Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 811

The DOI matches its Crossref record.

A generalized approach for estimating effective population size from temporal changes in allele frequency.

Waples, R S·1989·Genetics

Abstract

The temporal method for estimating effective population size (Ne) from the standardized variance in allele frequency change (F) is presented in a generalized form. Whereas previous treatments of this method have adopted rather limiting assumptions, the present analysis shows that the temporal method is generally applicable to a wide variety of organisms. Use of a revised model of gene sampling permits a more generalized interpretation of Ne than that used by some other authors studying this method. It is shown that two sampling plans (individuals for genetic analysis taken before or after reproduction) whose differences have been stressed by previous authors can be treated in a uniform way. Computer simulations using a wide variety of initial conditions show that different formulas for computing F have much less effect on Ne than do sample size (S), number of generations between samples (t), or the number of loci studied (L). Simulation results also indicate that (1) bias of F is small unless alleles with very low frequency are used; (2) precision is typically increased by about the same amount with a doubling of S, t, or L; (3) confidence intervals for Ne computed using a chi 2 approximation are accurate and unbiased under most conditions; (4) the temporal method is best suited for use with organisms having high juvenile mortality and, perhaps, a limited effective population size.

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 · 10.1093/genetics/121.2.379

Cites

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

Cited by

See all 811

Metadata

Authors
Waples, R. S.
Venue
Genetics
Published
1989-02-01
Volume
121
Issue
2
Pages
379-391
ISSN
  • 0016-6731 (ISSN-L)
  • 1943-2631
OpenAlex
W2131700426
Cited by
811
References
0
FWCI
2.72
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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A generalized approach for estimating effective population size from temporal changes in allele frequency. https://app.cochat.ai/papers/10.1093/genetics/121.2.379
The paper
Waples, R. S. (1989). A generalized approach for estimating effective population size from temporal changes in allele frequency. Genetics. https://doi.org/10.1093/genetics/121.2.379

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.