فهرست مطالب zeinab jafarian

Environmental factors play a pivotal role in determining the flora and fauna distribution in a region, contributing to increased ecosystem biodiversity and species composition on a large scale. Given the intricate nature of natural systems, species distribution models are employed to comprehend the impact of these factors on species' potential niches. In recent studies, bioclimatic variables from the CHELSA database (1979-2013), derived from temperature and precipitation data interpolation, have been widely used for this purpose.

This study investigates the potential distribution and preference tendencies of Bromus stenostachyus in the Hyrcanian rangelands of Mazandaran province using CHELSA bioclimatic variables, along with physiographic and anthropogenic factors. Stratified random sampling, based on physiognomy-florestic structure, was employed to collect species occurrence data at one square kilometer resolution. After selecting key environmental variables, an ensemble method incorporating seven modeling algorithms—Generalized Linear Model (GLM), Gradient Boosting Machine (GBM), Multivariate Adaptive Regression Spline (MARS), Random Forest (RF), Artificial Neural Network (ANN), Maximum Entropy (Maxent), and Classification Tree Analysis (CTA)—was utilized. Model performances were evaluated using area under the curve (AUC) and threshold-dependent measures such as True Skill Statistic (TSS), Sensitivity, and Specificity. Sensitivity analysis was conducted to determine the importance of environmental variables, and species response curves were plotted based on the most efficient model to identify optimal ecological conditions.

Based on validation criteria, all the fitted models showed excellent performance to predict the species habitat. The ensemble model outperformed single models, and among single models, GBM and RF showed the best performance. According to the results of sensitivity analysis, maximum temperature of warmest month (Bio5) was determined the most important variable to fit the species distribution models, in a way that explained more than a quarter of changes in the distribution. After averaging ten model runs, the species potential distribution map was produced under single models and the ensemble model. Because the prediction of each model depends on its mathematical functions, the distribution models had different results. But in general, the species habitats are distributed in parts of province where the elevation and precipitation are higher than the average elevation and precipitation in the whole province, but their temperature is lower than the average temperature of the province. On the response curves, the optimum habitats for the species were located in areas where the maximum temperature of warmest month is less than 23 °C, temperature annual range is less than 32 °C, precipitation of wettest month is at most 100 mm, isothermality is less than 26 and temperature seasonality is in the range of 63-68. 

The ensemble modeling approach yields more realistic simulations of species distribution by emphasizing common areas of agreement among single models. The study results can inform practical planning for the preservation and management of Hyrcanian rangelands, as well as suggest suitable species for reclamation, rehabilitation, and restoration efforts in ecologically similar areas. These findings facilitate optimal exploitation and informed management decisions while preserving native species.

The aim of this study is to identify the areas prone to gully erosion and landslide as a two-hazard map in the form of a single map in Gorganrood watershed. In addition, the use of two machine learning models such as RF and SVM to establishing the spatial relationship between these hazards and the GEFs and any hazard susceptibility mapping separately. In addition, the validation of the hazards susceptibility maps was conducted based on the ROC curve method, and the best model was chosen with the highest predictive performances. Finally, by combining the susceptibility landslides and gully maps, the two-hazard probability maps were produced, which were a combination of different models and the best model. The results showed a RF model with (AUC = 82.9) for landslide and (AUC = 96.9) for gully erosion have higher accuracy compared to the SVM model with a value of (AUC = 0.76) for landslide and (AUC = 93.9) for gully erosion. Finally, a single and comprehensive map was obtained by combining of the each hazard susceptibility map for identification the areas prone to both hazards based on both models. The final two-hazard map can be used as a valuable tool for sustainable land use planning in multi-hazard prone areas.

Organic carbon is a crucial parameter for assessing soil fertility, productivity, and quality, particularly in dry and semi-dry lands. Rangelands cover approximately 50% of the Earth's land area and store over 33% of the global carbon reservoirs. Considering rangelands as significant terrestrial ecosystems and natural carbon reserves, understanding and quantifying carbon sequestration in these ecosystems is of great importance.

This research focused on rangelands in the southern domain of Damavand mountain. Four height groups were selected based on geographic conditions, regional plant cover, and slope. Each height group represented a different elevation range: group 1 (2504-2664 m), group 2 (2730-2896 m), group 3 (2923-3050 m), and group 4 (3119-3545 m). Soil sampling was conducted at two depths (0-15 cm and 15-30 cm) using 13 random points within each height group. Soil organic carbon and bulk density were measured, and carbon sequestration was calculated at the hectare level by multiplying organic carbon and depth. Regression equations and response surface models (RSM) were developed using design software to predict carbon sequestration and compare their accuracy.

