New horizons for comparative studies and meta-analyses

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Patrice Pottier , Daniel W.A. Noble, Frank Seebacher, Nicholas C. Wu , Malgorzata Lagisz, Lisa Schwanz, Szymon Marian Drobniak, Shinichi Nakagawa


Comparative analyses and meta-analyses are key tools to elucidate broad biological principles, yet the two approaches often appear different in purpose. We propose an integrated approach that can generate deeper insights into eco-evolutionary processes. Marrying comparative and meta-analytic approaches will allow for 1) a more accurate investigation of drivers of biological variation; 2) a greater ability to account for sources of non-independence in experimental data; 3) more effective control of publication bias; and 4) improved transparency and reproducibility. Stronger integration of meta-analytic and comparative studies can also broaden the scope from species-centric investigations to community-level responses and function-valued traits (e.g., reaction norms). We illuminate commonalities, differences, and the transformative potential of combining these methodologies for advancing ecology and evolutionary biology.



Life Sciences


multilevel modelling, multivariate analysis, phylogenetic generalized linear mixed model, sampling variance, phylogenetic signal, multivariate meta-analysis, phylogenetic generalized linear mixed model, sampling variance, Phylogenetic signal, open science, PGLM, phylogenetic least square regression


Published: 2023-09-25 11:34

Last Updated: 2024-01-15 11:50

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CC BY Attribution 4.0 International

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Conflict of interest statement:
The authors declare no conflicts of interest

Data and Code Availability Statement:
Data and code are available at