Literature DB >> 32512630

Illustrating the importance of meta-analysing variances alongside means in ecology and evolution.

Alfredo Sánchez-Tójar1, Nicholas P Moran1,2, Rose E O'Dea3, Klaus Reinhold1, Shinichi Nakagawa3.   

Abstract

Meta-analysis is increasingly used in biology to both quantitatively summarize available evidence for specific questions and generate new hypotheses. Although this powerful tool has mostly been deployed to study mean effects, there is untapped potential to study effects on (trait) variance. Here, we use a recently published data set as a case study to demonstrate how meta-analysis of variance can be used to provide insights into biological processes. This data set included 704 effect sizes from 89 studies, covering 56 animal species, and was originally used to test developmental stress effects on a range of traits. We found that developmental stress not only negatively affects mean trait values, but also increases trait variance, mostly in reproduction, showcasing how meta-analysis of variance can reveal previously overlooked effects. Furthermore, we show how meta-analysis of variance can be used as a tool to help meta-analysts make informed methodological decisions, even when the primary focus is on mean effects. We provide all data and comprehensive R scripts with detailed explanations to make it easier for researchers to conduct this type of analysis. We encourage meta-analysts in all disciplines to move beyond the world of means and start unravelling secrets of the world of variance.
© 2020 The Authors. Journal of Evolutionary Biology published by John Wiley & Sons Ltd on behalf of European Society for Evolutionary Biology.

Entities:  

Keywords:  coefficient of variation; early-life effects; opportunity for selection; parental effects; variability; variance ratio

Mesh:

Year:  2020        PMID: 32512630     DOI: 10.1111/jeb.13661

Source DB:  PubMed          Journal:  J Evol Biol        ISSN: 1010-061X            Impact factor:   2.411


  3 in total

1.  Viviparous mothers impose stronger glucocorticoid-mediated maternal stress effects on their offspring than oviparous mothers.

Authors:  Kirsty J MacLeod; Geoffrey M While; Tobias Uller
Journal:  Ecol Evol       Date:  2021-11-29       Impact factor: 2.912

2.  Low statistical power and overestimated anthropogenic impacts, exacerbated by publication bias, dominate field studies in global change biology.

Authors:  Yefeng Yang; Helmut Hillebrand; Malgorzata Lagisz; Ian Cleasby; Shinichi Nakagawa
Journal:  Glob Chang Biol       Date:  2021-12-10       Impact factor: 13.211

Review 3.  Terrestrial ecosystem restoration increases biodiversity and reduces its variability, but not to reference levels: A global meta-analysis.

Authors:  Joe Atkinson; Lars A Brudvig; Max Mallen-Cooper; Shinichi Nakagawa; Angela T Moles; Stephen P Bonser
Journal:  Ecol Lett       Date:  2022-05-12       Impact factor: 11.274

  3 in total

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