PREDICTING SITE INDEX FOR ORIENTAL SPRUCE (PICEA ORIENTALIS L. (LINK)) USING ECOLOGICAL FACTORS IN THE EASTERN BLACK SEA, TURKEY

Oriental spruce is a very important commercial timber species in Turkey. Its distribution area is recognized as one of the 25 biodiversity hotspots in the world. The present study aims to model site index (SI) of oriental spruce stands using some topographic, climatic and edaphic variables in a moun...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Fresenius environmental bulletin 2018-05, Vol.27 (5), p.3107
Hauptverfasser: Yener, Ismet, Altun, Lokman
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 5
container_start_page 3107
container_title Fresenius environmental bulletin
container_volume 27
creator Yener, Ismet
Altun, Lokman
description Oriental spruce is a very important commercial timber species in Turkey. Its distribution area is recognized as one of the 25 biodiversity hotspots in the world. The present study aims to model site index (SI) of oriental spruce stands using some topographic, climatic and edaphic variables in a mountainous ecoregion of the Eastern Black Sea, Turkey. Within this scope, 60 sample plots were visited in the study area, and the height, diameter at breast height and age of sample trees were measured. A soil pit was also dug in each sample plot for analyzing soil properties. Then, some physical (sand, silt, clay, plant available water capacity) and chemical properties (pH, electrical conductivity, organic matter content and exchangeable cations) were examined on each soil sample. Finally, regression tree and multiple linear regression methods were used to model SI. Their adjusted coefficient of determination (R2 adj) values were found to be as 0.70 and 0.53, respectively. According to the outperformed model, longitude, soil K+ content and landform were the most important factors affecting the SI. The results show that the regression tree model which is proposed in the present study may be used by forest planners and silviculture experts as a decision support tool for scheduling proper forestry activities.
format Article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2166063533</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2166063533</sourcerecordid><originalsourceid>FETCH-LOGICAL-p113t-ca493324c0c609c2fa017336166cf6305f575a50c15fdf8e096024e38ef3c7823</originalsourceid><addsrcrecordid>eNo9zVFLwzAQB_AiCo6573DgywZWklybto81S7fQ0pYkBX0aJTYPQ9xct3c_uhWH9_L_c3C_uwlmlFMSMiTR7dQJTcOI0-w-WIzjnkzDWcI4zoLvVsu1ElbVGzDKSlD1Wr5C0WhotJK1zSswre6EhGWrhMz_18pA9QzLStXlagWd-RWkaKpmo8R0VOTCNtpMHtitBJkbK3UNL1UuSjAyfwLb6VK-PQR3vv8Yh8U150FXSCu24RUKj5TiOXR9lCGyyBHHSeaY7wlNEDnl3HmOJPZxEvcxcTT27z4dSMYJiwZMB48uSRnOg8c_93g6fF2G8bzbHy6nz-nljk0I4Rgj4g85gU_y</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2166063533</pqid></control><display><type>article</type><title>PREDICTING SITE INDEX FOR ORIENTAL SPRUCE (PICEA ORIENTALIS L. (LINK)) USING ECOLOGICAL FACTORS IN THE EASTERN BLACK SEA, TURKEY</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Yener, Ismet ; Altun, Lokman</creator><creatorcontrib>Yener, Ismet ; Altun, Lokman</creatorcontrib><description>Oriental spruce is a very important commercial timber species in Turkey. Its distribution area is recognized as one of the 25 biodiversity hotspots in the world. The present study aims to model site index (SI) of oriental spruce stands using some topographic, climatic and edaphic variables in a mountainous ecoregion of the Eastern Black Sea, Turkey. Within this scope, 60 sample plots were visited in the study area, and the height, diameter at breast height and age of sample trees were measured. A soil pit was also dug in each sample plot for analyzing soil properties. Then, some physical (sand, silt, clay, plant available water capacity) and chemical properties (pH, electrical conductivity, organic matter content and exchangeable cations) were examined on each soil sample. Finally, regression tree and multiple linear regression methods were used to model SI. Their adjusted coefficient of determination (R2 adj) values were found to be as 0.70 and 0.53, respectively. According to the outperformed model, longitude, soil K+ content and landform were the most important factors affecting the SI. The results show that the regression tree model which is proposed in the present study may be used by forest planners and silviculture experts as a decision support tool for scheduling proper forestry activities.