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Cited by 553Meta-analysis and systematic reviewsPsychology Research and Bibliometricsscientometrics and bibliometrics research

How much variance can be explained by ecologists and evolutionary biologists?

Møller, Anders, Jennions, Michael D.·2002·Oecologia
DOI 10.1007/s00442-002-0952-2
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Abstract

The average amount of variance explained by the main factor of interest in ecological and evolutionary studies is an important quantity because it allows evaluation of the general strength of research findings. It also has important implications for the planning of studies. Theoretically we should be able to explain 100% of the variance in data, but randomness and noise may reduce this amount considerably in biological studies. We performed a meta-analysis using data from 43 published meta-analyses in ecology and evolution with 93 estimates of mean effect size using Pearson's r and 136 estimates using Hedges' d or g. This revealed that (depending on the exact analysis) the mean amount of variance (r 2 ) explained was 2.51-5.42%. The various 95% confidence intervals fell between 1.99 and 7.05%. There was a strongly positive relationship between the fail-safe number (the number of null results needed to nullify an effect) and the coefficient of determination (r 2 ) or effect size. Analysis at the level of individual tests of null hypotheses showed that the amount of variance key factors explained differed among fields with the largest amount in physiological ecology, lower amounts in ecology and the lowest in evolutionary studies. In all fields though, the hypothesized relationship (e.g. main effect of a fixed treatment) explained little of the variation in the trait of interest. Our finding has important implications for the interpretation of scientific studies. Across studies…

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  • In complex systems such as animal communities and ecosystems, the relationship between measurable variables is rarely high, as shown by a review of meta-analyses in ecology (r = 0.18, CI [0.15, 0.21]).

    “In complex systems such as animal communities and ecosystems, the relationship between measurable variables is rarely high, as shown by a review of meta‐analyses in ecology (r = 0.18, CI [0.15, 0.21]; Møller & Jennions, 2002).”

    From Acoustic indices as proxies for biodiversity: a meta‐analysis (2022) · cites this paper as Møller & Jennions, 2002

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Authors
Møller, A., & Jennions, M. D.
Affiliations
  • Centre National de la Recherche Scientifique (FR)
  • Australian National University (AU)
Corresponding author
Møller, Anders
ORCID
Venue
Oecologia
Publisher
Springer Science and Business Media LLC
Published
2002-08
Volume
132
Issue
4
Pages
492-500
ISSN
  • 0029-8549 (ISSN-L)
  • 1432-1939
DOI
10.1007/s00442-002-0952-2
OpenAlex
W2132059682
Cited by
553
References
2
Citations by year
2026: 26 · 2025: 21 · 2024: 15 · 2023: 26 · 2022: 19 · 2021: 39 · 2020: 26 · 2019: 22 · 2018: 33 · 2017: 18 · 2016: 27 · 2015: 24 · 2014: 30 · 2013: 23 · 2012: 22
FWCI
24.44
Type
journal article
Language
en
Open access
closed
Licence
www.springer.com/tdm (tdm)
Locations
  • Oecologia (publishedVersion)
  • PubMed (publishedVersion)
  • ANU Open Research (Australian National University) (submittedVersion)
  • Smithsonian Digital Repository (Smithsonian Institution) (submittedVersion)
Topics
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
Keywords
explained variance, effect size, statistical power, sample size, null hypothesis testing, ecological study, evolutionary studies, statistical significance, study design planning

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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.

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