Literature DB >> 27912008

Heterogeneity in ecological and evolutionary meta-analyses: its magnitude and implications.

Alistair M Senior1,2, Catherine E Grueber3,4, Tsukushi Kamiya5, Malgorzata Lagisz6, Katie O'Dwyer7, Eduardo S A Santos8, Shinichi Nakagawa6.   

Abstract

Meta-analysis is the gold standard for synthesis in ecology and evolution. Together with estimating overall effect magnitudes, meta-analyses estimate differences between effect sizes via heterogeneity statistics. It is widely hypothesized that heterogeneity will be present in ecological/evolutionary meta-analyses due to the system-specific nature of biological phenomena. Despite driving recommended best practices, the generality of heterogeneity in ecological data has never been systematically reviewed. We reviewed 700 studies, finding 325 that used formal meta-analysis, of which total heterogeneity was reported in fewer than 40%. We used second-order meta-analysis to collate heterogeneity statistics from 86 studies. Our analysis revealed that the median and mean heterogeneity, expressed as I2 , are 84.67% and 91.69%, respectively. These estimates are well above "high" heterogeneity (i.e., 75%), based on widely adopted benchmarks. We encourage reporting heterogeneity in the forms of I2 and the estimated variance components (e.g., τ2 ) as standard practice. These statistics provide vital insights in to the degree to which effect sizes vary, and provide the statistical support for the exploration of predictors of effect-size magnitude. Along with standard meta-regression techniques that fit moderator variables, multi-level models now allow partitioning of heterogeneity among correlated (e.g., phylogenetic) structures that exist within data.
© 2016 by the Ecological Society of America.

Keywords:  zzm321990Izzm3219902zzm321990; Cochran's Q; eco-evolutionary meta-analysis; effect size; homogeneity; meta-regression; mixed model; phylogenetic signal/heritability; quantitative review; sampling variance; systematic review; weighted regression

Mesh:

Year:  2016        PMID: 27912008     DOI: 10.1002/ecy.1591

Source DB:  PubMed          Journal:  Ecology        ISSN: 0012-9658            Impact factor:   5.499


  26 in total

1.  How general is cognitive ability in non-human animals? A meta-analytical and multi-level reanalysis approach.

Authors:  Marc-Antoine Poirier; Dovid Y Kozlovsky; Julie Morand-Ferron; Vincent Careau
Journal:  Proc Biol Sci       Date:  2020-12-09       Impact factor: 5.349

Review 2.  Linking personality and cognition: a meta-analysis.

Authors:  Liam R Dougherty; Lauren M Guillette
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2018-09-26       Impact factor: 6.237

3.  High plant diversity and slow assembly of old-growth grasslands.

Authors:  Ashish N Nerlekar; Joseph W Veldman
Journal:  Proc Natl Acad Sci U S A       Date:  2020-07-16       Impact factor: 11.205

4.  Structural colours reflect individual quality: a meta-analysis.

Authors:  Thomas E White
Journal:  Biol Lett       Date:  2020-04-15       Impact factor: 3.703

5.  Meta-analysis reveals weak associations between intrinsic state and personality.

Authors:  Petri T Niemelä; Niels J Dingemanse
Journal:  Proc Biol Sci       Date:  2018-02-28       Impact factor: 5.349

Review 6.  Meta-analysis and the science of research synthesis.

Authors:  Jessica Gurevitch; Julia Koricheva; Shinichi Nakagawa; Gavin Stewart
Journal:  Nature       Date:  2018-03-07       Impact factor: 49.962

7.  Temporal and spatial limitations in global surveillance for bat filoviruses and henipaviruses.

Authors:  Daniel J Becker; Daniel E Crowley; Alex D Washburne; Raina K Plowright
Journal:  Biol Lett       Date:  2019-12-11       Impact factor: 3.703

8.  A meta-analysis on the evolution of the Lombard effect reveals that amplitude adjustments are a widespread vertebrate mechanism.

Authors:  Hansjoerg P Kunc; Kyle Morrison; Rouven Schmidt
Journal:  Proc Natl Acad Sci U S A       Date:  2022-07-18       Impact factor: 12.779

9.  Meta-analytic evidence that animals rarely avoid inbreeding.

Authors:  Raïssa A de Boer; Regina Vega-Trejo; Alexander Kotrschal; John L Fitzpatrick
Journal:  Nat Ecol Evol       Date:  2021-05-03       Impact factor: 15.460

Review 10.  Comparing the Ecological Stoichiometry in Green and Brown Food Webs - A Review and Meta-analysis of Freshwater Food Webs.

Authors:  Michelle A Evans-White; Halvor M Halvorson
Journal:  Front Microbiol       Date:  2017-06-29       Impact factor: 5.640

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