Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availability

Detalhes bibliográficos
Autor(a) principal: Scolforo, Henrique Ferraco
Data de Publicação: 2019
Outros Autores: McTague, John Paul, Burkhart, Harold, Roise, Joseph, McCarter, James, Alvares, Clayton Alcarde, Stape, Jose Luiz [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.foreco.2019.06.006
http://hdl.handle.net/11449/196186
Resumo: Growth and yield (G &Y) model systems aim at forecasting forest productivity. The lack of environmental variables to account for how water availability constrains eucalyptus production in Brazil, however, is argued to be a major drawback of these model systems. Thus, this study aimed to develop a stand-level G & Y model system that accounts for water availability (G & Y with SWD), highlighting its usefulness when applied for clonal eucalypt stands under drier climatic conditions. The dataset is composed of remeasurement information of sixteen research sites that span all climatic regions in Brazil. A total of eleven eucalypt clones were planted in single block plots at each site, and extra replications under the rainfall exclusion system were also installed for these eleven clones in fourteen sites. Linear algebra techniques were used to simultaneously fit a compatible set of prediction and projection basal area equations. A stand-level volume equation was also developed. These equations were validated through the use of an independent dataset composed of the rainfall exclusion plots. Finally, the accuracy and usefulness of a conventional G & Y model system applied to clonal eucalypt stands in Brazil was compared to the new proposed G & Y model system, which accounts for the impact of water availability in eucalyptus productivity. The prediction and projection basal area equations accounting for water availability displayed estimates in the order of 5% more accurate compared to the conventional basal area modeling. Stand-level volume estimates were 40% and 74% less biased through the use of the new G & Y model system. This result highlighted how useful and powerful the newly developed approach is, since the model system was capable to provide accurate estimates through the use of the rainfall exclusion plots. The new G & Y model system is a powerful alternative to estimate forest afforestation yield and is fully capable to accurately update forest inventories. The model system can also be used for projecting how forest growth may be impacted by short-term climate variation.
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spelling Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availabilityEnvironmentAccuracyClimatic water deficitVolumeBasal areaForest productionGrowth and yield (G &Y) model systems aim at forecasting forest productivity. The lack of environmental variables to account for how water availability constrains eucalyptus production in Brazil, however, is argued to be a major drawback of these model systems. Thus, this study aimed to develop a stand-level G & Y model system that accounts for water availability (G & Y with SWD), highlighting its usefulness when applied for clonal eucalypt stands under drier climatic conditions. The dataset is composed of remeasurement information of sixteen research sites that span all climatic regions in Brazil. A total of eleven eucalypt clones were planted in single block plots at each site, and extra replications under the rainfall exclusion system were also installed for these eleven clones in fourteen sites. Linear algebra techniques were used to simultaneously fit a compatible set of prediction and projection basal area equations. A stand-level volume equation was also developed. These equations were validated through the use of an independent dataset composed of the rainfall exclusion plots. Finally, the accuracy and usefulness of a conventional G & Y model system applied to clonal eucalypt stands in Brazil was compared to the new proposed G & Y model system, which accounts for the impact of water availability in eucalyptus productivity. The prediction and projection basal area equations accounting for water availability displayed estimates in the order of 5% more accurate compared to the conventional basal area modeling. Stand-level volume estimates were 40% and 74% less biased through the use of the new G & Y model system. This result highlighted how useful and powerful the newly developed approach is, since the model system was capable to provide accurate estimates through the use of the rainfall exclusion plots. The new G & Y model system is a powerful alternative to estimate forest afforestation yield and is fully capable to accurately update forest inventories. The model system can also be used for projecting how forest growth may be impacted by short-term climate variation.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)University of Sao PauloSao Paulo State UniversityFederal University of LavrasFederal University of Rio Grande do NorteColorado State UniversityNorth Carolina State UniversityUSDA Forest ServiceFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Anglo AmericanAraucoArborgenArcelorMittalCenibraCMPCComigoCopenerDuratexEldoradoFazenda Campo BomFibriaFlorestal ItaquariForestal OrientalGerdauGMRInternational PaperJariKlabinLwarcelMontes del PlataPlantarRigesaSuzanoVallourecVeracelNorth Carolina State Univ, Dept Forestry & Environm Resources, 2820 Faucette Dr,Campus Box 8001, Raleigh, NC 27695 USAVirginia Polytech Inst & State Univ, Dept Forest Resources & Environm Conservat, 310 W Campus Dr,Campus Box 169, Blacksburg, VA 24061 USAForestry Sci & Res Inst, Via Comendador Pedro Morganti 3500, BR-13415000 Piracicaba, SP, BrazilState Univ Sao Paulo, Dept Forest Sci, Ave