Determining Indicator Plant Species of Pinus brutia Ten. Using Interspecific Correlation Analysis in Antalya (Turkey)

Detalhes bibliográficos
Autor(a) principal: Özdemir, Serkan
Data de Publicação: 2023
Outros Autores: Çınar, Tunahan
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Cerne (Online)
Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/3188
Resumo: Background: We performed a vegetation study in Antalya, where the Mediterranean climate prevails, in order to determine the indicator plant species of red pine (Pinus brutia Ten.). Red pine can be widely distributed from sea level to 1200 meters. Its main distribution is in the main Mediterranean vegetation zone between 500-1000 meters. However, the variation of the habitat factors may be low in this range. Therefore, the productivity relationships of species such as red pine, whose sustainable use is important, cannot be directly explained by environmental variables. In such cases, it is important to determine the indicator plant species. For this reason, indicator plant species were determined by using interspecific correlation analysis (ICA) in the study. Then, using principal components analysis, the relationship of indicator plant species with the variables of elevation, slope, aspect and soil depth was revealed. In the principal components analysis, the plant species that were determined as an indicator were also added to the graph as a class variable, and the effects of the variables on the indicator plant species were also investigated. Results: The results of the ICA showed that Dryopteris flix-mas (L.) Schott, Abies cilicica (Antoine & Kotschy) Carrière, Cedrus libani A. RICH and Colutea cilicica Boiss. & Bal. species were negative indicators of productivity. On the other hand, Cistus creticus L. and Smilax aspera L. species were positive indicators of productivity. Conclusions: Interspecific correlation analysis is a useful tool to determine the ecological properties of species that have a local distribution or a vertical distribution in a narrow altitude range. It also offers practical and effective results, especially for species with high commercial value such as red pine.    
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spelling Determining Indicator Plant Species of Pinus brutia Ten. Using Interspecific Correlation Analysis in Antalya (Turkey)Interspecific Correlation AnalysisPrincipal Component AnalysisRed PineSite Index ValueBackground: We performed a vegetation study in Antalya, where the Mediterranean climate prevails, in order to determine the indicator plant species of red pine (Pinus brutia Ten.). Red pine can be widely distributed from sea level to 1200 meters. Its main distribution is in the main Mediterranean vegetation zone between 500-1000 meters. However, the variation of the habitat factors may be low in this range. Therefore, the productivity relationships of species such as red pine, whose sustainable use is important, cannot be directly explained by environmental variables. In such cases, it is important to determine the indicator plant species. For this reason, indicator plant species were determined by using interspecific correlation analysis (ICA) in the study. Then, using principal components analysis, the relationship of indicator plant species with the variables of elevation, slope, aspect and soil depth was revealed. In the principal components analysis, the plant species that were determined as an indicator were also added to the graph as a class variable, and the effects of the variables on the indicator plant species were also investigated. Results: The results of the ICA showed that Dryopteris flix-mas (L.) Schott, Abies cilicica (Antoine & Kotschy) Carrière, Cedrus libani A. RICH and Colutea cilicica Boiss. & Bal. species were negative indicators of productivity. On the other hand, Cistus creticus L. and Smilax aspera L. species were positive indicators of productivity. Conclusions: Interspecific correlation analysis is a useful tool to determine the ecological properties of species that have a local distribution or a vertical distribution in a narrow altitude range. It also offers practical and effective results, especially for species with high commercial value such as red pine.    CERNECERNE2023-04-26info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/3188CERNE; Vol. 29 No. 1 (2023); e-103188CERNE; v. 29 n. 1 (2023); e-1031882317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://cerne.ufla.br/site/index.php/CERNE/article/view/3188/1335http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessÖzdemir, SerkanÇınar, Tunahan2023-05-05T11:55:38Zoai:cerne.ufla.br:article/3188Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2024-05-21T19:54:50.828395Cerne (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv Determining Indicator Plant Species of Pinus brutia Ten. Using Interspecific Correlation Analysis in Antalya (Turkey)
