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Equations of bark thickness and volume profiles at different heights with easy-measurement variables

The objective of this work was to develop equations of thickness profile and bark volume at different heights with easy-measurement variables, taking as a study case Nothofagus pumilio forests, growing in different site qualities and growth phases in Southern Patagonia. Data was collected from 717 h...

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Main Authors: Cellini, Juan Manuel, Galarza, Martín, Burns, Sarah Lilian, Martinez Pastur, Guillermo José, Lencinas, María Vanessa
Format: Artículo
Language:Inglés
Published: Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (España) 2022
Subjects:
Nothofagus
Espesor
Nothofagus pumilio
Inventarios Forestales
Análisis por Regresión Múltiple
Medición
Thickness
Forest Inventories
Multiple Regression Analysis
Measurement
Online Access:http://hdl.handle.net/20.500.12123/11354
https://revistas.inia.es/index.php/fs/article/view/1963
https://doi.org/10.5424/fs/2112211-01963
Summary:The objective of this work was to develop equations of thickness profile and bark volume at different heights with easy-measurement variables, taking as a study case Nothofagus pumilio forests, growing in different site qualities and growth phases in Southern Patagonia. Data was collected from 717 harvested trees. Three models were fitted using multiple, non-lineal regression and generalized linear model, by stepwise methodology, iteratively reweighted least squares method for maximum likelihood estimation and Marquardt algorithm. The dependent variables were diameter at 1.30 m height (DBH), relative height (RH) and growth phase (GP). The statistic evaluation was made through the adjusted determinant coefficient (r2-adj), standard error of the estimation (SEE), mean absolute error and residual analysis. All models presented good fitness with a significant correlation with the growth phase. A decrease in the thickness was observed when the relative height increase. Moreover, a bark coefficient was made to calculate volume with and without bark of individual trees, where significant differences according to site quality of the stands and DBH class of the trees were observed. It can be concluded that the prediction of bark thickness and bark coefficient is possible using DBH, height, site quality and growth phase, common and easy measurement variables used in forest inventories.

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