode was 5.40 grade "Credit", which was superior to other modes in the recovery of available phosphorus and potassium.[Conclusions] It is suggested that the mode of C. mollissima + J. regia mixed forest should be adopted to restore the abandoned tailing land. Meanwhile, leguminous deciduous shrubs should be selected to be planted under the forest and phosphorus fertilizer should be applied timely and appropriately to accelerate the recovery of organic matter and available phosphorus. The AHP-PCA evaluation model may reflect the actual situation of the evaluation objects more comprehensively, and the evaluation effect is better than the single method, which has significant practical value for the evaluation of soil nutrients and ecological restoration.
闫升, 杨建英, 史常青, 张璐瑶, 赵廷宁. 基于AHP-PCA的铁尾矿不同植被恢复模式土壤养分评价[J]. 中国水土保持科学, 2019, 17(6): 111-118.
YAN Sheng, YANG Jianying, SHI Changqing, ZHANG Luyao, ZHAO Tingning. Soil nutrient evaluation of iron tailings in different vegetation restoration modes based on AHP-PCA. SSWC, 2019, 17(6): 111-118.
陈颖, 李晨光, 徐学华, 等. 铁尾矿废弃地火炬树林水土保持功能[J]. 水土保持学报, 2015, 29(3):107. CHEN Ying, LI Chenguang, XU Xuehua, et al. Soil and water conservation function of Rhus typhina L. forest in Iron tailings[J]. Journal of Soil and Water Conservation, 2015, 29(3):107.
[2]
王超, 毕君, 尤海舟. 矿山废弃地生态退化程度评价[J]. 生态环境学报, 2014, 23(6):1070. WANG Chao, BI Jun, YOU Haizhou. Evaluation of ecological degradation on mine wasteland[J]. Ecology & Environmental Sciences, 2014, 23(6):1070.
[3]
闫德民, 赵方莹, 孙建新. 铁矿采矿迹地不同恢复年限的植被特征[J]. 生态学杂志, 2013, 32(1):2. YAN Demin, ZHAO Fangying, SUN Jianxin. Characters of the vegetations with different restoration age on a mining site of Shouyun Iron Ore Mine, Beijing[J]. Chinese Journal of Ecology, 2013, 32(1):2.
[4]
GOMEZ-ROS J M, GARCIA G, PEAS J M. Assessment of restoration success of former metal mining areas after 30 years in a highly polluted Mediterranean mining area:Cartagena-La Unión[J]. Ecological Engineering, 2013, 57(3):394.
[5]
VICKERS H, GILLESPIE M, GRAVINA A. Assessing the development of rehabilitated grasslands on post-mined landforms in Northwest Queensland, Australia[J]. Agriculture Ecosystems & Environment, 2012, 163(6):73.
[6]
赵川, 和丽萍, 李贵祥, 等. 昆阳磷矿废弃地植被恢复对土壤质量的影响及评价[J]. 西部林业科学, 2018, 47(2):107. ZHAO Chuan, HE Liping, LI Guixiang, et al. Effect and assessment of vegetation restoration on soil quality in Kunyang phosphorite mine area[J]. Journal of West China Forestry Science, 2018, 47(2):107.
[7]
李文, 任晓旭, 蔡体久. 不同排矸年限煤矸石废弃地养分含量及重金属污染评价[J]. 林业科学, 2011, 47(6):163. LI Wen, REN Xiaoxu, CAI Tijiu. Assessment of nutrient content and heavy metal pollution in gangue waste lands with different dumping years[J]. Scientia Silvae Sinicae, 2011, 47(6):163.
[8]
赵韵美, 樊金拴, 苏锐, 等. 阜新矿区不同植被恢复模式下煤矿废弃地土壤养分特征[J]. 西北农业学报, 2014, 23(8):211. ZHAO Yunmei, FAN Jinshuan, SU Rui, et al. Soil Nutrient characteristics for different vegetation restoration models in an abandoned area of Fuxin coal mine[J]. Acta Agriculturae Boreali-Occidentalis Sinica, 2014, 23(8):211.
[9]
李峰, 刘小阳, 于雪涛, 等. 基于AHP-PCA模型的煤炭城市生态环境质量评价[J]. 矿业安全与环保, 2017, 44(5):106. LI Feng, LIU Xiaoyang, YU Xuetao, et al. Eco-environmental quality evaluation of coal city based on AHP-PCA Model[J]. Mining Safety and Environmental Protection, 2017, 44(5):106.
