|
|
![](/consulta/web/img/deny.png) | Acesso ao texto completo restrito à biblioteca da Embrapa Solos. Para informações adicionais entre em contato com cnps.biblioteca@embrapa.br. |
Registro Completo |
Biblioteca(s): |
Embrapa Solos. |
Data corrente: |
13/10/2008 |
Data da última atualização: |
11/04/2024 |
Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
Autoria: |
MENDONÇA-SANTOS, M. de L.; SANTOS, H. G. dos; DART, R. de O.; PARES, J. G. |
Afiliação: |
MARIA DE LOURDES MENDONÇA SANTOS BREFIN, CNPS; HUMBERTO GONCALVES DOS SANTOS, CNPS; RICARDO DE OLIVEIRA DART, CNPS; JERÔNIMO GUEDES PARÉS. |
Título: |
Digital mapping of soil classes in Rio de Janeiro State, Brazil: data, modelling and prediction. |
Ano de publicação: |
2008 |
Fonte/Imprenta: |
In: HARTEMINK, A. E.; McBRATNEY, A.; MENDONÇA-SANTOS, M. de L. (ed.). Digital soil mapping with limited data. Dordrecht: Springer, 2008. cap. 34, p. 381-396. |
DOI: |
https://doi.org/10.1007/978-1-4020-8592-5_34 |
Idioma: |
Inglês |
Conteúdo: |
A soil database for Rio de Janeiro State was collated in Access, for a project on quantifying the magnitude, spatial distribution and organic carbon in the soils of Rio de Janeiro State (Projeto Carbono_RJ). The main activities were the search, selection, analysis and review of the data for each soil profile already described in the study area, the georeferencing of each soil profile (when spatial coordinates were not available) and the input of new soil profiles into a new interface. The Rio de Janeiro soil dataset now contains 731 soil profiles, 2744 soil horizons, and 48 soil attributes usually described at the soil survey process. From this soil dataset, only 431 soil profiles that were adequately geo-located have been used in this application. The dataset contains limited data for bulk density and hydraulic soil properties, among others. From this dataset, quantitative modelling and digital soil mapping have been completed experimentally at 90 m resolution, using soil data and predictor variables, such as satellite images, lithology, a prior soil map and a DEM and its derivates. This dataset, which is one of the more complete soil datasets in Brazil, is being used as a testbed for learning and teaching DSM, using a variety of methods based on the scorpan model (Embrapa, 2006). In the first instance, the soil dataset was used to predict soil classes at the Order level of the Brazilian Soil Classification System ? SiBCS (Embrapa, 2006). Five models were built and their results were compared and mapped. MenosA soil database for Rio de Janeiro State was collated in Access, for a project on quantifying the magnitude, spatial distribution and organic carbon in the soils of Rio de Janeiro State (Projeto Carbono_RJ). The main activities were the search, selection, analysis and review of the data for each soil profile already described in the study area, the georeferencing of each soil profile (when spatial coordinates were not available) and the input of new soil profiles into a new interface. The Rio de Janeiro soil dataset now contains 731 soil profiles, 2744 soil horizons, and 48 soil attributes usually described at the soil survey process. From this soil dataset, only 431 soil profiles that were adequately geo-located have been used in this application. The dataset contains limited data for bulk density and hydraulic soil properties, among others. From this dataset, quantitative modelling and digital