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Registros recuperados : 9 | |
1. | | LEGESE, M. T.; BEKELE, T.; MATTOS, P. P. de; CANETTI, A.; BRAZ, E. M.; TORRES, C. M. M. E. Population management of Juniperus procera tree from Ethiopia. Pesquisa Florestal Brasileira, Colombo, v. 39, (nesp), e201902043, 2019. p. 154. Edição especial dos resumos do IUFRO World Congress, 25., 2019, Curitiba. Biblioteca(s): Embrapa Florestas. |
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2. | | TORRES, C. M. M. E.; JACOVINE, L. A. G.; TOLEDO, D. P.; RIBEIRO, S. C.; SOARES, C. P. B. Quantificação da biomassa aérea da cultura de Jatropa curcas L., ao terceiro ano, no município de Viçosa - MG. In: CONGRESSO BRASILEIRO SOBRE FLORESTAS ENERGÉTICAS, 1., 2009, Belo Horizonte. Anais. Colombo: Embrapa Florestas, 2009. 1 CD-ROM. (Embrapa Florestas. Documentos, 178). Seção: Silvicultura e Produção de Biomassa. Biblioteca(s): Embrapa Florestas. |
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3. | | OLIVEIRA, A. C.; PEREIRA, B. L. C.; CARNEIRO, A. de C. O.; CARDOSO JÚNIOR, J. F.; TORRES, C. M. M. E.; REIS, B. E. Avaliação de diferentes marcas de carvão vegetal comercializados na cidade de Viçosa, MG. In: CONGRESSO BRASILEIRO SOBRE FLORESTAS ENERGÉTICAS, 1., 2009, Belo Horizonte. Anais. Colombo: Embrapa Florestas, 2009. 1 CD-ROM. (Embrapa Florestas. Documentos, 178). Seção: Matéria Prima e Processos de Conversão Energética. Biblioteca(s): Embrapa Florestas. |
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4. | | ANDRADE, C. G. C.; SILVA, M. L. da; TORRES, C. M. M. E.; RUSCHEL, A. R.; SILVA, L. F. da; ANDRADE, D. F. C. de; REIS, L. P. Crescimento diamétrico e tempo de passagem de Minquartia guianensis após manejo na Floresta Nacional do Tapajós. Pesquisa Florestal Brasileira, Colombo, v. 37, n. 91, p. 299-309, jul./set. 2017. Biblioteca(s): Embrapa Amazônia Oriental; Embrapa Florestas. |
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5. | | TESHOME, M.; BRAZ, E. M.; TORRES, C. M. M. E.; RAPTIS, D. I.; MATTOS, P. P. de; TEMESGEN, H.; RUBIO-CAMACHO, E. A.; SILESHI, G. W. Mixed-effects height prediction model for Juniperus procera trees from a Dry Afromontane Forest in Ethiopia. Forests, v. 15, n. 3, 443, p. 1-19, 2024. Biblioteca(s): Embrapa Florestas. |
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6. | | TESHOME, M.; TORRES, C. M. M. E.; SILESHI, G. W.; MATTOS, P. P. de; BRAZ, E. M.; TEMESGEN, H.; ROCHA, S. J. S. S. da; ALEBACHEW, M. Mixed-Species allometric equations to quantify stem volume and tree biomass in Dry Afromontane Forest of Ethiopia. Open Journal of Forestry, v. 12, p. 263-296, 2022. Biblioteca(s): Embrapa Florestas. |
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7. | | MACHADO FILHO, C.; MARTINS, M. C.; RIBEIRO, G. A.; LIMA, G. S.; CARDOSO, M. T.; TORRES, C. M. M. E.; PINTO, F. B. Eficiência de um retardante de fogo de longa duração utilizado em incêndios florestais. Ciência Florestal, Santa Maria, RS, v. 22, n. 2, p. 365-371, 2012. Nota técnica. Biblioteca(s): Embrapa Florestas. |
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8. | | TORRES, C. M. M. E.; JACOVINE, L. A. G.; TOLEDO, D. de P.; SOARES, C. P. B.; RIBEIRO, S. C.; MARTINS, M. C. Biomass and carbon stock in Jatropha curcas L. Cerne, Lavras, v. 17, n. 3, p. 353-359, jul./set. 2011. Biblioteca(s): Embrapa Florestas. |
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9. | | TORRES, C. M. M. E.; JACOVINE, L. A. G.; OLIVEIRA NETO, S. N. de; BRIANEZI, D.; ALVES, E. B. B. M. Sistemas agroflorestais no Brasil: uma abordagem sobre a estocagem de carbono. Pesquisa Florestal Brasileira, Colombo, v. 34, n. 79, p. 217-224, jul./set. 2014. Artigo de revisão. Biblioteca(s): Embrapa Florestas. |
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Registros recuperados : 9 | |
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Registro Completo
Biblioteca(s): |
Embrapa Amazônia Oriental. |
Data corrente: |
26/10/2016 |
Data da última atualização: |
23/05/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
REIS, L. P.; SOUZA, A. L. de; MAZZEI, L.; REIS, P. C. M. dos; LEITE, H. G.; SOARES, C. P. B.; TORRES, C. M. M. E.; SILVA, L. F. da; RUSCHEL, A. R. |
Afiliação: |
Leonardo Pequeno Reis, UFV; Agostinho Lopes de Souza, UFV; LUCAS JOSE MAZZEI DE FREITAS, CPATU; Pamella Carolline Marques dos Reis, UFV; Hélio Garcia Leite, UFV; Carlos Pedro Boechat Soares, UFV; Carlos Moreira Miquelino Eleto Torres, UFV; Liniker Fernandes da Silva, UFV; ADEMIR ROBERTO RUSCHEL, CPATU. |
Título: |
Prognosis on the diameter of individual trees on the eastern region of the amazon using artificial neural networks. |
Ano de publicação: |
2016 |
Fonte/Imprenta: |
Forest Ecology and Management, v. 382, p. 161-167, Dec. 2016. |
DOI: |
http://dx.doi.org.ez103.periodicos.capes.gov.br/10.1016/j.foreco.2016.10.022 |
Idioma: |
Inglês |
Conteúdo: |
