America's political strategy and norms in dealing with countries are not uniform and have a different nature, and the US strategy in the Middle East as one of the most geopolitical and geoeconomic areas has not been excluded. Different religions, oil and gas resources, the formation of the State of Israel, regional and global rivalries of major powers such as China and Russia, Iran's nuclear issues, etc. have caused the US to pay more attention to its international equations in the Middle East. In this study, the reasons for changing and diversifying US strategies towards Middle East with Iran's focus were investigated. The research method is descriptive-field research and the research hypotheses were investigated using Spearman correlation method, model closest to ideal solution (topsis) and Shiite geoculture and questionnaire adjustment. The results of the study showed that most of all, adopting different US strategies and insisting on staying in the Middle East is the question of its current and future energy supply for its industries (sig = 0.304), Also in terms of geopolitical weight among the Middle East countries is Iran (Di = 0.14356), which has attracted most US strategic attention, In other words, the biggest obstacle to achieving US goals is Iran, And finally, the Shiite geoculture is one of the most important factors that make US policies (especially Israel, the energy market and the presence of Russian and Chinese rivals) in the region particularly problematic in Shiite countries.

Introduction: The lack of sufficient information in the pedigree of the animals prevents the correct estimation of the breeding values. Henderson proposed a genetic grouping for a more realistic estimation of breeding values for phenotypic records in different years. For these groups, the birth year, the year that the first daughter of the male had recorded, or the year that the male animal was used for insemination were used for grouping. In fact, this grouping was considered for calculating the genetic trend over the years. The incomplete recording of the animals in the population will result in the elimination of true genetic relationships between animals. Although, these animals are considered as the base animal in the analysis, but not born at the same time, and can affect the accuracy of estimated breeding values. The available pedigree information in Iran does not have a good quality index. So that the average of pedigree completeness criterion for Iranian Holstein cows has been reported less than 0. 7. Genetic evaluation of Iranian Holstein cows with unknown parents may cause a bias in estimating genetic parameters and breeding values. The use of genetic groups in genetic analysis can partly correct the problem of animals with unknown parents. In this regard, the purpose of this study was to estimate the genetic parameters and breeding values of the production traits (milk, fat, protein) of Iranian Holstein cows with and without genetic grouping in model. Materials and Methods: In this study, the pedigree of 1555702 heads of the Iranian Holstein cattle from 14623 sires and 697940 dams that collected by Animal breeding center of Iran till 2013, were used. Production traits, including milk, fat and protein corrected for 305 days and twice milking from first to third lactation periods were used to estimate variance components and breeding values. Herds under 100 heads were not considered for analysis and for all production traits; pedigree related to animals with the record was extracted from the general pedigree using CFC software and used. For animals with unknown parents, genetic grouping was performed based on the sex and the birth year. Traits at different lactation periods analyzed with (model 2) and without (model 1) genetic grouping in the model and genetic trend was calculated. Then the accuracy of breeding values and genetic trend of traits obtained from different models were compared with each other. The Spearman rank correlation was used to investigate the change in animal ranking in a result of considering the genetic grouping. Results and Discussion: The additive genetic variance and their standard error were lower for milk, fat and protein production traits in model with genetic grouping (model 21) than the model without genetic grouping (model 1). The estimated heritability range for milk, fat and protein production in three lactation periods with model 1 was 0. 094-0. 162, 0. 069-0. 114, and 0. 079-0. 123, respectively, that these values were higher than model 21 in terms of magnitude. Spearman rank correlation between the estimated breeding values with model 1 and 21 was significantly different from 1, indicating a change in animal rank with consideration of genetic grouping in the model. The spearman rank correlation was lower for males than females, suggesting a higher change in male animal's rank than females. The average accuracy estimated breeding values with model 21 was higher than model 1 and the average accuracy difference was significant between two models. The genetic trend in the first, second and third lactation periods with the model 21 was estimated 63. 06, 59. 60 and 44. 64 for milk production, 1. 346, 1. 095 and 0. 943 for fat and 1. 542, 1. 514 and 1. 035 kg per year for protein, which were higher than the estimates of model 1. Conclusion: The results showed that consideration of genetic grouping in the model reduced the additive genetic variances of traits and the heritability estimated were higher without consideration of genetic grouping. The significance of the Spearman rank correlation indicates that the rank of males and females changed by inserting genetic groups into the model and change in the animal's rank for males was higher than females. The high accuracy of estimated breeding values and the genetic trends of traits in the model with genetic grouping suggests that genetic grouping for animals with unknown parents has been done and entered into the model in order to more accurately estimate the breeding values and to better reflect the performance of the breeding programs.

