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Prototyping a Methodology for Long-Term (1680–2100) Historical-to-Future Landscape Modeling for the Conterminous United States

Overview of attention for article published in Land, May 2021
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

twitter
7 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
6 Mendeley
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Title
Prototyping a Methodology for Long-Term (1680–2100) Historical-to-Future Landscape Modeling for the Conterminous United States
Published in
Land, May 2021
DOI 10.3390/land10050536
Authors

Jordan Dornbierer, Steve Wika, Charles Robison, Gregory Rouze, Terry Sohl

Twitter Demographics

The data shown below were collected from the profiles of 7 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 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 50%
Student > Ph. D. Student 1 17%
Unknown 2 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 1 17%
Earth and Planetary Sciences 1 17%
Engineering 1 17%
Unknown 3 50%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 11 November 2021.
All research outputs
#5,767,304
of 21,131,454 outputs
Outputs from Land
#435
of 2,110 outputs
Outputs of similar age
#113,756
of 345,391 outputs
Outputs of similar age from Land
#8
of 18 outputs
Altmetric has tracked 21,131,454 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 2,110 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done well, scoring higher than 79% 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 345,391 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 66% of its contemporaries.
We're also able to compare this research output to 18 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 61% of its contemporaries.