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404793 occurrences (No.42 in the rank) during 5 years in the PubMed. [cache]
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404793 occurrences (No.42 in the rank) during 5 years in the PubMed. [cache]
| 2) 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%. |
| PMID:34657980 DOI:10.1007/s10661-021-09524-x |
| 2021 Environmental monitoring and assessment |
| * Bark thickness models for oak forests being converted from coppice to high forests in Northwestern Turkey. |
| - 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. |
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