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Taxonomic and Functional Differences between Microbial Communities in Qinghai Lake and Its Input Streams

Overview of attention for article published in Frontiers in Microbiology, November 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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Title
Taxonomic and Functional Differences between Microbial Communities in Qinghai Lake and Its Input Streams
Published in
Frontiers in Microbiology, November 2017
DOI 10.3389/fmicb.2017.02319
Pubmed ID
Authors

Ze Ren, Fang Wang, Xiaodong Qu, James J. Elser, Yang Liu, Limin Chu

Abstract

Understanding microbial communities in terms of taxon and function is essential to decipher the biogeochemical cycling in aquatic ecosystems. Lakes and their input streams are highly linked. However, the differences between microbial assemblages in streams and lakes are still unclear. In this study, we conducted an intensive field sampling of microbial communities from lake water and stream biofilms in the Qinghai Lake watershed, the largest lake in China. We determined bacterial communities using high-throughput 16S rRNA gene sequencing and predicted functional profiles using PICRUSt to determine the taxonomic and functional differences between microbial communities in stream biofilms and lake water. The results showed that stream biofilms and lake water harbored distinct microbial communities. The microbial communities were different taxonomically and functionally between stream and lake. Moreover, streams biofilms had a microbial network with higher connectivity and modularity than lake water. Functional beta diversity was strongly correlated with taxonomic beta diversity in both the stream and lake microbial communities. Lake microbial assemblages displayed greater predicted metabolic potentials of many metabolism pathways while the microbial assemblages in stream biofilms were more abundant in xenobiotic biodegradation and metabolism and lipid metabolism. Furthermore, lake microbial assemblages had stronger predicted metabolic potentials in amino acid metabolism, carbon fixation, and photosynthesis while stream microbial assemblages were higher in carbohydrate metabolism, oxidative phosphorylation, and nitrogen metabolism. This study adds to our knowledge of stream-lake linkages from the functional and taxonomic composition of microbial assemblages.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 24%
Student > Master 10 14%
Student > Bachelor 6 9%
Researcher 5 7%
Student > Postgraduate 3 4%
Other 7 10%
Unknown 22 31%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 19%
Biochemistry, Genetics and Molecular Biology 11 16%
Environmental Science 8 11%
Immunology and Microbiology 5 7%
Engineering 2 3%
Other 5 7%
Unknown 26 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 December 2017.
All research outputs
#3,277,685
of 23,007,887 outputs
Outputs from Frontiers in Microbiology
#3,084
of 25,108 outputs
Outputs of similar age
#73,616
of 437,838 outputs
Outputs of similar age from Frontiers in Microbiology
#99
of 532 outputs
Altmetric has tracked 23,007,887 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 25,108 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 437,838 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 532 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.