You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Ecological prediction at macroscales using big data: Does sampling design matter?
|
|---|---|
| Published in |
Ecological Applications, April 2020
|
| DOI | 10.1002/eap.2123 |
| Pubmed ID | |
| Authors |
Patricia A. Soranno, Kendra Spence Cheruvelil, Boyang Liu, Qi Wang, Pang‐Ning Tan, Jiayu Zhou, Katelyn B. S. King, Ian M. McCullough, Jemma Stachelek, Meridith Bartley, Christopher T. Filstrup, Ephraim M. Hanks, Jean‐François Lapierre, Noah R. Lottig, Erin M. Schliep, Tyler Wagner, Katherine E. Webster |
X Demographics
The data shown below were collected from the profiles of 22 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 9 | 41% |
| United Kingdom | 1 | 5% |
| Venezuela, Bolivarian Republic of | 1 | 5% |
| Tanzania, United Republic of | 1 | 5% |
| Bangladesh | 1 | 5% |
| Ecuador | 1 | 5% |
| Unknown | 8 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 55% |
| Scientists | 8 | 36% |
| Science communicators (journalists, bloggers, editors) | 2 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 28% |
| Student > Master | 7 | 14% |
| Student > Ph. D. Student | 6 | 12% |
| Student > Doctoral Student | 3 | 6% |
| Student > Bachelor | 1 | 2% |
| Other | 3 | 6% |
| Unknown | 16 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 26% |
| Environmental Science | 12 | 24% |
| Engineering | 5 | 10% |
| Earth and Planetary Sciences | 1 | 2% |
| Unknown | 19 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 02 September 2020.
All research outputs
#2,654,768
of 24,696,958 outputs
Outputs from Ecological Applications
#692
of 3,334 outputs
Outputs of similar age
#64,228
of 380,438 outputs
Outputs of similar age from Ecological Applications
#21
of 68 outputs
Altmetric has tracked 24,696,958 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,334 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.9. 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 380,438 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 83% of its contemporaries.
We're also able to compare this research output to 68 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 70% of its contemporaries.