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 | Acesso ao texto completo restrito à biblioteca da Embrapa Florestas. Para informações adicionais entre em contato com cnpf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
28/05/2013 |
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Data da última atualização: |
19/02/2015 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
LACERDA, A. E. B. de; NIMMO, E. R.; SEBBENN, A. M. |
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Afiliação: |
ANDRE EDUARDO BISCAIA DE LACERDA, CNPF; EVELYN ROBERTA NIMMO, University of Manitoba; ALEXANDRE MAGNO SEBBENN, INSTITUTO FLORESTAL DE SÃO PAULO. |
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Título: |
Modeling the long-term impacts of logging on genetic diversity and demography of Hymenaea courbaril. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
Forest Science, v. 59, n. 1, p. 15-26, 2013. |
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Idioma: |
Inglês |
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Conteúdo: |
Although selective logging is a common practice for timber production in the Brazilian Amazon, very little is known about its impacts on genetic diversity and demography of the harvested species. This study explores the sustainability of current forest management systems in the Brazilian Amazon by modeling harvesting cycles and examining the impacts on the genetic diversity and demography of the highly valued species Hymenaea courbaril. Using extensive field data, we introduced a two-step modeling procedure for EcoGene software that allowed us to identify optimal felling cycles that were later used for testing and defining sustainable logging parameters. The results show that logging cycles for H. courbaril should be approximately of 110 years, as opposed to the 30-year cycle currently used in Brazil, and harvesting levels should consider a combination of larger minimum cutting diameters (75–100 cm) and lower logging intensities (10–50%). We conclude that current practices in Brazil (30-year cycle, logging intensities of 90%, and minimum cutting diameters of 50 cm) are unsustainable for H. courbaril and that the current practice of using general logging prescriptions for all species does not deliver sustainable forest management in the Amazon. Brazilian forest harvesting regulations need to move toward species-specific prescriptions to ensure real sustainability in the long term. |
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Palavras-Chave: |
Árvore tropical; Diversidade genética; Microssatélite. |
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Thesagro: |
Hymenaea Courbaril. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02002naa a2200193 a 4500
001 1958990
005 2015-02-19
008 2013 bl uuuu u00u1 u #d
100 1 $aLACERDA, A. E. B. de
245 $aModeling the long-term impacts of logging on genetic diversity and demography of Hymenaea courbaril.$h[electronic resource]
260 $c2013
520 $aAlthough selective logging is a common practice for timber production in the Brazilian Amazon, very little is known about its impacts on genetic diversity and demography of the harvested species. This study explores the sustainability of current forest management systems in the Brazilian Amazon by modeling harvesting cycles and examining the impacts on the genetic diversity and demography of the highly valued species Hymenaea courbaril. Using extensive field data, we introduced a two-step modeling procedure for EcoGene software that allowed us to identify optimal felling cycles that were later used for testing and defining sustainable logging parameters. The results show that logging cycles for H. courbaril should be approximately of 110 years, as opposed to the 30-year cycle currently used in Brazil, and harvesting levels should consider a combination of larger minimum cutting diameters (75–100 cm) and lower logging intensities (10–50%). We conclude that current practices in Brazil (30-year cycle, logging intensities of 90%, and minimum cutting diameters of 50 cm) are unsustainable for H. courbaril and that the current practice of using general logging prescriptions for all species does not deliver sustainable forest management in the Amazon. Brazilian forest harvesting regulations need to move toward species-specific prescriptions to ensure real sustainability in the long term.
650 $aHymenaea Courbaril
653 $aÁrvore tropical
653 $aDiversidade genética
653 $aMicrossatélite
700 1 $aNIMMO, E. R.
700 1 $aSEBBENN, A. M.
773 $tForest Science$gv. 59, n. 1, p. 15-26, 2013.
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Registro original: |
Embrapa Florestas (CNPF) |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
05/04/2023 |
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Data da última atualização: |
05/04/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
C - 0 |
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Autoria: |
VASCONCELOS, J. C. S.; SPERANZA, E. A.; ANTUNES, J. F. G.; BARBOSA, L. A. F.; CHRISTOFOLETTI, D.; SEVERINO, F. J.; CANÇADO, G. M. de A. |
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Afiliação: |
JULIO CEZAR SOUZA VASCONCELOS, FUNDAÇÃO DE APOIO A PESQUISA E AO DESENVOLVIMENTO; EDUARDO ANTONIO SPERANZA, CNPTIA; JOAO FRANCISCO GONCALVES ANTUNES, CNPTIA; LUIZ ANTONIO FALAGUASTA BARBOSA, CNPTIA; DANIEL CHRISTOFOLETTI, COOPERATIVA DOS PLANTADORES DE CANA DO ESTADO DE SÃO PAULO; FRANCISCO JOSÉ SEVERINO, COOPERATIVA DOS PLANTADORES DE CANA DO ESTADO DE SÃO PAULO; GERALDO MAGELA DE ALMEIDA CANCADO, CNPTIA. |
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Título: |
Development and validation of a model based on vegetation indices for the prediction of sugarcane yield. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
AgriEngineering, v. 5, n. 2, p. 698-719, June 2023. |
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DOI: |
https://doi.org/10.3390/ agriengineering5020044 |
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Idioma: |
Inglês |
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Conteúdo: |
This study aimed to develop a predictive model for sugarcane production based on data extracted from aerial imagery obtained from drones or satellites, allowing the precise tracking of plant development in the field. |
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Palavras-Chave: |
Agricultura digital; Digital agriculture; Distribuição gaussiana inversa; Inverse Gaussian distribution; Modelo preditivo; Remotely piloted aircraft systems; RPAS. |
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Thesagro: |
Cana de Açúcar; Saccharum Officinarum. |
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Thesaurus NAL: |
Models; Sugarcane; Vegetation index. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1153006/1/AP-Development-validation-2023.pdf
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Marc: |
LEADER 01324naa a2200349 a 4500
001 2153006
005 2023-04-05
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3390/ agriengineering5020044$2DOI
100 1 $aVASCONCELOS, J. C. S.
245 $aDevelopment and validation of a model based on vegetation indices for the prediction of sugarcane yield.$h[electronic resource]
260 $c2023
520 $aThis study aimed to develop a predictive model for sugarcane production based on data extracted from aerial imagery obtained from drones or satellites, allowing the precise tracking of plant development in the field.
650 $aModels
650 $aSugarcane
650 $aVegetation index
650 $aCana de Açúcar
650 $aSaccharum Officinarum
653 $aAgricultura digital
653 $aDigital agriculture
653 $aDistribuição gaussiana inversa
653 $aInverse Gaussian distribution
653 $aModelo preditivo
653 $aRemotely piloted aircraft systems
653 $aRPAS
700 1 $aSPERANZA, E. A.
700 1 $aANTUNES, J. F. G.
700 1 $aBARBOSA, L. A. F.
700 1 $aCHRISTOFOLETTI, D.
700 1 $aSEVERINO, F. J.
700 1 $aCANÇADO, G. M. de A.
773 $tAgriEngineering$gv. 5, n. 2, p. 698-719, June 2023.
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Embrapa Agricultura Digital (CNPTIA) |
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