Konno Ko, Akasaka Munemitsu, Koshida Chieko, Katayama Naoki, Osada Noriyuki, Spake Rebecca, Amano Tatsuya
School of Natural Sciences Bangor University Gwynedd UK.
Institute of Agriculture Tokyo University of Agriculture and Technology Fuchu Japan.
Ecol Evol. 2020 May 29;10(13):6373-6384. doi: 10.1002/ece3.6368. eCollection 2020 Jul.
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.
元分析在生态学和生物多样性保护的定量证据综合中起着至关重要的作用。元分析中估计值的可靠性在很大程度上取决于对原始研究的无偏抽样。尽管早期研究已经探讨了生态元分析中的潜在偏差,但不同语言发表的报告统计结果及相关研究特征中的偏差在环境科学中从未得到检验。我们通过系统检索已发表的元分析,并比较现有元分析中纳入的英文和日文研究的效应量估计值,来填补这一知识空白。在日本机构附属人员撰写的40篇已发表的生态元分析文章中,我们发现有三篇元分析文章检索了两种语言的研究,且涉及足够数量的英文和日文研究,从而产生了四项符合条件的元分析(即这三篇元分析文章中进行的四项元分析)。在这四项中的两项中,元分析中纳入的英文和日文研究之间的效应量存在显著差异,当排除日文研究时,总体平均效应量甚至其方向都发生了相当大的变化。观察到的效应量差异可能归因于英文和日文研究在报告的统计结果及相关研究特征(特别是分类群和生态系统)方面的系统差异。尽管样本量较小,但我们的研究结果表明,由于英文和非英文语言在研究特征和效应量估计方面存在系统差异,忽略非英文语言的研究可能会使生态元分析的结果产生偏差。我们提供了一份元分析人员未来可以采取的行动清单,以降低语言偏差的风险。