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Covariation patterns of phytoplankton and bacterioplankton in hypertrophic shallow lakes.
FEMS Microbiology Ecology ( IF 4.2 ) Pub Date : 2020-08-20 , DOI: 10.1093/femsec/fiaa161
M R Schiaffino 1, 2 , P Huber 3 , M Sagua 1, 2 , C A Sabio Y García 4, 5 , M Reissig 6
Affiliation  

The aim of this work was to assess the temporal patterns in the community composition of phytoplankton (PCC) and bacterioplankton (BCC) in two interconnected and hypertrophic Pampean shallow lakes (Argentina). Factors shaping their community dynamics and community temporal covariations were also analysed. We performed 4 years of seasonal samplings (2012–2016) and communities were studied by Utermöhl approach (PCC) and Illumina MiSeq sequencing (BCC). We found marked seasonal variations in both communities, and inter-annual variations with decreasing microbial community similarities along the study. We also observed covariation in community-level dynamics among PCC and BCC within- and between-shallow lakes. The within-lake covariations remained positive and significant, while controlling for the effects of intrinsic (environmental) and extrinsic (temporal and meteorological) factors, suggesting a community coupling mediated by intrinsic biotic interactions. Algal-bacterial associations between different taxa of phytoplankton and bacterioplankton within each lake were also found. PCC was mainly explained by pure regional extrinsic (17–21%) and intrinsic environmental (8–9%) factors, while BCC by environmental (8–10%) and biotic interactions with phytoplankton (7–8%). Our results revealed that the influence of extrinsic regional factors can be channeled to bacterioplankton through both environmental (i.e. water temperature) and phytoplankton effects.

中文翻译:

肥厚浅水湖泊中浮游植物和浮游植物的协变模式。

这项工作的目的是评估两个相互联系且肥大的庞氏浅湖(阿根廷)中浮游植物(PCC)和浮游细菌(BCC)的群落组成的时间格局。还分析了影响其社区动态和社区时间变异的因素。我们进行了4年的季节性采样(2012-2016年),并通过Utermöhl方法(PCC)和Illumina MiSeq测序(BCC)对社区进行了研究。我们在研究中发现两个社区都有明显的季节性变化,并且年际变化伴随微生物群落相似性的降低。我们还观察到浅水湖泊之间和浅水湖泊之间PCC和BCC之间的社区级动态协变。湖内协变量仍然为正且显着,同时控制内在(环境)和外在(时间和气象)因素的影响,表明由内在生物相互作用介导的社区耦合。还发现了每个湖中浮游植物和浮游细菌的不同分类之间的藻类细菌联系。PCC主要由纯区域外在因素(17–21%)和内在环境因素(8–9%)解释,而BCC由环境因素(8–10%)和与浮游植物的生物相互作用(7–8%)解释。我们的研究结果表明,外部环境因素的影响可以通过环境(即水温)和浮游植物的影响传递给浮游细菌。还发现了每个湖中浮游植物和浮游细菌的不同种类之间的藻类细菌联系。PCC主要由纯区域外在因素(17–21%)和内在环境因素(8–9%)解释,而BCC由环境因素(8–10%)和与浮游植物的生物相互作用(7–8%)解释。我们的研究结果表明,外部环境因素的影响可以通过环境(即水温)和浮游植物的影响传递给浮游细菌。还发现了每个湖中浮游植物和浮游细菌的不同种类之间的藻类细菌联系。PCC主要由纯区域外在因素(17–21%)和内在环境因素(8–9%)解释,而BCC由环境因素(8–10%)和与浮游植物的生物相互作用(7–8%)解释。我们的研究结果表明,外部环境因素的影响可以通过环境(即水温)和浮游植物的影响传递给浮游细菌。
更新日期:2020-08-20
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