Non-linear growth models for tree species used for forest restoration in Brazilian Amazon Arc of Deforestation

Detalhes bibliográficos
Autor(a) principal: Terra , Marcela de Castro Nunes Santos
Data de Publicação: 2022
Outros Autores: Lima, Marcos Gabriel Braz de, Santos, Juliano de Paulo dos, Cordeiro, Natielle Gomes, Pereira, Kelly Marianne Guimarães, Dantas, Daniel, Calegario, Natalino, Botelho, Soraya Alvarenga
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa Florestal Brasileira (Online)
Texto Completo: https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/2180
Resumo: The large amount of degraded areas and productive potential of the legal reserves in Brazil make restoration an environmental demand and a commercial opportunity. We modelled the diameter growth as a function of age of eight tree species in restoration plantations in the Brazilian Amazon. From 14 years of annual forest inventory data, for each species, we tested variations of logistic function: simple logistic, logistic with covariant (plant area at the time of planting), logistic with random effect, logistic with random effect and covariant. Amongst the studied species, Schizolobium parahyba var. amazonicum, Tectona grandis and Simarouba amara showed the highest growth rates while Cordia alliodora, Cedrela odorata and three species of the genus Handroanthus showed slower growth. The gains from using the covariant in modeling were small for both fixed and mixed-effect models. Gains from the inclusion of the random effect were substantial. Mixed-effect models had the best performance in modeling the growth of the species. Our results provide basis for a critical view of the criteria and possibilities for degraded areas restoration and management practices in legal reserves of the Amazon. An economic analysis is required to ensure the viability of these areas’ sustainable exploitation.
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spelling Non-linear growth models for tree species used for forest restoration in Brazilian Amazon Arc of DeforestationModelos de crescimento não linear para espécies de árvores usadas na restauração florestal no Arco do Desmatamento da Amazônia brasileiraFlorestas plantadasLogistic analysisModellingForest plantationsLogistic analysisModellingThe large amount of degraded areas and productive potential of the legal reserves in Brazil make restoration an environmental demand and a commercial opportunity. We modelled the diameter growth as a function of age of eight tree species in restoration plantations in the Brazilian Amazon. From 14 years of annual forest inventory data, for each species, we tested variations of logistic function: simple logistic, logistic with covariant (plant area at the time of planting), logistic with random effect, logistic with random effect and covariant. Amongst the studied species, Schizolobium parahyba var. amazonicum, Tectona grandis and Simarouba amara showed the highest growth rates while Cordia alliodora, Cedrela odorata and three species of the genus Handroanthus showed slower growth. The gains from using the covariant in modeling were small for both fixed and mixed-effect models. Gains from the inclusion of the random effect were substantial. Mixed-effect models had the best performance in modeling the growth of the species. Our results provide basis for a critical view of the criteria and possibilities for degraded areas restoration and management practices in legal reserves of the Amazon. An economic analysis is required to ensure the viability of these areas’ sustainable exploitation.A grande quantidade de áreas degradadas e o potencial produtivo das reservas legais no Brasil tornam a restauração uma demanda ambiental e oportunidade comercial. Modelamos o crescimento do diâmetro em função da idade de oito espécies de árvores em plantações de recomposição na Amazônia brasileira. A partir de 14 anos de dados de inventário florestal anual, testamos variações da função logística: logística simples, logística com covariante (área da planta na época do plantio), logística com efeito aleatório, logística com efeito aleatório e covariante. As espécies Schizolobium parahyba var. amazonicum, Tectona grandis e Simarouba amara apresentaram as maiores taxas de crescimento, enquanto Cordia alliodora, Cedrela odorata e três espécies do gênero Handroanthus apresentaram crescimento mais lento. Os ganhos com o uso da covariante na modelagem foram pequenos para modelos de efeitos fixos e mistos. Os ganhos com a inclusão do efeito aleatório foram substanciais. Os modelos de efeitos mistos tiveram o melhor desempenho na modelagem do crescimento das espécies. Nossos resultados fornecem subsídios para uma visão crítica sobre os critérios, possibilidades de recomposição e práticas de manejo de áreas degradadas em reservas legais na Amazônia. Uma análise econômica é necessária para garantir a viabilidade da exploração sustentável dessas áreas.Embrapa Florestas2022-12-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/octet-streamhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/218010.4336/2022.pfb.42e202102180Pesquisa Florestal Brasileira; v. 42 (2022)Pesquisa Florestal Brasileira; Vol. 42 (2022)1983-26051809-3647reponame:Pesquisa Florestal Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAenghttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/2180/1668Copyright (c) 2022 Marcela de Castro Nunes Santos Terra , Marcos Gabriel Braz de Lima, Juliano de Paulo dos Santos, Natielle Gomes Cordeiro, Kelly Marianne Guimarães Pereira, Daniel Dantas, Natalino Calegario, Soraya Alvarenga Botelhohttps://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccess Terra , Marcela de Castro Nunes SantosLima, Marcos Gabriel Braz de Santos, Juliano de Paulo dos Cordeiro, Natielle Gomes Pereira, Kelly Marianne Guimarães Dantas, Daniel Calegario, Natalino Botelho, Soraya Alvarenga 2022-12-14T14:46:53Zoai:pfb.cnpf.embrapa.br/pfb:article/2180Revistahttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/PUBhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/oaipfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br1983-26051809-3647opendoar:2022-12-14T14:46:53Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Non-linear growth models for tree species used for forest restoration in Brazilian Amazon Arc of Deforestation
Modelos de crescimento não linear para espécies de árvores usadas na restauração florestal no Arco do Desmatamento da Amazônia brasileira
title Non-linear growth models for tree species used for forest restoration in Brazilian Amazon Arc of Deforestation
spellingShingle Non-linear growth models for tree species used for forest restoration in Brazilian Amazon Arc of Deforestation
Terra , Marcela de Castro Nunes Santos
Florestas plantadas
Logistic analysis
Modelling
Forest plantations
Logistic analysis
Modelling
title_short Non-linear growth models for tree species used for forest restoration in Brazilian Amazon Arc of Deforestation
title_full Non-linear growth models for tree species used for forest restoration in Brazilian Amazon Arc of Deforestation
title_fullStr Non-linear growth models for tree species used for forest restoration in Brazilian Amazon Arc of Deforestation
title_full_unstemmed Non-linear growth models for tree species used for forest restoration in Brazilian Amazon Arc of Deforestation
title_sort Non-linear growth models for tree species used for forest restoration in Brazilian Amazon Arc of Deforestation
author Terra , Marcela de Castro Nunes Santos
author_facet Terra , Marcela de Castro Nunes Santos
Lima, Marcos Gabriel Braz de
Santos, Juliano de Paulo dos
Cordeiro, Natielle Gomes
Pereira, Kelly Marianne Guimarães
Dantas, Daniel
Calegario, Natalino
Botelho, Soraya Alvarenga
author_role author
author2 Lima, Marcos Gabriel Braz de
Santos, Juliano de Paulo dos
Cordeiro, Natielle Gomes
Pereira, Kelly Marianne Guimarães
Dantas, Daniel
Calegario, Natalino
Botelho, Soraya Alvarenga
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Terra , Marcela de Castro Nunes Santos
Lima, Marcos Gabriel Braz de
Santos, Juliano de Paulo dos
Cordeiro, Natielle Gomes
Pereira, Kelly Marianne Guimarães
Dantas, Daniel
Calegario, Natalino
Botelho, Soraya Alvarenga
dc.subject.por.fl_str_mv Florestas plantadas
Logistic analysis
Modelling
Forest plantations
Logistic analysis
Modelling
topic Florestas plantadas
Logistic analysis
Modelling
Forest plantations
Logistic analysis
Modelling
description The large amount of degraded areas and productive potential of the legal reserves in Brazil make restoration an environmental demand and a commercial opportunity. We modelled the diameter growth as a function of age of eight tree species in restoration plantations in the Brazilian Amazon. From 14 years of annual forest inventory data, for each species, we tested variations of logistic function: simple logistic, logistic with covariant (plant area at the time of planting), logistic with random effect, logistic with random effect and covariant. Amongst the studied species, Schizolobium parahyba var. amazonicum, Tectona grandis and Simarouba amara showed the highest growth rates while Cordia alliodora, Cedrela odorata and three species of the genus Handroanthus showed slower growth. The gains from using the covariant in modeling were small for both fixed and mixed-effect models. Gains from the inclusion of the random effect were substantial. Mixed-effect models had the best performance in modeling the growth of the species. Our results provide basis for a critical view of the criteria and possibilities for degraded areas restoration and management practices in legal reserves of the Amazon. An economic analysis is required to ensure the viability of these areas’ sustainable exploitation.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-14
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/2180
10.4336/2022.pfb.42e202102180
url https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/2180
identifier_str_mv 10.4336/2022.pfb.42e202102180
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/2180/1668
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/octet-stream
dc.publisher.none.fl_str_mv Embrapa Florestas
publisher.none.fl_str_mv Embrapa Florestas
dc.source.none.fl_str_mv Pesquisa Florestal Brasileira; v. 42 (2022)
Pesquisa Florestal Brasileira; Vol. 42 (2022)
1983-2605
1809-3647
reponame:Pesquisa Florestal Brasileira (Online)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
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instacron_str EMBRAPA
institution EMBRAPA
reponame_str Pesquisa Florestal Brasileira (Online)
collection Pesquisa Florestal Brasileira (Online)
repository.name.fl_str_mv Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv pfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br
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