Background: The release of metals from industrial factories is one of the most important sources ofenvironmental pollution. The present study aimed to determine the concentration of heavy metals likecadmium (Cd), chromium (Cr), manganese (Mn), nickel (Ni), and lead (Pb) in dust around the cementfactory.Methods: A total of 22 dust samples were collected from areas around the cement factory in Isfahanprovince in spring and summer and transferred to laboratory for chemical digestion. Risk index (RI),integrated pollution index (IPI), mean of contamination degree (mCd), and contamination factor (Cfi)were calculated to determine the contamination status.Results: The concentration of heavy metals in the falling dust around the factory was expressed as Cd<Ni <Pb <Mn <Cr. Pearson correlation showed that there is only a significant negative relationshipbetween the concentration of Cd and the distance from the factory. By increasing the distance from thefactory, the concentration of Cd in dust decreased. The results of falling dust analysis showed that Crhas a high-risk potential in two seasons of spring and summer and Cd has a middle level of pollutionin spring.Conclusion: According to the results, the deposited dust of study area is considered as a polluted dustand it is at higher risk of pollution with Cd and Cr.
Basiri R., Moradi M., Kiani B., Maasumi Babaarabi M. (2018): Evaluation of distance methods for estimating population density in Populus euphratica Olivier natural stands (case study: Maroon riparian forests, Iran). J. For. Sci., 64: 230-244.The aim of this study was to determine the performance of distance methods in terms of accuracy, precision, bias, consumed time and sampling efficiency in the Maroon riparian forests, Iran. 40 estimators were used to evaluate the density of Populus euphratica Olivier trees in pure and mixed stands. Fifty quadrates (30 × 30 m) were established in each stand. To evaluate the accuracy, precision, bias, consumed time and efficiency of sampling techniques, relative root mean square error -RRMSE (%), coefficient of variation -CV (%), relative bias -RBIAS (%), t × RBIAS 2 , t × E 2 , where t is study time and E (%) is sampling error at a confidence level of 95%, and efficiency ratio between method j and k (Ef jk ) were used. A compound of three basic distance estimators sampling method and n-tree were the best in both stands according to all criteria for density estimation. Moreover, variable area transect by Parker (g = 3) and quadrat method were the best methods for density estimation only in pure stand, while the angle order-point-centred quarter method was superior in mixed stand. Regarding to the results, we recommend the use of compound of three basic distances (BDAV3) and basic distance-nearest neighbour (BDNN2) for density estimation of P. euphratica stands in riparian forests.
Wild pistachio (Pistacia atlantica Desf.) is an important tree species from dry forests of Eurasia. Seedlings must usually compete with other tree and shrub species in the dry harsh environment of mountain forests. In this study, we identified the main competitor species and evaluated some widely used competition indices, including distance-dependent and distance-independent ones, to quantify the relationship between the reference seedlings and their neighbors. The results indicated that the main competitors are mountain almond (Amygdalus scoparia Spach.), thorny almond (Amygdalus lycioides Spach.), montpellier maple (Acer monspessulanum subsp. cinerascens Boiss.) and other wild pistachio seedlings. We found that competition increases the height growth but reduces the diameter, basal area growth and crown development of wild pistachio seedlings. Some competition indices had a noticeable correlation with seedling growth, indicating that competition does exist. A combination of log-transformed indices could explain 85% of the diameter growth variations, 46% of height growth, 76% of basal area growth and 72% of crown area development with a good precision.
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