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| Registros recuperados : 7.126 | |
| 272. |  | FERREIRA, M. E.; RANGEL, P. H. N. Aporte biotecnológico ao pré-melhoramento vegetal. In: LOPES, M. A.; FÁVERO, A. P.; FERREIRA, M. A. J. da F.; FALEIRO, F. G.; FOLLE, S. M.; GUIMARÃES, E. P. (Ed.). Pré-melhoramento de plantas: estado da arte e experiências de sucesso. Brasília, DF: Embrapa Informação tecnológica: Embrapa Recursos Genéticos e Biotecnologia; Planaltina, DF: Embrapa Cerrados, 2011. p. 59-84.| Biblioteca(s): Embrapa Arroz e Feijão; Embrapa Recursos Genéticos e Biotecnologia. |
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| 274. | | BRONDANI, C.; BORBA, T. C. de O.; RANGEL, P. H. N.; RANGEL, P. N.; MENDONÇA, J. A.; CRUZEIRO, G. A. V.; BRONDANI, R. P. V. Pré-melhoramento do arroz. In: LOPES, M. A.; FÁVERO, A. P.; FERREIRA, M. A. J. da F.; FALEIRO, F. G.; FOLLE, S. M.; GUIMARÃES, E. P. (Ed.). Pré-melhoramento de plantas: estado da arte e experiências de sucesso. Brasília, DF: Embrapa Informação tecnológica: Embrapa Recursos Genéticos e Biotecnologia; Planaltina, DF: Embrapa Cerrados, 2011. p. 293-316.| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 279. | | MELO, L. C.; PEREIRA, H. S.; FARIA, L. C. de; AGUIAR, M. S. de; COSTA, J. G. C. da; WENDLAND, A.; CABRERA DIAZ, J. L.; CARVALHO, H. W. L. de; COSTA, A. F. da; ALMEIDA, V. M. de; MELO, C. L. P. de; ITO, M. A.; MAGALDI, M. C. de S.; SOUZA, N. P. de; SOUZA, T. L. P. O. de. BRS FC104: super-early carioca seeded common bean cultivar with high yield potential. Crop Breeding and Applied Biotechnology, v. 19, n. 4, p. 471-475, out./dez. 2019. Cultivar release.| Biblioteca(s): Embrapa Arroz e Feijão; Embrapa Soja. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Amazônia Ocidental. Para informações adicionais entre em contato com cpaa.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Ocidental; Embrapa Florestas. |
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Data corrente: |
27/09/2018 |
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Data da última atualização: |
18/01/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
BASTIN, J. F.; RUTISHAUSER, E.; KELLNER, J. R.; SAATCHI, S.; PÉLISSIER, R.; HÉRAULT, B.; SLIK, F.; BOGAERT, J.; DE CANNIÈRE, C.; MARSHALL, A. R.; POULSEN, J.; ALVAREZ-LOYAYZA, P.; ANDRADE, A.; ANGBONGA-BASIA, A.; ARAUJO-MURAKAMI, A.; ARROYO, L.; AYYAPPAN, N.; AZEVEDO, C. P. de; BANKI, O.; BARBIER, N.; BARROSO, J. G.; BEECKMAN, H.; BITARIHO, R.; BOECKX, P.; BOEHNING-GAESE, K.; BRANDÃO, H.; BREARLEY, F. Q.; HOCKEMBA, M. B. N.; BRIENEN, R.; CAMARGO, J. L. C.; CAMPOS-ARCEIZ, A.; CASSART, B.; CHAVE, J.; CHAZDON, R.; CHUYONG, G.; CLARK, D. B.; CLARK, C. J.; CONDIT, R.; CORONADO, E. N. H.; DAVIDAR, P.; HAULLEVILLE, T. de; DESCROIX, L.; DOUCET, J-L.; DOURDAIN, A.; DROISSART, V.; DUNCAN, T.; ESPEJO. J. S.; ESPINOSA, S.; FARWIG, N.; FAYOLLE, A.; FELDPAUSCH, T. R.; FERRAZ, A.; FLETCHER, C.; GAJAPERSAD, K.; GILLET, J-F.; AMARAL, I. L. do; GONMADJE, C.; GROGAN, J.; HARRIS, D.; HERZOG, S. K.; HOMEIER, J.; HUBAU, W.; HUBBELL, S. P.; HUFKENS, K.; HURTADO, J.; KAMDEM, N. G.; KEARSLEY, E.; KENFACK, D.; KESSLER, M.; LABRIÈRE, N.; LAUMONIER, Y.; LAURANCE, S.; LAURANCE, W. F.; LEWIS, S. L.; LIBALAH, M. B.; LIGOT, G.