Agradecimentos: The authors would like to thank the owner, manager, and staff of the Campina farm (CV Nelore Mocho) for their support and assistance. We are also grateful to the undergraduate and graduate students, postdoctoral researchers, and also to the technicians for helping with the field data collection and preparation. NIPE and FEAGRI/UNICAMP are acknowledged for the infrastructure and support provided for this project development. Meteorological data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program. This research was funded by CNPq (Process number 167705/2018-0) and FAPESP (Process numbers 2017/50205-9, 2018/24707-0, and 2020/06775-8) Ver menos

Abstract: Process-based models (PBM) are important tools for understanding the benefits of Integrated Crop-Livestock Systems (ICLS), such as increasing land productivity and improving environmental conditions. PBM can provide insights into the contribution of agricultural production to climate change and help identify potential greenhouse gas (GHG) mitigation and carbon sequestration options. Rehabilitation of degraded lands is a key strategy for achieving food security goals and can reduce the need for new agricultural land. This study focused on the calibration and validation of the DayCent PBM for a typical ICLS adopted in Brazil from 2018 to 2020. We also present the DayCent parametrization for two forage species (ruzigrass and millet) grown simultaneously, bringing some innovation in the modeling challenges. We used aboveground biomass to calibrate the model, randomly selecting data from 70% of the paddocks in the study area. The calibration obtained a coefficient of determination (R2) of 0.69 and a relative RMSE of 37.0%. During the validation, we used other variables (CO2 flux, grain biomass, and soil water content) measured in the ICLS and performed a double validation for plant growth to evaluate the robustness of the model in terms of generalization. R2 validations ranged from 0.61 to 0.73, and relative RMSE from 11.3 to 48.3%. Despite the complexity and diversity of ICLS results show that DayCent can be used to model ICLS, which is an important step for future regional analyses and large-scale evaluations of the impacts of ICLS Ver menos