Volume 59, Issue 333, September - December 2023

Exploring nonlinear models for predicting Diameter-Height and Diameter-Volume relationships in Shorea robusta trees: A study in the forests of Putalaibazar Municipality, Syangja

Sagar Budhathoki^1♦, Sanchita Budhathoki², Lochana Adhikari³, Sahayog Chhetri¹, Padam Prakash Jaishi⁴

¹Faculty of Forestry, Agriculture and Forestry University, Hatauda, Nepal
²Department of Natural Resource Ecology and Management, Oklahoma State University, Oklahoma, United States
³School of Environmental Science and Management, Pokhara University, Kathmandu, Nepal
⁴Department of Earth and Environment Science, University of West Florida, Pensacola, United States

^♦Corresponding author
Faculty of Forestry, Agriculture and Forestry University, Hatauda, Nepal

ABSTRACT

This study aims to determine the most suitable models among a set of five candidate models to describe the relationships between diameter height and diameter volume for individual Shorea robusta trees within the forests of Putalaibazar Municipality, Syangja. The methodology involved measuring the diameter at breast height and total height of 137 individual trees and calculating their respective volumes. The normality of these variables was assessed by a nonparametric Kolmogorov-Smirnov test (p ≤ 0.05), which revealed non-normality and only five nonlinear models were employed to fit the height-diameter and volume-diameter relationship by a transformation of variables. The study estimated model parameters, including intercepts and regression coefficients, and assessed model performance using fit statistics such as the adjusted coefficient of determination (adj. R²) and root mean square error (RMSE). Statistical significance of parameters was determined through parametric t-tests for regression parameters, with all parameters found to be statistically significant (p ≤ 0.05). The selection of the best-fitting model was based on models exhibiting the highest adjusted coefficient of determination, lowest root mean square error, and lowest Akaike Information Criterion (AIC) value. Visual assessments, including histogram analyses, normal probability plot curves, and scattered plot diagrams, were also employed. Among the models tested, the Wykoff model (H(Height, m)=Bh(Breast Height, m)+exp(3.19+(-9.203)/(D+1)), where D represents diameter at breast height in cm, demonstrated superior performance for characterizing the Diameter-Height relationship. For the Diameter-Total Volume relationship, the model V = (-0.049) + 0.001 * D² proved to be optimal. These selected models are recommended for predicting the height and volume of individual Shorea robusta trees. It is essential to note that these models are explicitly site-specific and should be applied exclusively to sites, sizes, and stand conditions congruent with those examined in this study.

Keywords: Model, best-fit, RMSE, adjusted R2

Discovery, 2023, 59, e115d1356

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DOI: https://doi.org/10.54905/disssi.v59i333.e115d1356

Published: 14 October 2023