黄土丘陵沟壑区不同植被恢复格局下土壤微生物群落结构

Soil microbial community structure under different vegetation restoration patterns in the loess hilly area

针对典型黄土丘陵沟壑区陕西延安羊圈沟小流域坡面上单一刺槐林、单一撂荒草地以及林草搭配的草地-林地-草地及林地-草地-林地4种不同植被格局,利用磷脂脂肪酸(phospholipid fatty acid,PLFA)谱图分析法对土壤微生物群落结构进行监测研究,旨在揭示坡面上不同的植被恢复格局对土壤微生物群落结构的影响。研究发现4种不同植被格局下,2种林草搭配的植被格局磷脂脂肪酸的结构比较相似,与单一植被格局相比,表层土壤中表征真菌的特征脂肪酸所占的比例有所提高。主成分分析显示4种植被格局0—10 cm土壤微生物群落结构存在差异,差异主要存在于2种林草搭配的植被格局与2种单一的植被格局之间,其中草地-林地-草地的植被格局与刺槐林和撂荒草地之间土壤微生物群落结构的差异均达到了显著水平。不同微生物菌群的量在4种植被格局土壤间显著性差异主要存在于表层土壤中的细菌菌群和革兰氏阳性菌,革兰氏阴性菌和真菌在4种植被格局土壤之间无显著差异。总之,4种不同植被恢复格局的土壤微生物群落结构存在差异且差异主要存在于表层土壤,坡面上人工林的种植及林草搭配的恢复模式较直接撂荒更有利于提高微生物菌群的生物量。

Soil erosion is still severe in the Loess Plateau, and vegetation restoration practices are effective measures to fight it by reducing nutrient loss and improving soil quality. Soil microorganisms are important for soil ecosystem, which play crucial roles in biogeochemical cycling and ecosystem functioning. Soil biological and biochemical properties, such as microbial biomass, microbial community composition, and microbial functional diversity are frequently used for detecting accurate changes in soil properties. The major purpose of this study therefore, is to discover the effects of different vegetation restoration patterns on soil microbial community structures in the Loess Plateau. The study area was located in Yangjuangou catchment, a typical loess hilly area near Yan＇an city of northern Shaanxi province, China. Four typical hillslopes, including F （artificial forest）, G （grass）, G-F-G （grass on the upper and lower slopes and artificial forest on the middle slope）, and F-G-F （artificial forest on the upper and lower slopes and grass on the middle slope）, were chosen. Several soil sampling sites, each covered by an area of 200m2, were conducted on the summit, shoulder, backslope, footslope and toeslope along each hillslope, respectively. Three experimental plots in each site were conducted with an area of 25 m2. Soil samples in the first two vertical layers （0-10 cm and 10-20 cm） were collected in August of 2007, for analyzing soil microbial community structure and soil physicochemical properties. Soil microbial community structure was analyzed by using phospholipid fatty acid （PLFA） analytical method and soil physicochemical properties were done by general soil and agricultural chemistry analytical methods. Results showed that significant difference of phospholipid fatty acid composition existed between different soil layers and soils with different vegetation restoration patterns, mainly in surface soil layer collected from G-F-G and F-G-F differing with that from F and G. The proportion of phospholipid fatty acid indicated fungi was higher in the surface soils under G-F-G and F-G-F, compared to F and G. Principal components analysis （PCA） showed that in the 0-10 cm soil layer, the phospholipid fatty acid structure of G-F-G was different with that of F and G, while the phospholipid fatty acid structure of F-G-F was different with F significantly. The biomass of soil bacteria, fungi, Gram-negative bacteria and Gram-positive bacteria under F-G-F pattern were all captured the highest values. There was significant difference of soil bacteria biomass and Gram-positive bacteria biomass in the surface soil layers among the four mentioned vegetation restoration patterns. The biomass of soil bacteria and fungi, however, had non-significant difference among 10-20 cm soil layers with different vegetation restoration patterns. Redundancy analysis （RDA） showed that soil organic carbon and total nitrogen had more important relationship with soil microbial community. However, the effects of some physicochemical properties such like pH and bulk density on soil microbial community needed more study. In conclusion, microbial community structure was dissimilar in soils and significant difference mainly appeared in surface soil layers under four vegetation restoration patterns. The roles of artificial forestation and forest-grass collocation on the slope in improving soil microbial biomass were believed much better than abandoned farmland.