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

Author(s)

Lopez-Noronha, Renato ^[1] ; de Souza, Zigomar Menezes ^[1] ; Rodrigues Soares, Marcelo Dayron ^[2] ; Costa Campos, Milton Cesar ^[2] ; Vieira Farhate, Camila Viana ^[1] ; de Medeiros Oliveira, Stanley Robson ^{[1, 3]}

Affiliation

^[1] Univ Estadual Campinas, Sch Agr Engn, BR-13083875 Campinas, SP - Brazil

^[2] Univ Amazonas, Inst Educ Agr & Environm, BR-69800000 Humaita, Amazonas - Brazil

^[3] Brazilian Agr Res Corp Embrapa, Agr Informat Sci Comp Lab, BR-13083886 Campinas, SP - Brazil

• Document type: Journal article
• Source: AGRONOMY JOURNAL; v. 112, n. 5, p. 4437-4450, SEP-OCT 2020.
• Web of Science Citations: 0

Abstract

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 chi (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). (AU)

• FAPESP's process: 15/24280-8 - Physical quality soil in black land transformed archaeological and natural
• Grantee: Zigomar Menezes de Souza
• Support Opportunities: Regular Research Grants