Analysis of variance (ANOVA) showed that only sampling depth significantly affected soil carbon sequestration, while sampling height and the interaction between depth and height had no significant effect. Carbon sequestration was higher at a depth of 15-30 cm compared to 0-15 cm. Among the height groups, group 4 (3119-3545 m) exhibited the highest soil carbon sequestration, followed by group 1 (2504-2664 m). The highest carbon sequestration (6046.54 g/m2) was observed in height group 4 at a depth of 15-30 cm, while the lowest (2250 g/m2) was found in height group 2 at a depth of 0-15 cm. The quadratic model of the response surface methodology demonstrated higher accuracy (R2 = 0.7363) in predicting soil carbon sequestration compared to the linear model (R2 = 0.6014) and the less accurate regression model (R2 = 0.428). The response surface method successfully optimized the inputs, suggesting a height of 3500 meters and a specific depth to achieve a soil carbon sequestration amount of 8088.117 g/m2 with a satisfaction level of 0.976.

The response surface methodology (RSM) proved to be a valuable tool for predicting and optimizing soil carbon sequestration in rangelands, considering different sampling depths and heights. It can also be utilized for predicting various parameters in rangeland science, such as above and underground biomass volume and plant species coverage. RSM offers a novel approach for understanding and managing rangeland ecosystems.

Ecotourism in addition to creating employment and increasing income prevents the outflow of human and material capital from rural areas; which, of course, has positive and negative effects. Then, according many limitations and problems in the study area, including the lack of effective employment opportunities, high unemployment and low incomes, the study of socio-economic effects of ecotourism as the most important dimension of the effects of ecotourism can take an effective step in solving these problems. So, the purpose of this study is to investigate the direct and indirect positive or negative socio-economic and environmental effects of ecotourism on local communities.

The study area is a mountainous watershed, called Balade-Nour, located in the Mazandaran Province, Nour city and in 55 kilometers from the main road of Haraz (Amol-Tehran). The summer grazing lands rangelands of this area are based on communally-council ownership. The research method is based on descriptive-analytical method. Survey data is collected from the sample heads of households and the Islamic Council of the villages. The pre-test questionnaire was used and the reliability coefficient (Cronbach's alpha) was calculated. The content validity of the questionnaire was confirmed by consulting professors and experts. The main variables were determined and the final questionnaires were completed by 214 people of local communities and 9 villages by random sampling method. In these questionnaires, various variables were examined, including socio-economic characteristics of the pastoralists, technical characteristics of the rangelands and other related questions affecting the empowerment of local communities using path way analysis method. Path analysis method is commonly used in investigating the direct and indirect effects of independent variables on the dependent variable. In order to investigate the relationships between the latent variables of the research on each other, the structural equation modeling method has been used.

The results showed that the highest frequency (49.2%) of stakeholders had 50-75 years old. Most respondents (81.8%) had undergraduate degree (ill educated and illetrate). The lowest frequency (0.5%) belonged to people with master's degree or higher. Independent variables explained about 69% of the total variance of ecotourism effects. The sum of direct and indirect effects of social (0.43) and economic (0.37) indicators were the most influential positive factors on the evaluation of ecotourism effects, respectively. Then, work experience, income, and environmental factors had a negative impact on local communities, respectively. Therefore, the social factor as the most important and influential variable of the structural model of analysis both in terms of quantity and in terms of paths of influence reflects the good feeling of the local community about the arrival of tourists and the formation of social connections between people. In addition, have a good effect on the economic situation of the region, especially solving the problem of seasonal unemployment. Hence the social effects and consequently the positive effects that ecotourism has on the livelihood diversity of local communities is so effective that it increases the participation and social cohesion of individuals to work together for the benefit of ecotourism.

According to the results, social index are the main necessary factor causes empowerment the local communities of the studied region. Improving the quality of life, increasing public awareness of the value of rangelands, increasing familiarity with social rights and interest in ancient cultures and traditions, more village fame, encourage and develop people's cultural and social participation, disseminate and strengthen indigenous and local culture, reduce migration, creating opportunities for rural women to work in side jobs, familiarity of tourists and local people with different types of cultural tourism are operational and scientific solutions to encourage ranchers to provide more participation.

Predicting the effect of climate change on native ecosystems is one of the longstanding goals of ecologists and is essential for their conservation and management. Species distribution models (SDMs) are the most widely used tools to predict the effects of climate change on the geographical range of plants. In this study, two regression techniques (GLM and MARS) and two machine learning techniques (ANN and RF), along with environmental factors were used to predict the distribution of Onobrychis cornuta L. The species response to future climate (2050-2070) was investigated under optimistic (SSP1-2.6), pessimistic (SSP3-7.0) and very pessimistic (SSP5-8.5) emission scenarios of the IPSL-CM6A-LR climatic model from CMIP6 models. Based on results, the ensemble model and then MARS presented the most accurate prediction. ANN had the lowest prediction accuracy with a significant difference from other models (p<0.05). The sensitivity analysis revealed altitude (24.64%), maximum temperature of the warmest month (20.31%), temperature seasonality (16.57%) and diurnal range of mean temperature (16%) as the most effective variables on the distribution. According to the ensemble model, the suitable habitat occupies about 27% of the area, but its distribution will be decrease under the future climate. The SSP5-8.5 scenario will have the greatest impact on the displacement of the species distribution range. The resulting prediction maps provide valuable information for conservation strategies, including identifying suitable places for its reintroduction and cultivation in the framework of rangeland management plans.

