Height-Diameter Modeling ofCinnamomum tamalaGrown in Natural Forest in Mid-Hill of Nepal

Mukti Ram Subedi,Surendra Shrestha,Sophan Chhin,Bishwa Nath Oli

doi:10.1155/2018/6583948

Mukti Ram Subedi, Surendra Shrestha + Show 2 more

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https://doi.org/10.1155/2018/6583948

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Abstract

Tree height (H) and diameter at breast height (D) are key variables to calculate tree volume and biomass. We developed a height-diameter (H-D) model forCinnamomum tamalaby evaluating 18 nonlinear models. Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Root Mean Square Error (RMSE), mean bias, Mean Absolute Error (MAE), graphical appearance, and biological logic were the criteria used to evaluate the predictive performance of the models. Gompertz model (M14) performed the best for predicting the total height ofC. tamalatrees with the least RMSE (1.742 m), mean bias (0.012 m), and MAE (1.342 m) and satisfied model assumptions and biological logic. Validation data ranked the Gompertz model as the best model with RMSE (1.546 m), mean bias (-0.106 m), and MAE (1.149 m). Despite the consistent performance of the Gompertz model, it tended to underestimate the height prediction for taller (dominant crown class) and larger trees. Further work on refitting and validation of the proposed model with data from a larger geographic area, wider-ranging sites, and stand conditions is recommended.

Highlights

Tree height (H) and diameter at breast height (D) are fundamental variables in most forest inventories which are required to calculate tree volume, biomass, carbon storage, and survival analysis [1,2,3,4]
The study was conducted at Mijure Danda Village Development Committee (VDC) of Kaski district, Nepal, which extends from 28∘13󸀠57󸀠󸀠 to 28∘20󸀠57󸀠󸀠N latitude and 84∘08󸀠53󸀠󸀠 to 84∘12󸀠42󸀠󸀠E longitude
The forest in the study area is managed by the Sikles unit of Annapurna Conservation Area Project (ACAP) and constitutes C. tamala as a dominant species having contiguous distribution pattern and with an Important Value Index (IVI) of 158.0 [27]

Summary

Introduction

Tree height (H) and diameter at breast height (D) are fundamental variables in most forest inventories which are required to calculate tree volume, biomass, carbon storage, and survival analysis [1,2,3,4]. Accurate in situ measurement of D is easy and cost-effective. Height measurement is labor-intensive, time-consuming, expensive, and prone to observational and measurement errors [5, 6]. Predicting forest dynamics through growth and yield simulation requires individual tree level information, such as H and D. A height-diameter (H-D) relationship model can be built when both H and D variables are measured. The model can be used to estimate missing tree height, biomass production, and stand dynamics

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