Effects of tropical forest conversion on soil and aquatic systems in southwestern Brazilian Amazonia: A synthesis.

Southwestern Brazilian Amazonia has suffered intense forest conversion in a short period of time (~60 years) and deforestation is ongoing. Around 70% of the deforested area has been designated for cattle ranching. This forest clearing and pasture establishment is abruptly disrupting the functioning of the ecosystem. In this paper, we provide an overview of the effects of land conversion from forest to pasture on the soil and aquatic systems. Forest conversion to pasture has two clear effects: a) an on-site effect on the hillslope domain and 2) an off-site effect on the river system. The conversion of forest to pasture affects the soil physical-chemical properties, soil carbon content, water resources, and aquatic system. However, many of these changes are not straightforward or obvious. For example, in some conditions, the soil carbon stock increases in pasture. Despite the advances in our understanding of the effects of land conversion on environmental processes, knowledge gaps persist, and we identify some research needs.

Modeling the soil burn effect for temperature prediction by energy dispersive X ray Fluorescence in an haplic cambisol soil.

Considered an important hydrological and geomorphological agent, fire can cause physical, chemical and biological changes in the soil. Besides wildfire, the study of fire effects is also related to traditional agriculture. This study presents the characterization and analysis of soil samples submitted to burn simulation with the objective to build a temperature prediction model in order to determine the maximum temperature reached by real soil burn samples. For this purpose, surface soil samples (0-2.5 cm) classified as Haplic Cambisol were collected from a native forest area close to the studied field. The temperature of the simulation samples ranged from 50 to 750 °C. Moreover, a real burn set of samples were measured for temperature prediction using the proposed model. The characterization and quantification of the chemical elements present in the soil were done by Energy Dispersive X-ray Fluorescence (EDXRF) measurements. Plots with Fe concentration and with the Rayleigh and Compton scattering data versus temperature were constructed. The Fe/Rh and Fe/RhC ratios resulted in relative deviations ranging from 14% to 22% using univariate analysis. Multivariate analysis was also applied through partial least squares regression (PLSR) method in four different spectrum regions. The best result was obtained for the model using the spectrum scattering region with r2 = 0.90 and relative deviation ranging from 8% to 25% for the predicted temperature. The use of local multivariate PLSR models improved the results when compared to the univariate regression results.

X-ray fluorescence and gamma-ray spectrometry combined with multivariate analysis for topographic studies in agricultural soil.

Physical and chemical properties of soils play a major role in the evaluation of different geochemical signature, soil quality, discrimination of land use type, soil provenance and soil degradation. The objectives of the present study are the soil elemental characterization and soil differentiation in topographic sequence and depth, using Energy Dispersive X-Ray Fluorescence (EDXRF) as well as gamma-ray spectrometry data combined with Principal Component Analysis (PCA). The study area is an agricultural region of Boa Vista catchment which is located at Guamiranga municipality, Brazil. PCA analysis was performed with four different data sets: spectral data from EDXRF, spectral data from gamma-ray spectrometry, concentration values from EDXRF measurements and concentration values from gamma-ray spectrometry. All PCAs showed similar results, confirmed by hierarchical cluster analysis, allowing the data grouping into top, bottom and riparian zone samples, i.e. the samples were separated due to its landscape position. The two hillslopes present the same behavior independent of the land use history. There are distinctive and characteristic patterns in the analyzed soil. The methodologies presented are promising and could be used to infer significant information about the region to be studied.