Importance of climate change and global warming and effect of soil temperature on issues such as changing the hydrological behavior of the system shows that it is essential to have a clear understanding of the temperature trend especially in arid region. Therefore, in this study, the trend of air temperature and various depths of soil temperature at three central synoptic stations in southeast of Iran including Kerman, Zahedan and Bandar Abbas during the years (1957-2018) was investigated using nonparametric Mann-Kendall test, Spearman test and Pearson's correlation coefficient. For this purpose, monthly and annual air and soil temperatures data in various depths of 5, 20, 50 cm were used. Also the power test percentage method was used to evaluate the accuracy of the methods used. The results demonstrated that the trend of mean air temperature in Kerman and Zahedan station showed a significant increasing trend in annual scale. But, the air temperature at Bandar abbas station did not follow a specific trend. Also, soil surface temperature was increased from surface to depth 20 cm in annual scale at 3 stations. In the monthly scale, , the trend of soil temperature changes was incremental in depth 50 cm from august to December at 3 stations. Based on the test power percentage results, The nonparametric Mann-Kendall test was determined as the most accurate test for estimating air and soil temperature trends.

Given the climatic changes and threats to food security in recent years, they have have become a major issue in agricultural climatology. The present study aimed to investigate the status of agricultural climate suitable for the cultivation of rice in the light of the influential climatic conditions in the past. Given the effect of temperature and the amount of precipitations on rice growth and the sensitivity of rice to these two variables, the study examined the predicted future temperature and rainfall and their effects on rice. Data related to the temperature and rainfalls were obtained from the Meteorological Organization. Additionally, the temperature and agricultural potential of the region were considered. By preparing the agricultural calendar for the cultivation of rice, the correlation between temperature, precipitation and rice productivity was calculated using the Spearman Correlation coefficient. By using the SDSM model, future data and temperature and precipitation return period were determined in the SMADA software. The results demonstrated that minimum spring temperature tended to be late spring. The minimum temperature had the highest impact in April, the maximum temperature had the highest impact in July and the maximum rainfall had the highest effect in both June and July. Based on the results of the prediction models, the studied region would experience an increase in temperature and rainfall by providing favorable conditions for the cultivation of rice. However, delays in the cold season and shortness of the growth period increased the risks associated with the cultivation of rice in this period.

Background and Objectives: Estimating the biomass and carbon content of trees and the other vegetation is important, in particular in context of global warming and climate change and the determination of biomass is essential in order to influence the climate and management of natural resources. In forest areas with high altitudinal gradients, values of the quantitative characteristics of forest stands usually change. The purpose of this study was to determine the effect of altitudinal gradient on quantitative forest characteristics including number of trees per hectare, basal area, standing volume, biomass and carbon storage in District 3 of Sangdeh Forests. Materials and Methods: The area was initially divided into three altitudinal levels, with a range of 1400-1600, 1600-1800 and 1800-2000 m a. s. l. 50 circular sample plots were randomly assigned to each level, resulting in a total sampled area of 10 ares (0. 1ha) to cover each level. In each plot, species type, height and diameter at breast height were recorded for all trees with DBH > 7. 5 cm. Then, the density of all species was determined by sampling followed by further analysis in laboratory. Then, the biomass was calculated in the sample plots based on the FAO global model and the amount of above-ground carbon storage calculated using coefficient. Results: The results showed that from the lowest altitude to the highest the number of trees per ha is 477, 384 and 372 and the basal area is 25. 58, 29. 49 and 30. 84 m2, respectively. Also, the volume per ha were estimated to be 314. 25, 393. 98 and 424. 75 silve, respectively. The results of this research showed the amount of biomass for all three altitudinal levels based on gradient increase is 406. 68, 478. 26 and 522. 30 t ha-1 and carbon stock is 203. 34, 239. 12 and 261. 15 ton per hectare, respectively, that shows an upward trend as the a. s. l. increases. The analysis of variance indicated a significant difference between the altitude and the characteristics (P<0. 05). In addition, Spearman correlation showed that there was a significant correlation between altitude and tree characteristics including basal area, standing volume and above-ground biomass (AGB) per ha (P<0. 01). Conclusion: Conclusively, the results of this research in the study area show that changes in altitude from the sea level have caused changes in some of the quantitative characteristics of forest stands and thus the elevation gradient has been effective on the distribution of AGB, so that with increasing a. s. l, the amount of AGB has also increased and AGB has the highest correlation with the altitude from the sea level.

