The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Selection experiments and the study of phenotypic plasticity
Abstract
Laboratory selection experiments are powerful tools for establishing evolutionary potentials. Such experiments provide two types of information, knowledge about genetic architecture and insight into evolutionary dynamics. They can be roughly classified into two types: (1) artificial selection in which the experimenter selects on a focal trait or trait index, and (2) quasi-natural selection in which the experimenter establishes a set of environmental conditions and then allows the population to evolve. Both approaches have been used in the study of phenotypic plasticity. Artificial selection experiments have taken various forms including: selection directly on a reaction norm, selection on a trait in multiple environments, and selection on a trait in a single environment. In the latter experiments, evolution of phenotypic plasticity is investigated as a correlated response. Quasi-natural selection experiments have examined the effects of both spatial and temporal variation. I describe how to carry out such experiments, summarize past efforts, and suggest further avenues of research.
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.
Integrity signals
Registry
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.
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
The measurement of selection on correlated characters
Lande, R., & Arnold, S. J. (1983) · Evolution · doi:10.1111/j.1558-5646.1983.tb00236.x · Cited by 5,437
Cited by
LANDE, R. (2009) · Journal of Evolutionary Biology · doi:10.1111/j.1420-9101.2009.01754.x · Cited by 1,084
Old wine in new bottles: reaction norms in salmonid fishes
Hutchings, J. A. (2011) · Heredity · doi:10.1038/hdy.2010.166 · Cited by 195
Metadata
- Authors
- Scheiner, S. M.
- Venue
- Journal of Evolutionary Biology
- Publisher
- Oxford University Press (OUP)
- Published
- 2002-11-01
- Volume
- 15
- Issue
- 6
- Pages
- 889-898
- ISSN
- 1010-061X (ISSN-L)
- 1420-9101
- OpenAlex
- W1563138337
- Cited by
- 194
- References
- 1
- FWCI
- 10.75
- 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: Selection experiments and the study of phenotypic plasticity. https://app.cochat.ai/papers/10.1046/j.1420-9101.2002.00468.x
- The paper
- Scheiner, S. M. (2002). Selection experiments and the study of phenotypic plasticity. Journal of Evolutionary Biology. https://doi.org/10.1046/j.1420-9101.2002.00468.x
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.