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 | Acesso ao texto completo restrito à biblioteca da Embrapa Amazônia Oriental. Para informações adicionais entre em contato com cpatu.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
02/01/2017 |
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Data da última atualização: |
20/05/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
RESTREPO-COUPE, N.; LEVINE, N. M.; CHRISTOFFERSEN, B. O.; ALBERT, L. P.; WU, J.; COSTA, M. H.; GALBRAITH, D.; IMBUZEIRO, H.; MARTINS, G.; ARAUJO, A. C. da; MALHI, Y. S.; ZENG, X.; MOORCROFT, P.; SALESKA, S. R. |
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Afiliação: |
NATALIA RESTREPO-COUPE, University of Technology Sydney / University of Arizona; NAOMI M. LEVINE, University of Southern California / Harvard University; BRADLEY O. CHRISTOFFERSEN, University of Arizona / Los Alamos National Laboratory; LOREN P. ALBERT, University of Arizona; JIN WU, University of Arizona / Brookhaven National Lab; MARCOS H. COSTA, UFV; DAVID GALBRAITH, University of Leeds; HEWLLEY IMBUZEIRO, UFV; GIORDANE MARTINS, INPA; ALESSANDRO CARIOCA DE ARAUJO, CPATU; YADVINDER S. MALHI, University of Oxford; XUBIN ZENG, University of Arizona; PAUL MOORCROFT, Harvard University; SCOTT R. SALESKA, University of Arizona. |
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Título: |
Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Global Change Biology, v. 23, n. 1, p. 191-208, Jan. 2017. |
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DOI: |
10.1111/gcb.13442 |
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Idioma: |
Inglês |
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Conteúdo: |
To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of other fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, ?soil water stress? and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. Correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments. MenosTo predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of other fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, ?soil water stress? and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consis... Mostrar Tudo |
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Palavras-Chave: |
Carbon dynamics; Dinâmica do carbono; Dynamic global vegetation models; Ecosystem–climate interactions; Florestas tropicais; Modelos dinâmicos de vegetação; Sazonalidade; Seasonality; Tropical forests phenology. |
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Thesagro: |
Fenologia. |
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Thesaurus Nal: |
Amazonia; eddy covariance. |
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Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
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Marc: |
null
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Registro original: |
Embrapa Amazônia Oriental (CPATU) |
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
23/05/2022 |
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Data da última atualização: |
23/05/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 2 |
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Autoria: |
SANTOS, L. M. dos; FERRAZ, G. A. e S.; MARIN, D. B.; CARVALHO, M. A. de F.; DIAS, J. E. L.; ALECRIM, A. de O.; SILVA, M. de L. O. e. |
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Afiliação: |
LUANA MENDES DOS SANTOS, UFLA; GABRIEL ARAÚJO E SILVA FERRAZ, UFLA; DIEGO BEDIN MARIN, UFLA; MILENE ALVES DE FIGUEIREDO CARVALHO, CNPCa; JESSICA ELLEN LIMA DIAS, HUNGARIAN UNIVERSITY OF AGRICULTURE AND LIFE SCIENCES; ADEMILSON DE OLIVEIRA ALECRIM, UFLA; MIRIAN DE LOURDES OLIVEIRA E SILVA, UFLA. |
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Título: |
Vegetation indices applied to suborbital multispectral images of healthy coffee and coffee infested with coffee leaf miner. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
AgriEngineering, v. 4, n. 1, p. 311-319, Mar. 2022. |
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Idioma: |
Inglês |
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Conteúdo: |
The coffee leaf miner (Leucoptera coffeella) is a primary pest for coffee plants. The attack of this pest reduces the photosynthetic area of the leaves due to necrosis, causing premature leaf falling, decreasing the yield and the lifespan of the plant. Therefore, this study aims to analyze vegetation indices (VI) from images of healthy coffee leaves and those infested by coffee leaf miner, obtained using a multispectral camera, mainly to differentiate and detect infested areas. The study was conducted in two distinct locations: At a farm, where the camera was coupled to a remotely piloted aircraft (RPA) flying at a 3 m altitude from the soil surface; and the second location, in a greenhouse, where the images were obtained manually at a 0.5 m altitude from the support of the plant vessels, in which only healthy plants were located. For the image processing, arithmetic operations with the spectral bands were calculated using the ?Raster Calculator? obtaining the indices NormNIR, Normalized Difference Vegetation Index (NDVI), Green-Red NDVI (GRNDVI), and Green NDVI (GNDVI), the values of which on average for healthy leaves were: 0.66; 0.64; 0.32, and 0.55 and for infested leaves: 0.53; 0.41; 0.06, and 0.37 respectively. The analysis concluded that healthy leaves presented higher values of VIs when compared to infested leaves. The index GRNDVI was the one that better differentiated infested leaves from the healthy ones. |
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Palavras-Chave: |
Agricultura digital. |
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Thesagro: |
Agricultura de Precisão; Coffea Arábica; Sensoriamento Remoto. |
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Thesaurus NAL: |
Precision agriculture; Remote sensing; Unmanned aerial vehicles. |
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Categoria do assunto: |
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URL: |
https://www.alice.cnptia.embrapa.br/alice/bitstream/doc/1143380/1/Vegetation-Indices-Applied-2022.pdf
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Marc: |
null
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Registro original: |
Embrapa Café (CNPCa) |
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