This study investigates the sensitivity of five statistical tests (CE, quadrat 3x3, CDF, MAD, and DCLF) in detecting anomalies within originally random tree distributions in forested areas. By simulating tree disappearance due to various anomalies, the effectiveness of these tests is assessed across different tree densities and anomaly magnitudes. Results indicate that the quadrat test and Monte Carlo-based tests (MAD and DCLF) are significantly more sensitive to deviations from randomness than the CE and CDF tests, particularly in denser forests with higher levels of tree disappearance. The findings underline the importance of selecting appropriate statistical tools for analyzing spatial patterns in ecological research.
Authors: Zsolt György TÓTH – Adrienn NOVOTNI (2025)
Full text:
https://publicatio.uni-sopron.hu/3831/
Acta Silvatica et Lignaria Hungarica: An International Journal in Forest Wood and Environmental Sciences 21 (1)
