scholarly journals Development of a stem taper equation and modelling the effect of stand density on taper for Chinese fir plantations in Southern China

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1929 ◽  
Author(s):  
Aiguo Duan ◽  
Sensen Zhang ◽  
Xiongqing Zhang ◽  
Jianguo Zhang
Keyword(s):  
Predictive Accuracy ◽  
Southern China ◽  
Model Development ◽  
Stand Density ◽  
Chinese Fir ◽  
Planting Density ◽  
Jiangxi Province ◽  
Stem Taper ◽  
Taper Equation ◽  
Taper Equations

Chinese fir (Cunninghamia lanceolata) is the most important commercial tree species in southern China. The objective of this study was to develop a variable taper equation for Chinese fir, and to quantify the effects of stand planting density on stem taper in Chinese fir. Five equations were fitted or evaluated using the diameter-height data from 293 Chinese fir trees sampled from stands with four different densities in Fenyi County, Jiangxi Province, in southern China. A total of 183 trees were randomly selected for the model development, with the remaining 110 trees used for model evaluation. The results show that the Kozak’s, Sharma/Oderwald, Sharma/Zhang and modified Brink’s equations are superior to the Pain/Boyer equation in terms of the fitting and validation statistics, and the modified Brink’s and Sharma/Zhang equations should be recommended for use as taper equations for Chinese fir because of their high accuracy and variable exponent. The relationships between some parameters of the three selected equations and stand planting densities can be built by adopting some simple mathematical functions to examine the effects of stand planting density on tree taper. The modelling and prediction precision of the three taper equations were compared with or without incorporation of the stand density variable. The predictive accuracy of the model was improved by including the stand density variable and the mean absolute bias of the modified Brink’s and Sharma/Zhang equations with a stand density variable were all below 1.0 cm in the study area. The modelling results showed that the trees have larger butt diameters and more taper when stand density was lower than at higher stand density.

scholarly journals Variable-Exponent Taper Equation Based on Multilevel Nonlinear Mixed Effect for Chinese Fir in China

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 126
Author(s):  
Sensen Zhang ◽  
Jianjun Sun ◽  
Aiguo Duan ◽  
Jianguo Zhang
Keyword(s):  
Variable Exponent ◽  
Southern China ◽  
Information Criteria ◽  
Chinese Fir ◽  
Tree Level ◽  
Mixed Effect ◽  
Basic Model ◽  
Taper Equation ◽  
Taper Equations ◽  
Taper Models

A variable-exponent taper equation was developed for Chinese fir (Cunninghamia lanceolate (Lamb.) Hook.) trees grown in southern China. Thirty taper equations from different groups of models (single, segmented, or variable-exponent taper equation) were compared to find the excellent basic model with S-plus software. The lowest Akaike information criteria (AIC), Bayesian information criteria (BIC), and -2loglikelihood (-2LL) was chosen to determine the best combination of random parameters. Single taper models were found having the lowest precision, and the variable-exponent taper equations had higher precision than the segmented taper equations. Four variable-exponent taper models that developed by Zeng and Liao, Bi, Kozak, Sharma, and Zhang respectively, were selected as basic model and had no difference in fit statistics between them. Compared with the model without seldom parameter, the nonlinear mixed-effects (NLME) model improves the fitting performance. The plot-level NLME model was found not to remove the residual autocorrelation. The tree-level and two-level NLME model had better simulation accuracy than the plot-level NLME model, and there were no significant differences between the tree-level and two-level NLME model. Variable-exponent taper model developed by Kozak showed the best performance while considering two-level or tree-level NLME model, and produced better predictions for medium stems compared to lower and upper stems.

scholarly journals Growth, Biomass Production and Root Development of Chinese fir in Relation to Initial Planting Density

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 236 ◽  
Author(s):  
Taimoor Farooq ◽  
Wenjing Wu ◽  
Mulualem Tigabu ◽  
Xiangqing Ma ◽  
Zongming He ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Biomass Production ◽  
Stand Density ◽  
Tree Height ◽  
Root Systems ◽  
Chinese Fir ◽  
High Density ◽  
Planting Density ◽  
Low Density ◽  
Intermediate Density

