Evidence map›Paper›PMID 29720718›Full record

ArticleHeredity2019

Incorporating non-equilibrium dynamics into demographic history inferences of a migratory marine species.

E L Carroll, R Alderman, J L Bannister, M Bérubé, P B Best, L Boren, C S Baker, R Constantine, K Findlay, R Harcourt and 9 more

Abstract read
In one paragraph

Article in Heredity, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Phylogeography ofParasitology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

E L CarrollScottish Oceans Institute, University of St Andrews, St Andrews, Fife, Scotland. carrollemz@gmail.com.ORCID 0000-0003-3193-7288
R AldermanDepartment of Primary Industries, Parks, Water and Environment, Hobart, Australia.
J L BannisterThe Western Australian Museum, Welshpool, DC, Australia.
M BérubéMarine Evolution and Conservation, Groningen Institute of Evolutionary Life Sciences, University of Groningen, Groningen, The Netherlands.
P B Best
L BorenNew Zealand Department of Conservation, Wellington, New Zealand.
C S BakerMarine Mammal Institute and Department of Fisheries and Wildlife, Hatfield Marine Science Center, Oregon State University, Newport, OR, USA.
R ConstantineSchool of Biological Sciences, University of Auckland, Auckland, New Zealand.
K FindlayCape Peninsula University of Technology, Cape Town, South Africa.
R HarcourtDepartment of Biological Sciences, Macquarie University, Sydney, NSW, Australia.ORCID 0000-0003-4666-2934
L LemaireScottish Oceans Institute, University of St Andrews, St Andrews, Fife, Scotland.
P J PalsbøllMarine Evolution and Conservation, Groningen Institute of Evolutionary Life Sciences, University of Groningen, Groningen, The Netherlands.ORCID 0000-0002-4198-7599
N J PatenaudeCollégial International Sainte-Anne, Montréal, QC, Canada.
V J RowntreeDepartment of Biology, University of Utah, Salt Lake City, UT, USA.
J SegerDepartment of Biology, University of Utah, Salt Lake City, UT, USA.
D SteelMarine Mammal Institute and Department of Fisheries and Wildlife, Hatfield Marine Science Center, Oregon State University, Newport, OR, USA.
L O ValenzuelaDepartment of Biology, University of Utah, Salt Lake City, UT, USA.
M WatsonDepartment of the Environment, Land, Water and Planning, Barwon South West Region, Warrnambool, VIC, Australia.
O E GaggiottiScottish Oceans Institute, University of St Andrews, St Andrews, Fife, Scotland.ORCID 0000-0003-1827-1493

Funding

Wellcome Trust
6 · The paper itself

Abstract

Understanding how dispersal and gene flow link geographically separated the populations over evolutionary history is challenging, particularly in migratory marine species. In southern right whales (SRWs, Eubalaena australis), patterns of genetic diversity are likely influenced by the glacial climate cycle and recent history of whaling. Here we use a dataset of mitochondrial DNA (mtDNA) sequences (n = 1327) and nuclear markers (17 microsatellite loci, n = 222) from major wintering grounds to investigate circumpolar population structure, historical demography and effective population size. Analyses of nuclear genetic variation identify two population clusters that correspond to the South Atlantic and Indo-Pacific ocean basins that have similar effective breeder estimates. In contrast, all wintering grounds show significant differentiation for mtDNA, but no sex-biased dispersal was detected using the microsatellite genotypes. An approximate Bayesian computation (ABC) approach with microsatellite markers compared the scenarios with gene flow through time, or isolation and secondary contact between ocean basins, while modelling declines in abundance linked to whaling. Secondary-contact scenarios yield the highest posterior probabilities, implying that populations in different ocean basins were largely isolated and came into secondary contact within the last 25,000 years, but the role of whaling in changes in genetic diversity and gene flow over recent generations could not be resolved. We hypothesise that these findings are driven by factors that promote isolation, such as female philopatry, and factors that could promote dispersal, such as oceanographic changes. These findings highlight the application of ABC approaches to infer the connectivity in mobile species with complex population histories and, currently, low levels of differentiation.

Indexed as

Evolution, MolecularGenetics, PopulationAnimalsClimateDNA, MitochondrialGene FlowGenetic VariationGenotypeHaplotypesMicrosatellite RepeatsPacific OceanPhylogenyPopulation DensityWhalesDNA, Mitochondrial

Identifiers

PMID29720718
PMCPMC6288115

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.