Heterogeneity in ecological and evolutionary meta‐analyses: its magnitude and implications
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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., τ 2) 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.
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Another challenge is an unfortunate outcome of the high impact and growing prestige of meta-analyses coupled with use of metrics such as citation numbers and h-indices in evaluations of research accomplishments, resulting in unease among some primary researchers about the fairness and rewards of the scientific process.
“Another challenge is an unfortunate outcome of the high impact and growing prestige of metaanalyses 71 , coupled with use of metrics such as citation numbers and h -indices in evaluations of research accomplishments, resulting in unease among some primary researchers about the fairness and rewards of the scientific process 72 .”
From Meta-analysis and the science of research synthesis (2018) · cites this paper as [71]
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- Authors
- Senior, A. M., Grueber, C. E., Kamiya, T., Lagisz, M., O'Dwyer, K., Santos, E. S. A., & Nakagawa, S.
- Affiliations
- The University of Sydney (AU)
- University of Toronto (CA)
- UNSW Sydney (AU)
- Department of Chemistry and Biology Ryerson University Toronto Ontario M5B 2K3 Canada
- Universidade de São Paulo (BR)
- Corresponding author
- Senior, Alistair M.
- ORCID
- Venue
- Ecology
- Publisher
- Wiley
- Published
- 2016-12
- Volume
- 97
- Issue
- 12
- Pages
- 3293-3299
- ISSN
- 0012-9658 (ISSN-L)
- 1939-9170
- OpenAlex
- W2531477340
- Cited by
- 299
- References
- 41
- Citations by year
- 2026: 40 · 2025: 32 · 2024: 40 · 2023: 42 · 2022: 48 · 2021: 25 · 2020: 23 · 2019: 22 · 2018: 18 · 2017: 7 · 2013: 1
- FWCI
- 14.63
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Ecology (publishedVersion)
- PubMed (publishedVersion)
- UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
- Funders
- Fundação de Amparo à Pesquisa do Estado de São Paulo (2012/20468‐4)
- Australian Research Council (FT130100268)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- heterogeneity, I2 statistic, reporting practices, phylogenetic structure, multi-level model, meta-regression
- MeSH terms
- Data Interpretation, Statistical, Ecology, Biological Evolution, Research Design, Meta-Analysis as Topic, Models, Statistical, Bias
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