Biomass data for young, planted Norway spruce (Picea abies (L.) Karst.) trees in Eastern Carpathians of Romania

Dutcă, Ioan

doi:10.1016/j.dib.2018.07.033

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…This small Q-ratio resulted however from parameter estimates of hierarchical linear models on log-log transformed data. Nevertheless, using ordinary least squares with a linear model and log-log transformed data (Dutcă, 2018), the resulting Q-ratio was larger than 2.0 (i.e., Q = 4.5).…”

Section: Discussionmentioning

confidence: 99%

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

Dutcă

McRoberts

Næsset

et al. 2019

Forestry: An International Journal of Forest Research

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Tree diameter at breast height (D) and tree height (H) are often used as predictors of individual tree biomass. Because D and H are correlated, the combined variable D2H is frequently used in regression models instead of two separate independent variables, to avoid collinearity related issues. The justification for D2H is that aboveground biomass is proportional to the volume of a cylinder of diameter, D, and height, H. However, the D2H predictor constrains the model to produce parameter estimates for D and H that have a fixed ratio, in this case, 2.0. In this paper we investigate the degree to which the D2H predictor reduces prediction accuracy relative to D and H separately and propose a practical measure, Q-ratio, to guide the decision as to whether D and H should or should not be combined into D2H. Using five training biomass datasets and two fitting approaches, weighted nonlinear regression and linear regression following logarithmic transformations, we showed that the D2H predictor becomes less efficient in predicting aboveground biomass as the Q-ratio deviates from 2.0. Because of the model constraint, the D2H-based model performed less well than the separate variable model by as much as 12 per cent with regard to mean absolute percentage residual and as much as 18 per cent with regard to sum of squares of log accuracy ratios. For the analysed datasets, we observed a wide variation in Q-ratios, ranging from 2.5 to 5.1, and a large decrease in efficiency for the combined variable model. Therefore, we recommend using the Q-ratio as a measure to guide the decision as to whether D and H may be combined further into D2H without the adverse effects of loss in biomass prediction accuracy.

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Section: Discussionmentioning

confidence: 99%

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

Dutcă

McRoberts

Næsset

et al. 2019

Forestry: An International Journal of Forest Research

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“…Preference to one of the methods can be decided based on the raw data availability. Nevertheless, access to raw observations should not be an issue given the increasing trend in publication of biomass datasets, e.g., [44,[55][56][57][58]. (c) The generic biomass sample should contain as many species-specific observations as possible, including very large trees (D-range should match that of the local population for which the models are developed).…”

Section: Discussionmentioning

confidence: 99%

Allometric Biomass Models for European Beech and Silver Fir: Testing Approaches to Minimize the Demand for Site-Specific Biomass Observations

Dutcă

Zianis

Petriţan

et al. 2020

Forests

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In this paper, site-specific allometric biomass models were developed for European beech (Fagus sylvatica L.) and silver fir (Abies alba Mill.) to estimate the aboveground biomass in Șinca virgin forest, Romania. Several approaches to minimize the demand for site-specific observations in allometric biomass model development were also investigated. Developing site-specific allometric biomass models requires new measurements of biomass for a sample of trees from that specific site. Yet, measuring biomass is laborious, time consuming, and requires extensive logistics, especially for very large trees. The allometric biomass models were developed for a wide range of diameters at breast height, D (6–86 cm for European beech and 6–93 cm for silver fir) using a logarithmic transformation approach. Two alternative approaches were applied, i.e., random intercept model (RIM) and a Bayesian model with strong informative priors, to enhance the information of the site-specific sample (of biomass observations) by supplementing with a generic biomass sample. The appropriateness of each model was evaluated based on the aboveground biomass prediction of a 1 ha sample plot in Șinca forest. The results showed that models based on both D and tree height (H) to predict tree aboveground biomass (AGB) were more accurate predictors of AGB and produced plot-level estimates with better precision, than models based on D only. Furthermore, both RIM and Bayesian approach performed similarly well when a small local sample (of seven smallest trees) was used to calibrate the allometric model. Therefore, the generic biomass observations may effectively be combined with a small local sample (of just a few small trees) to calibrate an allometric model to a certain site and to minimize the demand for site-specific biomass measurements. However, special attention should be given to the H-D ratio, since it can affect the allometry and the performance of the reduced local sample approach.

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“…Validation of tree volume and biomass equations were essential in predicting the forest dynamics, socio-economic values, global trends of climate change and estimation of carbon sequestration (Ribeiro et al, 2011;Carreiras et al, 2017). Both total tree volume and models biomass regression equations use diameter at breast height and total tree height to predict the aboveground biomass accumulated in a given forest (Dutcă, 2018). Measurement of independent variables used to predict tree volume and biomass should be free measurement error, however error free measurement of variables is hardly practicable and might lead to under or (Vieira et al, 2008; Table 4).…”

Section: Model Selection and Evaluationmentioning

confidence: 99%

Total Volume and Aboveground Biomass Models for <i>Juniperus procera</i> Plantation in Wondo Genet, Southern Ethiopia

Gereslassie¹,

Workineh²,

Takele³

et al. 2019

OJF

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Species specific allometric equations are important for estimation and quantification of net volume and aboveground biomass of living trees. This study was basically focused on fitting total volume and aboveground biomass models for Juniperus procera plantations in Wondo Genet, Sidama Zone, Ethiopia. Data for fitting the total volume and aboveground biomass models were obtained by destructively sampling of trees from the ten diameter classes of the Juniperus procera plantation in the study area. A total of one hundred ten and fifty-one trees were destructively sampled to fit six total volume and six aboveground biomass models respectively. After important measurements of parameters have completed, model performance evaluation and selecting of best fit models were undertaken using standard error of estimates (SEE), coefficient of determination (R 2), bias (B) and mean of the absolute value of errors (MAE). Accordingly, the total volume model Vt = −5.466 + 0.959Dbh 0.005 H 003 and aboveground biomass model of B = 0.348Dbh 0.57 H 0.032 were found to be the best predictive models for total tree volume and aboveground biomass respectively. In addition to the above results, diameter at breast height and total tree height data obtained from 69 circular sample plots of 0.01 ha area drawn from the plantation were used to estimate the total volume and aboveground biomass per hectare BEF which was estimated to be 0.64 Mg/m 3. Generally, the selected models and computed BEF in this study are believed to be applied by different organisations and researches to estimate the total volume and aboveground biomass of the J. procera.

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Biomass data for young, planted Norway spruce (Picea abies (L.) Karst.) trees in Eastern Carpathians of Romania

Cited by 4 publications

References 6 publications

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

Allometric Biomass Models for European Beech and Silver Fir: Testing Approaches to Minimize the Demand for Site-Specific Biomass Observations

Total Volume and Aboveground Biomass Models for <i>Juniperus procera</i> Plantation in Wondo Genet, Southern Ethiopia

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Biomass data for young, planted Norway spruce (Picea abies (L.) Karst.) trees in Eastern Carpathians of Romania

Cited by 4 publications

References 6 publications

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

Allometric Biomass Models for European Beech and Silver Fir: Testing Approaches to Minimize the Demand for Site-Specific Biomass Observations

Total Volume and Aboveground Biomass Models for &lt;i&gt;Juniperus procera&lt;/i&gt; Plantation in Wondo Genet, Southern Ethiopia

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Product

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Total Volume and Aboveground Biomass Models for <i>Juniperus procera</i> Plantation in Wondo Genet, Southern Ethiopia