Prediction of net greenhouse gas emissions under agrosystems intensification and climate change scenarios in Brazilian savanna

• Grant number: 22/15778-6
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: November 01, 2023
• End date: October 31, 2024
• Field of knowledge: Agronomical Sciences - Agronomy - Soil Science
• Principal Investigator: Carlos Eduardo Pellegrino Cerri
• Grantee: Jorge Luiz Locatelli
• Supervisor: Stephen Del Grosso
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
• Institution abroad: Center for Agricultural Resources Research (CARR), United States
• Associated to the scholarship: 21/14989-0 - The role of Cerrado agriculture in mitigation of climate change: intensification of agroecosystems and soil carbon balance, BP.DR

Abstract

The increasing demand for resources due to population growth has accentuated greenhouse gas (GHG) emissions, aggravating the climate change process. In this sense, the adoption of management practices that reduce GHG emissions and increase the potential for carbon (C) sequestration in the soil is essential to tackle the climate change process, in addition to contributing to a more sustainable agriculture. The main objective of this proposal is to predict, using modeling tools, the long-term impacts of agroecosystems intensification strategies on soil organic matter (SOM) dynamics in the Brazilian savanna region. Specifically, to calibrate the DayCent model to simulate soil C changes and CH4 and N2O emissions and calculate soil C balance. Soil samples were collected up to 1 m deep, in the localities of Costa Rica - MS, Itiquira - MT, and Diamantino - MT. The treatments in these three sites comprise areas managed under different levels of intensification (soil tillage systems and crop diversification levels). Changes in soil C and N stocks were quantified, as well as the N2O and CH4 fluxes. This information will be organized and will be used in the DayCent model to perform the stages of parameterization, simulation, calibration, and validation. Once the model is validated, long-term simulations will be carried out to assess SOM changes, GHG fluxes, and net GHG emissions considering the current uses/treatments assessed in the study sites. Finally, new scenarios will be predicted considering management strategies and climate change projections. With this project, we expect to identify the best long-term strategies capable of reducing GHG emissions and increasing the potential of agrosystems to mitigate and adapt to climate change. These results will largely contribute to improving national inventories that are essential for the establishment of initiatives that seek to cooperate with the global climate agenda and achieve C neutrality. (AU)