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On using integral projection models to generate demographically driven predictions of species' distributions: development and validation using sparse data

Overview of attention for article published in Ecography, July 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

twitter
13 tweeters
facebook
1 Facebook page

Readers on

mendeley
149 Mendeley
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Title
On using integral projection models to generate demographically driven predictions of species' distributions: development and validation using sparse data
Published in
Ecography, July 2014
DOI 10.1111/ecog.00839
Authors

Cory Merow, Andrew M. Latimer, Adam M. Wilson, Sean M. McMahon, Anthony G. Rebelo, John A. Silander, Merow, Cory, Latimer, Andrew M., Wilson, Adam M., McMahon, Sean M., Rebelo, Anthony G., Silander, John A.

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 149 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 4%
Germany 3 2%
Switzerland 3 2%
South Africa 2 1%
Brazil 2 1%
France 1 <1%
Australia 1 <1%
Finland 1 <1%
China 1 <1%
Other 5 3%
Unknown 124 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 44 30%
Student > Ph. D. Student 39 26%
Student > Master 25 17%
Professor > Associate Professor 12 8%
Student > Bachelor 7 5%
Other 22 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 92 62%
Environmental Science 48 32%
Unspecified 4 3%
Earth and Planetary Sciences 3 2%
Arts and Humanities 1 <1%
Other 1 <1%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 10 December 2014.
All research outputs
#1,166,902
of 7,557,885 outputs
Outputs from Ecography
#372
of 973 outputs
Outputs of similar age
#30,182
of 177,122 outputs
Outputs of similar age from Ecography
#15
of 34 outputs
Altmetric has tracked 7,557,885 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 973 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one has gotten more attention than average, scoring higher than 61% 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 177,122 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 82% of its contemporaries.
We're also able to compare this research output to 34 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 55% of its contemporaries.