Biodiversity is one of the most important indicators of ecosystem diversity and dynamism. Birds, as a clinker indicator of ecosystem biodiversity, are considered as the habitat suitability and other necessary living conditions for any species. Therefore, the study of birds, especially migratory birds, is of particular importance as a clinker indicator. Due to the need for studies in this field, the present study was conducted to investigate the desirability of the habitat and identify the most important environmental variables affecting the distribution of the Anser anser species as a migratory and index species in Iran. Using 23 environmental variables and the nine models in the BIOMOD software package under R software, the Anser anser species is distributed in three types of habitats including winter-passing, summer-passing and breeding and stopeover modeling. The findings from species modeling showed that the models, used in species distribution modeling, have high accuracy in studying species distribution. In general, temperature and precipitation variables are the most important, while the variables such as vegetation and distance to roads are less important in the distribution of Anser anser species in Iran.  According to the results, 15.91% of the surface of Iran was identified as a desirable habitat for Anser anser species, which overlaps with 15.95% of the protected areas. Therefore, the used method in this study identifies the desired habitats of the species correctly. Besides, it can be applied as a suitable method to model the habitat suitability of similar species, which is essential from the perspective of conservation providing comprehensive and practical wildlife management programs.

Bird watching or the scientific study of birds is one of the oldest environmental sciences. The migration of birds, especially aquatic species, has long been of interest to many researchers. Birds, as a clinker indicator of ecosystem biodiversity, are considered as the habitat suitability and other necessary living conditions for any species. Therefore, the study of birds, especially migratory waterfowl, is of particular importance. Due to the need for studies in this field, the present study aims to investigate the desirability of the habitat and identify the most important environmental variables affecting the distribution of Anser anser species as a migratory and index aquatic species in Iran.

In this study, 10 presence spots for the summer-passing and breeding population, 116 presence spots for overwintering population and 25 presence spots for the passing population of Anser anser have been applied in order to model the distribution of Anser anser species in three habitat types including winter-passing, summer-passing and hatchery, as well as stopping places in Iran. These spots were obtained from the bird census reports of the Environmental Protection Agency. Three groups of environmental variables including topography, climate and land use / land cover were used to investigate the factors affecting the distribution of Anser anser species. Finally, 23 environmental variables were called for modeling in the biomod software package.

The values ​​of accuracy evaluation indices reveal that models such as FDA and RF have high accuracy in the modeling process out of the nine models implemented in modeling Anser anser stopover. Moreover, variables such as seasonal rainfall, distance to rural areas and the amount of rainfall in the least rainy season play an important role in the selection of stopover by the Anser anser. According to the results of the overlap analysis of the total area of ​​Iran, only 20.99% is known as desirable habitats of this species, which includes 18.69% of the total desirable habitats in protected areas.
Based on from modeling the habitat of summer Anser anser, all the models used in this study have high accuracy in studying the species distribution. On the other hand, the distribution of this species in Iran depends on factors such as distance to wetlands, distance to forest and distance to streams. According to the findings, 3.22% of the total area of ​​Iran is known as a suitable habitat summer Anser anser and overlaps with the presence of species, which is 4.09% of the total summer habitats. Optimal laying and hatching of this species is covered by protected areas.
The results of modeling the Anser anser species in the surface of wintering habitats indicate that all models have high accuracy. The distribution of this species in the surface of wintering habitats is affected by factors such as rainfall, distance to the city and the warmest rainfall of the year. Optimal habitats of this species cover 23.52% of Iran, which is 25.09% of the total desirable habitats of the studied species overlap with protected areas.
Examining the distribution of species at the level of ecological nests and understanding the relationship between environmental variables and the distribution of species using a biomod software package show how species respond to environmental changes at the present time. The findings from evaluating the algorithms used in modeling the habitat types of the Anser anser species reveal that the biomod software package has a high ability to predict the optimal habitats of this species. Thus, it has identified desirable species habitats at the present time, habitats that can be used in the future and have favorable conditions for species introduction, as well as habitats that had ideal conditions in the past. In this regard, the species of Anser anser Choose to spend winters in areas such as Urmia Lake, Fars province, Sistan and Baluchestan, Azerbaijan, Kurdistan and the southern parts of the Caspian Sea and in some eastern and northern areas of the country that have ideal biological conditions. According to the frindings from modeling, the Anser anser is mainly present in summers in Azerbaijan province, especially Urmia Lake and the surrounding wetlands. These areas are more preferred than other parts of the country due to favorable weather conditions, adequate security and availability of food resources. Locations of Anser anser in the country include areas such as the southern shores of the Caspian Sea, parts of the west and northwest, as well as northeastern areas. Proper identification of stops and providing applications to protect these areas is important due to the functional role of stopping places in meeting the needs of migratory species. In general, in the present study, it is found that 15.95% of the total habitats of the Anser anser species are located in protected areas. This indicates the existence of a large part of the desirable habitats of this species outside the protected areas. Therefore, the results of the present study show the need to reconsider the demarcation of protected areas in the future more than in the past in Iran.

