Individual area and spatial distribution of saplings

TL;DR

This study applies Voronoi tessellation to determine individual sapling areas in a forest, analyzing spatial patterns and competition, and introduces software tools for practical analysis.

Contribution

It demonstrates the use of Voronoi tessellation in forest ecology to quantify sapling spatial distribution and competition, with new software tools for analysis.

Findings

Voronoi tessellation effectively characterizes sapling spatial patterns.

APA coefficient of variation correlates with growth and competition.

Software tools facilitate practical spatial analysis.

Abstract

Forest regeneration is a spatial multifaceted process with numerous unknown variables. The individual area or the area potentially available (APA) to an individual plant embodies an idea widely used in population ecology but it has fewer applications in forest research. It was used a Voronoi/ Thiessen tessellation in order to determine the individual area of each sapling. The study was conducted in a naturally regenerated area; using data collected from over seven thousands saplings positioned in a network of permanent rectangular sampling plots. The Voronoi/ Thiessen polygons were used to characterize spatial pattern of sapling distribution as well as the competition relations between the individuals. It is obvious that, at least from the mathematically point of view, the Voronoi tessellation represents one of the best solutions to determine neighbouring competitors of a tree. There were studied the correlations between APA values and the main biometrical attributes, height growth and competition indices. Furthermore, it is shown that APA coefficient of variation is a straight-forward indicator with positive results as an indicator of spatial pattern. The statistical significance of this indicator was evaluated by comparing the results with the values of a 95% confidence envelope generated by Monte-Carlo simulations. Two practical software tools were produced using Visual Basic (VORONOI and ARIA VORONOI) in order to simplify the analyses.