</description><identifier>ISSN: 1018-4619</identifier><identifier>EISSN: 1610-2304</identifier><language>eng</language><publisher>Freising: Parlar Scientific Publications</publisher><subject>Biodiversity ; Biodiversity hot spots ; Cation exchanging ; Cations ; Chemical properties ; Commercial species ; Electrical conductivity ; Electrical resistivity ; Forestry ; Landforms ; Organic chemistry ; Organic matter ; Regression analysis ; Regression models ; Silt ; Silviculture ; Site index ; Soil analysis ; Soil properties</subject><ispartof>Fresenius environmental bulletin, 2018-05, Vol.27 (5), p.3107</ispartof><rights>Copyright Parlar Scientific Publications May 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784</link.rule.ids></links><search><creatorcontrib>Yener, Ismet</creatorcontrib><creatorcontrib>Altun, Lokman</creatorcontrib><title>PREDICTING SITE INDEX FOR ORIENTAL SPRUCE (PICEA ORIENTALIS L. (LINK)) USING ECOLOGICAL FACTORS IN THE EASTERN BLACK SEA, TURKEY</title><title>Fresenius environmental bulletin</title><description>Oriental spruce is a very important commercial timber species in Turkey. Its distribution area is recognized as one of the 25 biodiversity hotspots in the world. The present study aims to model site index (SI) of oriental spruce stands using some topographic, climatic and edaphic variables in a mountainous ecoregion of the Eastern Black Sea, Turkey. Within this scope, 60 sample plots were visited in the study area, and the height, diameter at breast height and age of sample trees were measured. A soil pit was also dug in each sample plot for analyzing soil properties. Then, some physical (sand, silt, clay, plant available water capacity) and chemical properties (pH, electrical conductivity, organic matter content and exchangeable cations) were examined on each soil sample. Finally, regression tree and multiple linear regression methods were used to model SI. Their adjusted coefficient of determination (R2 adj) values were found to be as 0.70 and 0.53, respectively. According to the outperformed model, longitude, soil K+ content and landform were the most important factors affecting the SI. The results show that the regression tree model which is proposed in the present study may be used by forest planners and silviculture experts as a decision support tool for scheduling proper forestry activities.</description><subject>Biodiversity</subject><subject>Biodiversity hot spots</subject><subject>Cation exchanging</subject><subject>Cations</subject><subject>Chemical properties</subject><subject>Commercial species</subject><subject>Electrical conductivity</subject><subject>Electrical resistivity</subject><subject>Forestry</subject><subject>Landforms</subject><subject>Organic chemistry</subject><subject>Organic matter</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Silt</subject><subject>Silviculture</subject><subject>Site index</subject><subject>Soil analysis</subject><subject>Soil properties</subject><issn>1018-4619</issn><issn>1610-2304</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNo9zVFLwzAQB_AiCo6573DgywZWklybto81S7fQ0pYkBX0aJTYPQ9xct3c_uhWH9_L_c3C_uwlmlFMSMiTR7dQJTcOI0-w-WIzjnkzDWcI4zoLvVsu1ElbVGzDKSlD1Wr5C0WhotJK1zSswre6EhGWrhMz_18pA9QzLStXlagWd-RWkaKpmo8R0VOTCNtpMHtitBJkbK3UNL1UuSjAyfwLb6VK-PQR3vv8Yh8U150FXSCu24RUKj5TiOXR9lCGyyBHHSeaY7wlNEDnl3HmOJPZxEvcxcTT27z4dSMYJiwZMB48uSRnOg8c_93g6fF2G8bzbHy6nz-nljk0I4Rgj4g85gU_y</recordid><startdate>20180501</startdate><enddate>20180501</enddate><creator>Yener, Ismet</creator><creator>Altun, Lokman</creator><general>Parlar Scientific Publications</general><scope>7ST</scope><scope>7T7</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>SOI</scope></search><sort><creationdate>20180501</creationdate><title>PREDICTING SITE INDEX FOR ORIENTAL SPRUCE (PICEA ORIENTALIS L. (LINK)) USING ECOLOGICAL FACTORS IN THE EASTERN BLACK