The current study aims to investigate the distribution of Anser anser species and the effect of environmental variables on the distribution of this species in Iran using a biomod software package.  Based on the results, the method used in this study correctly identifies the desired habitats of the species and can be used as a suitable method to model the habitat suitability of similar species and also to study the biodiversity of habitats. This is essential from the point of view of conservation and the presentation of comprehensive and practical wildlife management programs.

Global climate change has led to change in the ecological amplitude of plant growth, expand plant adaptation to hot climates, and decrease plant adaptation to cold climates. Climate change resulting from human activities occurs at such a speed that many species will not be able to adapt to it. These changes have led to a change in the range of plants growth. Such high-speed changes have caused subsequent changes in the structure and entire ecosystems of the earth, therefore predicting the effect of climate change on the distribution of plant species has become a major field of research for its conservation measures and programs. Changes in the range of distribution of plants are mostly predicted by species distribution models. In this sense, every environmental factor affecting the distribution of plant species has a minimum, maximum and optimal value, which, in combination with other factors, separates the territory of the species and forms an ecological niche. These models are used to investigate species distribution and are based on ecological niche theory. This research was conducted with the aim of determining the potential habitats of Pistacia vera L. species and the factors affecting it in the present and future in Razavi Khorasan province.

For this purpose, 28 bioclimatic variables including topographic (4 cases), climatic (19 cases), soil (4 cases), and geological (1 case) factors as prediction variables have been analyzed for the correlation coefficient. The variables with high correlation (more than 80 %) have been removed. Environmental variables in ASCII format along with presence points were added for modeling in R software of the desired species. According to the size of the study area, sampling of data points was done based on the field visit during the period 2021-2022 from the introduced areas. through using the Global Positioning System (GPS) of 129 points from 8 regions (as points of presence) were recorded. Then, in order to prevent spatial autocorrelation and reduce the sampling error, the useful areas were converted into 1000×1000 meters grids in ArcGIS 10.5 software, and one presence point was obtained from each cell. In the modeling process, 70 % of the presence points (Pistacia vera L.) were used to generate models and 30 % of the presence points were used to evaluate the performance of the models. Also, to increase the modeling accuracy, the number of repetitions was considered 10. Then all data and points through R software and using Biomed 2 package models including GLM, GBM, CTA, ANN, SRE, FDA, MARS, RF, and MaxEnt Phillips models, in determining the relationship between vegetation and environmental factors in rangelands of Khorasan Razavi province at current and future distribution of this species in 2080-2100 were predicted under climate scenarios ssp1-2.6 and ssp5-8.5 model. The accuracy of the models was evaluated using the values of KAPPA, TSS and ROC indices, which are prominent and widely used indices for determining and identifying the areas of equal potential.

The variables of climatic factors were removed from the modeling due to the high correlation of 80 %, and the analysis was done using four topographic factors, eight climatic factors, four soil factors and one geological factor. The results of this research showed that according to the accuracy evaluation index, the best modeling for the present time is done by the random forest (RF) model with the ROC, KAPPA, and TSS equal to 100. In the future, the 2.6 and 8.5 scenarios of the random forest model for the ROC, KAPPA, and TSS indicators, with the accuracy of 0.999, 0..982, and 0.989 respectively, have the highest level of accuracy; Also, in the random forest model, the factors that had the greatest impact included: Bio12 (annual precipitation) and Bio15 (seasonal precipitation changes) and land unit at the present time, in the future time under the scenario 2.6 Bio12 (annual precipitation) and Bio15 (seasonal precipitation changes) and DEM and in the scenario 8.5 Bio15 (seasonal precipitation changes) and Bio12 (annual precipitation) and aspect. The results of the relative importance show the great influence of climatic factors on the distribution of this species. It is most present in the habitat with an annual rainfall of 200-285 mm, and more than this amount of rainfall was associated with a decrease in suitability for the establishment of the species. Besides, the height of 800-1300 meters above sea level and rainfall changes up to 7.8 mm in seasonal rainfall also had a positive effect on the suitability of the habitat for the presence of wild pistachio. Also, the most desirable habitat is in low to relatively high hills with a rounded and sometimes flat top consisting of limestone, metamorphic, conglomerate, and shale sandstones and a slope of 40 to 50 % and with shallow to relatively deep gravelly soils. The highest distribution of Pistacia vera L. species is in the northeastern region to the east of Khorasan province. In general, by examining the outputs of the random forest model and comparing the areas prone to the growth of Pistacia vera L. species in the present and future climate scenarios, it can be stated that the trend of stable habitat in the province can be expected.

