Special Issue "Fluctuating Asymmetry"
A special issue of Symmetry (ISSN 2073-8994).
Deadline for manuscript submissions: closed (30 January 2015)
Fluctuating asymmetry is the random deviation from perfect symmetry in populations of organisms. It is a measure of developmental noise, which reflects a population’s average state of adaptation and coadaptation. Moreover, it often increases under both environmental and genetic stress. Researchers study fluctuating asymmetry as deviations from bilateral, radial, rotational, dihedral, translational, helical, and fractal symmetries. Fluctuating asymmetry is measured via traditional measures of dispersion (variances and mean absolute deviations), landmark methods for shape asymmetry, and continuous symmetry measures. It has numerous applications in evolutionary biology, quantitative genetics, environmental biology, ecotoxicology, conservation biology, anthropology, agriculture and aquaculture, evolutionary psychology, and medicine and public health.
The aim of this Special Issue is to highlight all aspects of fluctuating asymmetry in the biological sciences. Research papers, comprehensive reviews, and discussions of theory are especially welcome. However, any other kind of paper: communication, technical note, short overview or comment will also be taken into consideration.
Dr. John H. Graham
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- fluctuating asymmetry
- directional asymmetry
- symmetry breaking
- developmental noise
- biological indicators
- Darwinian fitness
- measuring deviations from perfect symmetry
- sexual selection
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Effects of Variation in Measurement Error in the Assessment of (Fluctuating) Asymmetry: a Bayesian Model and Its Application to Simulated and Empirical Data
Author: Stefan Van Dongen
Affiliation: Evolutionary Ecology, Department of Biology, University of Antwerp; StatUA Statistics Center, University of Antwerp, Groenenborgerlaan 171 - B-2020 Antwerp, Belgium
Abstract: As the magnitude of fluctuating asymmetry (FA) is usually small relative to trait size, assessing the amount of measurement error (ME) is an important aspect in asymmetry studies. While the statistical methodology to assess and correct for ME has been developed decades ago, it is always assumed that ME does not vary across individuals. In this paper we develop a statistical model to explicitly incorporate this variation in ME in a Bayesian framework. The performance of the model is explored using simulated datasets. The model is then applied to a number of empirical datasets to assess the amount of variation in ME in real data.