There were relationships and interactions between plant species and environmental factors. Because there are many effecting environmental factors in natural ecosystems such as rangeland, it is necessary to determine the most important of them to save on cost and time in the management and rehabilitation programs.  To achieve these relationships, there are several methods such as statistical methods including regression and ordination to use. The object of this research is to use logistical regression in the dry Sorkhdeh Rangelands in the Semnan provinces for determination most important soil, topography and climate factors.

The area was divided into 23 homogenous units based on slop, aspect, height and geology, and 10 plots 1m2 were established in each unit for the sampling of vegetation. 6 plant species were recognized as dominant in the study area. 3 soil samples were taken at depths of 0-15 cm in each unit, with a total of 69. Overall, 16 environmental factors were measured, including 3 climatic (mean annual temperature, mean annual precipitation and men annual humidity), 3 topographic (slop, aspect and height) and 10 edaphic (carbon, nitrogen, calcium, phosphorus, potassium, CaCo3, pH, EC, percentage of sand, silt and clay) factors.

The results showed that the vegetation distribution is mainly related to soil characteristics such as soil texture, Caco3, N, EC, and topographic factors such as aspect, and slop. The presence of Salsola dendroides, had a relationship with EC and pH and Hypocylix kerneri had most effectives from sand percent. Salsola arbusculiformis had a direct relationship with Caco3 and clay percent. and Artemisia aucheri with C, mmps, Mmts. Salicornia herbaceae had direct relationships with pH, Clay, K, and Halocnemum strobilaceum with EC. All of the models were significant at p<0.01 level.

As the results of the present research showed, this method was able to extract the most important factors and their effectiveness. Among the advantages of this method, can be referred the possibility of using data on the presence or absence of plant species without using other vegetation information, such as the percentage of plant cover, density and frequency, which are affected by the sampling method, plot size and fluctuation of rainfalls.

Rangelands supply many benefits to society as forage and non-forage goods and services. While some of these can be valued in monetary terms, but it is not possible for some products and services such as recreational use of rangelands. So, the present study was conducted for the purpose of the recreational value of Mazandaran Badab-e Surt GeoPark summer rangelands using the Contingent Valuation Method (CVM) based on the maximum likelihood logit regression model. Data were collected from 311 sample visitors randomly by face-to-face interview and Double-Bounded Dichotomous Choice (DB-DC) questionnaire in 2016- 2017. The results showed that majority of the visitors (96.34%) were Willingness-To-Pay (WTP) for ecotourism in the region. The average WTP for an entrance fee was found to be about $0.4 per visitor, and $2.17 for each family. The total annual recreation value of the region estimated at $39.84 per hectare. Logit regression model indicated that the involved variables, bid, income, number of family members, education, and regional quality were significant. However, based on research findings, the economic value of the recreational function of Badab-e Surt is very low, but other benefits such as environmental culture, job creation for the local community, alternative livelihoods and increased economic prosperity in the region will also be available using a nature tour in addition to the calculated amounts.

Slope instability and landslides are important hazards to human activities that often result in the loss of economic resources, property damage and facilities. These hazards occur in the natural or man-made slopes. In the current study, the maximum entropy model was used which is one of the progressive data mining models, in order to modelling landslide susceptibility map for Gorganrood watershed. In the first step, the landslide inventory map was prepared consiste of 351 landslides. 18 geo-environmental factors were selected as predictors, such as: Digital elevation model, slope percent, aspect, distance from fault, distance from river, distance from road, rainfall, landuse, drainage density, lithology, soil texture, plan curvature, profil curvature, lithological formation, Topographic wetness index, LS factor, stream power index, Relative Slope Position and Surface roughness index. Three different sample data sets (S1, S2, and S3) including 70% for training and 30% for validation were randomly prepared to evaluate the robustness of the model. The accuracy of the predictive model was evaluated by drawing receiver operating characteristic (ROC) curves and by calculating the area under the ROC curve (AUC). The ME model performed excellently both in the degree of fitting and in predictive performance (AUC values well above 0.8), which resulted in accurate predictions. Furthermore, In this study the importance of variables was evaluated by the model. Dem (digital elevation model) (32.4% importance), lithology (22.9% importance) and distance from fault (14.8% importance) were identified respectively the main controlling factor among all other variables.

