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Abstract The results of this study provide the first baseline for predicting D b from soil properties for soils across the Amazon basin. Bulk density values are needed to convert nutrient content and organic carbon (OC) content to weight of nutrient and OC per unit area; unfortunately, common field methods to measure D b are limited with regard to reliable, complete, and uniform soil data. Much effort has been made in finding alternative solutions to predict D b from soil properties. We hypothesized that D b could be reliably estimated by multiple regression of OC, soil textural properties, and some chemical properties. Using the data of 323 soil horizons from the Brazilian Amazon basin, a stepwise multiple regression (SMR) procedure was developed to predict D b from other soil properties. Multiple regression relationships were obtained for all the data, which were also partitioned by layer and then by main soil order: Latossolos (Oxisols, 62 horizons) and Podzólicos (Alfisols and Ultisols, 212 horizons). The SMR on all the data showed that clay content is the best predictor of D b , accounting for 37% of the variation. Adding OC content increased the explained variance up to nearly 50%. Predictions of the models were improved when the data were partitioned by order and by horizon type. In the case of Latossolos (Oxisols), the use of OC and clay content as predictors increased the percentage of explained variation, reaching 71% using all layers and 79% for A horizons. The results of this study will provide a basis for estimating OC stocks in the Amazon basin.
Bernoux et al. (Fri,) studied this question.