The results of this research can be used to identify areas prone to growth, improvement, development, protection, economic exploitation, and expansion of the habitat of Pistacia vera L. species. From the ecological point of view, the wild pistachio species is considered as one of the most important factors preventing and destroying land in the high mountains of arid and semi-arid regions in many geographical and ecological regions. On the other hand, the economic importance and the income-generating aspect of wild pistachios are also important for local operators. In general, it can be stated that vector machine models provide very good performance for identifying such prone areas. In this research, an attempt was made to evaluate different species distribution vector machine models, and then the most suitable model, which was random forest, was selected.

In recent years, advancements in computer technologies, remote sensing systems, software, and various models have enabled the prediction of ecological niches for diverse plant and animal species. Over the past decades, alterations in human lifestyles, industrialization, and production processes have resulted in increased atmospheric pollutants, leading to severe climate change. Global climate change has induced shifts in plant growth ranges, with an expansion of warm-weather-adapted plants and a decline in cold-weather-adapted ones. These changes consequently modify the structure and ecosystems of the entire planet, directly and indirectly impacting ecosystem services crucial for human well-being and economic prosperity. Consequently, predicting the effects of climate change on plant distribution has emerged as a pivotal research area to inform conservation strategies and programs. Species distribution models primarily predict the impact of climate change on plant growth ranges. Accurate predictions of species distribution are essential for effective conservation planning and sustaining forest ecosystem services in the face of climate change. Given the significance of this issue, this research aimed to identify the most critical climatic and environmental factors influencing the distribution of Rhume ribes L. species and ascertain its current geographical range within Razavi Khorasan Province, located in northeastern Iran.

For this purpose, 68 bioclimatic variables including soil characteristics (45 cases), topographical factors (four cases), and climatic factors (19 cases) were first subjected to correlation analysis as predictive variables and variables with high correlation (above 80%) were removed. Due to the large size of the studied area, sampling of presence points was done with field visits during the period of 1400-1401 of the introduced areas, and a total of 232 presence points from eight regions were registered as presence points using the global positioning system (GPS). Then all the environmental data and presence points in R software using Biomed 2 package models which include GLM, GBM, GAM, CTA, ANN, SRE, FDA, MARS, RF, and MaxEnt models in determining the relationship between vegetation and environmental factors in pastures Razavi Khorasan Province was predicted in the present time. The accuracy of the models was evaluated using the values of KAPPA, TSS, and ROC indices, which are prominent and widely used indices for determining and identifying the potential areas.

The results of this research showed that according to the accuracy evaluation index, the best modeling for the current time is the random forest model with an accuracy of 95.5%, which indicates the accuracy of the modeling at an excellent level. Also, the relative importance of the selected models and the variables that have had the greatest impact at present include digital elevation model (DEM), Average monthly (BIO2), This is the sum of all total monthly precipitation values (BIO12), The average temperatures experienced during the wettest quarter (BIO 8) and the amount of sand at a depth of 15-30 cm from the soil surface (Sand 15-30), which indicates the great influence of climatic factors on the distribution of this species, and in the next stage, the height above sea level and finally the soil factors have the greatest influence. The most distribution of Rhume ribes L. species at present is in the east of Razavi Khorasan Province including the cities of Bakharz, Torbat Jam, Taibad, Zaveh, Khaf, and Rashtkhwar in the form of a strip on their border and in the west of the Province on the border of Koh Sorkh and Neishabur cities and the north of the Province on the border Binaloud, Zabarkhan and Mashhad cities and the south of the Province in Gonabad city has spread in a strip and limited way.

The results of this research can be used to improve, protect, and economically exploit and expand the habitat of the Rhume ribes L. species. Destructive human activities, such as livestock grazing and the corrupt exploitation of rhubarb, combined with climate change, have endangered the current habitats of this species in Razavi Khorasan Province. These unprincipled exploitations, disregarding environmental capacities in natural resource management, are a significant problem in Razavi Khorasan Province and the country, gradually leading to water, soil, and plant loss in the region. While this study sufficiently examined current climatic and soil factors to identify areas suitable for rhubarb species, a deeper understanding is required to effectively restore damaged areas, preserve those at risk, and enhance the predictive capabilities of ecological models. In addition to climatic and soil factors, the potential habitats of plant species are influenced by various factors, including human activities, exploitation methods, livestock grazing, wildlife, economic and social conditions, and other direct and indirect impacts on distribution. Numerous studies have been conducted on different plant species. This research evaluated various machine learning-based species distribution models, selecting random forests as the most suitable. Species distribution models are valuable, cost-effective tools for natural resource managers, increasing their awareness and decision-making abilities regarding the effects of climate change on species.

