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Mendeley readers
Attention Score in Context
| Title |
Population distribution models: species distributions are better modeled using biologically relevant data partitions
|
|---|---|
| Published in |
BMC Ecology and Evolution, September 2011
|
| DOI | 10.1186/1472-6785-11-20 |
| Pubmed ID | |
| Authors |
Sergio C Gonzalez, J Angel Soto-Centeno, David L Reed |
| Abstract |
Predicting the geographic distribution of widespread species through modeling is problematic for several reasons including high rates of omission errors. One potential source of error for modeling widespread species is that subspecies and/or races of species are frequently pooled for analyses, which may mask biologically relevant spatial variation within the distribution of a single widespread species. We contrast a presence-only maximum entropy model for the widely distributed oldfield mouse (Peromyscus polionotus) that includes all available presence locations for this species, with two composite maximum entropy models. The composite models either subdivided the total species distribution into four geographic quadrants or by fifteen subspecies to capture spatially relevant variation in P. polionotus distributions. |
Mendeley readers
The data shown below were compiled from readership statistics for 184 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 5 | 3% |
| Germany | 4 | 2% |
| United States | 4 | 2% |
| Italy | 3 | 2% |
| Portugal | 2 | 1% |
| Greece | 2 | 1% |
| Czechia | 1 | <1% |
| United Kingdom | 1 | <1% |
| Bulgaria | 1 | <1% |
| Other | 4 | 2% |
| Unknown | 157 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 37 | 20% |
| Researcher | 32 | 17% |
| Student > Master | 28 | 15% |
| Student > Bachelor | 18 | 10% |
| Student > Doctoral Student | 13 | 7% |
| Other | 33 | 18% |
| Unknown | 23 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 108 | 59% |
| Environmental Science | 34 | 18% |
| Arts and Humanities | 2 | 1% |
| Nursing and Health Professions | 2 | 1% |
| Earth and Planetary Sciences | 2 | 1% |
| Other | 7 | 4% |
| Unknown | 29 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 22 September 2011.
All research outputs
#17,286,645
of 25,374,917 outputs
Outputs from BMC Ecology and Evolution
#2,929
of 3,714 outputs
Outputs of similar age
#99,734
of 141,299 outputs
Outputs of similar age from BMC Ecology and Evolution
#43
of 61 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,714 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one is in the 14th percentile – i.e., 14% 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 141,299 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.