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Attention Score in Context
| Title |
Differential influences of local subpopulations on regional diversity and differentiation for greater sage‐grouse (Centrocercus urophasianus)
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|---|---|
| Published in |
Molecular Ecology, September 2016
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| DOI | 10.1111/mec.13776 |
| Pubmed ID | |
| Authors |
Jeffrey R. Row, Sara J. Oyler‐McCance, Bradley C. Fedy |
| Abstract |
The distribution of spatial genetic variation across a region can shape evolutionary dynamics and impact population persistence. Local population dynamics and among-population dispersal rates are strong drivers of this spatial genetic variation, yet for many species we lack a clear understanding of how these population processes interact in space to shape within-species genetic variation. Here, we used extensive genetic and demographic data from 10 subpopulations of greater sage-grouse to parameterize a simulated approximate Bayesian computation (ABC) model and 1) test for regional differences in population density and dispersal rates for greater sage-grouse subpopulations in Wyoming, and 2) quantify how these differences impact subpopulation regional influence on genetic variation. We found a close match between observed and simulated data under our parameterized model and strong variation in density and dispersal rates across Wyoming. Sensitivity analyses suggested that changes in dispersal (via landscape resistance) had a greater influence on regional differentiation, whereas changes in density had a greater influence on mean diversity across all subpopulations. Local subpopulations, however, varied in their regional influence on genetic variation. Decreases in the size and dispersal rates of central populations with low overall and net immigration (i.e., population sources) had the greatest negative impact on genetic variation. Overall, our results provide insight into the interactions among demography, dispersal, and genetic variation and highlight the potential of ABC to disentangle the complexity of regional population dynamics and project the genetic impact of changing conditions This article is protected by copyright. All rights reserved. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 3% |
| Unknown | 37 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 29% |
| Student > Ph. D. Student | 8 | 21% |
| Student > Master | 7 | 18% |
| Other | 3 | 8% |
| Professor > Associate Professor | 3 | 8% |
| Other | 3 | 8% |
| Unknown | 3 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 24 | 63% |
| Environmental Science | 6 | 16% |
| Veterinary Science and Veterinary Medicine | 1 | 3% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Computer Science | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 5 | 13% |
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 20 September 2016.
All research outputs
#18,472,072
of 22,889,074 outputs
Outputs from Molecular Ecology
#5,828
of 6,356 outputs
Outputs of similar age
#255,843
of 334,696 outputs
Outputs of similar age from Molecular Ecology
#125
of 133 outputs
Altmetric has tracked 22,889,074 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,356 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one is in the 2nd percentile – i.e., 2% of its peers scored the same or lower than it.
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We're also able to compare this research output to 133 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.