A. Alijanpour, A. Banj Shafiei , A. Asghari1,
Volume 3, Issue 7 (6-2014)
Abstract
Cornalian cherry (Cornus mas L.) is a native woody species in Arasbaran, N.W. Iran. It commonly grows as a wild tree on the forest edges and in forest openings areas. In this study, the influence of physiographic and environmental factors such as aspect, climate (temperature, precipitation) and physical and chemical properties of soil on the tree ring width of Cornalian cherry was examined and statistically analyzed. Totally, 48 trees at four aspects (north, east, west and south), 12 trees in each one, were randomly selected, and a 2 cm thick disk was taken at 10 cm height above ground for each stem. For soil analysis, a soil sample was taken from 0 to 30 cm of depth just next to those stems in which the discs had been got in each aspect (totally 48 samples). After scanning the disks, the width of growth rings was measured using Image-j software. Comparison of tree ring width average in different aspects using Duncan's multiple comparison showed that there was significant difference between average widths in different aspects (α=0.05). The tree ring width in the east aspect had the most growth (1.34 mm) compared to others. The relationship between the rings width and climate conditions (precipitation and temperature) was shown using Pearson's correlation. It was found that there was a significant positive relationship between the annual ring width and temperature in northern and eastern aspects and between the width of the annual rings and precipitation in the southern aspect. Soil results also showed that CaCo3% (28.8), clay% (45), NH4+ (57.3 mg/kg), NO3- (12 mg/kg) and exchangeable Ca (22.9 cmol/kg) were significantly higher in the east compared to other aspects. Eventually, using cornellian cherry as a multi-purposes species suggested the possibility of rehabilitating degraded forest stands in Arasbaran region, which is located in the eastern aspect.
H. Modares Gorji, M. Pir Bavaghar, L. Ghahramani,
Volume 4, Issue 13 (12-2015)
Abstract
The study site, Armardeh forest, is located in Baneh, Kurdistan Province. The study area covers approximately 17000 ha. In this study, logistic regression and discriminant analysis methods were used and their performances were compared. Two random sampling grids were overlaid on the presence and absence area of Quercus libani type as dependent variables. Physiographic factors including slope, aspect, elevation and distance from drains were extracted for each sampling site and considered as independent variables. The results showed that the area under the ROC curve (0.746) for logistic regression method is higher than the discriminant analysis with 0.502. Furthermore, the overall accuracy of the classification of the logistic regression was higher than discriminate analysis. The results of this study can be used in management and restoration of these forests.
R. Abedi,
Volume 9, Issue 4 (2-2021)
Abstract
The current study aimed to investigate changes in growth models of hornbeam (Carpinus betulus), as the most abundant species in Arasbaran forest, at different altitude ranges and aspects. Sampling was performed in one-hectare plots at the altitude range of 1200 to 1500 meters and hornbeam trees were measured on the diameter at the breast height (DBH), total height and the diameter of crown canopy. Data analysis was carried out by Nonlinear Regression Models and the best models were fitted based on maximum correlation coefficient, coefficient of determination, minimum standard error and Akaike coefficient for the relationship between diameter (independent variables), and height, basal area and the crown canopy (dependent variable). Results showed that there was a positive correlation between DBH, height, and basal area of trees (r = 0.994) but DBH and crown canopy had a negative correlation. In addition, there was a significant difference in height and crown canopy of the trees across altitudes and aspects. The results of nonlinear models revealed that Exponential Linear Model, Rational Model, Heat Capacity, Sinusoidal, Exponential Association 3, Gaussian, Natural Logarithm and Reciprocal Quadratic YD were the most important models. The hornbeam species follows different models at different altitudes and aspects (except in the northeast aspect which only showed a Rational Model at different altitudes). Nonlinear Regression Models performed reasonable in showing the relationship between tree characteristics including diameter-basal area and diameter-canopy cover. It is recommended to use such models for other species in the region with environmental factors to provide complementary results for more accurate management guidelines.