soil mapping have been completed experimentally at 90 m resolution, using soil data and predictor variables, such as satellite images, lithology, a prior soil map and a DEM and its derivates. This dataset, which is one of the more complete soil datasets in Brazil, is being used as a testbed for learning and teaching DSM, using a variety of methods based on the scorpan model (Embrapa, 2006). In the first instance, the soil dataset was used to predict soil classes at the Order level of the Brazilian Soil Classification System ? SiBCS (Embrapa, 2006). Five models were built and their re... Mostrar Tudo |
Palavras-Chave: |
Brasil; Mapeamento digital; Rio de Janeiro. |
Thesagro: |
Solo. |
Thesaurus Nal: |
Soil map. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
Marc: |
LEADER 02339naa a2200229 a 4500 001 1337609 005 2024-04-11 008 2008 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1007/978-1-4020-8592-5_34$2DOI 100 1 $aMENDONÇA-SANTOS, M. de L. 245 $aDigital mapping of soil classes in Rio de Janeiro State, Brazil$bdata, modelling and prediction.$h[electronic resource] 260 $c2008 520 $aA soil database for Rio de Janeiro State was collated in Access, for a project on quantifying the magnitude, spatial distribution and organic carbon in the soils of Rio de Janeiro State (Projeto Carbono_RJ). The main activities were the search, selection, analysis and review of the data for each soil profile already described in the study area, the georeferencing of each soil profile (when spatial coordinates were not available) and the input of new soil profiles into a new interface. The Rio de Janeiro soil dataset now contains 731 soil profiles, 2744 soil horizons, and 48 soil attributes usually described at the soil survey process. From this soil dataset, only 431 soil profiles that were adequately geo-located have been used in this application. The dataset contains limited data for bulk density and hydraulic soil properties, among others. From this dataset, quantitative modelling and digital soil mapping have been completed experimentally at 90 m resolution, using soil data and predictor variables, such as satellite images, lithology, a prior soil map and a DEM and its derivates. This dataset, which is one of the more complete soil datasets in Brazil, is being used as a testbed for learning and teaching DSM, using a variety of methods based on the scorpan model (Embrapa, 2006). In the first instance, the soil dataset was used to predict soil classes at the Order level of the Brazilian Soil Classification System ? SiBCS (Embrapa, 2006). Five models were built and their results were compared and mapped. 650 $aSoil map 650 $aSolo 653 $aBrasil 653 $aMapeamento digital 653 $aRio de Janeiro 700 1 $aSANTOS, H. G. dos 700 1 $aDART, R. de O. 700 1 $aPARES, J. G. 773 $tIn: HARTEMINK, A. E.; McBRATNEY, A.; MENDONÇA-SANTOS, M. de L. (ed.). Digital soil mapping with limited data. Dordrecht: Springer, 2008. cap. 34, p. 381-396.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Solos (CNPS) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
![](/consulta/web/img/deny.png) | Acesso ao texto completo restrito à biblioteca da Embrapa Amazônia Oriental. Para informações adicionais entre em contato com cpatu.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Amazônia Oriental. |
Data corrente: |
18/12/2023 |
Data da última atualização: |
18/12/2023 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
