Evidence map›Paper›PMID 34657980›Full record

ArticleEnvironmental monitoring and assessment2021

Bark thickness models for oak forests being converted from coppice to high forests in Northwestern Turkey.

Ersel Yilmaz, Emrah Ozdemir, Ender Makineci

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Article in Environmental monitoring and assessment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Ersel YilmazDepartment of Forest Yield and Biometry, Faculty of Forestry, Istanbul University-Cerrahpaşa, 34473, Bahcekoy, Sariyer, Istanbul, Turkey.
Emrah OzdemirDepartment of Forest Yield and Biometry, Faculty of Forestry, Istanbul University-Cerrahpaşa, 34473, Bahcekoy, Sariyer, Istanbul, Turkey.
Ender MakineciDepartment of Soil Science and Ecology, Faculty of Forestry, Istanbul University-Cerrahpaşa, 34473, Bahcekoy, Sariyer, Istanbul, Turkey. emak@istanbul.edu.tr.ORCID http://orcid.org/0000-0003-3396-3279

Funding

Türkiye Bilimsel ve Teknolojik Araştirma Kurumu TOVAG-107O750
6 · The paper itself

Abstract

The research was carried out in the coppice-originated pure oak stands that are being converted to high forests in northwest Turkey. The main goal of the research was to determine the bark thickness (BT) based on tree variables, such as tree diameter at breast height (DBH), total tree height (H), crown diameter (CD), and age (AGE) of the stem sections taken from a total of 350 trees that were destructively sampled from different sites, different oak species (Quercus petraea, Quercus frainetto, Quercus cerris), and different development stages. Models were developed with stepwise multiple regression analysis to predict BT based on the variables. For all oak species, all models obtained by stepwise multiple regression analysis were found to be significant at p = 0.001 level. In Quercus petraea, only the DBH-dependent model explained the variation in BT at a rate of 73%, estimating with an absolute error rate of 21%. The fit statistics of the models (based on DBH and DBH-H explanatory variables) obtained for Quercus frainetto are very close to each other, and they explained the variation in BT at a rate of 69% and estimated with an error rate of 26%. Models (based on DBH and DBH-H explanatory variables) explain the variation in BT in Turkey oak at a rate of 91%, indicating species-specific results. The models based on only DBH can be used with high accuracy to estimate BT.

Indexed as

QuercusEnvironmental MonitoringForestsPlant BarkTurkeyAICDBHQuercus cerrisQuercus frainettoQuercus petraea

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.