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Keeping things local: Subpopulation Nb and Ne in a stream network with partial barriers to fish migration

Overview of attention for article published in Evolutionary Applications, February 2017
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Title
Keeping things local: Subpopulation Nb and Ne in a stream network with partial barriers to fish migration
Published in
Evolutionary Applications, February 2017
DOI 10.1111/eva.12454
Pubmed ID
Authors

Andrew R. Whiteley, Jason A. Coombs, Matthew J. O'Donnell, Keith H. Nislow, Benjamin H. Letcher

Abstract

For organisms with overlapping generations that occur in metapopulations, uncertainty remains regarding the spatiotemporal scale of inference of estimates of the effective number of breeders (N^b) and whether these estimates can be used to predict generational Ne. We conducted a series of tests of the spatiotemporal scale of inference of estimates of Nb in nine consecutive cohorts within a long-term study of brook trout (Salvelinus fontinalis). We also tested a recently developed approach to estimate generational Ne from N^b and compared this to an alternative approach for estimating N^e that also accounts for age structure. Multiple lines of evidence were consistent with N^b corresponding to the local (subpopulation) spatial scale and the cohort-specific temporal scale. We found that at least four consecutive cohort-specific estimates of N^b were necessary to obtain reliable estimates of harmonic mean N^b for a subpopulation. Generational N^e derived from cohort-specific N^b was within 7%-50% of an alternative approach to obtain N^e, suggesting some population specificity for concordance between approaches. Our results regarding the spatiotemporal scale of inference for Nb should apply broadly to many taxa that exhibit overlapping generations and metapopulation structure and point to promising avenues for using cohort-specific N^b for local-scale genetic monitoring.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 29%
Student > Master 9 20%
Researcher 8 18%
Professor 4 9%
Student > Postgraduate 3 7%
Other 4 9%
Unknown 4 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 53%
Environmental Science 10 22%
Biochemistry, Genetics and Molecular Biology 5 11%
Veterinary Science and Veterinary Medicine 1 2%
Unknown 5 11%

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 23 December 2016.
All research outputs
#15,828,487
of 17,911,762 outputs
Outputs from Evolutionary Applications
#1,128
of 1,205 outputs
Outputs of similar age
#329,279
of 395,002 outputs
Outputs of similar age from Evolutionary Applications
#23
of 25 outputs
Altmetric has tracked 17,911,762 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
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