生态与农村环境学报 ›› 2017, Vol. 33 ›› Issue (6): 564-570.doi: 10.11934/j.issn.1673-4831.2017.06.011

• 研究方法 • 上一篇    下一篇

有机耕作方式对我国南方典型土壤质量影响的评价

王磊1, 杨静2, 席运官1, 陈秋会1, 殷奎阳1, 李刚1, 张弛1, 田伟1, 张红旗1, 李旭1, 张纪兵1, 肖兴基1   

  1. 1. 环境保护部南京环境科学研究所, 江苏 南京 210042;
    2. 国家认监委认证认可技术研究所, 北京 100020
  • 收稿日期:2016-07-26 出版日期:2017-06-25 发布日期:2017-06-15
  • 通讯作者: 席运官,E-mail:xygofrcc@126.com;肖兴基,E-mail:xxj@nies.org E-mail:xygofrcc@126.com;xxj@nies.org
  • 作者简介:王磊 (1984-),男,山东济阳人,副研究员,博士,研究方向为有机农业与生态环境修复。E-mail:wlofrcc@126.com
  • 基金资助:

    国家科技支撑计划(2014BAK19B01);环保公益性行业科研专项(201309036);国家自然科学基金青年基金(41401336);中央级公益性科研院所基本科研业务费(20160201,20160303);云南省环保公益专项(45010);公益性行业(农业)科研专项(201003014-2)

Assessment of Quality of Soils Under Organic Farming in South China

WANG Lei1, YANG Jing2, XI Yun-guan1, CHEN Qiu-hui1, YIN Kui-yang1, LI Gang1, ZHANG Chi1, TIAN Wei1, ZHANG Hong-qi1, LI Xu1, ZHANG Ji-bing1, XIAO Xing-ji1   

  1. 1. Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing 210042, China;
    2. China Certification and Accreditation Institute, Beijing 100020, China
  • Received:2016-07-26 Online:2017-06-25 Published:2017-06-15

摘要:

选取南方14个典型农场,包括7个有机农场和7个相邻的常规农场,对其土壤物理指标(容重)、化学指标(pH值、有机质含量、全氮含量、全磷含量、速效磷含量、速效钾含量)和生物指标(微生物量碳含量,微生物群落多样性指数及优势度指数,线虫数量,线虫群落多样性指数及优势度指数)共13个指标进行统计分析。采用主成分分析法,筛选全氮含量、pH值、容重、微生物量碳含量、线虫数量和线虫群落优势度指数6个指标作为评价体系的最小数据集(minimum data set,MDS)。有机种植方式基于MDS的土壤质量指数(Is,q,6)为0.39~0.72,常规种植方式的Is,q,6为0.18~0.54,除1个样点外,有机种植方式的Is,q,6均高于常规种植方式。基于MDS的6个指标对土壤质量的贡献率为12.4%~21.8%,其中,线虫群落优势度贡献率最高。基于13个指标的土壤质量指数(Is,q,13)与Is,q,6呈显著正相关(r=0.89,P<0.05),表明基于MDS的土壤质量评价是一种有效可行的评价方法。

关键词: 有机农场, 常规农场, 最小数据集, 主成分分析, 土壤质量指数

Abstract:

Little information is available as reference for assessment of effect of organic farming on soil quality with soils under conventional farming as control, although large volumes of reports demonstrate that organic farming can ameliorate degraded soils. Soil samples were collected from 14 farms (i. e. 7 organic farms and 7 neighbouring conventional farms) for analysis of soil physicochemical properties, i. e. bulk density, pH, organic matter, total N, total P, readily available P and readily available K, and biological properties as well, i. e. microbial biomass carbon, diversity and dominance of microbial communities, and population, diversity and dominance of nematodes. Statistics of the 13 indices was done for principal components analysis. Out of the 13, 6 (TN, pH, bulk density, microbial biomass carbon, and population and dominance of nematodes) were cited to form a minimum data set (MDS). Soil quality index (Is,q,6) based on MDS was in the range of 0.39-0.72 in the soils under organic farming and in the range of 0.18-0.54 in the soils under conventional farming. The soils under organic farming, except in one sampling site were all higher than those under conventional farming in Is,q,6. Based on the fact that the 6 indices in MDS, particularly dominancy of the nematode community, contributed 12.4%-21.8% to soil quality and that Is,q,13(SQI derived from the 13 soil property indices) is significantly related to Is,q,6(r=0.89, P<0.05), it is quite clear that MDS-based soil quality assessment is a workable and effective tool.

Key words: organic farm, conventional farm, minimum data set, principal component analysis, soil quality index

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