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Related Experiment Video

Updated: Dec 20, 2025

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The orchard plot: Cultivating a forest plot for use in ecology, evolution, and beyond.

Shinichi Nakagawa1, Malgorzata Lagisz1, Rose E O'Dea1

  • 1Evolution & Ecology Research Centre, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia.

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Summary

The orchard plot is a new visualization for meta-analyses with many effect sizes, improving upon classic forest plots. It helps interpret heterogeneity and identify influential studies in ecology and evolution.

Keywords:
caterpillar plotcredibility intervalcredible intervalevidence synthesisgraphical toolmeta-regressionsummary forest plot

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Area of Science:

  • Ecology and Evolution
  • Meta-analysis
  • Data Visualization

Background:

  • Classic forest plots are limited for meta-analyses with over 100 effect sizes, common in ecology and evolution.
  • Most meta-analyses in these fields use "forest-like plots" for subgroups or categories.

Purpose of the Study:

  • Introduce the "orchard plot," a novel visualization for meta-analyses.
  • Enhance the interpretation of heterogeneity and individual effect sizes.

Main Methods:

  • Surveyed 102 meta-analyses in ecology and evolution.
  • Proposed the orchard plot, a modification of forest-like plots.
  • Utilized the R package "orchard" for visualization.

Main Results:

  • Only 11% of surveyed meta-analyses used classic forest plots.
  • Orchard plots include overall mean effects, confidence intervals, prediction intervals (PIs), and scaled individual effect sizes.
  • PIs aid in understanding the range of future study effects and data heterogeneity.

Conclusions:

  • The orchard plot is a valuable tool for visualizing large, heterogeneous datasets in meta-analyses.
  • It offers intuitive interpretation of heterogeneity and identification of influential effect sizes.
  • This visualization is beneficial for ecology, evolution, and potentially other scientific fields.