Exploring nonlinear models for predicting Diameter-Height and Diameter-Volume relationships in Shorea robusta trees: A study in the forests of Putalaibazar Municipality, Syangja
{"title":"Exploring nonlinear models for predicting Diameter-Height and Diameter-Volume relationships in Shorea robusta trees: A study in the forests of Putalaibazar Municipality, Syangja","authors":"Sagar Budhathoki, Sanchita Budhathoki, Lochana Adhikari, Sahayog Chhetri, Padam Prakash Jaishi","doi":"10.54905/disssi.v59i333.e115d1356","DOIUrl":null,"url":null,"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 non-parametric 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.","PeriodicalId":505009,"journal":{"name":"Discovery","volume":"35 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54905/disssi.v59i333.e115d1356","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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 non-parametric 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.