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Towards a common methodology for developing logistic tree mortality models based on ring-width data.

Maxime Cailleret1, Christof Bigler2, Harald Bugmann2

  • 1Forest Ecology, Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, ETH Zürich, CH-8092 Zürich, Switzerland. maxime.cailleret@usys.ethz.ch.

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Summary
This summary is machine-generated.

Developing reliable tree-ring based growth-mortality relationships requires careful consideration of sampling strategies and data analysis methods. This study provides insights into optimizing these methods for better understanding tree death likelihood.

Keywords:
Abies albaNothofagus dombeyiQuercus petraeagrowth-mortality relationshiplogistic modelsamplingsurvivaltree mortalitytree ring

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Area of Science:

  • Forest Ecology
  • Dendrochronology
  • Forest Dynamics

Background:

  • Tree mortality is a critical factor influencing forest dynamics.
  • Existing tree-ring based studies on growth-mortality relationships lack standardized methodologies, hindering synthesis and comparison.
  • There is a need for reliable indicators to predict tree death likelihood.

Purpose of the Study:

  • To assess the impact of methodological decisions on tree-ring based growth-mortality relationships.
  • To identify optimal statistical sampling schemes, explanatory growth variables, and time window lengths for predicting tree mortality.
  • To develop reliable, species-specific growth-mortality relationships accounting for sampling biases.

Main Methods:

  • Utilized logistic mixed-effects regression models to analyze tree-ring data.
  • Applied a constant sampling size approach across datasets.
  • Examined published tree-ring datasets for Abies alba, Nothofagus dombeyi, and Quercus petraea.

Main Results:

  • Tree-ring based mortality models showed good performance (AUC > 0.7) across all species.
  • Growth level was the primary predictor of mortality for Abies alba and Nothofagus dombeyi.
  • Growth trend was crucial for Quercus petraea, and time window length significantly influenced results, varying with tree age and sampling scheme.

Conclusions:

  • Methodological choices, particularly sampling strategy and time window selection, significantly impact growth-mortality relationship reliability.
  • Species-specific approaches are necessary, with growth level or trend being key predictors.
  • Standardizing methodologies is essential for advancing the understanding and modeling of tree mortality.