Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 2,024

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Microsatellite analysis of population structure in Canadian polar bears

PAETKAU, D., CALVERT, W., STIRLING, I., STROBECK, C.·1995·Molecular Ecology

Abstract

Attempts to study the genetic population structure of large mammals are often hampered by the low levels of genetic variation observed in these species. Polar bears have particularly low levels of genetic variation with the result that their genetic population structure has been intractable. We describe the use of eight hypervariable microsatellite loci to study the genetic relationships between four Canadian polar bear populations: the northern Beaufort Sea, southern Beaufort Sea, western Hudson Bay, and Davis Strait ‐ Labrador Sea. These markers detected considerable genetic variation, with average heterozygosity near 60% within each population. Interpopulation differences in allele frequency distribution were significant between all pairs of populations, including two adjacent populations in the Beaufort Sea. Measures of genetic distance reflect the geographic distribution of populations, but also suggest patterns of gene flow which are not obvious from geography and may reflect movement patterns of these animals. Distribution of variation is sufficiently different between the Beaufort Sea populations and the two more eastern ones that the region of origin for a given sample can be predicted based on its expected genotype frequency using an assignment test. These data indicate that gene flow between local populations is restricted despite the long‐distance seasonal movements undertaken by polar bears.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/j.1365-294x.1995.tb00227.x

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

Metadata

Authors
PAETKAU, D., CALVERT, W., STIRLING, I., & STROBECK, C.
Venue
Molecular Ecology
Publisher
Wiley
Published
1995-06
Volume
4
Issue
3
Pages
347-354
ISSN
  • 0962-1083 (ISSN-L)
  • 1365-294X
OpenAlex
W2072076632
Cited by
2,024
References
1
FWCI
8.92
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.