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Refining species distribution model outputs using landscape-scale habitat data: Forecasting grass carp and Hydrilla establishment in the Great Lakes region

Overview of attention for article published in Journal of Great Lakes Research, April 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
6 X users
facebook
1 Facebook page

Citations

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12 Dimensions

Readers on

mendeley
55 Mendeley
Title
Refining species distribution model outputs using landscape-scale habitat data: Forecasting grass carp and Hydrilla establishment in the Great Lakes region
Published in
Journal of Great Lakes Research, April 2017
DOI 10.1016/j.jglr.2016.09.008
Authors

Marion E. Wittmann, Gust Annis, Andrew M. Kramer, Lacey Mason, Catherine Riseng, Edward S. Rutherford, William L. Chadderton, Dmitry Beletsky, John M. Drake, David M. Lodge

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 27%
Student > Master 10 18%
Student > Bachelor 7 13%
Student > Ph. D. Student 5 9%
Student > Doctoral Student 2 4%
Other 7 13%
Unknown 9 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 36%
Environmental Science 15 27%
Computer Science 2 4%
Biochemistry, Genetics and Molecular Biology 1 2%
Arts and Humanities 1 2%
Other 3 5%
Unknown 13 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 2018.
All research outputs
#7,661,332
of 23,322,966 outputs
Outputs from Journal of Great Lakes Research
#605
of 1,705 outputs
Outputs of similar age
#121,493
of 310,397 outputs
Outputs of similar age from Journal of Great Lakes Research
#9
of 22 outputs
Altmetric has tracked 23,322,966 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,705 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has gotten more attention than average, scoring higher than 51% 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 310,397 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 53% of its contemporaries.
We're also able to compare this research output to 22 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 63% of its contemporaries.