Incorporating stand parameters in nonlinear height-diameter mixed-effects model for uneven-aged Larix gmelinii forests

Tree attributes, such as height (H) and diameter at breast height (D), are essential for predicting forest growth, evaluating stand characteristics and developing yield models for sustainable forest management. Measuring tree H is particularly challenging in uneven-aged forests compared to D. To ove...

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Main Authors: Muhammad Junaid Ismail, Tika Ram Poudel, Akber Ali, Lingbo Dong
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Forests and Global Change
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Online Access:https://www.frontiersin.org/articles/10.3389/ffgc.2024.1491648/full
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author Muhammad Junaid Ismail
Tika Ram Poudel
Akber Ali
Lingbo Dong
author_facet Muhammad Junaid Ismail
Tika Ram Poudel
Akber Ali
Lingbo Dong
author_sort Muhammad Junaid Ismail
collection DOAJ
description Tree attributes, such as height (H) and diameter at breast height (D), are essential for predicting forest growth, evaluating stand characteristics and developing yield models for sustainable forest management. Measuring tree H is particularly challenging in uneven-aged forests compared to D. To overcome these difficulties, the development of updated and reliable H-D models is crucial. This study aimed to develop robust H-D models for Larix gmelinii forest by incorporating stand variables. The dataset consisted of 7,069 Larix gmelinii trees sampled from 96 plots at Northeast China, encompassing a wide range of stand densities, age classes, and site conditions. Fifteen widely recognized nonlinear functions were assessed to model the H-D relationship effectively. Model performance was assessed using root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R2). Results identified the Ratkowsky model (M8) as the best performer, achieving the highest R2 (0.74), the lowest RMSE (16.47%) and MAE (12.50%), at statistically significant regression coefficients (p < 0.05). Furthermore, M8 was modified into 5 generalized models (GMs) by adding stand-variables (i.e., mean height, mean diameter and volume and their combination), the results indicate that GM2 was the best model achieving R2 of 0.82% and RMSE of 13.7%. We employed generalized nonlinear mixed-effects modeling approach with both fixed and random effects to account for variations at the individual plot level, enhancing the predictive accuracy. The model explained 71% of variability with significant trends in the residuals. The model was calibrated using response calibration method, through EBLUP theory. Our findings suggest that incorporating stand-level variables representing plot-specific characteristics can further improve the fit of mixed- effects models. These advancements provide forest authorities with enhanced tools for supporting sustainable forest management.
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spelling doaj-art-acce2ce0aecb4ac8919fc8a7320726d72025-01-07T06:46:24ZengFrontiers Media S.A.Frontiers in Forests and Global Change2624-893X2025-01-01710.3389/ffgc.2024.14916481491648Incorporating stand parameters in nonlinear height-diameter mixed-effects model for uneven-aged Larix gmelinii forestsMuhammad Junaid Ismail0Tika Ram Poudel1Akber Ali2Lingbo Dong3Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, College of Forestry, Northeast Forestry University, Harbin, ChinaFeline Research Center of National Forestry and Grassland Administration, College of Wildlife and Protected Area, Northeast Forestry University, Harbin, ChinaKey Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, College of Forestry, Northeast Forestry University, Harbin, ChinaKey Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, College of Forestry, Northeast Forestry University, Harbin, ChinaTree attributes, such as height (H) and diameter at breast height (D), are essential for predicting forest growth, evaluating stand characteristics and developing yield models for sustainable forest management. Measuring tree H is particularly challenging in uneven-aged forests compared to D. To overcome these difficulties, the development of updated and reliable H-D models is crucial. This study aimed to develop robust H-D models for Larix gmelinii forest by incorporating stand variables. The dataset consisted of 7,069 Larix gmelinii trees sampled from 96 plots at Northeast China, encompassing a wide range of stand densities, age classes, and site conditions. Fifteen widely recognized nonlinear functions were assessed to model the H-D relationship effectively. Model performance was assessed using root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R2). Results identified the Ratkowsky model (M8) as the best performer, achieving the highest R2 (0.74), the lowest RMSE (16.47%) and MAE (12.50%), at statistically significant regression coefficients (p < 0.05). Furthermore, M8 was modified into 5 generalized models (GMs) by adding stand-variables (i.e., mean height, mean diameter and volume and their combination), the results indicate that GM2 was the best model achieving R2 of 0.82% and RMSE of 13.7%. We employed generalized nonlinear mixed-effects modeling approach with both fixed and random effects to account for variations at the individual plot level, enhancing the predictive accuracy. The model explained 71% of variability with significant trends in the residuals. The model was calibrated using response calibration method, through EBLUP theory. Our findings suggest that incorporating stand-level variables representing plot-specific characteristics can further improve the fit of mixed- effects models. These advancements provide forest authorities with enhanced tools for supporting sustainable forest management.https://www.frontiersin.org/articles/10.3389/ffgc.2024.1491648/fullheight-diameter modelnonlinear mixed-effects modelheight predictionunevenaged forestLarix gmelinii
spellingShingle Muhammad Junaid Ismail
Tika Ram Poudel
Akber Ali
Lingbo Dong
Incorporating stand parameters in nonlinear height-diameter mixed-effects model for uneven-aged Larix gmelinii forests
Frontiers in Forests and Global Change
height-diameter model
nonlinear mixed-effects model
height prediction
unevenaged forest
Larix gmelinii
title Incorporating stand parameters in nonlinear height-diameter mixed-effects model for uneven-aged Larix gmelinii forests
title_full Incorporating stand parameters in nonlinear height-diameter mixed-effects model for uneven-aged Larix gmelinii forests
title_fullStr Incorporating stand parameters in nonlinear height-diameter mixed-effects model for uneven-aged Larix gmelinii forests
title_full_unstemmed Incorporating stand parameters in nonlinear height-diameter mixed-effects model for uneven-aged Larix gmelinii forests
title_short Incorporating stand parameters in nonlinear height-diameter mixed-effects model for uneven-aged Larix gmelinii forests
title_sort incorporating stand parameters in nonlinear height diameter mixed effects model for uneven aged larix gmelinii forests
topic height-diameter model
nonlinear mixed-effects model
height prediction
unevenaged forest
Larix gmelinii
url https://www.frontiersin.org/articles/10.3389/ffgc.2024.1491648/full
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