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Estimating Inbreeding Rates in Natural Populations: Addressing the Problem of Incomplete Pedigrees

Overview of attention for article published in Journal of Heredity, May 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

blogs
1 blog
twitter
1 tweeter

Citations

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1 Dimensions

Readers on

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13 Mendeley
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Title
Estimating Inbreeding Rates in Natural Populations: Addressing the Problem of Incomplete Pedigrees
Published in
Journal of Heredity, May 2017
DOI 10.1093/jhered/esx032
Pubmed ID
Authors

Mark P. Miller, Susan M. Haig, Jonathan D. Ballou, E. Ashley Steel

Abstract

Understanding and estimating inbreeding is essential for managing threatened and endangered wildlife populations. However, determination of inbreeding rates in natural populations is confounded by incomplete parentage information. We present an approach for quantifying inbreeding rates for populations with incomplete parentage information. The approach exploits knowledge of pedigree configurations that lead to inbreeding coefficients of F = 0.25 and F = 0.125, allowing for quantification of Pr(I|k): the probability of observing pedigree I given the fraction of known parents (k). We developed analytical expressions under simplifying assumptions that define properties and behavior of inbreeding rate estimators for varying values of k. We demonstrated that inbreeding is overestimated if Pr(I|k) is not taken into consideration and that bias is primarily influenced by k. By contrast, our new estimator, incorporating Pr(I|k), is unbiased over a wide range of values of k that may be observed in empirical studies. Stochastic computer simulations that allowed complex inter- and intra-generational inbreeding produced similar results. We illustrate the effects that accounting for Pr(I|k) can have in empirical data by revisiting published analyses of Arabian oryx (Oryx leucoryx) and Red deer (Cervus elaphus). Our results demonstrate that incomplete pedigrees are not barriers for quantifying inbreeding in wild populations. Application of our approach will permit a better understanding of the role that inbreeding plays in the dynamics of populations of threatened and endangered species and may help refine our understanding of inbreeding avoidance mechanisms in the wild.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 23%
Student > Master 2 15%
Student > Bachelor 2 15%
Other 2 15%
Student > Ph. D. Student 2 15%
Other 2 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 54%
Environmental Science 3 23%
Unspecified 1 8%
Biochemistry, Genetics and Molecular Biology 1 8%
Arts and Humanities 1 8%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 31 July 2018.
All research outputs
#1,728,388
of 12,422,413 outputs
Outputs from Journal of Heredity
#154
of 1,010 outputs
Outputs of similar age
#53,150
of 263,097 outputs
Outputs of similar age from Journal of Heredity
#5
of 23 outputs
Altmetric has tracked 12,422,413 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,010 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one has done well, scoring higher than 84% 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 263,097 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 79% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.