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Registro Completo |
Biblioteca(s): |
Embrapa Meio Ambiente. |
Data corrente: |
07/03/2015 |
Data da última atualização: |
08/03/2018 |
Tipo da produção científica: |
Resumo em Anais de Congresso |
Autoria: |
HOYOS, H. A. V.; MELO, I. S. de. |
Afiliação: |
HaroldAlexander Vargas Hoyos, ESALQ-USP; ITAMAR SOARES DE MELO, CNPMA. |
Título: |
Actinomycetes isolated from soil's Brazilian ecosystems: potential agents of biological control of Sclerotinia sclerotiorum in soybean (Glycine max l. Merrill). |
Ano de publicação: |
2014 |
Fonte/Imprenta: |
Hechos Microbiológicos, v. 5, n. 2, p. 101, 2014. Suplemento. Edição das Memorias do 22º Congreso Latinoamericano de Microbiologia e 4º Congreso Colombiano de Microbiologia, Cartagena, 2014. Ref. TLP-185. |
Idioma: |
Inglês |
Thesagro: |
Controle biológico; Sclerotinia Sclerotiorum; Soja. |
Thesaurus Nal: |
Actinomycetales. |
Categoria do assunto: |
V Taxonomia de Organismos |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/120327/1/2014RA-098.pdf
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Marc: |
LEADER 00747nam a2200157 a 4500 001 2010907 005 2018-03-08 008 2014 bl uuuu u00u1 u #d 100 1 $aHOYOS, H. A. V. 245 $aActinomycetes isolated from soil's Brazilian ecosystems$bpotential agents of biological control of Sclerotinia sclerotiorum in soybean (Glycine max l. Merrill).$h[electronic resource] 260 $aHechos Microbiológicos, v. 5, n. 2, p. 101, 2014. Suplemento. Edição das Memorias do 22º Congreso Latinoamericano de Microbiologia e 4º Congreso Colombiano de Microbiologia, Cartagena, 2014. Ref. TLP-185.$c2014 650 $aActinomycetales 650 $aControle biológico 650 $aSclerotinia Sclerotiorum 650 $aSoja 700 1 $aMELO, I. S. de
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Embrapa Meio Ambiente (CNPMA) |
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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 |
Circulação/Nível: |
A - 1 |
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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