AGUIRRE‐GUTIÉRREZ, J.; BERENGUER, E.; MENOR, I. O.; BAUMAN, D.; CORRA-RIVAS, J. J.; NAVA-MIRANDA, M. G.; BOTH, S.; NDONG, J. E.; ONDO, F. E.; BENGONE, N. N.; MIHINHOU, V.; DALLING, J. W.; HEINEMAN, K.; FIGUEIREDO, A.; GONZÁLEZ-M, R.; NORDEN, N.; HURTADO-M, A. B.; GONZÁLEZ, D.; SALGADO-NEGRET, B.; REIS, S. M.; SEIXAS, M. M. M. de; FARFAN-RIOS, W.; SHENKIN, A.; RIUTTA, T.; GIRARDIN, C. A. J.; MOORE, S.; ABERNETHY, K.; ASNER, G. P.; BENTLEY, L. P.; BURSLEM, D. F. R. P.; CERNUSAK, L. A.; ENQUIST, B. J.; EWERS, R. M.; FERREIRA, J. N.; JEFFERY, K. J.; JOLY, C. A.; MARIMON-JUNIOR, B. H.; MARTIN, R. E.; MORANDI, P. S.; PHILLIPS, O. L.; BENNETT, A. C.; LEWIS, S. L.; QUESADA, C. A.; MARIMON, B. S.; KISSLING, W. D.; SILMAN, M.; TEH, Y. A.; WHITE, L. J. T.; SALINAS, N.; COOMES, D. A.; BARLOW, J.; ADU-BREDU, S.; MALHI, Y. |
Afiliação: |
JESÚS AGUIRRE‐GUTIÉRREZ, UNIVERSITY OF OXFORD; ERIKA BERENGUER, UNIVERSITY OF OXFORD; IMMA OLIVERAS MENOR, UNIVERSITY OF OXFORD; DAVID BAUMAN, UNIVERSITY OF OXFORD; JOSE JAVIER CORRAL-RIVAS, UNIVERSIDAD JUÁREZ DEL ESTADO DE DURANGO; MARIA GUADALUPE NAVA-MIRANDA, UNIVERSIDAD JUÁREZ DEL ESTADO DE DURANGO; SABINE BOTH, UNIVERSITY OF NEW ENGLAND; JOSUÉ EDZANG NDONG, AGENCE NATIONALE DES PARCS NATIONAUX; FIDÈLE EVOUNA ONDO, AGENCE NATIONALE DES PARCS NATIONAUX; NATACHA N’SSI BENGONE, MINISTÈRE DES EAUX, DES FORÊTS, DE LA MER ET DE L’ENVIRONNEMENT; VIANET MIHINHOU, MINISTÈRE DES EAUX, DES FORÊTS, DE LA MER ET DE L’ENVIRONNEMENT; JAMES W. DALLING, SMITHSONIAN TROPICAL RESEARCH INSTITUTE; KATHERINE HEINEMAN, UNIVERSITY OF ILLINOIS; AXA FIGUEIREDO, INSTITUTO NACIONAL DE PESQUISAS DA AMAZÔNIA; ROY GONZÁLEZ-M, INSTITUTO DE INVESTIGACIÓN DE RECURSOS BIOLÓGICOS ALEXANDER VON HUMBOLDT; NATALIA NORDEN, INSTITUTO DE INVESTIGACIÓN DE RECURSOS BIOLÓGICOS ALEXANDER VON HUMBOLDT; ANA BELÉN HURTADO-M, INSTITUTO DE INVESTIGACIÓN DE RECURSOS BIOLÓGICOS ALEXANDER VON HUMBOLDT; DIEGO GONZÁLEZ, INSTITUTO DE INVESTIGACIÓN DE RECURSOS BIOLÓGICOS ALEXANDER VON HUMBOLDT; BEATRIZ SALGADO-NEGRET, UNIVERSIDAD NACIONAL DE COLOMBIA; SIMONE MATIAS REIS, UNIVERSITY OF OXFORD; MARINA MARIA MORAES DE SEIXAS; WILLIAM FARFAN-RIOS, WASHINGTON UNIVERSITY IN ST. LOUIS; ALEXANDER SHENKIN, UNIVERSITY OF OXFORD; TERHI RIUTTA, UNIVERSITY OF OXFORD; CÉCILE A. J. GIRARDIN, UNIVERSITY OF OXFORD; SAM MOORE, UNIVERSITY OF OXFORD; KATE ABERNETHY, UNIVERSITY OF STIRLING; GREGORY P. ASNER, ARIZONA STATE UNIVERSITY; LISA PATRICK BENTLEY, SONOMA STATE UNIVERSITY; DAVID F. R. P. BURSLEM, UNIVERSITY OF ABERDEEN; LUCAS A. CERNUSAK, JAMES COOK UNIVERSITY; BRIAN J. ENQUIST, UNIVERSITY OF ARIZONA; ROBERT M. EWERS, IMPERIAL COLLEGE LONDON; JOICE NUNES FERREIRA, CPATU; KATHRYN J. JEFFERY, IMPERIAL COLLEGE LONDON; CARLOS A. JOLY, UNIVERSIDADE ESTADUAL DE CAMPINAS; BEN HUR MARIMON-JUNIOR, UNIVERSIDADE DO ESTADO DE MATO GROSSO; ROBERTA E. MARTIN, ARIZONA STATE UNIVERSITY; PAULO S. MORANDI, UNIVERSIDADE DO ESTADO DE MATO GROSSO; OLIVER L. PHILLIPS, UNIVERSITY OF LEEDS; AMY C. BENNETT, UNIVERSITY OF LEEDS; SIMON L. LEWIS, UNIVERSITY OF LEEDS; CARLOS A. QUESADA, INSTITUTO NACIONAL DE PESQUISAS DA AMAZÔNIA; BEATRIZ SCHWANTES MARIMON, UNIVERSIDADE DO ESTADO DE MATO GROSSO; W. DANIEL KISSLING, UNIVERSITY OF AMSTERDAM; MILES SILMAN, WAKE FOREST UNIVERSITY; YIT ARN TEH, NEWCASTLE UNIVERSITY; LEE J. T. WHITE, MINISTÈRE DES EAUX, DES FORÊTS, DE LA MER ET DE L’ENVIRONNEMENT; NORMA SALINAS, PONTIFICIA UNIVERSIDAD CATÓLICA DEL PERÚ; DAVID A. COOMES, UNIVERSITY OF CAMBRIDGE; JOS BARLOW, LANCASTER UNIVERSITY; STEPHEN ADU-BREDU, CSIR‐FORESTRY RESEARCH INSTITUTE OF GHANA; YADVINDER MALHI, UNIVERSITY OF ILLINOIS. |