Chinese fir (Cunninghamia lanceolata (Lamb) Hook) is a commercially valuable timber species that is widely planted in southern China and accounts for 6.1% of the global plantation forests. However, appropriate planting density that ensures high plantation productivity is largely unexplored in this species. The aim of the study was to examine tree growth, biomass production, and its allocation among different organs in relation to initial planting density, and to examine whether planting density has an impact on root development. Mortality, diameter at breast height and tree-height of all trees were determined and measured in wider (2.36 × 2.36 m), intermediate (1.83 × 1.83 m) and narrow (1.44 × 1.44 m) spacing with stand density of 1450 trees ha−1, 2460 trees ha−1 and 3950 trees ha−1, respectively. In each stand, three plots of 20 × 20 m at a distance of 500 m were delineated as the sampling unit. Biomass was determined by destructive sampling of trees in each stand and developing allometric equations. Root morphological traits and their spatial distribution were also determined by carefully excavating the root systems. The results showed an increase in diameter of trees with decreasing stand density while tree height was independent of stand density. Biomass production of individual trees was significantly (p < 0.05) less in high-density stand (32.35 ± 2.98 kg tree−1) compared to low-density stand (44.72 ± 4.96 kg tree−1) and intermediate-density stand (61.35 ± 4.78 kg tree−1) while stand biomass production differed significantly in the order of intermediate (67.63 ± 5.14 t ha−1) > high (57.08 ± 3.13 t ha−1) > low (27.39 ± 3.42 t ha−1) stand density. Both average root length and root volume were significantly (p < 0.05) lower in the high-density stand than stands with low and intermediate density. Analysis of spatial distribution of root systems revealed no overlap between roots of neighboring trees in the competition zone in low-density stand, a subtle overlap in the intermediate density stand and larger overlap in the high-density stand. It can be concluded that better growth and biomass production in intermediate density stand could be explained by better root structural development coupled with minimal competition with understory vegetation and between trees; thus intermediate stand density can be optimal for sustaining long-term productivity and may reduce the management cost in the early phase of the plantation.

scholarly journals A Comparative Evaluation of Three Stem Profile Equations for Three Precious Tree Species in Southern China

Forests ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 669
Author(s):  
Jun Jiang ◽  
Jie Li ◽  
Lifeng Pang ◽  
Angang Ming
Keyword(s):  
Tree Species ◽  
Southern China ◽  
Tectona Grandis ◽  
Prediction Errors ◽  
Relative Height ◽  
Taper Equation ◽  
Erythrophleum Fordii ◽  
Individual Trees ◽  
Taper Equations ◽  
The Tropics

Accurately describing the stem curve of precious tree species and estimating the quantity of various types of wood and their volume in the tropics can provide technical support for reasonable bucking. This study utilized Erythrophleum fordii, Castanopsis hystrix and Tectona grandis as study objects. Forty replicates of each species were used for a total of 120 individual trees. Their tape equations were constructed using simple tape equations, segmented taper equations and variable form taper equations. Statistical indicators were utilized to determine the best taper equation for the three types of precious tree species. A number of methods were compared and analyzed, including the index of correlation, the residual sum of squares, the mean prediction error, the variance of prediction errors and the root mean square error. Finally, a preliminary quantitative analysis was conducted to determine the trends of these three types of tree species. The result shows that the precision of the three predictions developed for each species is high, and, in particular, the segmented taper equations with optimized algorithms is the best. The tendency of the three species to vary was shown to be the highest for T. grandis in the range of 0.0 to 0.8 for its relative height, followed by E. fordii, while the variation of C. hystrix was the smallest. However, in the range of 0.8 to 1.0 relative height, the variation of Castanopsis hystrix was the largest, and the variation of both E. fordii and T. grandis were almost the same. Therefore, the segmented taper equations with optimization algorithms was recommended to fit the three types of tree species in the tropics. These types of equations can be used to estimate the stumpage and timber quantity and as a guide reasonable bucking for these three species.

