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苏南村镇耕地景观格局对土壤重金属污染的影响

隋传嘉1,潘剑君2*,余泓2,魏善宝1#br#   

  1. 1南京农业大学公共管理学院, 南京  210095; 2南京农业大学资源与环境科学学院, 南京 210095)
  • 出版日期:2017-08-10 发布日期:2017-08-10

Impacts of farming landscape patterns on soil heavy metal pollution in towns of Southern Jiangsu Province.

SUI Chuan-jia1, PAN Jian-jun2*, YU Hong2, WEI Shan-bao1#br#   

  1. (1College of Public Administration, Nanjing Agricultural University, Nanjing 210095, China; 2College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China).
  • Online:2017-08-10 Published:2017-08-10

摘要: 景观格局容易受人类活动影响,为了精确掌握景观格局对土壤重金属污染的影响,实施更具针对性的防治措施,采用GIS以及地统计分析方法,基于村镇级小尺度,以苏南某镇为例,研究耕地表层土壤8种重金属的含量,揭示8种重金属的污染特征及其空间分布格局,探讨样点缓冲区内景观格局对重金属含量的影响,分析整体景观格局与各行政村重金属综合污染的相关性。结果表明,Cd含量超过国家土壤质量二级标准,重金属污染水平均小于1,99.36%的耕地无污染,0.64%的耕地需要警戒。缓冲区内As、Ni、Pb、Hg、Cd、Zn含量各自与少数景观格局指数有显著相关性(P<0.05),Cr、Cu含量与景观格局无显著相关性。斑块连通性/聚集度与重金属综合污染指数呈显著正相关(P<0.05),可以较好地解释各行政村耕地重金属的综合污染程度。

关键词: 夏玉米, 混播, 产量, 密度, 13C同化物

Abstract: Landscape pattern is easily affected by human activities. In order to accurately grasp the influences of landscape pattern on heavy metal pollution of soil and implement more targeted prevention and control measures, GIS and geostatistical analysis method were adopted. Based on a villagelevel small scale, the contents of 8 kinds of heavy metals in surface soil of cultivated land were measured in a town in South Jiangsu. The study objectives were to reveal the pollution characteristics of the 8 kinds of heavy metals and their spatial distribution pattern, to discover the influences of landscape pattern in buffer area, and to analyze the relationships between overall landscape pattern and heavy metal pollution in administrative villages. The results showed that the content of Cd exceeded national soil quality secondary standard of China. The heavy metal pollution levels were all less than 1; 99.36% of the cultivated land were not polluted and 0.64% of the cultivated land were on the alert against heavy metal pollution. In the buffer area, there was a significant correlation between contents of As, Ni, Pb, Hg, Cd and Zn and some landscape pattern indexes (P<0.05), while there was no significant correlation between contents of Cr and Cu and landscape pattern. There was a significant positive correlation between landscape connectivity/aggregation degree and comprehensive pollution index of heavy metals (P<0.05). Therefore, our results well explained the comprehensive pollution degree of heavy metals in cultivated lands in each administrative village.

Key words: summer maize, density, mixed-cropping, grain yield, 13C-photosynthate