Título: |
Functional susceptibility of tropical forests to climate change. |
Ano de publicação: |
2022 |
Fonte/Imprenta: |
Nature Ecology & Evolution, v. 6, p. 878-889, 2022. |
DOI: |
https://doi.org/10.1038/s41559-022-01747-6 |
Idioma: |
Inglês |
Conteúdo: |
Tropical forests are some of the most biodiverse ecosystems in the world, yet their functioning is threatened by anthropogenic disturbances and climate change. Global actions to conserve tropical forests could be enhanced by having local knowledge on the forestsʼ functional diversity and functional redundancy as proxies for their capacity to respond to global environmental change. Here we create estimates of plant functional diversity and redundancy across the tropics by combining a dataset of 16 morphological, chemical and photosynthetic plant traits sampled from 2,461 individual trees from 74 sites distributed across four continents together with local climate data for the past half century. Our findings suggest a strong link between climate and functional diversity and redundancy with the three trait groups responding similarly across the tropics and climate gradient. We show that drier tropical forests are overall less functionally diverse than wetter forests and that functional redundancy declines with increasing soil water and vapour pressure deficits. Areas with high functional diversity and high functional redundancy tend to better maintain ecosystem functioning, such as aboveground biomass, after extreme weather events. Our predictions suggest that the lower functional diversity and lower functional redundancy of drier tropical forests, in comparison with wetter forests, may leave them more at risk of shifting towards alternative states in face of further declines in water availability across tropical regions. MenosTropical forests are some of the most biodiverse ecosystems in the world, yet their functioning is threatened by anthropogenic disturbances and climate change. Global actions to conserve tropical forests could be enhanced by having local knowledge on the forestsʼ functional diversity and functional redundancy as proxies for their capacity to respond to global environmental change. Here we create estimates of plant functional diversity and redundancy across the tropics by combining a dataset of 16 morphological, chemical and photosynthetic plant traits sampled from 2,461 individual trees from 74 sites distributed across four continents together with local climate data for the past half century. Our findings suggest a strong link between climate and functional diversity and redundancy with the three trait groups responding similarly across the tropics and climate gradient. We show that drier tropical forests are overall less functionally diverse than wetter forests and that functional redundancy declines with increasing soil water and vapour pressure deficits. Areas with high functional diversity and high functional redundancy tend to better maintain ecosystem functioning, such as aboveground biomass, after extreme weather events. Our predictions suggest that the lower functional diversity and lower functional redundancy of drier tropical forests, in comparison with wetter forests, may leave them more at risk of shifting towards alternative states in face of further declines i... Mostrar Tudo |
