No 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.

Warming climate can cause release of carbon stocks in soils, but direct observations in tropical soils have been lacking. A unique data set from a study near Manaus, Brazil, allows comparison of samples taken before and after a ∼28‐yr period in 176 plots in undisturbed forest (i.e., intact forest with no visible sign of modern human action and >100 m from a forest edge, with 98% of the plots being >300 m from an edge). The data indicate a significant loss of carbon in the top 20 cm of soil (2.98 MgC ha‐1 over 28 yr, an average of 0.11 Mg ha‐1 yr‐1, or 0.3828% yr‐1 of the carbon stock). Carbon emissions would be substantial if the pattern for the top 20 cm at this location holds throughout Amazonia, and the implications are huge if the same pattern holds for the deeper soil layers. Release of soil carbon can contribute to a positive feedback, where emissions cause greater warming that further augments the emissions.

This study evaluated forest restoration projects filed at the state environmental agency of Rio de Janeiro (Inea), regarding the requirements contained in the Resolution Nº 36/2011. Legal, technical, environmental and ecological parameters of 65 restoration projects in the design and implementation phases were analyzed. Only 29% of the projects met the requirements of Resolution Nº 36/2011. The low compliance with the requirements of the resolution evidences the lack of knowledge of the current regulations in the state of Rio de Janeiro by the technical users of the system. This condition implies a longer time of environmental licensing. Recently, Inea has revoked Res. Nº 36/2011 through Res. Nº 143/2017, which, in addition to simplifying the presentation of restoration projects, gave rise to the State System for Monitoring and Evaluation of Forest Restoration -SEMAR.