Understanding the changes in groundwater quality has an important role on the planning and sustainable management of water and soil resources in any region. In this study, trends of groundwater quality of mazandaran plain using the information of the 24 piezometric wells were analyzed during 1994– 2011. For this purpose, the non – parametric Mann – Kendall and Spearman method were used. Before conducting the MK test, the effect of significant lag – 1 serial correlation was removed from the data set. Hydro-geochemical variables that analyzed were the total Anions, total Cations, pH, EC, TDS, SAR, which were measured once in a year, wet and dry periods. The magnitudes of trends were computed using the Sen’ s estimator method. The results showed that the line slope of the density changes of groundwater qualitative variables was downward in 43 percent of variables and upward in 57 percent of them. The results of our tests showed that Kendall and Spearman were positive trend related to variable EC (the equivalent of 56/3 = Z) and Mtghyrkl dissolved solids (TDS) with statistic Z (7. 14), respectively. The results were also indicative of the increase in chemical density and the decrease in quality of the well water in Mazandaran plain at all piezometric stations.

IntroductionDrastic model is an index and overlapping model that has been designed for producing vulnerability scores for different points by combining several thematic layers. Overlapping distinguished methods are the most applicable methods for evaluating vulnerability of aquifers because they are cheap, they can directly reach a defined goal, the used data in the methods are accessible or can be estimated, their final results can easily be described, and they are suitable for managerial decision making. However, ranking system of parameters of this method is an irrational and unreliable system. These classifications are based on Boolean method. If classification is done based on Boolean method, it will cause a zone to displace a story to a higher or lower score with little change which is not acceptable and justifiable. But it seems that one can present a suitable method for classification and ranking using fuzzy theoretical fundamentals compared with Boolean method.

Native and endemic plants are considered as genetic reserves of every habitat and due to favorable morphological traits, resistance to pests and diseases and adaptation to ecological conditions are of utmost importance. The aim of the current research was to identify medicinal plants from Arasbaran flora, Mardanaghomchay watershed and ethnobotanical study related to medicinal plants and its determinant factors. To achieve this goal, after identifying the region's flora and separation of the medicinal plants, data were randomly collected through questionnaires as 180 samples were taken from the population over 20 years old. The results showed that 30% of the region's flora included valuable medicinal plants belonging to 56 genera and 30 families, among them Labiatae, Compositae, Rosacea, Urticaceae, Umbellifereae and Grossulariaceae respectively were more harvested by local people for medicinal purposes. Data analysis of the questionnaires in SPSS software with coefficient correlation of Spearman and Kruskal-Wallis test revealed that among the effective factors on identification of medicinal plants in the region, the relationship between knowledge and harvesting of medicinal plants and access to rural health center for treatment was significant (P=0.05). It means that access to the physician has been effective on knowledge of the local people with medicinal plants and its relation with access of foresters to surrounding towns for cure is significant while there was no significant relation between the knowledge and rural people age, literacy level and the consumption of synthetic drugs (P=0.05).