Meta‐analysis is increasingly used in biology to both quantitatively summarize available evidence for specific questions and generate new hypotheses. Although this powerful tool has mostly been deployed to study mean effects, there is untapped potential to study effects on (trait) variance. Here, we use a recently published data set as a case study to demonstrate how meta‐analysis of variance can be used to provide insights into biological processes. This data set included 704 effect sizes from 89 studies, covering 56 animal species, and was originally used to test developmental stress effects on a range of traits. We found that developmental stress not only negatively affects mean trait values, but also increases trait variance, mostly in reproduction, showcasing how meta‐analysis of variance can reveal previously overlooked effects. Furthermore, we show how meta‐analysis of variance can be used as a tool to help meta‐analysts make informed methodological decisions, even when the primary focus is on mean effects. We provide all data and comprehensive R scripts with detailed explanations to make it easier for researchers to conduct this type of analysis. We encourage meta‐analysts in all disciplines to move beyond the world of means and start unravelling secrets of the world of variance.

中文翻译：

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说明元分析方差与生态学和进化中的手段的重要性

Meta 分析在生物学中越来越多地用于对特定问题的可用证据进行定量总结并产生新的假设。尽管这个强大的工具主要用于研究平均效应，但仍有未开发的潜力来研究对（特质）方差的影响。在这里，我们使用最近发布的数据集作为案例研究来展示如何使用方差的元分析来提供对生物过程的见解。该数据集包括来自 89 项研究的 704 个效应大小，涵盖 56 个动物物种，最初用于测试发育压力对一系列性状的影响。我们发现，发育压力不仅对平均特征值产生负面影响，还会增加特征方差，主要是在繁殖方面，展示了方差的荟萃分析如何揭示以前被忽视的影响。此外，我们展示了如何将方差的元分析用作帮助元分析人员做出明智的方法论决策的工具，即使主要关注点是平均效应。我们提供所有数据和全面的 R 脚本，并附有详细说明，以便研究人员更轻松地进行此类分析。我们鼓励所有学科的元分析师超越手段的世界，开始解开差异世界的秘密。