Communities or ecosystems with higher biodiversity also have higher levels of ecosystem function and services, so the relationship between functional diversity and sustainability of plant communities is essential to predict ecosystem functioning. The aim of the present study was to investigate the relationship between carbon stocks and different species diversity and functional indices as well as the effects of biological and mechanical actions on vegetation and soil components. For this aim, Arengeh watershed with an area of 10098.53 ha in Alborz province was selected. The biological and mechanical measures studied in this study were clumping, seedling and grazing, grazing managementrespectively. The functional diversity indices studied in the sampling area included Rao, CHull, FEve, FDive, and FRich indixes. Vegetation sampling was carried out in systematic-random method in 800 plots of 1 m 2 along 80 transects of 100 m in the growing season of May and June. During each transect, three soil samples were taken from different depths of 0-15 and 15-30 cm in different treatments of regeneration and control. To examine more closely the relationship between variables at both sites, Pearson correlation between soil properties as well as between functional diversity indices and carbon stock was calculated. Species richness and diversity indices and functional diversity indices were calculated using Fdiversity software. Multivariate linear regression was also used to investigate the relationship between carbon stocks of richness indices and species and functional diversity. The results of multivariate regression analysis indicated that the highest R2 was related to carbon biomass of 0.72 and the variables affecting it were species richness. Also, Raochr('39')s, evenness, Shannon and functional diversity indices were influenced by total ecosystem carbon. The results showed that the highest amount of vegetable carbon storage in mechanical treatments related to gabion treatment, surface soil carbon storage lower soil carbon storage related to mortar rock treatment and was observed total soil carbon sequestration in treatment Gabion. Also, for biological treatments, grazing, piling, natural rangeland, and exclosure had the highest carbon storage, litter, surface soil, lower soil and total carbon sequestration, respectively.

Species richness is a simple and interpretable indicator of biodiversity and is one of the most important and and practical measurements in the rangeland ecosystems. Experimental models of richness are used to determine the points of richness of suitable and unsuitable species, and the factors affecting it. The aim of this study is to compare two methods of modeling species richness S-SDM and MEM in the Sorkh-Griveh rangelands in Mazandaran province. For sampling of vegetation and soil, random-systematic stratification method was used. In each sampling unit, 10 plots of 1m2 and a total of 260 plots of one square meter were located. Species list, presence and absence of species were recorded in each plot. Also, three soil samples were taken in each sampling unit from a depth of 0-30 cm. Data related to a number of soil physical and chemical factors were collected in the measurement laboratory, topographic variables were determined with the help of GIS software and 15-year climatic data were collected from meteorological stations in nearby areas. Plant species richness was predicted by amplified regression tree (BRT) model with macroecological methods (MEM) and aggregated distribution model (S-SDM). Data analysis was performed using R software version 3.1.1. The results showed that the species richness observed with the richness predicted by both methods and the richness predicted by MEM method had a significant correlation with the richness predicted by the combination of MEM and S-SDM methods. The results obtained from Spearman's correlation between different methods of predicting the richness of plant species indicated that the S-SDM method with a value of -0.184 and then the MEM method with a value of 0.177 were more consistent with the observed species richness. The results show that by modeling species richness, information about plant community composition, species identification and their prediction in space and time can be used to investigate biodiversity changes.

The climate changes have an important role in distribution of plant species. Statistical species distribution models (SDMs) are widely used to predict the changes in species distribution under climate change scenarios. In the peresent study, the distribution of Alopecurus textilis in the current and future climate condition (2050) under the influence of climate change and two scenarios of RCP 4.5 and RCP 8.5 with the GCM data series of general circulation models BCC-CSM1-1، CCSM4 and MRI-CGCM3 by using of Five species distribution models such as Generalized Linear Model, Generalized Additive Model, Classification Tree Analyses, Generalized Boosting Model and Random Forest method in Mazandaran province were investigated. For this purpose, the number of 92 species presence data was recorded using Global Positioning System and along with layers of environmental factors including six bioclimatic variables and two physiographic variables were used in modeling. Among the environmental variables, mean temperature of driest quarter, precipitation seasonality, precipitation of warmest quarter and precipitation of coldest quarter had the most impact on the habitat suitability. Modeling evaluation indicated that the random forest and generalized boosting model had better predictions of climatic habitat than other models. Results showed that in comparison with current conditions under the emission scenarios of RCP 4.5 and RCP 8.5 respectively 22.25 and 36.22 percent of the climatic suitable area for this species will be reduced by 2050. Finally, the results of the present study can be an efficient tool for biodiversity protection, ecosystem management, and species re-habitation planning under future climate change scenarios.