; LLOYD, J.; LOVEJOY, T. E.; MALHI, Y.; MARIMON, B. S.; JUNIOR, B. H. M.; MARTIN, E. H.; MATIUS, P.; MEYER, V.; BAUTISTA, C. M.; MONTEAGUDO-MENDOZA, A.; MTUI, A.; NEILL, D.; GUTIERREZ, G. A. P.; PARDO, G.; PARREN, M.; PARTHASARATHY, N.; PHILLIPS, O. L.; PITMAN, N. C. A.; PLOTON, P.; PONETTE, Q.; RAMESH, B. R.; RAZAFIMAHAIMODISON, J-C.; RÉJOU-MÉCHAIN, M.; ROLIM, S. G.; SALTOS, H. R.; ROSSI, L. M. B.; SPIRONELLO, W. R.; ROVERO, F.; SANER, P.; SASAKI, D.; SCHULZE, M.; SILVEIRA, M.; SINGH, J.; SIST, P.; SONKE, B.; SOTO, J. D.; SOUZA, C. R. de; STROPP, J.; SULLIVAN, M. J. P.; SWANEPOEL, B.; STEEGE, H. ter.; TERBORGH, J.; TEXIER, N.; TOMA, T.; VALENCIA, R.; VALENZUELA, L.; FERREIRA, L. V.; VALVERDE, F. C.; ANDEL, T. R. van.; VASQUE, R.; VERBEECK, H.; VIVEK, P.; VLEMINCKX, J.; VOS, V. A.; WAGNER, F. H.; WARSUDI, P. P.; WORTEL, V.; ZAGT, R. J.; ZEBAZE, D. |
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Afiliação: |
Jean-François Bastin; Ervan Rutishauser; James R. Kellner; Sassan Saatchi; Raphael Pélissier; Bruno Hérault; Ferry Slik; Jan Bogaert; Charles De Cannière; Andrew R. Marshall; John Poulsen; Patricia Alvarez-Loyayza; Ana Andrade; Albert Angbonga-Basia; Alejandro Araujo-Murakami; Luzmila Arroyo; Narayanan Ayyappan; CELSO PAULO DE AZEVEDO, CPAA; Olaf Banki; Nicolas Barbier; Jorcely G. Barroso; Hans Beeckman; Robert Bitariho; Pascal Boeckx; Katrin Boehning-Gaese; Hilandia Brandão; Francis Q. Brearley; Mireille Breuer Ndoundou Hockemba; Roel Brienen; Jose Luis C. Camargo; Ahimsa Campos-Arceiz; Benoit Cassart; Jérôme Chave; Robin Chazdon; Georges Chuyong; David B. Clark; Connie J. Clark; Richard Condit; Euridice N. Honorio Coronado; Priya Davidar; Thalès de Haulleville; Laurent Descroix; Jean?Louis Doucet; Aurelie Dourdain; Vincent Droissart; Thomas Duncan; Javier Silva Espejo; Santiago Espinosa; Nina Farwig; Adeline Fayolle; Ted R. Feldpausch; Antonio Ferraz; Christine Fletcher; Krisna Gajapersad; Jean-François Gillet; Iêda Leão do Amaral; Christelle Gonmadje; James Grogan; David Harris; Sebastian K. Herzog; Jürgen Homeier; Wannes Hubau; Stephen P. Hubbell; Koen Hufkens; Johanna Hurtado; Narcisse G. Kamdem; Elizabeth Kearsley; David Kenfack; Michael Kessler; Nicolas Labrière; Yves Laumonier; Susan Laurance; William F. Laurance; Simon L. Lewis; Moses B. Libalah; Gauthier Ligot; Jon Lloyd; Thomas E. Lovejoy; Yadvinder Malhi; Beatriz S. Marimon; Ben Hur Marimon Junior; Emmanuel H. Martin; Paulus Matius; Victoria Meyer; Casimero Mendoza Bautista; Abel Monteagudo-Mendoza; Arafat Mtui; David Neill; Germaine Alexander Parada Gutierrez; Guido Pardo; Marc Parren; N. Parthasarathy; Oliver L. Phillips; Nigel C. A. Pitman; Pierre Ploton; Quentin Ponette; B. R. Ramesh; Jean-Claude Razafimahaimodison; Maxime Réjou-Méchain; Samir Gonçalves Rolim; Hugo Romero Saltos; LUIZ MARCELO BRUM ROSSI, CNPF; Wilson Roberto Spironello; Francesco Rovero; Philippe Saner; Denise Sasaki; Mark Schulze; Marcos Silveira; James Singh; Plinio Sist; Bonaventure Sonke; J. Daniel Soto; CINTIA RODRIGUES DE SOUZA, CPAA; Juliana Stropp; Martin J. P. Sullivan; Ben Swanepoel; Hans ter Steege; John Terborgh; Nicolas Texier; Takeshi Toma; Renato Valencia; Luis Valenzuela; Leandro Valle Ferreira; Fernando Cornejo Valverde; Tinde R. Van Andel; Rodolfo Vasque; Hans Verbeeck; Pandi Vivek; Jason Vleminckx; Vincent A. Vos; Fabien H. Wagner; Papi Puspa Warsudi; Verginia Wortel; Roderick J. Zagt; Donatien Zebaze. |
