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 | Acesso ao texto completo restrito à biblioteca da Embrapa Clima Temperado. Para informações adicionais entre em contato com cpact.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Clima Temperado; Embrapa Meio Ambiente. |
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Data corrente: |
01/08/2019 |
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Data da última atualização: |
04/12/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
ATTIA, A.; NOUVELLON, Y.; CUADRA, S. V.; CABRAL, O. M. R.; LACLAU, J. P.; GUILLEMOT, J.; CAMPOE, O.; STAPE, J.; GALDOS, M.; LAMPARELLI, R.; MARIE, G. L. |
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Afiliação: |
Ahmed Attia; Yann Nouvellon; SANTIAGO VIANNA CUADRA, CPACT; OSVALDO MACHADO RODRIGUES CABRAL, CNPMA; Jean-Paul Laclau; Joannès Guillemot; Otavio Campoe; José-Luiz Stape; Marcelo Galdos; Rubens Lamparelli; Guerric le Maire. |
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Título: |
Modelling carbon and water balance of Eucalyptus plantations at regional scale: Effect of climate, soil and genotypes. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Forest Ecology and Management, v. 449, p. 1-13, 2019. Article 117460. |
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DOI: |
https://doi.org/10.1016/j.foreco.2019.117460 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract:Carbon and water budgets of forest plantations are spatially and temporally variable and hardly empirically predictable. We applied G’DAY, a process-based ecophysiological model, to simulate carbon and water budgets and stem biomass production of Eucalyptus plantations in São Paulo State, Brazil. Our main objective was to assess the drivers of spatial variability in plantation production at regional scale. We followed a multi-site calibration approach: the model was first parameterized using a detailed experimental dataset. Then a subset of the parameters were re-calibrated on two independent experimental datasets. An additional genotype-specific calibration of a subset of parameters was performed. Model predictions of key carbon-related variables (e.g., gross primary production, leaf area index and stem biomass) and key water-related variables (e.g., plant available water and evapotranspiration) agreed closely with measurements. Application of the model across ca. 27,500?ha of forests planted with different genotypes of Eucalyptus indicated that the model was able to capture 89% of stem biomass variability measured at different ages. Several factors controlling Eucalyptus production variability in time and space were grouped in three categories: soil, climate, and the planted genotype. Modelling analysis showed that calibrating the model for genotypic differences was critical for stem biomass prediction at regional scale, but that taking into account climate and soil variability significantly improved the results. We conclude that application of process-based models at regional scale can be used for accurate predictions of Eucalyptus production, provided that an accurate calibration of the model for key genotype-specific parameters is conducted. MenosAbstract:Carbon and water budgets of forest plantations are spatially and temporally variable and hardly empirically predictable. We applied G’DAY, a process-based ecophysiological model, to simulate carbon and water budgets and stem biomass production of Eucalyptus plantations in São Paulo State, Brazil. Our main objective was to assess the drivers of spatial variability in plantation production at regional scale. We followed a multi-site calibration approach: the model was first parameterized using a detailed experimental dataset. Then a subset of the parameters were re-calibrated on two independent experimental datasets. An additional genotype-specific calibration of a subset of parameters was performed. Model predictions of key carbon-related variables (e.g., gross primary production, leaf area index and stem biomass) and key water-related variables (e.g., plant available water and evapotranspiration) agreed closely with measurements. Application of the model across ca. 27,500?ha of forests planted with different genotypes of Eucalyptus indicated that the model was able to capture 89% of stem biomass variability measured at different ages. Several factors controlling Eucalyptus production variability in time and space were grouped in three categories: soil, climate, and the planted genotype. Modelling analysis showed that calibrating the model for genotypic differences was critical for stem biomass prediction at regional scale, but that taking into account climate and so... Mostrar Tudo |
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Palavras-Chave: |
Ecophysiological model; Eucalyptus plantations; G'DAY; Optimization; Productivity. |
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Thesagro: |
Balanço Hídrico; Eucalipto; Modelo de Simulação. |
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Categoria do assunto: |
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P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 02833naa a2200349 a 4500
001 2111038
005 2019-12-04
008 2019 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.foreco.2019.117460$2DOI
100 1 $aATTIA, A.
245 $aModelling carbon and water balance of Eucalyptus plantations at regional scale$bEffect of climate, soil and genotypes.$h[electronic resource]
260 $c2019
520 $aAbstract:Carbon and water budgets of forest plantations are spatially and temporally variable and hardly empirically predictable. We applied G’DAY, a process-based ecophysiological model, to simulate carbon and water budgets and stem biomass production of Eucalyptus plantations in São Paulo State, Brazil. Our main objective was to assess the drivers of spatial variability in plantation production at regional scale. We followed a multi-site calibration approach: the model was first parameterized using a detailed experimental dataset. Then a subset of the parameters were re-calibrated on two independent experimental datasets. An additional genotype-specific calibration of a subset of parameters was performed. Model predictions of key carbon-related variables (e.g., gross primary production, leaf area index and stem biomass) and key water-related variables (e.g., plant available water and evapotranspiration) agreed closely with measurements. Application of the model across ca. 27,500?ha of forests planted with different genotypes of Eucalyptus indicated that the model was able to capture 89% of stem biomass variability measured at different ages. Several factors controlling Eucalyptus production variability in time and space were grouped in three categories: soil, climate, and the planted genotype. Modelling analysis showed that calibrating the model for genotypic differences was critical for stem biomass prediction at regional scale, but that taking into account climate and soil variability significantly improved the results. We conclude that application of process-based models at regional scale can be used for accurate predictions of Eucalyptus production, provided that an accurate calibration of the model for key genotype-specific parameters is conducted.