Knowledge of plants spatial distribution involves understanding and management of ecological factors affecting them which a prominent role in the evaluation, protection, development and regional planning. Due to the ecological and economic importance of Ferula gummosa Boiss, this study aimed to identify potential habitat using GAM model, distribution of this species with environmental factors and economic valuation was selected Lar rangeland custom unit at Tehran province. Identify and collect basic information of the study area, determination of the custom unit boundary by using a topographic and other map, typing of habitat, random sampling and estimation of soil surface cover properties and soil sampling to 30 cm depth, modeling of potential habitat, the prediction of the economic value of market value in the study area has been process of implementation of this study. The results showed that phosphorus factor with decreasing linear relationship and moisture, acidity and silt with 2 degree of freedom were the most important factors affecting density of Ferula gummosa Boiss (R2 is 0.44 and RMSE equals 1.32). Also, aspect, moisture, silt, potassium, organic matter and nitrogen with 1 degree of freedom and elevation with 2 degrees of freedom were major factors affecting canopy cover (R2 is 0.68 and RMSE equals 0.25). Also, from the thirteen factors examined, aspect with 1 degree of freedom and elevation and silt were major factors affecting on distribution Ferula gummosa Boiss 1 degree of freedom (AUC = 0.72 and Kappa coefficient = 0.49). Potential habitat map shows that 7.8 percent of the total study area has a perfect match, 37.9% fit, 44.9% are low and 8.5% inappropriate to predict the distribution of this species.

This study aimed at predicting the effect of climate change on the geographic distribution of Thymus kotschyanus Boiss and Hohen in Mazandaran province. Species presence data were recorded via the Global Positioning System (GPS). The distribution of T. kotschyanus Boiss and Hohen under current and future climatic conditions 2050 and 2070 (1428- 1448 Solar) applying  two scenarios of RCP 4.5 and RCP 8.5 climate change by using the GCM data series of general circulation models BCC-CSM1-1، CCSM4 and MRI-CGCM3  and the five species distribution models such as Generalized Linear Model, Generalized Additive Model, Classification Tree Analyses, Generalized Boosting Model and Random Forest methods was investigated. For this purpose, layers of environmental factors, including six bioclimatic and two physiographic variables, were used as inputs to species distribution models. Among the environmental variables, precipitation seasonality, precipitation in the coldest quarter, and isotherm had the greatest impact on habitat suitability. The assessment of the modelling indicated that the Generalized Additive Model and Generalized Boosting Model had better predictions of climate habitat than the other models. The results also indicate that climate change will change the range size of the T. kotschyanus Boiss and Hohen, and will move toward higher elevations in the future. The results of the present study may be used to plan habitat protection for the medicinal species of T. kotschyanus Boiss and Hohen, as well as its restoration and rehabilitation in the vast regions of the country.

Magnetic nanoparticles have received much attention in synthesizing organic compounds due to their unique properties such as high contact surface, recyclability, and easy separation. In this study, Rice husk ash (RHA), an agriculture waste, was used as a silica source for MCM-41 synthesis. Ag2S/RHA-MCM-41 nanocomposite synthesized and characterized with FT-IR, SEM, and XRD. Prepared nanocomposite used for the synthesis of azo-linked 1, 2, 4-triazole-3-thione derivatives. Our study result showed that Ag2S/RHA-MCM-41 nanocomposite showed high activity in the synthesis of azo-linked 1, 2, 4-triazole-3-thione derivatives because of good yields and desirable reaction time. The structure of all compounds was determined by FTIR, 1H-NMR and 13C-NMR spectroscopy. In all reactions, the catalyst is easily removable and reusable, and its catalytic activity is maintained after five runs.

Having comprehensive and new information on medicinal and industrial plants distribution is necessary for proper planning, managing and use of these resources. Due to the ecological and economic importance of Ferula gummosa, this study was conducted. Economical evaluation of the species and affecting environmental factors on its distribution were selected as the goal of the study. The study area is located on Lar customary settlement of Shemiranat, Tehran province. At the relevant habitat of the species vegetation were sampled using systematic-random method. Soil samples were taken from 30 cm depth. DCA and Canonical Comparative Analysis (CCA) methods were used to evaluate the relationships between vegetation and environmental factors. The results showed that soil electrical conductivity was the most important factor affecting on the distribution of plants in the study area. Elevation as a factor was also identified as one of the important factors on the distribution of plant. Considering the expected leachate production capacity of the whole study area, i.e., 18 tons/year, net economic value of the species was 16950 million Rials for a one period of operation.