|
Título: |
Pan-tropical prediction of forest structure from the largest trees. |
|
Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Global Ecology and Biogeography, v. 27, n. 11, p. 1366-1383, Nov. 2018. |
|
DOI: |
10.1111/geb.12803 |
|
Idioma: |
Inglês |
|
Conteúdo: |
Abstract
Aim: Large tropical trees form the interface between ground and airborne observa?
tions, offering a unique opportunity to capture forest properties remotely and to inves?
tigate their variations on broad scales. However, despite rapid development of metrics
to characterize the forest canopy from remotely sensed data, a gap remains between
aerial and field inventories. To close this gap, we propose a new pan?tropical model to
predict plot?level forest structure properties and biomass from only the largest trees.
Location: Pan?tropical.
Time period: Early 21st century.
Major taxa studied: Woody plants.
Methods: Using a dataset of 867 plots distributed among 118 sites across the tropics,
we tested the prediction of the quadratic mean diameter, basal area, Lorey’s height,
community wood density and aboveground biomass (AGB) from the ith largest trees.
Results: Measuring the largest trees in tropical forests enables unbiased predictions of
plot? and site?level forest structure. The 20 largest trees per hectare predicted quad?
ratic mean diameter, basal area, Lorey’s height, community wood density and AGB
with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error
in biomass prediction is driven by differences in the proportion of total biomass held
in medium?sized trees (50–70 cm diameter at breast height), which shows some conti?
nental dependency, with American tropical forests presenting the highest proportion
of total biomass in these intermediate?diameter classes relative to other continents.
Main conclusions: Our approach provides new information on tropical forest struc?
ture and can be used to generate accurate field estimates of tropical forest carbon
stocks to support the calibration and validation of current and forthcoming space
missions. It will reduce the cost of field inventories and contribute to scientific under?
standing of tropical forest ecosystems and response to climate change. MenosAbstract
Aim: Large tropical trees form the interface between ground and airborne observa?
tions, offering a unique opportunity to capture forest properties remotely and to inves?
tigate their variations on broad scales. However, despite rapid development of metrics
to characterize the forest canopy from remotely sensed data, a gap remains between
aerial and field inventories. To close this gap, we propose a new pan?tropical model to
predict plot?level forest structure properties and biomass from only the largest trees.
Location: Pan?tropical.
Time period: Early 21st century.
Major taxa studied: Woody plants.
Methods: Using a dataset of 867 plots distributed among 118 sites across the tropics,
we tested the prediction of the quadratic mean diameter, basal area, Lorey’s height,
community wood density and aboveground biomass (AGB) from the ith largest trees.