[10]
闫德民. 北京首云铁矿尾矿库生态恢复的植被特征分析[D]. 北京:北京林业大学, 2013:14. YAN Demin. Analysis of vegetational traits on tailings dam following ecological restoration at Shouyun iron ore mining site in suburban Beijing[D]. Beijing:Beijing Forestry University, 2013:14.
[11]
刘永光. 北京山区关停废弃矿山人工恢复效果及评价研究[D]. 北京:北京林业大学, 2012:19. LIU Yongguang. Evaluation of artificial restoration effect of the abandoned mines in Beijing[D]. Beijing:Beijing Forestry University, 2012:19.
郭庆勇, 王凤, 史惠堂. 基于层次分析法的页岩气产业风险评价探讨[J]. 矿业安全与环保, 2015, 42(1):113. GUO Qingyong, WANG Feng, SHI Huitang. Discussion on risk evaluation of shale gas industry based on analytic hierarchy process[J]. Mining safety & Environmental Protection, 2015, 42(1):113.
[14]
李江锋. 北京矿山废弃地生态恢复质量评价研究[D]. 北京:北京林业大学, 2010:42. LI Jiangfeng. Study on quality assessment of ecological restoration in mine derelict land in Beijing[D]. Beijing:Beijing Forestry University, 2010:42.
[15]
王超, 毕君, 尤海舟. 冀东地区铁矿废弃地生态治理效果评价研究[J]. 环境科学与技术, 2015, 38(52):433. WANG Chao, BI Jun, YOU Haizhou. Evaluation on ecological restoration of iron mine wasteland in eastern Hebei province[J]. Environmental Science & Technology, 2015, 38(52):433.
[16]
袁勇, 李小英, 刘晓梅, 等. 磷矿采空区恢复林地土壤养分:以云南昆阳磷矿为实例研究[J]. 基因组学与应用生物学, 2017(5):2013. YUAN Yong, LI Xiaoying, LIU Xiaomei, et al. Restoration of soil nutrients in phosphate mined-out areas:A case study of the phosphate mine in Kunyang, Yunnan[J]. Genomics & Applied Biology, 2017(5):2013.
[17]
何冰, 薛刚, 张小全, 等. 有机酸对土壤钾素活化过程的化学分析[J]. 土壤, 2015, 47(1):78. HE Bing, XUE Gang, ZHANG Xiaoquan, et al. Analysis on chemical mechanism of potassium release process from soil as influenced by organic acids[J]. Soils, 2015, 47(01):78.
[18]
任启文, 毕君, 李联地, 等. 冀北山地3种森林植被恢复类型对土壤质量的影响[J]. 生态环境学报, 2018, 27(10):45. REN Qiwen, BI Jun, LI Liandi, et al. Effects of three forest vegetation restoration types on soil quality in northern Hebei mountain area[J]. Ecology and Environmental Sciences, 2018, 27(10):45.
[19]
姚小华, 罗细芳. 生态经济林模式土壤养分与颗粒变化研究[J]. 水土保持研究, 2005, 12(4):163. YAO Xiaohua, LUO Xifang. Study on soil nutrient and soil granule of ecological economic forest[J]. Research of Soil & Water Conservation, 2005, 12(4):163.
[20]
李刚, 李建平, 孙晓蕾, 等. 主客观权重的组合方式及其合理性研究[J]. 管理评论, 2017, 29(12):18. LI Gang, LI Jianping, SUN Xiaolei, et al. Research on combination mode of subjective and objective weights and its rationalit[J]. Management Review, 2017, 29(12):18.
[21]
张耿杰. 矿区复垦土地质量监测与评价研究[D]. 北京:中国地质大学, 2013:118. ZHANG Gengjie. Study on monitoring and evaluation of the quality of reclaimed land in mining area[D]. Beijing:China University of Geosciences, 2013:118.
[22]
陈优良, 史琳, 王兆茹. GIS的矿区土壤重金属污染评价及空间分布[J]. 测绘科学, 2018, 238(4):85. CHEN Youliang, SHI Lin, WANG Zhaoru. Pollution assessment and spatial distribution of soil heavy metals in mining area based on GIS[J]. Science of Surveying and Mapping, 2018, 238(4):85.
2019, Vol. 17 
