Data/hora: 23/09/2024 02:43:02

Biblioteca(s): 	Embrapa Meio Ambiente.	
Data corrente: 	09/12/2019	
Data da última atualização: 	09/12/2019	
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.	
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.	
Título: 	Modelling eucalyptus biomass production at regional scale in Brazil.	
Ano de publicação: 	2019	
Fonte/Imprenta: 	In: EUCALYPTUS 2018, Montpellier. Managing Eucalyptus plantation under global changes: abstracts book... Montpellier, France: CIRAD, 2018.	
Páginas: 	p. 43.	
Idioma: 	Português	
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.	
Palavras-Chave: 	Ecophysiological Modelling; G’DAY; Regional Scale.	
Thesagro: 	Biomassa; Eucalipto.	
Thesaurus Nal: 	Biomass; Brazil; Eucalyptus.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/206504/1/RA-CabralOMR-Eucalyptus2018-Montpellier.pdf	
Registro original: 	Embrapa Meio Ambiente (CNPMA)	
Exemplares: 	CNPMA - (16586-1) - UPC - RA - DD -  -  -  - DIS