Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availability
Autor(a) principal: | |
---|---|
Data de Publicação: | 2019 |
Outros Autores: | , , , , , |
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. |
id |
UNSP_a196e41a6e8ee696ce0f19ca2ba1d037 |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/196186 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
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 |
|
_version_ |
1808129249230454784 |