Univ 3780, BR-18610034 Botucatu, SP, BrazilUniv Sao Paulo, Dept Forest Sci, Ave Padua Dias 11, BR-13418900 Piracicaba, SP, BrazilState Univ Sao Paulo, Dept Forest Sci, Ave Univ 3780, BR-18610034 Botucatu, SP, BrazilCNPq: 249979/2013-6Elsevier B.V.North Carolina State UnivVirginia Polytech Inst & State UnivForestry Sci & Res InstUniversidade Estadual Paulista (Unesp)Universidade de São Paulo (USP)Scolforo, Henrique FerracoMcTague, John PaulBurkhart, HaroldRoise, JosephMcCarter, JamesAlvares, Clayton AlcardeStape, Jose Luiz [UNESP]2020-12-10T19:36:21Z2020-12-10T19:36:21Z2019-09-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article22-33http://dx.doi.org/10.1016/j.foreco.2019.06.006Forest Ecology And Management. Amsterdam: Elsevier, v. 448, p. 22-33, 2019.0378-1127http://hdl.handle.net/11449/19618610.1016/j.foreco.2019.06.006WOS:000486553900003Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengForest Ecology And Managementinfo:eu-repo/semantics/openAccess2024-04-30T13:11:15Zoai:repositorio.unesp.br:11449/196186Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:47:38.921415Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availability
title Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availability
spellingShingle Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availability
Scolforo, Henrique Ferraco
Environment
Accuracy
Climatic water deficit
Volume
Basal area
Forest production
title_short Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availability
title_full Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availability
title_fullStr Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availability
title_full_unstemmed Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availability
title_sort Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availability
author Scolforo, Henrique Ferraco
author_facet Scolforo, Henrique Ferraco
McTague, John Paul
Burkhart, Harold
Roise, Joseph
McCarter, James
Alvares, Clayton Alcarde
Stape, Jose Luiz [UNESP]
author_role author
author2 McTague, John Paul
Burkhart, Harold
Roise, Joseph
McCarter, James
Alvares, Clayton Alcarde
Stape, Jose Luiz [UNESP]
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv North Carolina State Univ
Virginia Polytech Inst & State Univ
Forestry Sci & Res Inst
Universidade Estadual Paulista (Unesp)
Universidade de São Paulo (USP)
dc.contributor.author.fl_str_mv Scolforo, Henrique Ferraco
McTague, John Paul
Burkhart, Harold
Roise, Joseph
McCarter, James
Alvares, Clayton Alcarde
Stape, Jose Luiz [UNESP]
dc.subject.por.fl_str_mv Environment
Accuracy
Climatic water deficit
Volume
Basal area
Forest production
topic Environment
Accuracy
Climatic water deficit
Volume
Basal area
Forest production
description Growth and yield (G &Y) model systems aim at forecasting forest productivity. The lack of environmental variables to account for how water availability constrains eucalyptus production in Brazil, however, is argued to be a major drawback of these model systems. Thus, this study aimed to develop a stand-level G & Y model system that accounts for water availability (G & Y with SWD), highlighting its usefulness when applied for clonal eucalypt stands under drier climatic conditions. The dataset is composed of remeasurement information of sixteen research sites that span all climatic regions in Brazil. A total of eleven eucalypt clones were planted in single block plots at each site, and extra replications under the rainfall exclusion system were also installed for these eleven clones in fourteen sites. Linear algebra techniques were used to simultaneously fit a compatible set of prediction and projection basal area equations. A stand-level volume equation was also developed. These equations were validated through the use of an independent dataset composed of the rainfall exclusion plots. Finally, the accuracy and usefulness of a conventional G & Y model system applied to clonal eucalypt stands in Brazil was compared to the new proposed G & Y model system, which accounts for the impact of water availability in eucalyptus productivity. The prediction and projection basal area equations accounting for water availability displayed estimates in the order of 5% more accurate compared to the conventional basal area modeling. Stand-level volume estimates were 40% and 74% less biased through the use of the new G & Y model system. This result highlighted how useful and powerful the newly developed approach is, since the model system was capable to provide accurate estimates through the use of the rainfall exclusion plots. The new G & Y model system is a powerful alternative to estimate forest afforestation yield and is fully capable to accurately update forest inventories. The model system can also be used for projecting how forest growth may be impacted by short-term climate variation.
publishDate 2019
dc.date.none.fl_str_mv 2019-09-15
2020-12-10T19:36:21Z
2020-12-10T19:36:21Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.foreco.2019.06.006
Forest Ecology And Management. Amsterdam: Elsevier, v. 448, p. 22-33, 2019.
0378-1127
http://hdl.handle.net/11449/196186
10.1016/j.foreco.2019.06.006
WOS:000486553900003
url http://dx.doi.org/10.1016/j.foreco.2019.06.006
http://hdl.handle.net/11449/196186
identifier_str_mv Forest Ecology And Management. Amsterdam: Elsevier, v. 448, p. 22-33, 2019.
0378-1127
10.1016/j.foreco.2019.06.006
WOS:000486553900003
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Forest Ecology And Management
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 22-33
dc.publisher.none.fl_str_mv Elsevier B.V.
publisher.none.fl_str_mv Elsevier B.V.
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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