https://www.alice.cnptia.embrapa.br/alice/handle/item/349 Artigo em periódico indexado (CNPS) 2026-04-10T15:22:37Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1185934 Título: Capacidade de estocagem de carbono e nitrogênio em solos antrópicos e não antrópicos sob florestas secundárias no estado do Amazonas. Autoria: SOARES, R.; CAMPOS, D. V. B. de; MADARI, B. E.; MACHADO, P. L. O. de A.; MADDOCK, J. E. L. Conteúdo: Esse estudo tem como objetivos: (i) determinar os estoques de carbono e nitrogênio de Terras Pretas de Índio e Solos Não Antrópicos (Argissolos) sob florestas secundárias no estado do Amazonas (AM); (ii) avaliar o efeito do tempo de pousio entre duas áreas de Terras Pretas de Índio. 2026-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1185169 Título: Adaptive neuro-fuzzy inference system for predicting sandy soils bulk density. Autoria: LOURENÇONI, D.; SALVIANO, A. M.; OLSZEVSKI, N.; PEREIRA, J. S.; CAVALCANTE, E. H. M. Conteúdo: Soil compaction, often the result of intensive mechanization, is a major concern because it increases the bulk density of the soil, fundamentally altering its structure and reducing its capacity to support essential ecological and agricultural functions. Therefore, soil monitoring is essential, particularly through its main quality indicator, bulk density. However, the analysis of this attribute requires the collection of soil samples with subsequent laboratory analysis, which demands time and qualified labor. Thus, this study aimed to develop a neuro-fuzzy model to estimate the bulk density of sandy soils based on variations in the proportion of its particle size fractions. To achieve this, undisturbed samples were collected from soils in four municipalities in northern Bahia, located along the shores of Lake Sobradinho. The proportion of particle size fractions in the composition of each sample was used to develop models that integrate fuzzy logic and neural networks. They employed the Takagi-Sugeno inference method and hybrid learning algorithms for parameter adjustment and bulk density predictions. The performance of the models was evaluated using error statistics, with the model with the highest accuracy in density predictions being selected, achieving an R² of 71%. It is important to emphasize that the neuro-fuzzy model did not require data stratification and can be applied to estimate the sandy soil density of any soil type sampled. 2026-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1183343 Título: A scalable framework for soil property mapping tested across a highly diverse tropical data-scarce region. Autoria: MIRANDA, R. de Q.; NÓBREGA, R. L. B.; VERHOEF, A.; SILVA, E. L. R. da; SILVA, J. F. da; ARAUJO FILHO, J. C. de; MOURA, M. S. B. de; BARROS, A. H. C.; SOUZA, A. G. S. S.; YANG, W.; SHAO, H.; SRINIVASAN, R.; ZIADAT, F.; MONTENEGRO, S. M. G. L.; ARAÚJO, M. do S. B.; GALVÍNCIO, J. D. Conteúdo: Reliable soil property maps are essential for environmental modeling, yet conventional mapping methods remain costly and time-consuming. We developed a machine learning framework that integrates the Soil-Landscape Estimation and Evaluation Program (SLEEP) with gradient boosting to predict soil properties at regional scales and multiple depths. Our approach addresses multicollinearity through a recursive feature selection algorithm. We applied this framework to a tropical region characterized by a ∼700-km longitudinal gradient of contrasting topography, climate, and vegetation (∼98,000 km²; NE Brazil), where scarce soil physicochemical data limit environmental modeling. We used six topographical, ten climate, and two vegetation covariates, along with data from 223 soil profiles (∼1 profile per 440 km²). Training and testing of our framework demonstrated strong spatial performance (r² = 0.79–0.98 and percent bias = −1.39–1.14 %). Topographic and climatic factors held greater weight than other variables in predicting soil layers, texture, and sum of bases. Moreover, we used our soil parameters combined with multiple pedotransfer functions (PTFs) to derive soil hydraulic properties. Our PTFs-derived estimates of hydraulic conductivity were considerably lower than high-resolution global predictions available for our study areadue to differences in clay fraction and mineralogy. Therefore, we recommend the use of region-specific PTFs for hydraulic properties based on multi-covariate soil property maps. This cost-effective framework accurately integrates diverse environmental covariates, adapts to varying soil data availability, and scales across spatial resolutions, making it highly transferable to other data-scarce regions. 2025-01-01T00:00:00Z https://www.alice.cnptia.embrapa.br/alice/handle/doc/1183345 Título: Geochemical, granulometric, and dating characterization of anthropic sediment deposits within the shells of the Sambaqui - Fazenda Campos Novos - Cabo Frio - RJ - Brazil. Autoria: TEIXEIRA, W. G.; VALLE, L. G. F.; MANSUR, K. L. Conteúdo: This study characterizes the Fazenda Campos Novos (FCN) Sambaqui, a prehistoric shell mound site in Cabo Frio, Brazil. By analyzing the physical, geochemical, and paleoenvironmental aspects of the sambaqui, we aim to understand the environmental conditions associated with the sediments within the shell midden. Methods employed included sediment grain size analysis, X-ray fluorescence, wet chemical characterization, magnetic susceptibility analysis, and radiocarbon dating to provide chronological context. Granulometric data revealed a predominantly sandy loam texture and high magnetic susceptibility values, indicative of human-induced heating events. Chemical analyses revealed elevated levels of organic matter, phosphorus, strontium, and other elements, suggesting significant anthropic influence and resource utilization by prehistoric inhabitants. The presence of marine shells and sandy sediments indicates a coastal depositional environment. Radiocarbon dating placed the sambaqui’s age between 3230 and 3350 years BP, aligning with other regional archaeological sites. Paleoenvironmental reconstructions suggest that the FCN Sambaqui formed during a Holocene marine transgression. These findings enhance our understanding of the cultural practices, environmental conditions, and human-environment interactions associated with the FCN Sambaqui, providing a valuable record of prehistoric life and informing future research on coastal archaeology and paleoenvironmental studies. 2025-01-01T00:00:00Z