| Texto completo | |
| Autor(es): Mostrar menos - |
Attia, Ahmed
[1]
;
Nouvellon, Yann
[2, 3, 4]
;
Cuadra, Santiago
[5]
;
Cabral, Osvaldo
[6]
;
Laclau, Jean-Paul
[2, 3, 4]
;
Guillemot, Joannes
[2, 3, 4]
;
Campoe, Otavio
[7, 8]
;
Stape, Jose-Luiz
[7]
;
Galdos, Marcelo
[9]
;
Lamparelli, Rubens
[1]
;
le Maire, Guerric
[3, 1, 4]
Número total de Autores: 11
|
| Afiliação do(s) autor(es): | [1] Univ Estadual Campinas, NIPE, BR-13083860 Campinas, SP - Brazil
[2] Univ Sao Paulo, ESALQ, BR-13418900 Piracicaba, SP - Brazil
[3] CIRAD, UMR ECO & SOLS, F-34398 Montpellier - France
[4] Univ Montpellier, CIRAD, Eco & Sols, INRA, IRD, SupAgro, Montpellier - France
[5] EMBRAPA CNPTIA, BR-13083886 Campinas, SP - Brazil
[6] Embrapa Meio Ambiente, BR-13820000 Jaguariuna, SP - Brazil
[7] UNESP FCA, BR-18610300 Botucatu, SP - Brazil
[8] Fed Univ Lavras UFLA, BR-37200000 Lavras, MG - Brazil
[9] Univ Leeds, Sch Earth & Environm, Inst Climate & Atmospher Sci, Leeds LS2 9JT, W Yorkshire - England
Número total de Afiliações: 9
|
| Tipo de documento: | Artigo Científico |
| Fonte: | FOREST ECOLOGY AND MANAGEMENT; v. 449, OCT 1 2019. |
| Citações Web of Science: | 0 |
| Resumo | |
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 Sao 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. (AU) | |
| Processo FAPESP: | 14/50715-9 - Characterizing and predicting biomass production in sugarcane and eucalyptus plantations in Brazil |
| Beneficiário: | Rubens Augusto Camargo Lamparelli |
| Modalidade de apoio: | Auxílio à Pesquisa - Parceria para Inovação Tecnológica - PITE |
| Processo FAPESP: | 17/00886-0 - Modelagem dos processos de balanço de carbono em plantios de eucalipto |
| Beneficiário: | Ahmed Mohamed Attia Mohamed |
| Modalidade de apoio: | Bolsas no Brasil - Pós-Doutorado |
| Processo FAPESP: | 12/06933-6 - Dinâmica espaço-temporal do carbono do solo e emissões de óxido nitroso na cultura da cana-de-açúcar no Brasil - convergência entre modelos específicos de espaço e tempo |
| Beneficiário: | Marcelo Valadares Galdos |
| Modalidade de apoio: | Auxílio à Pesquisa - Programa BIOEN - Jovens Pesquisadores |