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| Registros recuperados : 119 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
09/12/2019 |
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Data da última atualização: |
09/12/2019 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
ATTIA, A.; CUADRA, S. V.; NOUVELLON, Y.; GUILLEMOT, J.; CAMPOE, O. C.; CABRAL, O. M. R.; LACLAU, J.; GALDOS, M.; LAMPARELLI, R.; Le MAIRE, G. |
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Afiliação: |
A. ATTIA, Unicamp; SANTIAGO VIANNA CUADRA, CPACT; Y. NOUVELLON, UMR EcoSols (Univ Montpellier, Cirad, Inra, IRD, Montpellier SupAgro) CIRAD, ESALQ; J. GUILLEMOT, UMR EcoSols (Univ Montpellier, Cirad, Inra, IRD, Montpellier SupAgro) CIRAD, ESALQ; O. C. CAMPOE, UFSC, UNESP; OSVALDO MACHADO RODRIGUES CABRAL, CNPMA; J. LACLAU, UMR EcoSols (Univ Montpellier, Cirad, Inra, IRD, Montpellier SupAgro) CIRAD, ESALQ, UNESP; M. GALDOS, School of Earth and Environment, University of Leeds (ICAS); R. LAMPARELLI, Unicamp; G. Le MAIRE. |
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Título: |
Modelling eucalyptus biomass production at regional scale in Brazil. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
In: EUCALYPTUS 2018, Montpellier. Managing Eucalyptus plantation under global changes: abstracts book... Montpellier, France: CIRAD, 2018. |
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Páginas: |
p. 43. |
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Idioma: |
Português |
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Conteúdo: |
Among forest vegetation grown in Brazil, Eucalyptus is the most widely planted tropicalhardwood genus covering approximately 5.7 million ha for an average yield of 49 m3 ha-1 yr-1.Wide differences of biomass production were observed among neighboring stands representingchallenges to forestry companies to spatially estimate biomass yield in large plantation zones.The first objective of the present research was to modify the carbon allocation scheme in theprocess-based model Generic Decomposition And Yield Model (G?DAY), to better capture thespatial variability in growth rates of Eucalyptus as influenced by environmental constraints suchas water stress. The model was parametrized and tested using experimental and long termcommercial datasets in the state of S ?ao Paulo Brazil. Measured data included several variablesof carbon and water fluxes and carbon stock. The calibrated model produced accurate predictionof the carbon key variables such as leaf area index, stem biomass, and gross primary productionand water related variables such as plant available water and evapotranspiration. Simulating thespatial variability among commercial Eucalyptus stands at landscape scale showed reasonableprediction of plant height with r2 of 0.89 but lower level of accuracy for stem biomass. This couldpartially be attributed to spatial soil data differences used at regional scales which came fromthe Global Soil Dataset for Earth Systems Modeling dataset, at a resolution of 1 km. Testingthe soil data with the use of soil type map crossed with soil profile measurements is expectedto improve the soil information for higher accuracy of stem simulation at landscape to regionalscale. MenosAmong forest vegetation grown in Brazil, Eucalyptus is the most widely planted tropicalhardwood genus covering approximately 5.7 million ha for an average yield of 49 m3 ha-1 yr-1.Wide differences of biomass production were observed among neighboring stands representingchallenges to forestry companies to spatially estimate biomass yield in large plantation zones.The first objective of the present research was to modify the carbon allocation scheme in theprocess-based model Generic Decomposition And Yield Model (G?DAY), to better capture thespatial variability in growth rates of Eucalyptus as influenced by environmental constraints suchas water stress. The model was parametrized and tested using experimental and long termcommercial datasets in the state of S ?ao Paulo Brazil. Measured data included several variablesof carbon and water fluxes and carbon stock. The calibrated model produced accurate predictionof the carbon key variables such as leaf area index, stem biomass, and gross primary productionand water related variables such as plant available water and evapotranspiration. Simulating thespatial variability among commercial Eucalyptus stands at landscape scale showed reasonableprediction of plant height with r2 of 0.89 but lower level of accuracy for stem biomass. This couldpartially be attributed to spatial soil data differences used at regional scales which came fromthe Global Soil Dataset for Earth Systems Modeling dataset, at a resolution of 1 km. Testingthe soil d... Mostrar Tudo |
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Palavras-Chave: |
Ecophysiological Modelling; G’DAY; Regional Scale. |
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Thesagro: |
Biomassa; Eucalipto. |
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Thesaurus NAL: |
Biomass; Brazil; Eucalyptus. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/206504/1/RA-CabralOMR-Eucalyptus2018-Montpellier.pdf
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Marc: |
LEADER 02624nam a2200325 a 4500
001 2116380
005 2019-12-09
008 2019 bl uuuu u00u1 u #d
100 1 $aATTIA, A.
245 $aModelling eucalyptus biomass production at regional scale in Brazil.$h[electronic resource]
260 $aIn: EUCALYPTUS 2018, Montpellier. Managing Eucalyptus plantation under global changes: abstracts book... Montpellier, France: CIRAD$c2018
300 $ap. 43.
520 $aAmong forest vegetation grown in Brazil, Eucalyptus is the most widely planted tropicalhardwood genus covering approximately 5.7 million ha for an average yield of 49 m3 ha-1 yr-1.Wide differences of biomass production were observed among neighboring stands representingchallenges to forestry companies to spatially estimate biomass yield in large plantation zones.The first objective of the present research was to modify the carbon allocation scheme in theprocess-based model Generic Decomposition And Yield Model (G?DAY), to better capture thespatial variability in growth rates of Eucalyptus as influenced by environmental constraints suchas water stress. The model was parametrized and tested using experimental and long termcommercial datasets in the state of S ?ao Paulo Brazil. Measured data included several variablesof carbon and water fluxes and carbon stock. The calibrated model produced accurate predictionof the carbon key variables such as leaf area index, stem biomass, and gross primary productionand water related variables such as plant available water and evapotranspiration. Simulating thespatial variability among commercial Eucalyptus stands at landscape scale showed reasonableprediction of plant height with r2 of 0.89 but lower level of accuracy for stem biomass. This couldpartially be attributed to spatial soil data differences used at regional scales which came fromthe Global Soil Dataset for Earth Systems Modeling dataset, at a resolution of 1 km. Testingthe soil data with the use of soil type map crossed with soil profile measurements is expectedto improve the soil information for higher accuracy of stem simulation at landscape to regionalscale.
650 $aBiomass
650 $aBrazil
650 $aEucalyptus
650 $aBiomassa
650 $aEucalipto
653 $aEcophysiological Modelling
653 $aG’DAY
653 $aRegional Scale
700 1 $aCUADRA, S. V.
700 1 $aNOUVELLON, Y.
700 1 $aGUILLEMOT, J.
700 1 $aCAMPOE, O. C.
700 1 $aCABRAL, O. M. R.
700 1 $aLACLAU, J.
700 1 $aGALDOS, M.
700 1 $aLAMPARELLI, R.
700 1 $aLe MAIRE, G.
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Embrapa Meio Ambiente (CNPMA) |
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