Modelling taper and stem volume considering stand density in Eucalyptus grandis and Eucalyptus dunnii

Hirigoyen, Andrés; Navarro-Cerrillo, Rafael M.; Bagnara, M.; Franco, Jorge; Requin, F.; Rachid-Casnati, Cecilia

doi:10.3832/ifor3604-014

Cited by 8 publications

(3 citation statements)

References 27 publications

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“…Because forest inventory data are spatially or temporally correlated (Fox et al 2001), the statistical assumptions are usually violated, and this leads to biased estimates (West et al 1984). To deal with the statistical problems, the autoregressive modeling technique (Hirigoyen et al 2021) and mixed-effect modeling technique (Karatepe et al 2022) can be used. However, some issues associated with these modeling techniques have remained in question (Wang et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Yield of forests in Ankara Regional Directory of Forestry in Turkey: comparison of regression and artificial neural network models based on statistical and biological behaviors

Bolat¹,

Ercanlı²,

Günlü³

2023

iForest

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Models of forest growth and yield provide important information on stand and tree developments and the interactions of these developments with silvicultural treatments. These models have been developed based on assumptions such as independence of observations, uncorrelated error terms, and error terms with constant variance; if these factors are absent, there may be problems with multicollinearity, autocorrelation, or heteroscedasticity, respectively. These problems, which have several adverse effects on parameter estimates, are statistical phenomena and must be avoided. In recent years, the artificial neural network (ANN) model, thanks to its superior features such as the ability to make successful predictions and the absence of the requirement for statistical assumptions, has been commonly used in forestry modeling. However, while goodness-of-fit measures were taken into consideration in the assessment of ANN models, the control of the biological characteristics of model predictions was ignored. In this study, variable-density yield models were developed using nonlinear regression and ANN techniques. These modeling techniques were compared based on some goodness-of-fit measures and the principles of forest yield. The results showed that ANN models were more successful in meeting expected biological patterns than regression models.

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Section: Introductionmentioning

confidence: 99%

Yield of forests in Ankara Regional Directory of Forestry in Turkey: comparison of regression and artificial neural network models based on statistical and biological behaviors

Bolat¹,

Ercanlı²,

Günlü³

2023

iForest

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“…While the volume of trees can be practically calculated using various tree volume equations, the volume or proportions of derived wood assortments such as mine poles, industrial wood, pulp and paper, and firewood cannot be so easily determined. For this reason, taper models that provide detailed estimates of both tree volume and wood assortments are needed (Diéguez-Aranda et al 2006, Çakir & Kahriman 2018, Hirigoyen et al 2021). Indeed, the stem diameter of a tree gradually decreases from the base to the top, and the rate of decrease in diameter along the stem is called the stem taper.…”

Section: Introductionmentioning

confidence: 99%

Modeling compatible taper and stem volume of pure Scots pine stands in Northeastern Turkey

Saygili¹,

Kahriman²

2023

iForest

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Compatible taper and volume equations for pure and natural Scots pine stands in the northeastern part of Turkey (Ardahan Province) were developed using a nonlinear mixed-effects modeling approach. Experimental data were obtained from 137 felled sample trees in different diameter and height classes. The most successful model (Jiang et al. 2005) explained 98.3% of the variance in stem diameter estimation and the RMSE, ME, MAE, AIC and BIC value obtained using this model were 1.955 cm, 0.043 cm, 1.300 cm, 9783.8 and 9812.6, respectively. Considering the criterion values of AIC, BIC and -2LnL, the model with random-effects in two parameters (b1 and b3) was the most successful for Scots pine. While the mixed model including random parameters did not completely solved the problem of the autocorrelation of errors in this study, the use of the autoregressive error structure AR(1) eliminated the autocorrelation in the residuals. In addition, the best estimation results among 20 different calibration options were obtained using the option of measuring two tree diameters at d1.30 and d5.30 with validation data. The most successful model explained 99.18% of the total variance in stem volume estimation in Scots pine.

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“…Contudo, é relevante salientar que a idade e aspectos genéticos, silviculturais e inerentes ao próprio sítio, como as condições edáficas e climáticas, influenciam a forma do fuste de árvores (Gomat et al, 2011;Souza et al, 2016;Hirigoyen et al, 2021). A forma do fuste oscila entre espaçamentos de plantio, fustes de maior conicidade tendem a ser encontrados nas ocasiões de maior espaço útil entre plantas (Soares et al, 2011;Sanquetta et al, 2014).…”

Section: Introductionunclassified

Comprimentos de seção e altura de fustes na cubagem rigorosa em diferentes espaçamentos de eucalipto

Lafetá¹,

Barbosa²,

Oliveira³

et al. 2021

Agrarian

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Objetivou-se avaliar a influência do comprimento de seções e alturas totais para a quantificação volumétrica de fustes de eucalipto em diferentes espaçamentos de plantio. Os volumes dos fustes com casca foram calculados utilizando-se a fórmula de Smalian, considerando seções de 1, 2, ..., 6 m de comprimento após a posição de 2 m de altura. As posições de cubagem da base foram padronizadas. Realizou-se a modelagem para a estimativa dos erros percentuais em função do comprimento de seção e altura de fustes. As estimativas de erro foram maiores em seções mais longas e fustes de menor altura total. Conclui-se que seções mais longas levam a superestimativas do volume acima da posição de 2 m de altura e, consequentemente, do volume total do fuste. Seções de comprimento superior a 2 m devem ser evitadas em cubagens rigorosas, sobretudo, quando realizadas em talhões instalados sob espaçamentos de 1,5 a 6 m2.

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Modelling taper and stem volume considering stand density in Eucalyptus grandis and Eucalyptus dunnii

Cited by 8 publications

References 27 publications

Yield of forests in Ankara Regional Directory of Forestry in Turkey: comparison of regression and artificial neural network models based on statistical and biological behaviors

Yield of forests in Ankara Regional Directory of Forestry in Turkey: comparison of regression and artificial neural network models based on statistical and biological behaviors

Modeling compatible taper and stem volume of pure Scots pine stands in Northeastern Turkey

Comprimentos de seção e altura de fustes na cubagem rigorosa em diferentes espaçamentos de eucalipto

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