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Registro Completo |
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Biblioteca(s): |
Embrapa Acre. |
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Data corrente: |
08/02/2024 |
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Data da última atualização: |
08/02/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
LACERDA, T. H. S.; FRANÇA, L. C. de J.; LOPES, I. L. e; LACERDA, S. L. S.; FIGUEIREDO, E. O.; BARBOSA, B. H. G.; SILVA, C. S. J. e; GOMIDE, L. R. |
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Afiliação: |
TALLES HUDSON SOUZA LACERDA; LUCIANO CAVALCANTE DE JESUS FRANÇA, UNIVERSIDADE FEDERAL DE UBERLÂNDIA; ISÁIRA LEITE E LOPES, UNIVERSIDADE FEDERAL DE LAVRAS; SÂMMILLY LORRAYNE SOUZA LACERDA, UNIVERSIDADE FEDERAL DE LAVRAS; EVANDRO ORFANO FIGUEIREDO, CPAF-AC; BRUNO HENRIQUE GROENNER BARBOSA, UNIVERSIDADE FEDERAL DE LAVRAS; CAROLINA SOUZA JAROCHINSKI E SILVA, UNIVERSIDADE FEDERAL DE LAVRAS; LUCAS REZENDE GOMIDE, UNIVERSIDADE FEDERAL DE LAVRAS. |
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Título: |
Multi‑objective forest harvesting under sustainable and economic principles. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Journal of Forestry Research, v. 34, p. 1379-1394, Oct. 2023. |
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ISSN: |
1007-662X |
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DOI: |
https://doi.org/10.1007/s11676-023-01614-5 |
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Idioma: |
Inglês |
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Conteúdo: |
Selective logging is well-recognized as an efective practice in sustainable forest management. However, the ecological efciency or resilience of the residual stand is often in doubt. Recovery time depends on operational variables, diversity, and forest structure. Selective logging is excellent but is open to changes. This may be resolved by mathematical programming and this study integrates the economic-ecological aspects in multi-objective function by applying two evolutionary algorithms. The function maximizes remaining stand diversity, merchantable logs, and the inverse of distance between trees for harvesting and log landings points. The Brazilian rainforest database (566 trees) was used to simulate our 216-ha model. The log landing design has a maximum volume limit of 500 m3 . The nondominated sorting genetic algorithm was applied to solve the main optimization problem. In parallel, a sub-problem (p-facility allocation) was solved for landing allocation by a genetic algorithm. Pareto frontier analysis was applied to distinguish the gradients α-economic, β-ecological, and γ-equilibrium. As expected, the solutions have high diameter changes in the residual stand (average removal of approximately 16 m3 ha−1). All solutions showed a grouping of trees selected for harvesting, although there was no formation of large clearings (percentage of canopy removal<7%, with an average of 2.5 ind ha−1). There were no diferences in foristic composition by preferentially selecting species with greater frequency in the initial stand for harvesting. This implies a lower impact on the demographic rates of the remaining stand. The methodology should support projects of reduced impact logging by using spatial-diversity information to guide better practices in tropical forests. MenosSelective logging is well-recognized as an efective practice in sustainable forest management. However, the ecological efciency or resilience of the residual stand is often in doubt. Recovery time depends on operational variables, diversity, and forest structure. Selective logging is excellent but is open to changes. This may be resolved by mathematical programming and this study integrates the economic-ecological aspects in multi-objective function by applying two evolutionary algorithms. The function maximizes remaining stand diversity, merchantable logs, and the inverse of distance between trees for harvesting and log landings points. The Brazilian rainforest database (566 trees) was used to simulate our 216-ha model. The log landing design has a maximum volume limit of 500 m3 . The nondominated sorting genetic algorithm was applied to solve the main optimization problem. In parallel, a sub-problem (p-facility allocation) was solved for landing allocation by a genetic algorithm. Pareto frontier analysis was applied to distinguish the gradients α-economic, β-ecological, and γ-equilibrium. As expected, the solutions have high diameter changes in the residual stand (average removal of approximately 16 m3 ha−1). All solutions showed a grouping of trees selected for harvesting, although there was no formation of large clearings (percentage of canopy removal<7%, with an average of 2.5 ind ha−1). There were no diferences in foristic composition by preferentially selecting specie... Mostrar Tudo |
