A holistic approach to determine tree structural complexity based on laser scanning data and fractal analysis

Area of Science:

• Forest ecology
• Ecosystem structure
• Quantitative botany

Background:

• Forest structure significantly influences ecosystem functions and services.
• Individual tree structure is a key component of overall forest architecture.
• Understanding tree complexity is crucial for forest management and ecological studies.

Purpose of the Study:

• To develop and present a novel, holistic approach for quantifying individual tree structural complexity.
• To introduce the box dimension as a fractal-based measure of tree structure.
• To investigate the relationship between tree structural complexity, species, growing conditions, competition, and growth rate.

Main Methods:

• Utilized three-dimensional point clouds obtained from laser scanning.
• Applied fractal analysis to calculate the box dimension of individual trees.
• Compared box dimension values across different tree species and growing conditions.

Main Results:

• The box dimension varied significantly among tree species and growing conditions (gap vs. forest interior).
• Differences in box dimension were observed based on the type of competition (intraspecific vs. interspecific).
• A positive correlation was found between the box dimension and tree growth rate.

Conclusions:

• The box dimension is a valuable and easily calculable metric for assessing individual tree structural complexity.
• This measure integrates the impacts of external drivers like competition on tree structure.
• The box dimension provides insights into structure-related properties, including tree growth dynamics.