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Registro Completo |
Biblioteca(s): |
Embrapa Clima Temperado; Embrapa Meio Ambiente. |
Data corrente: |
01/08/2019 |
Data da última atualização: |
04/12/2019 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
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. |
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. |
Título: |
Modelling carbon and water balance of Eucalyptus plantations at regional scale: Effect of climate, soil and genotypes. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
Forest Ecology and Management, v. 449, p. 1-13, 2019. Article 117460. |
DOI: |
https://doi.org/10.1016/j.foreco.2019.117460 |
Idioma: |
Inglês |
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 |
Palavras-Chave: |
Ecophysiological model; Eucalyptus plantations; G'DAY; Optimization; Productivity. |
Thesagro: |
Balanço Hídrico; Eucalipto; Modelo de Simulação. |
Categoria do assunto: |
-- P Recursos Naturais, Ciências Ambientais e da Terra |
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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Embrapa Clima Temperado (CPACT) |
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Biblioteca(s): |
Embrapa Milho e Sorgo. |
Data corrente: |
07/11/2019 |
Data da última atualização: |
06/07/2020 |
Tipo da produção científica: |
Comunicado Técnico/Recomendações Técnicas |
Autoria: |
VIANA, J. H. M.; OLIVEIRA, M. F. de. |
Afiliação: |
JOAO HERBERT MOREIRA VIANA, CNPMS; MAURILIO FERNANDES DE OLIVEIRA, CNPMS. |
Título: |
Variabilidade espacial dos teores de frações granulométricas em área sob experimento de manejo de solo de longa duração. |
Ano de publicação: |
2019 |
Fonte/Imprenta: |
Sete Lagoas: Embrapa Milho e Sorgo, 2019. |
Páginas: |
25 |
Série: |
(Embrapa Milho e Sorgo. Comunicado Técnico, 239). |
Idioma: |
Português |
Palavras-Chave: |
Distribuição espacial; Teor de argila. |
Thesagro: |
Argila; Solo. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/204390/1/Cot-239.pdf
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Marc: |
LEADER 00613nam a2200181 a 4500 001 2114035 005 2020-07-06 008 2019 bl uuuu u0uu1 u #d 100 1 $aVIANA, J. H. M. 245 $aVariabilidade espacial dos teores de frações granulométricas em área sob experimento de manejo de solo de longa duração.$h[electronic resource] 260 $aSete Lagoas: Embrapa Milho e Sorgo$c2019 300 $a25 490 $a(Embrapa Milho e Sorgo. Comunicado Técnico, 239). 650 $aArgila 650 $aSolo 653 $aDistribuição espacial 653 $aTeor de argila 700 1 $aOLIVEIRA, M. F. de
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