ABSTRACT Background: Biomass increment, one of the main components of net primary production (NPP) in forest ecosystems, plays an important role as well as total biomass in the global carbon cycle. In this study, the changes of increments of the above-ground total, stem and branch biomasses depending on stand characteristics (i.e., stand age, stand density, and site index) were investigated, and these relations were modeled for Crimean pine (Pinus nigra J.F.Arnold subsp. pallasiana (Lamb.) Holmboe) stands in Taşköprü region of Türkiye. Data were obtained from 109 sample trees within 74 sample plots representing the wide range of possible stand characteristics. Results: The equations developed for above-ground total, stem and branch biomass increments have quite high coefficients of determination (R 2 =0.784, 0.684 and 0.780, respectively), whereas low root mean square errors (RMSE=0.749, 0.692 and 0.116, respectively). The results indicated that the biomass increment estimates from the allometric equations developed were decreasing with stand age and increasing with stand density and site index and also stand density is the strongest stand characteristic on biomass increment. Conclusion: The estimates are also consistent with the growth patterns, so the equations can be used for biomass increment estimations and also for carbon storage and NPP projections for Crimean pine stands of the region.

ABSTRACT Background: Leaf area index (LAI) is an important stand characteristic in terms of forest productivity and stand growth, and it shows significant correlations with other stand characteristics. In this study, it is aimed to reveal the relationships between LAI and some other stand characteristics, i.e. mean diameter, stand age, dominant height, site index, number of trees, stand basal area, stand density, total crown biomass and crown dimensions for Anatolian black pine (Pinus nigra J.F. Arnold subsp. pallasiana (Lamb.) Holmboe) stands in Kastamonu region, which is one of the economically important tree species in Türkiye, and to develop a regression model for LAI estimations by using these relationships. Results: The data obtained from 119 temporary sample plots were used in the study. According to the results, stand basal area, stand density, total crown biomass, dominant height, number of trees, mean diameter, and site index positively correlated with LAI. LAI values were significantly different in terms of stand density and site classes. Among the candidate models for LAI estimations, the model containing site index and stand density as independent variables was the most successful model with the adjusted coefficient of determination ( R adj 2) of 0,63 and the Akaike information criterion ( AIC) of -67,25. Conclusion: The LAI, which is difficult to measure directly in practice, of Anatolian black pine stands in Kastamonu region of Türkiye could be estimated accurately with the help of the equation developed.

ABSTRACT Development of artificial neural network (ANN) models to estimate stem tapers of individual trees in mixed Fagus orientalis and Abies nordmanniana subsp. Equi-trojani stands distributed in Karabük region of Turkey, and comparison of the ANN models with stem taper equations were aimed in this study. The measurements were obtained from 516 sample trees (238 for Oriental beech and 278 for Kazdağı fir) in mixed stands of Karabük region. The measurements included diameter at breast height, tree height, diameter at stump height, and diameters at intervals of 1 m along the stem. In total, 45 ANN models and four stem taper equations were developed. Estimation performances of ANN models and stem taper equations were compared using relative rankings according to seven goodness-of-fit criteria. As a result, the ANN models were more successful in estimation of stem taper for both tree species. The most successful ANN model structures were (i) the model using logistic function in hidden layer with 10 nodes and hyperbolic tangent function in output layer for Fagus orientalis, and (ii) the model using logistic function in hidden layer with 10 nodes and linear function in output layer for Abies nordmanniana subsp. Equi-trojani.