Atributos físicos e estoque de carbono do solo em áreas de Terra Preta Arqueológica da Amazônia

Cunha, José Maurício da; Gaio, Denilton Carlos; Campos, Milton César Costa; Soares, Marcelo Dayron Rodrigues; Silva, Douglas Marcelo Pinheiro da; Lima, Alan Ferreira Leite de

doi:10.4136/ambi-agua.1890

Cited by 15 publications

(19 citation statements)

References 15 publications

(27 reference statements)

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“…In Figure 3G, the pH values with the highest frequency are distributed in the class 4.5-4.6 with frequencies of 50%, the other areas presented frequencies equal to or less than 20%, from the class 4.30 to the class 4.90. This result corroborates those of Cunha et al (2017), which state that most of the soils of the cultivated areas of the study region are acidic, with low cation exchange capacity, which translates into low natural fertility. In the VI environment, favorable conditions for OM accumulation and maintenance contributed to high potential acidity ( Figure 3I), according to Silva et al (2016) the abundance of organic acids in the forest soil releases H + ions that will compose the potential acidity.…”

Section: Cultivationsupporting

confidence: 90%

Multivariate analysis in the evaluation of soil attributes in areas under different uses in the region of Humaitá, AM

et al. 2019

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The recognition of the influence of management practices on soil physical and chemical conditions is substantial for sustainable agriculture. For this reason, this study was developed for the purpose of evaluating the behavior of soil attributes under different uses in the region of Humaitá, AM, using multivariate statistical methods. The study was developed in 8 rural properties producing bananas, grassland, maize, coffee, cassava, vegetables, agroforestry system and a forest fragment. Samples of soils with preserved structure in the 0.0 - 0.10 and 0.10 - 0.20 m layers were randomly collected in 5 small trenches per area, totaling 32 samples in the management systems, to determine the physical and chemical attributes. The data were then submitted to univariate and multivariate statistical analysis. Exploratory data analysis (principal components and dendrogram) and frequency of environmental covariates was efficient in distinguishing production environments, so multivariate classification based on physical and chemical attributes of the soil can help in the proper planning of land use. The analysis of the principal components indicates that the BD presents direct dependence with the SPR, signaling the use of the soil with grassland the only one in the process of compaction. Soil acidity is the main limiting factor for crop development, requiring the adoption of pH corrective practices with improvements in nutrient supply. The conversion of the forest to grassland maintained the structural characteristics of the soil, while the other uses increased improvements in physical quality and soil fertility.

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Section: Cultivationsupporting

confidence: 90%

Multivariate analysis in the evaluation of soil attributes in areas under different uses in the region of Humaitá, AM

et al. 2019

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“…The results for descriptive statistics before and after grazing showed similarity for the average and median, which indicated a symmetric distribution; the measures of central tendency were dominated by typical values in the distribution (Tables 2 and 3). According to the Kolmogorov-Smirnov test, all variables had normal distribution, with coefficients of asymmetry and kurtosis similar or equal to zero (Cunha et al, 2017).…”

Section: Resultsmentioning

confidence: 99%

Spatial variability of soil physical-hydric attributes under bovine trampling in agreste of Pernambuco State, Brazil

et al. 2018

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Soils under pastures suffer physical modifications, in greater or lesser intensity, via the action of animal trampling. Thus, the aim was to evaluate the spatial dependence of soil physical attributes under bovine trampling. The trial was performed at Roçadinho Farm, Agreste of Pernambuco, Brazil, in a 40 x 40 m paddock that was managed with continuous stocking by bovines and 12 AU ha-1 stocking rate. Soil samples were collected before and after grazing using a 6 x 6 m grid, totaling 36 sampling points. At each point, the bulk density, total porosity, moisture, soil penetration resistance at 0.00-0.10, 0.10-0.20, and 0.20-0.30 m depth were estimated, as was the hydraulic conductivity on the saturated soil surface. Descriptive statistics and geostatistics supported the data analysis. A normal distribution was verified for all variables, which were scored as either low or high variability in terms of the variation coefficient. The physical attributes (density, total porosity, moisture, soil penetration resistance and hydraulic conductivity) of the soil sampled presented a strong spatial dependence before and after grazing.

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“…This statement is strengthened by analyzing the two simplest rules found in the decision trees generated for the 0.05-to 0.10-m and 0.10to 0.20-m layers, where sand contents ≤ 398 and 444 g kg −1 , respectively, are associated with high soil C stock levels. In research conducted under similar conditions with ABE under the cultivation of pigeon peas and pasture, Cunha et al (2017) stated that the greater sand content present in these soils, when compared with areas with forest cover, is probably associated with the greater impact of raindrops in open areas. Also, and according to Corado Neto et al (2015), organic C losses may be associated with low vegetation cover and high surface runoff, the latter being a result of topography and the high annual rainfall (2,300 mm) in the study region (Campos, Ribeiro, Souza Júnior, Ribeiro Filho, & Almeida, 2012).…”

Section: Effect Of Sand On Soil Carbon Stockmentioning

confidence: 99%

Soil carbon stock in archaeological black earth under different land use systems in the Brazilian Amazon

et al. 2020

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In the Amazon, there are soils associated with continued human occupation known as "archeological black earth" (ABE). Due to its physical and chemical properties, ABE is more productive than other typical soils in the same region. Therefore, its carbon (C) sequestration mechanism has been a major topic of discussion by the scientific community, aiming to replicate similar characteristics in other soils. Thus, the objective of this study was to develop a predictive model using feature selection and decision tree induction methods for predicting soil C stock in ABE under different land use scenarios. The experiment was carried out in agricultural (coffee, cacao, and beans), pasture, and forest areas. Four feature selection approaches were used to identify the most relevant variables for the proposed model: (i) correlation-based feature selection, (ii) the χ 2 test, (iii) the Wrapper method, and (iv) no feature selection. The decision tree induction technique available in the Weka software was selected for data classification. Soils under cacao and coffee cultivation tend to accumulate more C when compared with soils located at bean crops, pasture, or forest land use systems. Land use and sand content were among the most important variables for the prediction of soil C stock in ABE. Furthermore, the use of a decision tree was effective at predicting soil C stocks for these soils because it enables the creation of models with high accuracy rates of 83, 74, and 81% (using seven, seven, and four rules at depths of 0.00-0.05, 0.05-0.10, and 0.10-0.20 m, respectively). 1 INTRODUCTION In the Amazon, soils with anthropogenic A horizon are associated with long-term human occupation by pre-Columbian indigenous societies (Santos et al., 2017), which formed extensive deposits of organic residues, significantly

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Atributos físicos e estoque de carbono do solo em áreas de Terra Preta Arqueológica da Amazônia

Cited by 15 publications

References 15 publications

Multivariate analysis in the evaluation of soil attributes in areas under different uses in the region of Humaitá, AM

Multivariate analysis in the evaluation of soil attributes in areas under different uses in the region of Humaitá, AM

Spatial variability of soil physical-hydric attributes under bovine trampling in agreste of Pernambuco State, Brazil

Soil carbon stock in archaeological black earth under different land use systems in the Brazilian Amazon

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