Results: Measuring the largest trees in tropical forests enables unbiased predictions of
plot? and site?level forest structure. The 20 largest trees per hectare predicted quad?
ratic mean diameter, basal area, Lorey’s height, community wood density and AGB
with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error
in biomass prediction is driven by differences in the proportion of total biomass held
in medium?sized trees (50–70 cm diameter at breast height), which shows some conti?
nental dependency, with American tropical forests presenting the highest proportion
of total biomass in these int... Mostrar Tudo |
|
Palavras-Chave: |
Tropical forest ecology. |
|
Thesaurus NAL: |
Carbon; Climate change. |
|
Categoria do assunto: |
--
K Ciência Florestal e Produtos de Origem Vegetal |
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Marc: |
LEADER 06464naa a2201777 a 4500
001 2096481
005 2019-01-18
008 2018 bl uuuu u00u1 u #d
024 7 $a10.1111/geb.12803$2DOI
100 1 $aBASTIN, J. F.
245 $aPan-tropical prediction of forest structure from the largest trees.$h[electronic resource]
260 $c2018
520 $aAbstract Aim: Large tropical trees form the interface between ground and airborne observa? tions, offering a unique opportunity to capture forest properties remotely and to inves? tigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan?tropical model to predict plot?level forest structure properties and biomass from only the largest trees. Location: Pan?tropical. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey’s height, community wood density and aboveground biomass (AGB) from the ith largest trees. Results: Measuring the largest trees in tropical forests enables unbiased predictions of plot? and site?level forest structure. The 20 largest trees per hectare predicted quad? ratic mean diameter, basal area, Lorey’s height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium?sized trees (50–70 cm diameter at breast height), which shows some conti? nental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate?diameter classes relative to other continents. Main conclusions: Our approach provides new information on tropical forest struc? ture and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific under? standing of tropical forest ecosystems and response to climate change.
650 $aCarbon
650 $aClimate change
653 $aTropical forest ecology
700 1 $aRUTISHAUSER, E.
700 1 $aKELLNER, J. R.
700 1 $aSAATCHI, S.
700 1 $aPÉLISSIER, R.
700 1 $aHÉRAULT, B.
700 1 $aSLIK, F.
700 1 $aBOGAERT, J.
700 1 $aDE CANNIÈRE, C.
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700 1 $aBANKI, O.
700 1 $aBARBIER, N.
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700 1 $aCORONADO, E. N. H.
700 1 $aDAVIDAR, P.
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700 1 $aDESCROIX, L.
700 1 $aDOUCET, J-L.
700 1 $aDOURDAIN, A.
700 1 $aDROISSART, V.
700 1 $aDUNCAN, T.
700 1 $aESPEJO. J. S.
700 1 $aESPINOSA, S.
700 1 $aFARWIG, N.
700 1 $aFAYOLLE, A.
700 1 $aFELDPAUSCH, T. R.
700 1 $aFERRAZ, A.
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700 1 $aLLOYD, J.
700 1 $aLOVEJOY, T. E.
700 1 $aMALHI, Y.
700 1 $aMARIMON, B. S.
700 1 $aJUNIOR, B. H. M.
700 1 $aMARTIN, E. H.
700 1 $aMATIUS, P.
700 1 $aMEYER, V.
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700 1 $aMONTEAGUDO-MENDOZA, A.
700 1 $aMTUI, A.
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700 1 $aPLOTON, P.
700 1 $aPONETTE, Q.
700 1 $aRAMESH, B. R.
700 1 $aRAZAFIMAHAIMODISON, J-C.
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700 1 $aROLIM, S. G.
700 1 $aSALTOS, H. R.
700 1 $aROSSI, L. M. B.
700 1 $aSPIRONELLO, W. R.
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700 1 $aSANER, P.
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700 1 $aVALENZUELA, L.
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700 1 $aVALVERDE, F. C.
700 1 $aANDEL, T. R. van.
700 1 $aVASQUE, R.
700 1 $aVERBEECK, H.
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700 1 $aZAGT, R. J.
700 1 $aZEBAZE, D.
773 $tGlobal Ecology and Biogeography$gv. 27, n. 11, p. 1366-1383, Nov. 2018.
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