Assessment of Carbon Stock and Uptake by Estimation of Stem Taper Equation for Pinus densiflora in Korea

2017 ◽  
Vol 8 (4) ◽  
pp. 415-424 ◽  
Author(s):  
Jin-Taek Kang ◽  
Yeong-Mo Son ◽  
Ju-Hyeon Jeon ◽  
Sun-Jeoung Lee
Keyword(s):  
Carbon Stock ◽  
Pinus Densiflora ◽  
Stem Taper ◽  
Taper Equation

Application of machine learning in predicting construction project profit in Ghana using Support Vector Regression Algorithm (SVRA)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Emmanuel Adinyira ◽  
Emmanuel Akoi-Gyebi Adjei ◽  
Kofi Agyekum ◽  
Frank Desmond Kofi Fugar
Keyword(s):  
Machine Learning ◽  
Support Vector Regression ◽  
Cash Flow ◽  
Predictive Accuracy ◽  
Model Development ◽  
Construction Project ◽  
Support Vector ◽  
Sensitivity Index ◽  
Content Type ◽  
Hyperparameter Selection

PurposeKnowledge of the effect of various cash-flow factors on expected project profit is important to effectively manage productivity on construction projects. This study was conducted to develop and test the sensitivity of a Machine Learning Support Vector Regression Algorithm (SVRA) to predict construction project profit in Ghana.Design/methodology/approachThe study relied on data from 150 institutional projects executed within the past five years (2014–2018) in developing the model. Eighty percent (80%) of the data from the 150 projects was used at hyperparameter selection and final training phases of the model development and the remaining 20% for model testing. Using MATLAB for Support Vector Regression, the parameters available for tuning were the epsilon values, the kernel scale, the box constraint and standardisations. The sensitivity index was computed to determine the degree to which the independent variables impact the dependent variable.FindingsThe developed model's predictions perfectly fitted the data and explained all the variability of the response data around its mean. Average predictive accuracy of 73.66% was achieved with all the variables on the different projects in validation. The developed SVR model was sensitive to labour and loan.Originality/valueThe developed SVRA combines variation, defective works and labour with other financial constraints, which have been the variables used in previous studies. It will aid contractors in predicting profit on completion at commencement and also provide information on the effect of changes to cash-flow factors on profit.

scholarly journals Identifying Human-Induced Spatial Differences of Soil Erosion Change in a Hilly Red Soil Region of Southern China

2019 ◽  
Vol 11 (11) ◽  
pp. 3103
Author(s):  
Dong Huang ◽  
Xiaohuan Yang ◽  
Hongyan Cai ◽  
Zuolin Xiao ◽  
Dongrui Han
Keyword(s):  
Soil Erosion ◽  
Human Impact ◽  
Human Impacts ◽  
Southern China ◽  
Red Soil ◽  
Jiangxi Province ◽  
Negative Effects ◽  
Gravity Center ◽  
Local Conditions ◽  
Spatial Differences

Soil erosion (SE) processes are closely related to natural conditions and human activities, posing a threat to environment and society. Identifying the human impact on regional SE changes is increasingly essential for pertinent SE management. Jiangxi province is studied here as a representative area of hilly-red-soil regions within southern China. The main objectives of this study were to investigate the changing trend of SE within Jiangxi and identify human impacts on regional SE change from the perspective of spatial differences, through a new approach based on a gravity-center model. Our results showed that SE status presented an overall amelioration from 1990 to 2015, while the average soil erosion modulus (SEM) declined from 864 to 281 Mg/(km2·a). Compared to the situation under human and natural impacts, human-induced spatial differences of SE change demonstrated that the western and northwest regions showed stronger negative effects; the southern region shifted towards negative effects; the northeast region presented a much weaker negative effect. Our results indicated that 4 cities with strong negative effects need more attention in further SE management suited to their local conditions and development, and also suggested that the approach based on a gravity-center has potential for identifying the human impact on regional SE change from the perspective of spatial patterns.

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