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Updated: Dec 13, 2025

Ecotoxicological Methodologies to Evaluate Biomarkers at Different Scales in Neotropical Anurans
Published on: April 28, 2023
Ignoring non-English-language studies may bias ecological meta-analyses
Ko Konno1, Munemitsu Akasaka2,3, Chieko Koshida4
1School of Natural Sciences Bangor University Gwynedd UK.
Abstract:
Meta-analysis plays a crucial role in syntheses of quantitative evidence in ecology and biodiversity conservation. The reliability of estimates in meta-analyses strongly depends on unbiased sampling of primary studies. Although earlier studies have explored potential biases in ecological meta-analyses, biases in reported statistical results and associated study characteristics published in different languages have never been tested in environmental sciences. We address this knowledge gap by systematically searching published meta-analyses and comparing effect-size estimates between English- and Japanese-language studies included in existing meta-analyses. Of the 40 published ecological meta-analysis articles authored by those affiliated to Japanese institutions, we find that three meta-analysis articles searched for studies in the two languages and involved sufficient numbers of English- and Japanese-language studies, resulting in four eligible meta-analyses (i.e., four meta-analyses conducted in the three meta-analysis articles). In two of the four, effect sizes differ significantly between the English- and Japanese-language studies included in the meta-analyses, causing considerable changes in overall mean effect sizes and even their direction when Japanese-language studies are excluded. The observed differences in effect sizes are likely attributable to systematic differences in reported statistical results and associated study characteristics, particularly taxa and ecosystems, between English- and Japanese-language studies. Despite being based on a small sample size, our findings suggest that ignoring non-English-language studies may bias outcomes of ecological meta-analyses, due to systematic differences in study characteristics and effect-size estimates between English- and non-English languages. We provide a list of actions that meta-analysts could take in the future to reduce the risk of language bias.
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