The aim of this study was to investigate the effect of land use age on dynamic of different forms of soil organic carbon in Chahar Dangeh region of Kiasar, Mazandaran province. In this area, the studied habitats include pastures conversion to agricultural lands (barley) and orchards (apples and walnuts) in three different ages (more than 30 years, more than 20 years and less than 10 years) in Era, Erost and Vavsar villages. In each land use, soil sampling was performed systematic- randomly from 0-15 and 15-30 cm depths. In total, ten soil samples from land uses were transferred to the laboratory for analysis of soil organic carbon, particulate organic carbon, microbial biomass carbon, labile organic carbon. The variance analysis results indicated that the higher values of soil organic carbon, particulate organic carbon, microbial biomass carbon, labile organic carbon found in orchard use during 30 years old, which was located at a depth of 0-15 cm. Due to the conversion of rangeland to orchard use (age more than 30 years), soil organic carbon, particulate organic carbon, microbial biomass carbon, labile organic carbon increased in 86.18%, 68.42%, 61.13% and 66.94% respectively. Also, the highest amount of EC was found in orchard use older than 30 years. But pH in barley land use older than 30 years at a depth of 15-30 cm had the highest value. In general, the results of this study indicated that the effects of the studied factors on different forms of soil organic carbon depend on the time. Therefore, soil organic carbon management strategies should be adjusted according to the time period.

The aim of this study was to investigate the effect of converting natural lands to agricultural lands in Vavsar village of Kiasar city. For this purpose, a rangeland use, along with three other uses, including lentil, wheat, and potato cultivation, were selected as the study area. Soil sampling was performed at a depth of 30-0 cm from each soil surface. A total of 40 soil samples were collected. Then the physical and chemical factors of the soil were measured including soil texture, aggregate stability, bulk density, total organic matter, total nitrogen, potassium, absorbable phosphorus, calcium carbonate, pH and EC. The results of variance analysis showed that the conversion of rangeland to the three mentioned uses had no effect on the overall soil texture and the soil texture in all four uses was Lummi. However, in the comparison of the average of the three factors that make up the soil texture (silt, clay and sand), it was found that there is a significant difference between the percentage of sand and silt at the level of 0.05. The results also showed that other factors such as aggregate stability, total organic matter, total nitrogen, calcium carbonate were significantly reduced as a result of this conversion. So that in the use of lentils, potatoes and wheat, the stability of the soil is 50.95, 20.44 and 8.86 percent, respectively, the total organic matter is 41.94, 24.73 and 22.44 percent, respectively, the total nitrogen is 42.86, respectively. 21.43% and 7.14% and calcium carbonate levels decreased by 72%, 62% and 88%, respectively. While phosphorus increased by 55.91, 86.39 and 24.39, respectively, and potassium increased by 44.05, 71.88 and 8.45%, respectively. But this conversion did not have a significant effect on pH, EC and bulk density. The results of this study showed that land use change can have different effects on soil quality characteristics. Therefore, it is suggested that continuous monitoring and evaluation of the fertility status and quality of the cultivated lands be done.

Grazing intensity should follow the management roles to prevent the soil compaction. Soil compaction decreases plant root penetration so that at 2 MPa the root extension and above ground biomass will stop. In this research, digital penetrometer was used to assessment the soil compaction level in Sabalan region in Ardabil province caused by livestock. Grazing intensity and distance from village were evaluated as independent variables. The results show that the grazing intensity and distance from village have significant effect on soil compaction at 1 percent of probability level. Grazing intensity at closer distance (200 m) increases the soil compaction and reduce the soil penetration. Modeling of different grazing intensities was made by ANFIS approach at MATLAB software. For assessment of models’ operation, root mean square error (RMSE) and correlation coefficient (R2) were used and the best model was determined. The results of best ANFIS model for prediction of soil compaction (RMSE=7.223 and R2=0.967) was compared with the result of regression model (RMSE=11.518 and R2=0.918). The results show that the ANFIS model had more R2 and less RMSE consequently more accuracy than the regression model.

One of the most important consequences increased radiative forcing due to anthropogenic activities is global warming, that created varied and challenging changes such as climate change on ecosystems. Predictions show that the increased radiative forcing will continue. Regarding to the existence of several climate models and error correction methods, selection of the right model is one of the key challenges. In this study, the accuracy and efficiency of the fifth report on regional climate models including CanESM2, CSIRO Mk3, EC- EARTH, IPSL, MIROC51, HadGEM2, MPI, NorESM1 and GFDL and statistical downscaling error correction methods including Linear Scaling (LS), Change Factor (CF), Distribution Mapping (DM),  Local Intensity Scaling(LI), Power Transformation (PT) and Variance Scaling (VS) Using T and F tests, the Taylor diagram and 10 statistical indices during two control (1956-2005) and validation (2006-2015) periods were assessed in Birjand station. The results show that; comparing the average of monthly period increases the efficiency of models and methods exaggeratedly. The best model is different based on statistical indicators and time series period. CF downscaling method is not accurate in validation period. LS and VS downscaling methods are appropriate selection for precipitation and temperature parameters respectively. Also, average accuracy of all models for both precipitation and temperature parameters is better than a single model. MPI and Earth climate models have good performance in simulating precipitation and temperature data.