Thesagro: |
Floresta Tropical; Mudança Climática. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
Marc: |
LEADER 03633naa a2200781 a 4500 001 2159912 005 2023-12-18 008 2022 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1038/s41559-022-01747-6$2DOI 100 1 $aAGUIRRE‐GUTIÉRREZ, J. 245 $aFunctional susceptibility of tropical forests to climate change.$h[electronic resource] 260 $c2022 520 $aTropical forests are some of the most biodiverse ecosystems in the world, yet their functioning is threatened by anthropogenic disturbances and climate change. Global actions to conserve tropical forests could be enhanced by having local knowledge on the forestsʼ functional diversity and functional redundancy as proxies for their capacity to respond to global environmental change. Here we create estimates of plant functional diversity and redundancy across the tropics by combining a dataset of 16 morphological, chemical and photosynthetic plant traits sampled from 2,461 individual trees from 74 sites distributed across four continents together with local climate data for the past half century. Our findings suggest a strong link between climate and functional diversity and redundancy with the three trait groups responding similarly across the tropics and climate gradient. We show that drier tropical forests are overall less functionally diverse than wetter forests and that functional redundancy declines with increasing soil water and vapour pressure deficits. Areas with high functional diversity and high functional redundancy tend to better maintain ecosystem functioning, such as aboveground biomass, after extreme weather events. Our predictions suggest that the lower functional diversity and lower functional redundancy of drier tropical forests, in comparison with wetter forests, may leave them more at risk of shifting towards alternative states in face of further declines in water availability across tropical regions. 650 $aFloresta Tropical 650 $aMudança Climática 700 1 $aBERENGUER, E. 700 1 $aMENOR, I. O. 700 1 $aBAUMAN, D. 700 1 $aCORRA-RIVAS, J. J. 700 1 $aNAVA-MIRANDA, M. G. 700 1 $aBOTH, S. 700 1 $aNDONG, J. E. 700 1 $aONDO, F. E. 700 1 $aBENGONE, N. N. 700 1 $aMIHINHOU, V. 700 1 $aDALLING, J. W. 700 1 $aHEINEMAN, K. 700 1 $aFIGUEIREDO, A. 700 1 $aGONZÁLEZ-M, R. 700 1 $aNORDEN, N. 700 1 $aHURTADO-M, A. B. 700 1 $aGONZÁLEZ, D. 700 1 $aSALGADO-NEGRET, B. 700 1 $aREIS, S. M. 700 1 $aSEIXAS, M. M. M. de 700 1 $aFARFAN-RIOS, W. 700 1 $aSHENKIN, A. 700 1 $aRIUTTA, T. 700 1 $aGIRARDIN, C. A. J. 700 1 $aMOORE, S. 700 1 $aABERNETHY, K. 700 1 $aASNER, G. P. 700 1 $aBENTLEY, L. P. 700 1 $aBURSLEM, D. F. R. P. 700 1 $aCERNUSAK, L. A. 700 1 $aENQUIST, B. J. 700 1 $aEWERS, R. M. 700 1 $aFERREIRA, J. N. 700 1 $aJEFFERY, K. J. 700 1 $aJOLY, C. A. 700 1 $aMARIMON-JUNIOR, B. H. 700 1 $aMARTIN, R. E. 700 1 $aMORANDI, P. S. 700 1 $aPHILLIPS, O. L. 700 1 $aBENNETT, A. C. 700 1 $aLEWIS, S. L. 700 1 $aQUESADA, C. A. 700 1 $aMARIMON, B. S. 700 1 $aKISSLING, W. D. 700 1 $aSILMAN, M. 700 1 $aTEH, Y. A. 700 1 $aWHITE, L. J. T. 700 1 $aSALINAS, N. 700 1 $aCOOMES, D. A. 700 1 $aBARLOW, J. 700 1 $aADU-BREDU, S. 700 1 $aMALHI, Y. 773 $tNature Ecology & Evolution$gv. 6, p. 878-889, 2022.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Amazônia Oriental (CPATU) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
Nenhum registro encontrado para a expressão de busca informada. |
|
|