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Palavras-Chave: |
Acre; Amazonia Occidental; Amazônia Ocidental; Análise de Fronteira de Pareto; Bosques primarios; Bujari (AC); Manejo florestal sustentável; Pareto frontier analysis; Regeneración forestal; Regeneración natural; Selective logging; Silvicultura sustentable; Western Amazon. |
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Thesagro: |
Exploração Florestal; Extração da Madeira; Floresta Nativa; Modelo Matemático; Regeneração Natural. |
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Thesaurus Nal: |
Forest regeneration; Mathematical models; Natural regeneration; Primary forests; Sustainable forestry. |
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Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1161859/1/27675.pdf
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Marc: |
LEADER 03345naa a2200505 a 4500
001 2161859
005 2024-02-08
008 2023 bl uuuu u00u1 u #d
022 $a1007-662X
024 7 $ahttps://doi.org/10.1007/s11676-023-01614-5$2DOI
100 1 $aLACERDA, T. H. S.
245 $aMulti‑objective forest harvesting under sustainable and economic principles.$h[electronic resource]
260 $c2023
520 $aSelective logging is well-recognized as an efective practice in sustainable forest management. However, the ecological efciency or resilience of the residual stand is often in doubt. Recovery time depends on operational variables, diversity, and forest structure. Selective logging is excellent but is open to changes. This may be resolved by mathematical programming and this study integrates the economic-ecological aspects in multi-objective function by applying two evolutionary algorithms. The function maximizes remaining stand diversity, merchantable logs, and the inverse of distance between trees for harvesting and log landings points. The Brazilian rainforest database (566 trees) was used to simulate our 216-ha model. The log landing design has a maximum volume limit of 500 m3 . The nondominated sorting genetic algorithm was applied to solve the main optimization problem. In parallel, a sub-problem (p-facility allocation) was solved for landing allocation by a genetic algorithm. Pareto frontier analysis was applied to distinguish the gradients α-economic, β-ecological, and γ-equilibrium. As expected, the solutions have high diameter changes in the residual stand (average removal of approximately 16 m3 ha−1). All solutions showed a grouping of trees selected for harvesting, although there was no formation of large clearings (percentage of canopy removal<7%, with an average of 2.5 ind ha−1). There were no diferences in foristic composition by preferentially selecting species with greater frequency in the initial stand for harvesting. This implies a lower impact on the demographic rates of the remaining stand. The methodology should support projects of reduced impact logging by using spatial-diversity information to guide better practices in tropical forests.
650 $aForest regeneration
650 $aMathematical models
650 $aNatural regeneration
650 $aPrimary forests
650 $aSustainable forestry
650 $aExploração Florestal
650 $aExtração da Madeira
650 $aFloresta Nativa
650 $aModelo Matemático
650 $aRegeneração Natural
653 $aAcre
653 $aAmazonia Occidental
653 $aAmazônia Ocidental
653 $aAnálise de Fronteira de Pareto
653 $aBosques primarios
653 $aBujari (AC)
653 $aManejo florestal sustentável
653 $aPareto frontier analysis
653 $aRegeneración forestal
653 $aRegeneración natural
653 $aSelective logging
653 $aSilvicultura sustentable
653 $aWestern Amazon
700 1 $aFRANÇA, L. C. de J.
700 1 $aLOPES, I. L. e
700 1 $aLACERDA, S. L. S.
700 1 $aFIGUEIREDO, E. O.
700 1 $aBARBOSA, B. H. G.
700 1 $aSILVA, C. S. J. e
700 1 $aGOMIDE, L. R.
773 $tJournal of Forestry Research$gv. 34, p. 1379-1394, Oct. 2023.
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Embrapa Acre (CPAF-AC) |
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