Data/hora: 10/06/2024 05:40:18

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	17/03/2022	
Data da última atualização: 	17/03/2022	
Autoria: 	SILVA, Y. F.; VALADARES, R. V.; DIAS, H. B.; CUADRA, S. V.; CAMPBELL, E. E.; LAMPARELLI, R. A. C.; MORO, E.; BATTISTI, R.; ALVES, M. R.; MAGALHÃES, P. S. G.; FIGUEIREDO, G. K. D. A.	
Afiliação: 	YANE FREITAS SILVA, FEAGRI/UNICAMP; RAFAEL VASCONCELOS VALADARES, NIPE/UNICAMP; HENRIQUE BORIOLO DIAS, NIPE/UNICAMP; SANTIAGO VIANNA CUADRA, CNPTIA; ELEANOR E. CAMPBELL, UNIVERSITY OF NEW HAMPSHIRE; RUBENS AUGUSTO CAMARGO LAMPARELLI, NIPE/UNICAMP; EDEMAR MORO, UNOESTE; RAFAEL BATTISTI, UFG; MARCELO R. ALVES, UNOESTE; PAULO S. G. MAGALHÃES, NIPE/UNICAMP; GLEYCE KELLY DANTAS ARAÚJO FIGUEIREDO, FEAGRI/UNICAMP.	
Título: 	Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model.	
Ano de publicação: 	2022	
Fonte/Imprenta: 	Sustainability, v. 14, n. 6, p. 1-24, Mar. 2022.	
DOI: 	https://doi.org/10.3390/su14063517	
Idioma: 	Inglês	
Notas: 	Article 3517.	
Conteúdo: 	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.	
Palavras-Chave: 	Biogeochemical model; Integrated Crop-Livestock Systems; Manejo de pastagens; Mixed pasture; Modelo biogeoquímico; Pastagem tropical; Sistemas Integrados Lavoura-Pecuária; Tropical pasture.	
Thesagro: 	Pastagem Mista; Soja; Solo Arenoso.	
Thesaurus Nal: 	Sandy soils; Soybeans.	
Categoria do assunto: 	--	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/232632/1/AP-Intense-Pasture-2022.pdf	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (21180-1) - UPC - AP - DD -  -  -  - DIS