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Öğe BIOMASS EQUATIONS FOR CALABRIAN PINE IN THE MEDITERRANEAN REGION OF TURKEY(Croatian Forestry Soc, 2016) Sönmez, Turan; Kahriman, Aydin; Sahin, Abdurrahman; Yavuz, MehmetThe aim of this study was to develop allometric equations for the estimation of above-ground biomass components of Calabrian pine (Pinus brutia Ten.) tree in the Mediterranean Region of Turkey. Using regression analysis, different allometric equations were fitted for the tree components of the above-ground biomass using diameter at breast height (dbh) and tree height as estimators. Two hundred and ninety-two trees between 0.4 and 63.0 cm in dbh were randomly sampled throughout 292 natural, pure Calabrian pine stands in Turkey's Mediterranean Region, where it forms diverse stand structures. Finally, the allometric equations were developed for the tree components of the Calabrian pine tree for the stem, bark, branch, needle and total above-ground biomass. The stem, bark and total biomass equations explained more than 90% of the observed variability, while the branch and needle biomass equations explained 82% and 65%, respectively.Öğe A novel approach to selecting a competition index: the effect of competition on individual-tree diameter growth of Calabrian pine(Canadian Science Publishing, Nrc Research Press, 2018) Kahriman, Aydin; Sahin, Abdurrahman; Sönmez, Turan; Yavuz, MehmetIn this study, we evaluated the performance of 18 competition indices composed of nine distance-dependent and nine distance-independent indices in explaining the variation in individual-tree diameter growth of Calabrian pine (Pinus brutia Ten.) in the central Mediterranean region of Turkey. The data were obtained from 432 sample plots with varying stand age, site index, and stand density. To evaluate the performance of each competition index, the mean square error reduction approach was used relative to the noncompetition. Also, this study compared fixed and mixed effects models to analyze diameter growth. Statistical analyses showed that the best distance-independent competition indices performed as well as the best distance-dependent competition indices. The distance-independent competition index of Schroder and Gadow (1999; Can. J. For. Res. 29(2): 280-283, doi:10.1139/x98-199) performed best and is recommended for use in future growth and yield models to be used in the central Mediterranean region of Turkey. Also, the best selection of competitive neighbors was achieved using the area of influence overlap method, whereas the fixed-radius and angle count sampling methods had no significant improvement in quantifying the competition effects. On the other hand, all mixed effects models provided much better fits than their fixed model counterparts.