No abstract

SUMMARYPeatlands are soil environments that store carbon and large amounts of water, due to their composition (90 % water), low hydraulic conductivity and a spongelike behavior. It is estimated that peat bogs cover approximately 4.2 % of the Earth's surface and stock 28.4 % of the soil carbon of the planet. Approximately 612 000 ha of peatlands have been mapped in Brazil, but the peat bogs in the Serra do Espinhaço Meridional (SdEM) were not included. The objective of this study was to map the peat bogs of the northern part of the SdEM and estimate the organic matter pools and water volume they stock. The peat bogs were pre-identified and mapped by GIS and remote sensing techniques, using ArcGIS 9.3, ENVI 4.5 and GPS Track Maker Pro software and the maps validated in the field. Six peat bogs were mapped in detail (1:20,000 and 1:5,000) by transects spaced 100 m and each transect were determined every 20 m, the UTM (Universal Transverse Mercator) coordinates, depth and samples collected for characterization and determination of organic matter, according to the Brazilian System of Soil Classification. In the northern part of SdEM, 14,287.55 ha of peatlands were mapped, distributed over 1,180,109 ha, representing 1.

This study aimed to evaluate the performance of three spatial association models used in digital soil mapping and the effects of additional point sampling in a steep-slope watershed (1,200 ha). A soil survey was carried out and 74 soil profiles were analyzed. The tested models were: Multinomial logistic regression (MLR), C5 decision tree (C5-DT) and Random forest (RF). In order to reduce the effects of an imbalanced dataset on the accuracy of the tested models, additional sampling retrieved by photointerpretation was necessary. Accuracy assessment was based on aggregated data from a proportional 5-fold cross-validation procedure. Extrapolation assessment was based on the multivariate environmental similarity surface (MESS). The RF model including additional sampling (RF*) showed the best performance among the tested models (overall accuracy = 49%, kappa index = 0.33). The RF* allowed to link soil mapping units (SMU) and, in the case of less-common soil classes in the watershed, to set specific conditions of occurrence on the space of terrain-attributes. MESS analysis showed reliable outputs for 82.5% of the watershed. SMU distribution across the watershed was: Typic Rhodudult (56%), Typic Hapludult* (13%), Typic Dystrudept (10%), Typic Endoaquent + Fluventic Dystrudept (10%), Typic Hapludult (9.5%) and Rhodic Hapludox + Typic Hapludox (2%).

No abstract

RESUMOA matéria orgânica do solo (MOS) é um dos grandes reservatórios de carbono (C) da Terra e constitui um dos principais componentes do ciclo do C. Turfeiras, ambientes acumuladores de MOS, são produto da decomposição de vegetais, que se desenvolvem e se acumulam em ambientes saturados com água, sendo o estádio inicial da sequência de carbonificação. A fitomassa participa de forma marcante no ciclo global do C, armazenando em torno de 85 % de todo o C terrestre acima do solo. O tecido vegetal é composto principalmente por lignina, celulose e hemicelulose, constituindo até 85 % da biomassa seca. As plantas discriminam C de forma diferenciada, em razão de seu ciclo fotossintético (C 3 , C 4 e CAM). As turfeiras da Serra do Espinhaço Meridional (SdEM-MG) são colonizadas por vegetação de Campo Limpo Úmido (CLU) e de Floresta Estacional Semidecidual (FES), onde ocorrem espécies dos ciclos fotossintéticos C 3 e C 4. Este trabalho objetivou avaliar a contribuição dessas duas fitofisionomias para o acúmulo de MOS, por meio da avaliação da fitomassa e da composição lignocelulósica e isotópica da vegetação e da MOS. A turfeira estudada localiza-se na SdEM e ocupa 81,75 ha.