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Updated: Jul 11, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

Modeling individual tree mortality for crimean pine plantations.

Mehmet Misir¹, Nuray Misir, Hakki Yavuz

¹Faculty of Forestry, Karadeniz Technical University, Trabzon-610 80, Turkey. mmisir@ktu.edu.tr

Journal of Environmental Biology

|October 6, 2007

Summary

A new logistic mortality model for Crimean pine (Pinus nigra subsp. pallasiana) plantations in Turkey accurately predicts tree death using competition index, site index, and basal area. This reliable model aids forest management by forecasting individual tree mortality.

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Area of Science:

Forestry
Ecology
Quantitative Ecology

Background:

Forest management requires accurate prediction of tree mortality for sustainable practices.
Crimean pine (Pinus nigra subsp. pallasiana) is an important species in Turkish plantations.
Understanding factors influencing individual tree mortality is crucial for ecological modeling.

Purpose of the Study:

To develop and validate a logistic regression model for predicting individual tree mortality in Crimean pine plantations.
To identify key predictor variables influencing tree mortality in these specific forest ecosystems.
To provide a reliable tool for forest managers to assess and mitigate tree mortality risks.

Main Methods:

Utilized data from 5-year remeasurements of 115 permanent sample plots, encompassing 5029 individual trees.
Employed weighted nonlinear regression analysis to estimate parameters of the logistic mortality equation.
Validated the model using 20% of the data, ensuring its predictive accuracy on independent observations.

Main Results:

The developed logistic mortality model demonstrated a good fit to observed data, with all parameter estimates being highly significant (p < 0.001).
Key predictors of mortality were identified as the ratio of subject tree diameter to mean basal area diameter (competition index), site index, and stand basal area.
Model validation on independent data confirmed its reliability and well-behaved predictive performance.

Conclusions:

The developed individual tree mortality model for Crimean pine is reliable and suitable for practical application in forest management.
The model's accuracy highlights the importance of competition, site conditions, and stand density in influencing tree survival.
Large, representative datasets are essential for building robust and dependable forest mortality models.