title Determining Indicator Plant Species of Pinus brutia Ten. Using Interspecific Correlation Analysis in Antalya (Turkey)
spellingShingle Determining Indicator Plant Species of Pinus brutia Ten. Using Interspecific Correlation Analysis in Antalya (Turkey)
Özdemir, Serkan
Interspecific Correlation Analysis
Principal Component Analysis
Red Pine
Site Index Value
title_short Determining Indicator Plant Species of Pinus brutia Ten. Using Interspecific Correlation Analysis in Antalya (Turkey)
title_full Determining Indicator Plant Species of Pinus brutia Ten. Using Interspecific Correlation Analysis in Antalya (Turkey)
title_fullStr Determining Indicator Plant Species of Pinus brutia Ten. Using Interspecific Correlation Analysis in Antalya (Turkey)
title_full_unstemmed Determining Indicator Plant Species of Pinus brutia Ten. Using Interspecific Correlation Analysis in Antalya (Turkey)
title_sort Determining Indicator Plant Species of Pinus brutia Ten. Using Interspecific Correlation Analysis in Antalya (Turkey)
author Özdemir, Serkan
author_facet Özdemir, Serkan
Çınar, Tunahan
author_role author
author2 Çınar, Tunahan
author2_role author
dc.contributor.author.fl_str_mv Özdemir, Serkan
Çınar, Tunahan
dc.subject.por.fl_str_mv Interspecific Correlation Analysis
Principal Component Analysis
Red Pine
Site Index Value
topic Interspecific Correlation Analysis
Principal Component Analysis
Red Pine
Site Index Value
description Background: We performed a vegetation study in Antalya, where the Mediterranean climate prevails, in order to determine the indicator plant species of red pine (Pinus brutia Ten.). Red pine can be widely distributed from sea level to 1200 meters. Its main distribution is in the main Mediterranean vegetation zone between 500-1000 meters. However, the variation of the habitat factors may be low in this range. Therefore, the productivity relationships of species such as red pine, whose sustainable use is important, cannot be directly explained by environmental variables. In such cases, it is important to determine the indicator plant species. For this reason, indicator plant species were determined by using interspecific correlation analysis (ICA) in the study. Then, using principal components analysis, the relationship of indicator plant species with the variables of elevation, slope, aspect and soil depth was revealed. In the principal components analysis, the plant species that were determined as an indicator were also added to the graph as a class variable, and the effects of the variables on the indicator plant species were also investigated. Results: The results of the ICA showed that Dryopteris flix-mas (L.) Schott, Abies cilicica (Antoine & Kotschy) Carrière, Cedrus libani A. RICH and Colutea cilicica Boiss. & Bal. species were negative indicators of productivity. On the other hand, Cistus creticus L. and Smilax aspera L. species were positive indicators of productivity. Conclusions: Interspecific correlation analysis is a useful tool to determine the ecological properties of species that have a local distribution or a vertical distribution in a narrow altitude range. It also offers practical and effective results, especially for species with high commercial value such as red pine.    
publishDate 2023
dc.date.none.fl_str_mv 2023-04-26
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://cerne.ufla.br/site/index.php/CERNE/article/view/3188
url https://cerne.ufla.br/site/index.php/CERNE/article/view/3188
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/3188/1335
dc.rights.driver.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv CERNE
CERNE
publisher.none.fl_str_mv CERNE
CERNE
dc.source.none.fl_str_mv CERNE; Vol. 29 No. 1 (2023); e-103188
CERNE; v. 29 n. 1 (2023); e-103188
2317-6342
0104-7760
reponame:Cerne (Online)
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Cerne (Online)
collection Cerne (Online)
repository.name.fl_str_mv Cerne (Online) - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv cerne@dcf.ufla.br||cerne@dcf.ufla.br
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