Predicting land-use change impacts on soil organic matter dynamics in the MATOPIBA region

• Grant number: 21/07676-6
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Effective date (Start): November 14, 2021
• Effective date (End): November 11, 2022
• Field of knowledge: Agronomical Sciences - Agronomy - Soil Science
• Principal Investigator: Carlos Eduardo Pellegrino Cerri
• Grantee: Rafael Silva Santos
• Supervisor: Maria Francesca Cotrufo
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
• Research place: Colorado State University, United States
• Associated to the scholarship: 19/17576-9 - Organic matter dynamics under the influence of land use change: effects on dissolved organic carbon, BP.DR

Abstract

In the so-called MATOPIBA region in northeastern Brazil, large areas of native vegetation (NV; the Cerrado biome) were converted to agricultural areas under no-tillage (NT; e.g., soybean and cotton production) in recent years. However, little is known about the long-term impacts of this land-use change (LUC) on soil organic matter (SOM) dynamics and greenhouse gas emissions. (e.g., CO2). This project aims i) to assess the impacts that the LUC from NV to NT has imposed on SOM dynamics in the MATOPIBA region; and ii) to use the obtained data set to predict SOM dynamics simulating strategies (e.g., levels of fertilization and cover crops management) that could help to alleviate the greenhouse gases emissions associated with agriculture. The fieldwork was carried out in the municipalities of Tasso Fragoso - MA, Luís Eduardo Magalhães - BA, and Correntina - BA. Soil samples were collected from paired plots (NV and NT) in each location up to 1-m depth for C and N determination in the bulk SOM, particulate (POM) and mineral-associated organic matter (MAOM), and water-extractable organic matter. Additionally, microbial analyses (e.g., microbial biomass, ²-glucosidase, and acid phosphatase) were assessed in the upmost soil layers (i.e., 0-20 cm). Based on this data set, SOM modeling will be performed using the MEMS 2.0 model. All modeling steps (e.g., data set interpretation, model training, parameterization, simulation, and validation) will be performed at the Colorado State University. The data will be integrated using multivariate statistics aiming to obtain a descriptive interpretation; and the correlation coefficient, residual mass coefficient, and coefficient of determination will be used to evaluate the sensitiveness of the model. It is expected to quantify and accurately predict the impacts induced by LUC on SOM dynamics in the MATOPIBA region. (AU)