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Journal of Desert Research ›› 2019, Vol. 39 ›› Issue (5): 71-79.DOI: 10.7522/j.issn.1000-694X.2018.00087

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Recovery of Soil Microbe Quantities Dependent on Fine Particle Contents after Establishment of Sand-fixing Revegetation in Desert Region

Lv Xingyu1,2, Zhang Zhishan1   

  1. 1. Shapotou Desert Research and Experiment Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2018-05-30 Revised:2018-09-14 Online:2019-09-29 Published:2019-09-29

Abstract: As an important component of desert ecosystem, soil microbes participate in the processes of soil-forming and biogeochemical cycle. Soil microbe quantities reflecting soil quality is an important index which can be used to determine the recovery degree of degraded ecosystems. We studied the quantities of fungi, bacteria, and actinomycetes with a restoration chronosequence in Shapotou sand-binding revegetation area, and analyzed their temporal and spatial distributions, recovery characteristics and their impact factors. The results showed that soil microbe quantities increase with increasing age of revegetation and soil depth. In general, soil microbe quantities were higher in summer and autumn than those in spring and winter. The recovery processes of microbe quantities followed S shape curve that the recovery rates reached to the maximum 18 to 24 years after the establishment of sand-fixing vegetation, and the microbe quantities reached to 31.6% to 83.7% of the natural vegetation area 24 to 36 years after the establishment. The microbe recovery processes were primarily influenced by the fine particle contents of soil and limited by soil pH. The results meant that soil microbes were sensitive to soil conditions and vegetation cover, and their fluctuation could make an early and sensitive indication of the changes in ecosystem functions.

Key words: sand-fixing revegetation, soil microbe quantities, recovery, temporal and spatial distributions, path analysis

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