Department of Landscape Architecture, School of Design, Shanghai Jiao Tong University, Shanghai, China.
Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, United States of America.
PLoS One. 2021 May 10;16(5):e0251501. doi: 10.1371/journal.pone.0251501. eCollection 2021.
As an alternative for phospholipid fatty acid (PLFA) analysis, a simpler ester linked fatty acid (ELFA) analysis has been developed to characterize soil microbial communities. However, few studies have compared the two methods in forest soils where the contribution of nonmicrobial sources may be larger than that of microbial sources. Moreover, it remains unclear whether the two methods yield similar relationships of microbial biomass and composition with environmental variables. Here, we compared PLFA and ELFA methods with respect to microbial biomass and composition and their relationships with environmental variables in six oriental oak (Quercus variabilis) forest sites along a 1500-km latitudinal gradient in East China. We found that both methods had a low sample-to-sample variability and successfully separated overall community composition of sites. However, total, bacterial, and fungal biomass, the fungal-to-bacterial ratio, and the gram-positive to gram-negative bacteria ratio were not significantly or strongly correlated between the two methods. The relationships of these microbial properties with environmental variables (pH, precipitation, and clay) greatly differed between the two methods. Our study indicates that despite its simplicity, the ELFA method may not be as feasible as the PLFA method for investigating microbial biomass and composition and for identifying their dominant environmental drivers, at least in forest soils.
作为磷脂脂肪酸(PLFA)分析的替代方法,一种更简单的酯键脂肪酸(ELFA)分析已被开发出来,用于表征土壤微生物群落。然而,在森林土壤中,非微生物来源的贡献可能比微生物来源的更大,因此很少有研究比较这两种方法。此外,目前尚不清楚这两种方法是否会产生与环境变量相似的微生物生物量和组成关系。在这里,我们比较了 PLFA 和 ELFA 方法在 6 个东方栎(Quercus variabilis)林地点的微生物生物量和组成及其与环境变量的关系,这些地点位于中国东部 1500 公里的纬度梯度上。我们发现,这两种方法的样品间变异性都较低,并且成功地分离了各地点的总体群落组成。然而,两种方法之间的总生物量、细菌生物量、真菌生物量、真菌与细菌的比例以及革兰氏阳性菌与革兰氏阴性菌的比例没有显著或强相关性。这些微生物特性与环境变量(pH 值、降水和粘土)之间的关系在两种方法之间有很大的差异。我们的研究表明,尽管 ELFA 方法很简单,但与 PLFA 方法相比,它在调查微生物生物量和组成以及确定其主要环境驱动因素方面可能并不那么可行,至少在森林土壤中是如此。