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Please use this identifier to cite or link to this item: http://142.54.178.187:9060/xmlui/handle/123456789/15551
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dc.contributor.authorGULSOY, SERKAN-
dc.contributor.authorSUEL, HALIL-
dc.contributor.authorCELIK, HALIL-
dc.contributor.authorOZDEMIR, SERKAN-
dc.contributor.authorOZKAN, KURSAD-
dc.date.accessioned2023-01-05T04:56:17Z-
dc.date.available2023-01-05T04:56:17Z-
dc.date.issued2014-03-05-
dc.identifier.citationGülsoy, S., Süel, H., Çelik, H. A. L. I. L., Özdemir, S., & Özkan, K. (2014). Modelling site productivity of Anatolian black pine stands in response to site factors in Buldan District, Turkey. Pakistan Journal of Botany, 46(1), 213-220.en_US
dc.identifier.issn2070-3368-
dc.identifier.urihttp://142.54.178.187:9060/xmlui/handle/123456789/15551-
dc.description.abstractThis study was performed to determine modeling height growth of Anatolian black pine (Pinusnigra Arn. ssp. pallasiana (Lamb.) Holmboe) stands according to the site factors in the Buldan forest district. Site index and environmental data obtained from 19 sample plots in the district were fitted by Stepwise Multiple Regression Analysis (SMRA) and Regression Tree (RT) using SPSS 17.0 and DTREG softwares. Schist structured quartzites, slope position and clay percent of B horizon (R2 =0,67) were determined as the most significant variables for the model obtained from SMRA. Two different models were determined by RT statistics. The first one was represented by slope position and altitude (R2 =0,67), while slope position and surface stoniness were the most important variables in the second model and prediction values of site index were separately calculated by all these models. Consequently, R2 =0,84 was the most significance level when theaverage of these prediction values correlated with the actual site index values.en_US
dc.language.isoenen_US
dc.publisherKarachi: Pakistan Botanical Societyen_US
dc.titleMODELING SITE PRODUCTIVITY OF ANATOLIAN BLACK PINE STANDS IN RESPONSE TO SITE FACTORS IN BULDAN DISTRICT, TURKEYen_US
dc.typeArticleen_US
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