SEA, TURKEY</title><author>Yener, Ismet ; Altun, Lokman</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p113t-ca493324c0c609c2fa017336166cf6305f575a50c15fdf8e096024e38ef3c7823</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Biodiversity</topic><topic>Biodiversity hot spots</topic><topic>Cation exchanging</topic><topic>Cations</topic><topic>Chemical properties</topic><topic>Commercial species</topic><topic>Electrical conductivity</topic><topic>Electrical resistivity</topic><topic>Forestry</topic><topic>Landforms</topic><topic>Organic chemistry</topic><topic>Organic matter</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Silt</topic><topic>Silviculture</topic><topic>Site index</topic><topic>Soil analysis</topic><topic>Soil properties</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yener, Ismet</creatorcontrib><creatorcontrib>Altun, Lokman</creatorcontrib><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Fresenius environmental bulletin</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yener, Ismet</au><au>Altun, Lokman</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>PREDICTING SITE INDEX FOR ORIENTAL SPRUCE (PICEA ORIENTALIS L. (LINK)) USING ECOLOGICAL FACTORS IN THE EASTERN BLACK SEA, TURKEY</atitle><jtitle>Fresenius environmental bulletin</jtitle><date>2018-05-01</date><risdate>2018</risdate><volume>27</volume><issue>5</issue><spage>3107</spage><pages>3107-</pages><issn>1018-4619</issn><eissn>1610-2304</eissn><abstract>Oriental spruce is a very important commercial timber species in Turkey. Its distribution area is recognized as one of the 25 biodiversity hotspots in the world. The present study aims to model site index (SI) of oriental spruce stands using some topographic, climatic and edaphic variables in a mountainous ecoregion of the Eastern Black Sea, Turkey. Within this scope, 60 sample plots were visited in the study area, and the height, diameter at breast height and age of sample trees were measured. A soil pit was also dug in each sample plot for analyzing soil properties. Then, some physical (sand, silt, clay, plant available water capacity) and chemical properties (pH, electrical conductivity, organic matter content and exchangeable cations) were examined on each soil sample. Finally, regression tree and multiple linear regression methods were used to model SI. Their adjusted coefficient of determination (R2 adj) values were found to be as 0.70 and 0.53, respectively. According to the outperformed model, longitude, soil K+ content and landform were the most important factors affecting the SI. The results show that the regression tree model which is proposed in the present study may be used by forest planners and silviculture experts as a decision support tool for scheduling proper forestry activities.</abstract><cop>Freising</cop><pub>Parlar Scientific Publications</pub></addata></record>
fulltext fulltext
identifier ISSN: 1018-4619
ispartof Fresenius environmental bulletin, 2018-05, Vol.27 (5), p.3107
issn 1018-4619
1610-2304
language eng
recordid cdi_proquest_journals_2166063533
source Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
subjects Biodiversity
Biodiversity hot spots
Cation exchanging
Cations
Chemical properties
Commercial species
Electrical conductivity
Electrical resistivity
Forestry
Landforms
Organic chemistry
Organic matter
Regression analysis
Regression models
Silt
Silviculture
Site index
Soil analysis
Soil properties
title PREDICTING SITE INDEX FOR ORIENTAL SPRUCE (PICEA ORIENTALIS L. (LINK)) USING ECOLOGICAL FACTORS IN THE EASTERN BLACK SEA, TURKEY
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T04%3A37%3A37IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=PREDICTING%20SITE%20INDEX%20FOR%20ORIENTAL%20SPRUCE%20(PICEA%20ORIENTALIS%20L.%20(LINK))%20USING%20ECOLOGICAL%20FACTORS%20IN%20THE%20EASTERN%20BLACK%20SEA,%20TURKEY&rft.jtitle=Fresenius%20environmental%20bulletin&rft.au=Yener,%20Ismet&rft.date=2018-05-01&rft.volume=27&rft.issue=5&rft.spage=3107&rft.pages=3107-&rft.issn=1018-4619&rft.eissn=1610-2304&rft_id=info:doi/&rft_dat=%3Cproquest%3E2166063533%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2166063533&rft_id=info:pmid/&rfr_iscdi=true