The prognosis of forest structure along the cutting cycle, using models of individual trees, is one of the alternatives to manage tropical forests aiming at sustainability. Currently, in forest management practiced in the Amazon Region, growth and production models are not used to predict the future stock of the forest. Thus, the sustainable economic and environmental aspects of this activity remain uncertain. The aim of this present work was to model the growth of individual trees in a forest managed in the Amazon Region, by using artificial neural networks (ANN) to serve as subsidy to the wielder in obtaining future stock after logging, thus reducing uncertainty on forest management sustainability. Selective harvest was carried out in 1979 with an intensity of 72.5 m3 ha−1 in a 64 ha area in the Tapajós National Forest - PA. In 1981, 36 permanent plots (50 m × 50 m) were installed at random and inventoried. There were nine successive measurements in 1982, 1983, 1985, 1987, 1992, 1997, 2007, 2010, and 2012. In the modeling of the future diameter, training and testing of ANN were carried out, including different semi-independent competition indexes (DSICI). All ANN, with and without DSICI, presented correlation above 99%, RMSE below 11%, and EF above 0.98. Based on the prognosis of tree growth, we were able to conclude that ANN can be effectively used to assist in the management of tropical forests and, thus, allow for the most suitable cutting intensity and cutting cycle per species, ensuring environmental and economic sustainability of forest management. MenosThe prognosis of forest structure along the cutting cycle, using models of individual trees, is one of the alternatives to manage tropical forests aiming at sustainability. Currently, in forest management practiced in the Amazon Region, growth and production models are not used to predict the future stock of the forest. Thus, the sustainable economic and environmental aspects of this activity remain uncertain. The aim of this present work was to model the growth of individual trees in a forest managed in the Amazon Region, by using artificial neural networks (ANN) to serve as subsidy to the wielder in obtaining future stock after logging, thus reducing uncertainty on forest management sustainability. Selective harvest was carried out in 1979 with an intensity of 72.5 m3 ha−1 in a 64 ha area in the Tapajós National Forest - PA. In 1981, 36 permanent plots (50 m × 50 m) were installed at random and inventoried. There were nine successive measurements in 1982, 1983, 1985, 1987, 1992, 1997, 2007, 2010, and 2012. In the modeling of the future diameter, training and testing of ANN were carried out, including different semi-independent competition indexes (DSICI). All ANN, with and without DSICI, presented correlation above 99%, RMSE below 11%, and EF above 0.98. Based on the prognosis of tree growth, we were able to conclude that ANN can be effectively used to assist in the management of tropical forests and, thus, allow for the most suitable cutting intensity and cutting cy... Mostrar Tudo |
Palavras-Chave: |
Ciclo de corte; Estrutura florestal; Sustentabilidade. |
Thesagro: |
Árvore; Diâmetro; Floresta Tropical. |
Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
Marc: |
LEADER 02548naa a2200301 a 4500 001 2055417 005 2022-05-23 008 2016 bl uuuu u00u1 u #d 024 7 $ahttp://dx.doi.org.ez103.periodicos.capes.gov.br/10.1016/j.foreco.2016.10.022$2DOI 100 1 $aREIS, L. P. 245 $aPrognosis on the diameter of individual trees on the eastern region of the amazon using artificial neural networks.$h[electronic resource] 260 $c2016 520 $aThe prognosis of forest structure along the cutting cycle, using models of individual trees, is one of the alternatives to manage tropical forests aiming at sustainability. Currently, in forest management practiced in the Amazon Region, growth and production models are not used to predict the future stock of the forest. Thus, the sustainable economic and environmental aspects of this activity remain uncertain. The aim of this present work was to model the growth of individual trees in a forest managed in the Amazon Region, by using artificial neural networks (ANN) to serve as subsidy to the wielder in obtaining future stock after logging, thus reducing uncertainty on forest management sustainability. Selective harvest was carried out in 1979 with an intensity of 72.5 m3 ha−1 in a 64 ha area in the Tapajós National Forest - PA. In 1981, 36 permanent plots (50 m × 50 m) were installed at random and inventoried. There were nine successive measurements in 1982, 1983, 1985, 1987, 1992, 1997, 2007, 2010, and 2012. In the modeling of the future diameter, training and testing of ANN were carried out, including different semi-independent competition indexes (DSICI). All ANN, with and without DSICI, presented correlation above 99%, RMSE below 11%, and EF above 0.98. Based on the prognosis of tree growth, we were able to conclude that ANN can be effectively used to assist in the management of tropical forests and, thus, allow for the most suitable cutting intensity and cutting cycle per species, ensuring environmental and economic sustainability of forest management. 650 $aÁrvore 650 $aDiâmetro 650 $aFloresta Tropical 653 $aCiclo de corte 653 $aEstrutura florestal 653 $aSustentabilidade 700 1 $aSOUZA, A. L. de 700 1 $aMAZZEI, L. 700 1 $aREIS, P. C. M. dos 700 1 $aLEITE, H. G. 700 1 $aSOARES, C. P. B. 700 1 $aTORRES, C. M. M. E. 700 1 $aSILVA, L. F. da 700 1 $aRUSCHEL, A. R. 773 $tForest Ecology and Management$gv. 382, p. 161-167, Dec. 2016.
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