Meta-analysis of magnitudes, differences and variation in evolutionary parameters.

Area of Science:

• Ecology
• Evolutionary Biology
• Statistical Methods

Background:

• Meta-analysis is a common tool for synthesizing ecological and evolutionary research.
• Informal meta-analyses, which ignore data observation processes, can introduce biases.
• Statistical noise in individual studies can lead to systematic errors in meta-analyses.

Purpose of the Study:

• To describe how ignoring noise in inferences can bias meta-analyses.
• To demonstrate that informal meta-analyses of parameter dispersion are often misleading.
• To re-analyze and correct previous informal meta-analyses.

Main Methods:

• General description of bias propagation from individual inferences to meta-analyses.
• Re-analysis of three published informal meta-analyses using mixed-model approaches.
• Application of widely available open-source software for statistical analyses.

Main Results:

• Failure to account for noise can lead to significant biases, especially for dispersion metrics.
• Re-analysis of three case studies showed original conclusions closely matched noise-induced artefacts.
• Alternative mixed-model analyses yielded substantially different conclusions in all re-analyzed studies.

Conclusions:

• Informal meta-analyses in ecology and evolution require careful methodological consideration.
• Statistical noise is a critical factor that can generate spurious biological conclusions.
• Robust statistical approaches, like mixed models, are essential for accurate synthesis of ecological and evolutionary data.