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Climatic extremes improve predictions of spatial patterns of tree species

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, November 2009
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

policy
1 policy source
twitter
2 X users

Citations

dimensions_citation
307 Dimensions

Readers on

mendeley
652 Mendeley
citeulike
1 CiteULike
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Title
Climatic extremes improve predictions of spatial patterns of tree species
Published in
Proceedings of the National Academy of Sciences of the United States of America, November 2009
DOI 10.1073/pnas.0901643106
Pubmed ID
Authors

Niklaus E. Zimmermann, Nigel G. Yoccoz, Thomas C. Edwards, Eliane S. Meier, Wilfried Thuiller, Antoine Guisan, Dirk R. Schmatz, Peter B. Pearman

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 652 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 16 2%
Switzerland 8 1%
Brazil 8 1%
France 5 <1%
Spain 4 <1%
Italy 3 <1%
Canada 3 <1%
United Kingdom 3 <1%
Germany 3 <1%
Other 19 3%
Unknown 580 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 194 30%
Student > Ph. D. Student 136 21%
Student > Master 56 9%
Student > Bachelor 41 6%
Student > Doctoral Student 37 6%
Other 121 19%
Unknown 67 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 286 44%
Environmental Science 201 31%
Earth and Planetary Sciences 27 4%
Biochemistry, Genetics and Molecular Biology 10 2%
Computer Science 5 <1%
Other 32 5%
Unknown 91 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 15 July 2021.
All research outputs
#7,629,858
of 26,017,215 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#62,782
of 104,451 outputs
Outputs of similar age
#46,046
of 184,971 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#525
of 871 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 104,451 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.5. This one is in the 37th percentile – i.e., 37% of its peers scored the same or lower than it.
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 184,971 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 72% of its contemporaries.
We're also able to compare this research output to 871 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.