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Effect of simulated atmospheric nitrogen deposition on soil microbial community structure in a temperate forest.

XU Ke, WANG Chun-mei*, ZHANG Yi, YANG Xin-tong, LIU Wei-min   

  1. (College of Environmental Science & Engineering, Beijing Forestry University, Beijing 100083, China).
  • Online:2016-10-10 Published:2016-10-10

Abstract: Atmospheric nitrogen (N) deposition is a serious threat to global ecosystems. Soil microbes are sensitive to environmental changes. Investigating the effects of N deposition on soil microbial community structure may provide theoretical basis for scientific management of forest ecosystems. A manipulative field experiment was conducted to investigate the effects of different forms (NH4NO3, (NH4)2SO4, NaNO3) and different levels (0, 50, 150 kg N·hm-2·a-1) of N addition on the microbial community structure in a temperate forest soil. Soil microbial community structure was measured using the method of phospholipid fatty acid analysis (PLFA) after three consecutive years of N addition treatments. Our results showed that the amounts of total PLFA, bacterial PLFA, G+ bacterial PLFA, G- bacterial PLFA and fungal PLFA in N addition plots were significantly higher than that in control plots, and N addition increased the amount of microbial PLFA significantly in the order of high N addition > low N addition > control. The amounts of total PLFA, bacterial PLFA, fungal PLFA and actinomyces PLFA in NH4NO3N addition plots were generally higher than that in NaNO3N addition and (NH4)2SO4N addition plots at the same N addition level. Principal component analysis (PCA) showed that microbial community structures were changed in all Nadded plots except the low (NH4)2SO4N addition plots. Overall, these results suggested that N addition would increase soil microbial biomass and change soil microbial community structure in forest soils when N addition level reaches a threshold, at least over the short term.

Key words: geographically weighted regression (GWR), Beijing-Tianjin-Tangshan urban agglomeration, land cover, land surface temperature (LST), spatial non-stationarity.