The purpose of this study was to compare the effectiveness of music training and bilateral brain training with regard to reorganization of brain in reduction of dyscalculia symptoms in female students (aging 7-9).

An experimental pre-post test design (tree groups), and a sample consisting of 20 dyscalculia students were selected randomly, and divided into three groups (music training group, bilateral brain training group and control group). A checklist for dyscalculia diagnosis (APA, 1994), Keymath Test, Wechsler Intelligence Test, Brain-Mapping were used to collect the data.

The findings of research show that music training and bilateral brain training could reduce dyscalculia symptoms and made bioelectric activities in brain (frontal, parietal…). Bilateral brain training reduced symptoms of dyscalculia in all of fields.

Such bilateral brain training and music training could be used to reduce symptoms of dyscalculia disorder.

 Although several studies have been conducted on the relationship between personality traits and sports injuries, their relationship with the occurrence of sports injuries is unclear. Therefore, the purpose of this systematic review study was to review the relationship between personality factors presented in Williams and Anderson’s stress sports injury model.

 The present study was a systematic review. Search for articles was conducted in the specialized databases “Embase,” “Medline,” “SPORTDiscus,” “Biomed Central,” “Web of Science,” and “PubMed” from inception until May 2021. The keywords “sports injury,” “sensation seeking,” “achievement motivation,” “locus of control,” “anxiety,” “personality traits,” and “hardiness” were used for the search.

 The literature search in different databases led to the extraction of 1283 articles. After duplicate removal, article screening, and full-text assessment, 28 articles were found that examined the association between personality traits and sports injuries. The study of the content of these articles showed a significant relationship between trait anxiety and the emergence of sports injuries. However, there are conflicting results regarding the relationship between locus of control and sensation seeking with the occurrence of sports injuries. Additionally, the number of studies on the relationship between hardiness and achievement motivation with sports injuries was limited.

 A review of previous studies suggests a significant relationship between competitive trait anxiety and sports injuries. Further studies are needed to draw better and stronger conclusions about the relationship between mental hardiness, locus of control, sensation seeking, and achievement motivation with sports injuries.

Ankle injuries are one of the most common musculoskeletal injuries in atheletes. Proper landing after jumping leads to the preparation for the next skill as well as prevention of various ankle injuries. This study aims to compare the electrical activity of selected ankle muscles in athletes duirng landing from different heights.

 This is a comparative study. Participants were 15 athletes (Mean age= 18.23 ± 2.3 years, mean height= 183.190 ± 6.3 cm, mean weight= 64.72 ±14.12 kg) with 3-5 years of experience in championship competitions. The landing skill was assessed from different heights (50%, 75%, 100% of maximum jump height). Electrical activity of selected ankle joint muscles (Gastrocnemius and Soleus) was recorded using an eight-channel BIOMED electromyography device with 96.34% validity and 91.29% reliability. Mean and standard deviation were used to describe the data, Shapiro-Wilk test was used to evaluate the normality of data distribution, and repeated measures analysis of variance was used to compare the collected data between groups followed by Bonferroni post hoc test. The significance level was set at 0.05.

 There was no significant difference in co-contraction of medial/lateral gastrocnemius and soleus muscles after jumping from three different heights. The peak contraction amplitude of the lateral gastrocnemius muscle was significantly different between the heights 50-75% (P= 0.006) and 50-100% (P= 0.002). The peak contraction amplitude of the medial gastrocnemius muscle was also significantly different between the heights 50-75% (P= 0.002) and 50-100% (P= 0.007). The peak contraction amplitude of soleus muscles was significantly different between the heights 75-100% (P=0.013) and 50-100% (P= 0.17).

 There is an increase in the contractile activity of selected ankle muscles in the anterior-posterior plane caused by the increase in jump height and subsequent landing due to the optimal use of appropriate strategies to control the eccentric muscle contraction and the extensor torque of the ankle joint by increasing the electrical muscle activity during the ground contact, resulted in the prevention of injury to the ankle joint. Coaches and athletes can use these results to adopt training methods to strengthen these ankle muscles by considering the optimal implementation of landing skills with an injury prevention approach.