Please use this identifier to cite or link to this item:
Title: Pedo-transfer functions for estimating soil bulk density in central Amazonia
Other Titles: Estimativa da densidade do solo por equações de pedotransferência na Amazônia central
Authors: Barros, Henrique Seixas
Fearnside, Philip Martin
Issue Date: 2015
metadata.dc.publisher.journal: Revista Brasileira de Ciencia do Solo
metadata.dc.relation.ispartof: Volume 39, Número 2, Pags. 397-407
Abstract: Under field conditions in the Amazon forest, soil bulk density is difficult to measure. Rigorous methodological criteria must be applied to obtain reliable inventories of C stocks and soil nutrients, making this process expensive and sometimes unfeasible. This study aimed to generate models to estimate soil bulk density based on parameters that can be easily and reliably measured in the field and that are available in many soil-related inventories. Stepwise regression models to predict bulk density were developed using data on soil C content, clay content and pH in water from 140 permanent plots in terra firme (upland) forests near Manaus, Amazonas State, Brazil. The model results were interpreted according to the coefficient of determination (R²) and Akaike information criterion (AIC) and were validated with a dataset consisting of 125 plots different from those used to generate the models. The model with best performance in estimating soil bulk density under the conditions of this study included clay content and pH in water as independent variables and had R² = 0.73 and AIC = -250.29. The performance of this model for predicting soil density was compared with that of models from the literature. The results showed that the locally calibrated equation was the most accurate for estimating soil bulk density for upland forests in the Manaus region. © 2015, Revista Brasileira de Ciencia do Solo. All rights reserved.
metadata.dc.identifier.doi: 10.1590/01000683rbcs20140358
Appears in Collections:Artigos

Files in This Item:
File Description SizeFormat 
artigo-inpa.pdf485,37 kBAdobe PDFThumbnail

This item is licensed under a Creative Commons License Creative Commons