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

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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.