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草业学报 ›› 2021, Vol. 30 ›› Issue (4): 68-79.DOI: 10.11686/cyxb2020371

• 研究论文 • 上一篇    下一篇

羊草及芨芨草草原和西北针茅草原土壤质量评价

张丽星1,2(), 海春兴1(), 常耀文1,2, 高晓媚1,2, 高文邦3, 解云虎4   

  1. 1.内蒙古师范大学地理科学学院,内蒙古 呼和浩特 010022
    2.内蒙古自治区高原环境与全球变化实验室,内蒙古 呼和浩特 010022
    3.北京师范大学地理科学学部,北京 100093
    4.内蒙古科技大学包头师范学院,内蒙古 包头 014030
  • 收稿日期:2020-08-03 修回日期:2020-11-02 出版日期:2021-04-20 发布日期:2021-03-16
  • 通讯作者: 海春兴
  • 作者简介:Corresponding author. E-mail: chunxinghai@163.com
    张丽星(1994-),女,内蒙古凉城人,在读硕士。E-mail: 15354803391@163.com
  • 基金资助:
    内蒙古师范大学研究生科研创新基金(CXJJS19140);内蒙古社会科学基金项目(20B67);内蒙古自治区水环境安全协同创新培育基金项目(XTCX003);内蒙古自治区科技重大专项课题子项目(ZDZX2018058);内蒙古自治区自然科学基金项目(2018MS04009)

Evaluation of soil quality in Leymus chinensis-Achnatherumsplendens grassland and in Stipa sareptana grassland

Li-xing ZHANG1,2(), Chun-xing HAI1(), Yao-wen CHANG1,2, Xiao-mei GAO1,2, Wen-bang GAO3, Yun-hu XIE4   

  1. 1.College of Geographical Science,Inner Mongolia Normal University,Hohhot 010022,China
    2.Laboratory of Mongolian Plateau Environment & Global Change,Hohhot 010022,China
    3.Faculty of Geographical Science,Beijing Normal University,Beijing 100093,China
    4.Baotou Teachers College of Inner Mongolia University of Science and Technology,Baotou 014030,China
  • Received:2020-08-03 Revised:2020-11-02 Online:2021-04-20 Published:2021-03-16
  • Contact: Chun-xing HAI

摘要:

为了解典型草原植被群落土壤质量情况,选择镶黄旗羊草及芨芨草草原和西北针茅草原土壤为研究对象。选取10项土壤理化指标作为总数据集,利用主成分分析及相关性分析方法结合Norm值构建评价指标最小数据集,通过非线性评价方法对该区羊草及芨芨草草原和西北针茅草原土壤质量进行综合评价。结果表明:1)羊草及芨芨草草原土壤水分和电导率在A2~Bk层显著高于针茅草原(P<0.05),在A2和AB层羊草及芨芨草草原土壤pH显著低于西北针茅草原(P<0.05),在A层羊草及芨芨草草原土壤平均养分含量大于西北针茅草原(P<0.05),但在Bk~C层则相反;2)土壤质量评价最小数据集由土壤有机质、电导率和容重这3个土壤指标组成,可以反映草原土壤质量有效信息,经总数据集验证具有较好准确性;3)土壤质量指数表现为:A1层羊草及芨芨草草原>西北针茅草原,A2~C层羊草及芨芨草草原<西北针茅草原(P<0.05)。研究结果可为草地可持续发展提供科学参数。

关键词: 羊草及芨芨草, 西北针茅, 土壤理化性质, 最小数据集, 土壤质量

Abstract:

This research investigated soil quality of the vegetation communities in typical grassland in Inner Mongolia. Two sites (approximately 1340 m altitude), one dominated by Leymus chinensis and Achnatherum splendens (Lc-As) mixed grassland (tolerant of soil salinity) andthe other by Stipa sareptana (Ss) grassland (intolerant of soil salinity) were selected for study. Soil quality data were evaluated for six soil horizons in Lc-As (A1, A2, AB, Bk, Bb, C>130 cm) and five horizons in Ss (A1, A2, AB, Bk, C>90 cm) using multivariate nonlinear methods. Initially, 10 soil physicochemical parameters were measured and a principal component (PC) analysis performed on these. From these 10 parameters a ‘minimum data set’ (MDS) was selected based on a ‘Norm’ score which assessed the influence of each parameter based on size of PC coefficients (≥0.5) and uniqueness of information (low Pearson correlation with other parameters). In this way three parameters were selected for inclusion in the MDS: soil organic matter (OM, indicative of nutrient status), electrical conductivity (EC, indicative of salinity) and bulk density (BD, lower bulk density indicating better soil aeration). It was found that: 1) Soil water content and electrical conductivity of Lc-As grassland in the A2 to Bk horizons was significantly higher than that of Ss grassland (P<0.05), and pH of Lc-As grassland in the A2 and AB horizons was higher than in Ss grassland (P<0.05). The average nutrient content of Lc-As grassland was higher than that of Ss grassland in the A horizon (P<0.05), but the opposite was true in the Bk to C horizons. 2) A soil quality index (SQI) was calculated from the MDS with OM, EC and BD weighted 0.39, 0.16 and 0.45, respectively. 3) The SQI of Lc-As grassland was higher than that of Ss in the A1 horizon, while in the A2 to C horizons, the SQI of Lc-As grassland was significantly lower than in Ss grassland (P<0.05). These research results provide scientific parameters useful for the development of sustainable grassland management practices.

Key words: Leymus chinensis and Achnatherum splendens, Stipa sareptana, soil physicochemical properties, minimum data set, soil quality