Management practices such as land use change is one of the main components of global change that affects the process, structure and function of ecosystems by changing microbial communities (due to their role in the decomposition of organic matter and food mineralization(.Changes in soil biological characteristics due to land use change and management practices may lead to significant changes in soil organic carbon dynamics, soil microbial respiration and affect nutrient cycle and plant growth. Therefore, to better understand human management on carbon cycle, it seems necessary to understand the correlation between soil microbial properties during land use change.

The aim of this study was to investigate the temporal dynamics of soil microbial characteristics during land use change in rangelands around Kiasar Chahardangeh city of Mazandaran. For this purpose, in this basin, the studied habitats were including Erost village with pastures turned into agricultural lands (barley) and orchards (apples and walnuts) with an age of more than 30 years, with a control pasture, Vavsar village with pastures turned into lands. Agriculture (barley) and orchard (apple and walnut) with an age of more than 20 years and also rangelands converted to garden use (apple and walnut) less than 10 years, with a control rangeland and Ara village with rangelands converted into agricultural land (Barley) less than 10 years old with a pasture. Soil sampling in each land use was done systematically randomly from two depths of 0-15 and 15-30 cm.In total, nine soil samples from landuses were transferred to the laboratory for analysis of soil physico-chemical characteristics including texture, bulk density, moisture content, organic carbon, total nitrogen, pH and microbial characteristics including Basal respiration, Substrate induced respiration, Microbial biomass carbon, Microbial biomass nitrogen and Microbial biomass phosphorus, qCO2, microbial ratio and carbon capability index.

The results showed that the highest amount of physicochemical characteristics (except sand and silt percentage and bulk density, pH and C/N) and soil microbial characteristics (qCO2, microbial ratio and carbon capability index and MBC/MBN) at both depths and mean depths belonged to orchard land uses older than 20 and 30 years. Principal Component Analysis (PCA) indicates that over time, higher values of microbial activity and soil fertility in the orchard uses are older than 20 and 30 years with a completely different location on the axis. In general, the results of this study showed that the variability of organic carbon, total nitrogen, acidity and soil moisture content in the long run caused an increase in microbial respiration rate (Basal respiration and Substrate induced respiration), While the qCO2 in the orchard less than 10 years old and control rangeland for lands older than 20 years, also the microbial ratio in the control rangeland for lands less than ten years old had the highest value, while the carbon capability index showed no significant difference between users of different ages.

In general, the results of this study showed that soil characteristics in orchard uses with older ages were in a better condition. Also, variability in soil physicochemical properties changed the microbial characteristics of the soil over time. Therefore, it is suggested that long-term studies and management strategies to reduce uncertainty and estimate the rate of organic carbon pool of ecosystems, which are not unrelated to soil microbial characteristics, are considered necessary during land use change.

Thymus vulgaris L. is one of the most widely used medicinal plants in various industries, and its feasibility is very important in saline lands.To investigate the effect of salt stress on medicinal plant garden thyme (Thymus vulgaris L.) A field experiment in a Block complete random design with three replicates was fitted. Salinity treatments used in this experiment were 1, 4 and 7 DS/m which were applied well water with natural salt for agriculture. In order to avoid the impact of the results of research on the type of salts, water with a salinity of 9 to 10 DS/m of agricultural wells, was moved to the farm. Then water with a salinity of 6 DS/m mixed and desired salinity was ready. Measurements of dry weight of stem and leaves, the amount of sodium and potassium elements, Proline and active constituents were done in the stage before flowering. The results showed that with the increase of salinity up to level 4 DS/m; the dry weight of stem and leaves and amount of proline were increased 27.6 and 68.86 percentages respectively. While the increase of salinity up to level 7 DS/m reduces these 49.53 and 22.86 percentages respectively. With an increase in salinity, the amount of sodium increased while potassium and potassium / sodium ratio showed reduced. Salt stress were increased some of the essential ingredients in the herb garden thyme and some others were reduced by salt stress. Such can be concluded in order to irrigate the plant thyme garden with salty water, the best results in terms of product yields and composition of essential oil in 4 DS/m is obtained.

