Mirzaei, M., Bonyad, A.E., Moradi Emamgheysi, I., Hassanzad Navroodi, I., 2019. Effects of inventory grids on estimation of tree species diversity in semi-arid forests of Iran. Folia Oecologica, 46: 24-29.Species diversity is one of the most important indices used to evaluate the sustainability of forest communities. The sampling method and the number of plots are factors affecting the estimation of plant biodiversity. In the present study, effects of different inventory grids on estimation of tree species diversity were compared in semi-arid forests of Iran. There were selected 50 hectares of these forests representing the regional forests. Sampling procedures were carried out on circular plots (1,000m 2 ) within inventory grids, with dimensions of 50 × 50 m (200 plots), 100 × 50 m (100 plots), 100 × 100 m (50 plots), 200 × 50 m (50 plots), 200 × 100 m (25 plots), and 250 × 200 m (10 plots). For each plot, the type of the species and the number of trees were recorded. Simpson (1-D), Hill (N 2 ), Shannon-Wiener (H ' ), Mc Arthur (N 1 ), Smith-Wilson (E var ) and Margalef (R 1 ) indices were used to estimate the tree species diversity. The inventory grid was evaluated based on the precision and cost criteria (E% 2 × T). The obtained sampling error values showed that the inventory grid consisting of 200 plots exhibited more accuracy for estimating the biodiversity indices. But based on the results of E% 2 × T, the inventory grid with 25 plots was selected as the most appropriate one for estimating the tree species diversity in semi-arid forests. The results of this study can also serve to estimate the tree species diversity in other semi-arid forests of Iran.

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ABSTRACT:Quantitative and qualitative characteristics of Persian oak (Quercus persica) were studied in relation to altitude and slope variations in Ilam province. A total area of 1,500 m 2 (30 × 50 m) was covered in five altitudinal classes ranging from 800 to 1,800 m a.s.l. Samples were taken based on a systematic random sampling method with 24 sample plots at each class. In total, 120 sample plots (in five classes) were collected covering four gradient categories ranging from < 20 to > 60%. An analysis of variance (ANOVA) was carried out to compare differences between group means in gradient categories and Duncan's post-hoc test was performed to reveal differences between the means of various quantitative characteristics (e.g. growing stock, basal area, diameter at breast height, tree height and regeneration) and the altitudinal classes. The Kruskal-Wallis test was used to examine the differences between the means of qualitative variables and different altitudes and slopes categories. The results indicated that variations with altitudes may have a higher impact than slopes on the quantitative characteristics of the oak stands in the region while the qualitative variables of the native species were influenced by both altitudes and slope variations.

Velvet maple (Acer velutinum) is one of the woody species in the Hyrcanian forests. In this study, the relationship between height and diameter of velvet maple was surveyed. A complete list of the selected heightdiameter models was used and nineteen candidate models were considered. Various criteria were chosen and applied to evaluate the predictive performance of the models. These criteria include Akaike information criterion (AIC), Bayesian information criterion (BIC), root mean square error (RMSE), mean error (ME), and adjusted coefficient of determination (R 2 adj ). Fitting of nineteen height-diameter models using nonlinear least square regression showed that all of the parameters in models were significant (P < 0.01). The results of goodness of fit for the calibration and k-fold validation and the performance criteria (RMSE, ME, AIC, R 2 adj and BIC) showed that R 2 adj ranged from 0.743 (model 8) to 0.8592 (model 11) and RMSE from 2.6983 (model 11) to 10.1897 (model 9). The range of ME among the models is from -7.0787 (model 9) up to 0.063m (model 7). By considering the AIC for each model it is evident that model (11) and model (9) have the lowest and highest values, respectively. Plotting the residuals showed that for all these models the residuals were randomly distributed and the models had heterogeneous residuals. According to the results, models (11), (14), (13), (15) and (12) had a better fitness compared to other models. Among these models, model (11) was the best model for predicting total height of Acer velutinum trees in this region.