650 $aBalanço Hídrico
650 $aEucalipto
650 $aModelo de Simulação
653 $aEcophysiological model
653 $aEucalyptus plantations
653 $aG'DAY
653 $aOptimization
653 $aProductivity
700 1 $aNOUVELLON, Y.
700 1 $aCUADRA, S. V.
700 1 $aCABRAL, O. M. R.
700 1 $aLACLAU, J. P.
700 1 $aGUILLEMOT, J.
700 1 $aCAMPOE, O.
700 1 $aSTAPE, J.
700 1 $aGALDOS, M.
700 1 $aLAMPARELLI, R.
700 1 $aMARIE, G. L.
773 $tForest Ecology and Management$gv. 449, p. 1-13, 2019. Article 117460.
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Registro original: |
Embrapa Clima Temperado (CPACT) |
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Origem |
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Cutter |
Registro |
Volume |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Cerrados; Embrapa Meio-Norte. |
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Data corrente: |
10/04/2023 |
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Data da última atualização: |
10/04/2023 |
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Tipo da produção científica: |
Boletim de Pesquisa e Desenvolvimento |
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Autoria: |
BASTOS, E. A.; ANDRADE JUNIOR, A. S. de; SALES, R. A. de; BEZERRA, R. L. S.; CUADRA, S. V.; SILVA, F. A. M. da. |
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Afiliação: |
EDSON ALVES BASTOS, CPAMN; ADERSON SOARES DE ANDRADE JUNIOR, CPAMN; RAMON AMARO DE SALES, UNIVERSIDADE FEDERAL DE VIÇOSA, MG; RUAN LUÍS SANTANA BEZERRA, UNIVERSIDADE FEDERAL DO PIAUÍ; SANTIAGO VIANNA CUADRA, CNPTIA; FERNANDO ANTONIO MACENA DA SILVA, CPAC. |
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Título: |
Calibração do modelo CROPGRO-cowpea para simulação do crescimento e rendimento de grãos de feijão-caupi com e sem deficit hídrico. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Teresina: Embrapa Meio-Norte, 2023. |
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Páginas: |
24 p. |
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Série: |
(Embrapa Meio-Norte. Boletim de Pesquisa e Desenvolvimento, 149). |
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Idioma: |
Português |
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Conteúdo: |
O objetivo desta pesquisa foi calibrar o modelo CROPGRO-cowpea do DSSAT para possibilitar, futuramente, o desenvolvimento de uma metodologia técnico-científica para a elaboração de zoneamento agrícola de risco climático baseada em um índice de produtividade climática para a cultura do feijão-caupi. |
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Palavras-Chave: |
DSSAT; Feijão-caupi; Modelagem; Modeling; ZARC. |
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Thesagro: |
Modelo de Simulação; Vigna Unguiculata; Zoneamento Agrícola; Zoneamento Climático. |
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Thesaurus NAL: |
Agricultural zoning; Cowpeas; Zoning. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1153058/1/CalibracaoModeloCROPGROCowpeaSimulacaoCrescimentoRendimentoGraosBPD149.2023.pdf
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Marc: |
LEADER 01335nam a2200337 a 4500
001 2153058
005 2023-04-10
008 2023 bl uuuu u0uu1 u #d
100 1 $aBASTOS, E. A.
245 $aCalibração do modelo CROPGRO-cowpea para simulação do crescimento e rendimento de grãos de feijão-caupi com e sem deficit hídrico.$h[electronic resource]
260 $aTeresina: Embrapa Meio-Norte$c2023
300 $a24 p.
490 $a(Embrapa Meio-Norte. Boletim de Pesquisa e Desenvolvimento, 149).
520 $aO objetivo desta pesquisa foi calibrar o modelo CROPGRO-cowpea do DSSAT para possibilitar, futuramente, o desenvolvimento de uma metodologia técnico-científica para a elaboração de zoneamento agrícola de risco climático baseada em um índice de produtividade climática para a cultura do feijão-caupi.
650 $aAgricultural zoning
650 $aCowpeas
650 $aZoning
650 $aModelo de Simulação
650 $aVigna Unguiculata
650 $aZoneamento Agrícola
650 $aZoneamento Climático
653 $aDSSAT
653 $aFeijão-caupi
653 $aModelagem
653 $aModeling
653 $aZARC
700 1 $aANDRADE JUNIOR, A. S. de
700 1 $aSALES, R. A. de
700 1 $aBEZERRA, R. L. S.
700 1 $aCUADRA, S. V.
700 1 $aSILVA, F. A. M. da
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Embrapa Meio-Norte (CPAMN) |
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