Fire is one of the most important ecological factors that can change the function of natural ecosystems. Plant growth depends on the soil, and fire can cause various changes in it. In order to investigate the effect of fire on soil and vegetation, two sites were selected including control and firefighting, each of them with an area of 37 ha, in Varcheshmeh Tusmal Rangeland of Kiasar in Mazandaran province. And in each site was done sampling of vegetation and soil by random – systematic sampling. In each site, 10 drilling and sampling profiles were performed from a depth of 0-15 and 0-30 cm. 30 square plots (1m2) were used to collect vegetation data. Plant characteristics including life form, biodiversity and soil characteristics including moisture, texture, electrical conductivity, acidity carbon, organic matter, lime, nitrogen, phosphorus, potassium were determined. The results of life forms in control and burnt rangelands showed that due to the fire of perennial species, the burned areas decreased by 33.15% compared to control. While it did not have a significant effect on annual and biennial species. The results of the effect of fire on the diversity of the whole species showed that the characteristics of the number of species, Simpson, Shannon, Margalf and Mannhinik richness were decreased 66.66, 45.6, 57.92, 67.74 and 129.49% respectively. While fire had no significant effect on the uniformity index. The results of soil experiments showed that the percentage of sand and silt, soil absorbable potassium, adsorbent phosphorus, soil nitrogen, lime, carbon, organic matter, soil acidity and electrical conductivity in burned treatment increased significantly. However, the percentage of clay and the percentage of soil moisture in the burned areas compared to the control showed a decreasing trend.

The purpose of this study was to map the spatial distribution of common yarrow(Achilla millefolium)and thyme (Thymus kotschianus) using artificial neural network model in rangelands Donna, Mazandaran Province.

Sampling was carried out with equal random classification in 29 homogenous units. In each unit, 3 soil samples were harvested from depth of 0-30 cm. In this study, 20 environmental factors were the independent variables and the presence of plant species were the dependent variable. For the preparation spatial distribution map of the species, environmental data were converted to maps in GIS. Then each of these factors was classified using the frequency. In this research, network Multilayer Perceptron that is the most common feed forward neural network was used. Optimal structure for the network was determined 1, 20, and 20. Then distribution maps of studied species were prepared with 4 class absence and low presence, medium presence and high presence in the GIS software. Models were evaluated using ROC curves and Kappa coefficient.

AUC were 96.8 and 84.7 for the species Achilla millefolium and Thymus kotschianus was, respectively  that indicates models are excellent or very good for the prediction.

Also kappa coefficient were calculated as 89.0 and 76.0 for Achilla millefolium and Thymus kotschyanus,  respectively which  indicate very good and good prediction.

Functional traits of plant species are displayed ecological properties, life strategy, and species ability for an encounter with a special environment. In this study, seven elevation points with 50 m interval with 1500 to 2002 m distance on the ground were selected and each point, 10 plots were established along a transect perpendicular on slope. To investigate the function of plant species groups, six functional traits including plant height, growth form, life form, reproduction type, life span, and type of nitrogen fixation were measured or collected. Functional plant species groups and five functional diversity indices were extracted using FDivesity software. The ANOVA test was done to investigate the effect of elevation on functional traits. Results show that elevation had significant effect on Rao index and functional divergence and there was no significant effect on other indices. Compare of means frequency and plant height was shown that there is significant difference between two functional groups. Results indicate that functional traits provide a suitable tool for studying and understanding environmental changes.

Nepeta asterotricha Rech.f. is a medicine plant. The goal of this research is to investigate the effect of some environmental factors on amount of essential oil of Nepeta asterotricha Rech.f at 8 habitats in Yazd province to determine optimal environmental factors for rangeland management and reclamation. Soil samples were collected and measured phosphorus, nitrogen, and potassium and pH, electrical conductivity, and sand, silt, and clay (Hydrometric) at three replications from each habitat. Topographic factors including elevation, slop, and aspect were recorded in habitats. Plant samples in three replications in 8 habitat and essential oils were obtained by hydro distillation for 3 hours. Investigation on the correlation between essential oils and some ecological factors were done by using Redundancy Analysis v. 4. Comparison of means were done using Tukey tests (p≤ 0.05). Number of identified chemical compounds were 31 that 24 components had different between habitats. Results showed that the active ingredients in Nepeta asterotricha Rech.f including α-Thujene, α-Terpinene, p-Cymene, (Z) -β-Ocimene, γ-Terpinene, terpinen-4-ol, cis-Sabinene hydrate, α-Terpinolene, 4aβ, 7α, 7aα-nepetalactone and 4aα, 7α, 7aβ-nepetalactone had significant differences at 95% level in growing and flowering phases, and 8 habitats.The active substances of 1, 8-Cineole, cis-Sabinene hydrate, trans-Caryophyllene and Limonene had most of amount in the growing phase and the Rose furan epoxide, 4 aβ, 7α, 7aα-nepetalactone, α-Pinene, cis-Linalool oxide, α -Terpinolene in the flowering phase.Eelectrical conductivity, potassium, sand and elevation from sea level among environmental factors,had more effects in flowering phase. Scine, Thghiabad and Dehbala habitats had better situations of environmental factors and the essential oil are recommended to ude from the species of these habitats for reclamation of regions with similar environmental factors. Also these habitats were determined as the optimal habitats for this species in Yazd province.