Simultaneous Equations to Estimate Aboveground Biomass of Pinus caribaea var . hondurensis

Coutinho, Vinícius Morais; Sanquetta, Carlos Roberto; Bittencourt, Patrícia Anjos; Silva, Samuel Alves; Proceke, Karina Henkel; Delarrmelina, Willian Macedo; Moreau, Julia Siqueira

doi:10.1590/2179-8087.045216

Cited by 4 publications

(6 citation statements)

References 17 publications

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“…Thus, it can be said that additivity is a fundamental property of biomass equations, ensuring biological consistency. Recently, several researchers have used SUR and NSUR to develop additive biomass equations, such as Dong et al (2014), Sanquetta et al (2015), Zhao et al (2015), Zheng et al (2015), and Coutinho et al (2018).…”

Section: Resultsmentioning

confidence: 99%

“…In other words, the application of seemingly unrelated regression in this study provided positive aspects in tree biomass modeling. Likewise, when studying the use of simultaneous fitting, Correia et al (2008), Zhang et al (2016), andCoutinho et al (2018) noted substantial improvements in goodnessof-fit statistics when compared to the traditional approach. In their studies, equations decreased standard errors and led to biological consistency regarding the components' additivity.…”

Section: Resultsmentioning

confidence: 99%

“…Several authors addressed the inclusion of basic wood density in allometric models, such as Chave et al (2014), Tashi et al (2017), and Coutinho et al (2018). These authors found that this auxiliary variable improved the performance of allometric equations.…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

How to Estimate Black Wattle Aboveground Biomass From Heteroscedastic Data?

Oliveira

Coutinho

Fiorentin

et al. 2020

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This study developed a system of equations for predicting total aboveground and component biomass in black wattle trees. A total of 140 black wattle trees at age 10 years were measured regarding their diameter at 1.30 m height above the ground (d), total tree height (h), basic wood density (branches and stem), and biomass (stem, crown, and aboveground). We evaluated the performance of linear and nonlinear allometric models by comparing the statistics of R2adj., RRMSE%, and BIC. Nonlinear models performed better when predicting crown biomass (using only d as an independent variable), and stem and aboveground biomass (using d and h as independent variables). Adding basic density did not significantly improve biomass modeling. The residuals had non-homogeneous variance; thus, the fitted equations were weighted, with weights derived from a function containing the same independent variables of the fitted biomass function. Subsequently, we used a simultaneous set of equations to ensure that the sum of each component's estimated biomass values was equal to the total biomass values. Simultaneous fitting improved the performance of the equations by guaranteeing the components' additivity, and weighted regression allowed to stabilize error variance, ensuring the homoscedasticity of the residuals.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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How to Estimate Black Wattle Aboveground Biomass From Heteroscedastic Data?

Oliveira

Coutinho

Fiorentin

et al. 2020

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“…The most appropriate models were chosen and selected based on its higher R value and plotted residuals in order to test the reliability of the equations. The same method was used by both (Subasinghe and Harpriya 2014) in Sri Lanka and, (Coutinho et al 2018) in Brazil for the calculation of biomass content.…”

Section: Abg Vol X Wsg X Bef X Cf =mentioning

confidence: 99%

Estimation of above ground biomass and carbon of Pinus caribaea in Bulolo forest plantation, Papua New Guinea

Palpali¹,

Riwasino

2022

Maderas, Cienc. tecnol.

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Planted forest plays vital role in tree biomass which stored as carbon through carbon sequestration process and help reduce global warming and climate change effect. Estimation of biomass volume is the important process to determine the carbon contents stored in planted forest trees. Study was conducted to estimate the biomass and carbon content of Pinus caribaea trees using allometry models at Bulolo forest plantation in Morobe Province of Papua New Guinea. Study involves center plot of the cluster design in order to collect field data as sample size The field data was collected by measuring stem of Pinus caribaea tree species using two variables, diameter at breast height (DBH) and height. Finding reveals that first and highest rank biomass stem content and carbon stocking was 472,4 biomass/ha, followed by 407,076 biomass/ha and the least was 320,97 biomass/ha. Study reveals that biomass stem content and carbon stocking with 407,076 biomass/ha was the more suitable and applicable model for calculation of Pinus caribaea in Bulolo forest plantation. Study recommends the log formula derived from the biomass stem content and carbon stocking of 407,076 biomass/ ha, as the reliable model to be used for estimation of biomass content and carbon stock of Pinus caribaea tree species Bulolo forest plantation and else way in Papua New Guinea.

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“…The model fit and validation statistics indicate that the systems of equations developed in this study will contribute to the accurate estimation of total biomass. The NSUR method is not intended to improve the precision of AGB estimates, but rather to reconcile estimates of total biomass and the sum of biomass fractions (Coutinho et al 2018). With the application of NSUR, we have developed full allometric models, which can be used to compute the biomass of components for trees of interest.…”

Section: Individual Tree Component and Agb Modelsmentioning

confidence: 99%

Stand biomass estimation methods for Eucalyptus grandis and Eucalyptus dunnii in Uruguay

et al. 2021

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Biomass additivity is a desirable characteristic of a system of equations for predicting components and total biomass, since equations independently adjusted generate biologically inconsistent results. The aim of this study was to fit and compare three methods for modelling biomass: (i) total biomass individual regression, (ii) total biomass regression function calculated as the sum of separate biomass components, and (iii) simultaneous equations of biomass components based on Nonlinear Seemingly Unrelated Regression. A total of 208 trees of Eucalyptus dunnii and Eucalyptus grandis were harvested and destructively sampled to record above-ground biomass. Results indicate that a system of equations adjusted by simultaneous equations provides accurate biomass estimations, guaranteeing additivity. This model system showed good fit and good prediction performance, given that the correlation coefficient was higher than 97 % for total above-ground biomass, for both species; whereas root mean square error was 23.9 kg and 30.2 kg for E. grandis and E. dunnii, respectively. A system of biomass equations was developed for each eucalyptus species, such that the sum of the estimations of the biomass components equaled the estimate of above-ground biomass. Results showed that the systems of equations have high potential for improving the accuracy of individual tree above-ground biomass estimates for both species.

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Simultaneous Equations to Estimate Aboveground Biomass of Pinus caribaea var . hondurensis

Cited by 4 publications

References 17 publications

How to Estimate Black Wattle Aboveground Biomass From Heteroscedastic Data?

How to Estimate Black Wattle Aboveground Biomass From Heteroscedastic Data?

Estimation of above ground biomass and carbon of Pinus caribaea in Bulolo forest plantation, Papua New Guinea

Stand biomass estimation methods for Eucalyptus grandis and Eucalyptus dunnii in Uruguay

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