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Understanding tree failure-A systematic review and meta-analysis.

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Tree failure risk assessments lack objective data. This study identifies key factors like height and stem weight influencing tree failure, urging more data collection for accurate urban tree risk management.

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Area of Science:

  • Arboriculture and Urban Forestry
  • Biomechanics
  • Risk Assessment

Background:

  • Tree failure likelihood and impact are increasing, driven by biomechanical and physical factors.
  • Current urban tree risk assessments are subjective, lacking observational support despite available data.
  • There is a critical need for objective, data-driven methods to assess urban tree hazardousness.

Purpose of the Study:

  • To systematically review and identify factors influencing tree failure (stem, root, and branch).
  • To provide an overview of biomechanical and physical variables impacting urban tree stability.
  • To address the absence of empirically supported tree risk assessment models.

Main Methods:

  • Systematic literature review following PRISMA guidelines, analyzing 161 articles.
  • Meta-analysis of effect sizes and p-values for factors directly linked to tree failure.
  • Bayes Factor calculation for factor likelihood and regression tests for publication bias.

Main Results:

  • Height and Stem weight are significant predictors of stem failure, along with Age, DBH, DBH², DBH³, and Tree weight.
  • Stem weight and Tree weight positively correlate with root failure.
  • No specific factors were identified as significantly relating to branch failure in the reviewed literature.

Conclusions:

  • Objective factors like Height and Stem weight are crucial for predicting stem and root failure in urban trees.
  • A unified model incorporating all tree failure factors is currently lacking, complicating risk estimation.
  • Further data collection by arborists on identified factors is recommended to improve tree risk assessment accuracy.