A three level system for estimating the biomass of Castanea sativa Mill. coppice stands in north-west Spain
By María Menéndez-Miguélez, E. Canga, Marcos Barrio-Anta, Juan Majada, P. Álvarez-Álvarez. 2013
52 citations recorded by the source corpus.
Abstract Aboveground biomass was studied in Castanea sativa Mill. coppice stands in north-west Spain, and biomass equations were fitted at three levels (individual tree, stool and stand). Four systems of biomass estimation were developed. In two of the systems, the following individual tree variables were taken into account: standing tree variables and stump dimension variables. In the other two systems, biomass was estimated at stool and stand level, respectively. In order to represent the existing range of ages, stand densities and sites in the study area, samples of 120 trees (for the individual tree level), 45 stools (for the stool level) and 70 plots (for the stand level) were chosen for study. The trees were felled and destructively sampled to separate biomass into the following components: wood, bark, thick branches, medium branches, thin branches and leaves. Several equations for quantifying the biomass of the different biomass components were evaluated. Heterocedasticity was corrected for by weighted fitting. To guarantee the additivity of the different biomass components, the equations were fitted simultaneously by nonlinear seemingly unrelated regressions (NSURs). The different biomass levels considered accounted for between 60% and 90% of the total variability, depending on the level and component evaluated. Most of the equations developed in this study were evaluated with an independent dataset, which confirmed the good performance of the biomass equations for prediction purposes.
Subfields: Forestry, Mechanical Engineering, Nature and Landscape Conservation
View Paper: https://www.semanticscholar.org/paper/48882264017ec1cff17dc2369638aa732f4ec0dc
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Citations in the corpus
- A Three-Step Proportional Weighting System of Nonlinear Biomass Equations (2015, methodology): “NSUR is increasingly general and flexible and has become more popular as a parameter estimation method for nonlinear simultaneous biomass models (Parresol 2001, Li and Zhao 2013, Menendez-Miguelez et al. 2013).”
- Developing Two Additive Biomass Equations for Three Coniferous Plantation Species in Northeast China (2016, background): “However, some researchers suggest that data analysis and modeling should be performed on the original data of measurement via nonlinear regression [10,27].”