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Combining nutrient, productivity, and landscape‐based regressions improves predictions of lake nutrients and provides insight into nutrient coupling at macroscales

Overview of attention for article published in Limnology & Oceanography, July 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

twitter
11 X users

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
25 Mendeley
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Title
Combining nutrient, productivity, and landscape‐based regressions improves predictions of lake nutrients and provides insight into nutrient coupling at macroscales
Published in
Limnology & Oceanography, July 2018
DOI 10.1002/lno.10944
Authors

Tyler Wagner, Erin M. Schliep

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 32%
Researcher 6 24%
Student > Master 4 16%
Student > Doctoral Student 2 8%
Other 1 4%
Other 1 4%
Unknown 3 12%
Readers by discipline Count As %
Environmental Science 11 44%
Agricultural and Biological Sciences 5 20%
Earth and Planetary Sciences 2 8%
Mathematics 1 4%
Physics and Astronomy 1 4%
Other 1 4%
Unknown 4 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 18 July 2018.
All research outputs
#6,605,934
of 26,542,140 outputs
Outputs from Limnology & Oceanography
#1,081
of 3,556 outputs
Outputs of similar age
#100,831
of 343,887 outputs
Outputs of similar age from Limnology & Oceanography
#19
of 39 outputs
Altmetric has tracked 26,542,140 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,556 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has gotten more attention than average, scoring higher than 69% 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 343,887 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.