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Evaluation of regression models for above-ground biomass determination in Amazon rainforest

Published online by Cambridge University Press:  10 July 2009

Johannes Petrus Maria Overman ,
Hendrik Johannes Louis Witte  and
Juan Guillermo Saldarriaga
Johannes Petrus Maria Overman
Affiliation:
Hugo de Vries Laboratory, Faculty of Biology, University of Amsterdam, Kruislaan 318, 1098 SM Amsterdam, the Netherlands.
Hendrik Johannes Louis Witte
Affiliation:
Hugo de Vries Laboratory, Faculty of Biology, University of Amsterdam, Kruislaan 318, 1098 SM Amsterdam, the Netherlands.
Juan Guillermo Saldarriaga
Affiliation:
Tropenbos-Colombia Programme, A.A. 036062, Santafé de Bogotá, Colombia.
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Abstract

In a mature lowland ‘terra firme’ forest near Araracuara in Colombia, a study was conducted to determine the above-ground biomass by means of regression analysis. Dry weight, DBH (i.e. stem diameter at 1.3 m above ground level, or just above buttresses if these surpassed 1.3 m in height), total height and specific wood density were measured on 54 harvested trees, chosen in a ‘selected random’ manner. Nine different regression models were evaluated for statistical correctness, accuracy of the estimates and for practical use. The logarithmically transformed models with DBH2, and DBH2 × height as independent variables appeared to be the only models meeting the above criteria, the latter being the most accurate.

The exclusion of big trees (DBH >45 cm) from the regression did not result in significant changes of the regression coefficients.

Keywords

AmazonbiomassColombiaDBHlowland rainforestregression models
Type
Research Article
Information
Journal of Tropical Ecology , Volume 10 , Issue 2 , May 1994 , pp. 207 - 218
Copyright
Copyright © Cambridge University Press 1994

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