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应用生态学报 ›› 2022, Vol. 33 ›› Issue (1): 219-228.doi: 10.13287/j.1001-9332.202201.036

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宁夏南部生态移民迁出区不同恢复模式土壤微生物群落特征

杨虎1, 马巧蓉1, 杨君珑1*, 周亮1, 曹兵1, 张维江2   

  1. 1宁夏大学农学院, 银川 750021;
    2宁夏大学土木与水利工程学院, 银川 750021
  • 收稿日期:2021-03-29 接受日期:2021-11-02 出版日期:2022-01-15 发布日期:2022-07-15
  • 通讯作者: * E-mail: yangjunlong-2002@163.com
  • 作者简介:杨 虎, 男, 1996年生, 硕士研究生。主要从事森林土壤微生物研究。E-mail: 1986340981@qq.com
  • 基金资助:
    国家自然科学基金项目(31860122)和宁夏回族自治区重点研发计划项目(2018BEG02010)

Characteristics of soil microbial communities in different restoration models in the ecological immigrants' emigration area in southern Ningxia, China

YANG Hu1, MA Qiao-rong1, YANG Jun-long1*, ZHOU Liang1, CAO Bing1, ZHANG Wei-jiang2   

  1. 1School of Agriculture, Ningxia University, Yinchuan 750021, China;
    2School of Civil and Hydraulic Engineering, Ningxia University, Yinchuan 750021, China
  • Received:2021-03-29 Accepted:2021-11-02 Online:2022-01-15 Published:2022-07-15

摘要: 为了揭示人工林对土壤微生物环境的作用机理,利用高通量测序技术,比较了宁南山区刺槐、河北杨、油松、青海云杉和自然恢复林地的土壤真菌、细菌群落组成及多样性,分析了土壤理化性质与优势菌群的关系。结果表明: 1)不同恢复模式土壤真菌优势菌门为子囊菌门、担子菌门、被孢霉门、未分类真菌,占总真菌群落的90%以上;细菌优势菌门为放线菌门、变形菌门、酸杆菌门、绿弯菌门和其他细菌门,占总细菌群落相对丰度的80%以上。2)油松林地土壤真菌多样性最高,Shannon指数和 Simpson 指数分别为3.72±0.37、0.07±0.04。自然恢复林地真菌物种数量最高,Ace和Chao1指数分别为708.19±137.25、706.26±125.34;油松林地细菌多样性和物种数量都最高,Shannon、Simpson、Ace和Chao1指数分别为6.57±0.04、0.004±0.00、3439.81±41.67和3463.14±32.16。3)不同恢复模式相对丰度差异显著的真菌属为产油菌属、枝孢菌属、链格孢属,细菌属为67-14科未定名属、红色杆菌科红色杆菌属、鞘脂单胞菌科鞘脂单胞菌属。4)微生物优势菌群与土壤理化性质的冗余分析(RDA)表明,土壤容重(BD)、碳氮比(C/N)、pH是影响真菌优势菌群的主要因子,BD、氮磷比(N/P)、全磷(TP)、全碳(TC)是影响细菌优势菌群的主要因子。总体而言,不同恢复模式间真菌丰度差异性高于细菌丰度,表明真菌群落组成及其多样性对于不同树种和土壤环境变化较细菌群落更为敏感。研究结果将为宁南山区植被恢复措施及生态系统功能稳定性的维持提供理论支持。

关键词: 生态移民迁出区, 恢复模式, 高通量测序, 微生物群落

Abstract: To reveal the effects of plantations on soil microbial environment,the composition and diversity of soil fungi and bacterial communities in five restoration models (Robinia pseudoacacia, Populus hopeiensis, Pinus tabuliformis, Picea crassifolia, natural restoration) in the mountainous area of southern Ningxia were compared by using high-throughput sequencing technology. The correlation between soil physical-chemical properties and dominant microbial groups was analyzed. The results showed that: 1) Dominant fungi in different restoration models were Ascomycota, Basidiomycota, Mortierellomycota, and unclassified fungi, which accounted for 90% of total fungal community. The dominant soil bacteria were Actinobacteria, Proteobacteria, Acidobacteriota, Chloroflexi, and other bacteria, accounting for more than 80% of total bacterial community. 2) The diversity of soil fungi in P. tabuliformis forest was the highest, with Shannon index, and Simpson index being 3.72±0.37 and 0.07±0.04, respectively. The richness of fungi in naturally restored forest land was the highest, with Ace and Chao1 index of 708.19±137.25 and 706.26±125.34, respectively. The bacterial diversity and richness of species in P. tabuliformis forest land was the highest. The Shannon, Simpson, Ace and Chao1 indices were 6.57±0.04, 0.004±0.00, 3439.81±41.67, 3463.14±32.16, respectively. 3) The fungus with significant difference among restoration models were Solicoccozyma, Cladosporium, and Alternaria. Bacteria from Norank_f_67-14, Rubrobacter_f_Rubrobacteraceae, Sphingomonas_f_Sphingomonadaceae had significant difference among restoration models. 4) The RDA ordination of the dominant microbial flora and soil physical-chemical properties showed that soil bulk density (BD), carbon to nitrogen ratio (C/N), and pH were the major factors affecting the dominant fungal flora. BD, nitrogen to phosphorus ratio (N/P), total phosphorus (TP), and total carbon (TC) were the main factors affecting the dominant bacterial flora. In general, the difference of composition and diversity in the fungal community of different restoration models was higher than that of the bacterial community, indicating that the fungal communities were more sensitive to the changes of tree species and soil environment than bacterial communities. Our results could provide the theoretical foundation for vegetation restoration measures and the maintenance of ecosystem function stability in southern Ningxia.

Key words: ecological migration area, restoration model, high-throughput sequencing, microbial community