Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model.

Detalhes bibliográficos
Autor(a) principal: SILVA, Y. F.
Data de Publicação: 2022
Outros Autores: 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.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1141004
https://doi.org/10.3390/su14063517
Resumo: 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.
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spelling Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model.Modelo biogeoquímicoPastagem tropicalSistemas Integrados Lavoura-PecuáriaManejo de pastagensMixed pastureBiogeochemical modelIntegrated Crop-Livestock SystemsTropical pasturePastagem MistaSojaSolo ArenosoSandy soilsSoybeansAbstract. 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.Article 3517.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.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.2022-03-17T18:00:45Z2022-03-17T18:00:45Z2022-03-172022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleSustainability, v. 14, n. 6, p. 1-24, Mar. 2022.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1141004https://doi.org/10.3390/su14063517enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2022-03-17T18:00:55Zoai:www.alice.cnptia.embrapa.br:doc/1141004Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542022-03-17T18:00:55Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model.
title Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model.
spellingShingle Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model.
SILVA, Y. F.
Modelo biogeoquímico
Pastagem tropical
Sistemas Integrados Lavoura-Pecuária
Manejo de pastagens
Mixed pasture
Biogeochemical model
Integrated Crop-Livestock Systems
Tropical pasture
Pastagem Mista
Soja
Solo Arenoso
Sandy soils
Soybeans
title_short Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model.
title_full Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model.
title_fullStr Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model.
title_full_unstemmed Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model.
title_sort Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model.
author SILVA, Y. F.
author_facet 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.
author_role author
author2 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.
author2_role author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv 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.
dc.contributor.author.fl_str_mv 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.
dc.subject.por.fl_str_mv Modelo biogeoquímico
Pastagem tropical
Sistemas Integrados Lavoura-Pecuária
Manejo de pastagens
Mixed pasture
Biogeochemical model
Integrated Crop-Livestock Systems
Tropical pasture
Pastagem Mista
Soja
Solo Arenoso
Sandy soils
Soybeans
topic Modelo biogeoquímico
Pastagem tropical
Sistemas Integrados Lavoura-Pecuária
Manejo de pastagens
Mixed pasture
Biogeochemical model
Integrated Crop-Livestock Systems
Tropical pasture
Pastagem Mista
Soja
Solo Arenoso
Sandy soils
Soybeans
description 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.
publishDate 2022
dc.date.none.fl_str_mv 2022-03-17T18:00:45Z
2022-03-17T18:00:45Z
2022-03-17
2022
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Sustainability, v. 14, n. 6, p. 1-24, Mar. 2022.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1141004
https://doi.org/10.3390/su14063517
identifier_str_mv Sustainability, v. 14, n. 6, p. 1-24, Mar. 2022.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1141004
https://doi.org/10.3390/su14063517
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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