فهرست مطالب mohammadali zare chahouki

Shrubs with diverse ecological functions cover a large area of arid and semi-arid lands. Evaluation of changes in soil properties in shrublands can be effective in understanding the ecological relationships of these biomes and their nutritional status for land management. In this research, the spatial changes of soil fertility characteristics based on patch structure and open spaces between patches were studied in pure shrubs including Artemisia sieberi, Scariola orientalis and Astragalus myriacanthus types located in the ari lands of the central plateau of Iran. The evaluation of soil yield characteristics and soil quality was investigated by selecting the reference open space between the patches and recording the morphological characteristics of the patches to study the relationship between them. The results showed that the properties of organic matter, nitrogen, phosphorus and soil quality index (SQI) had the most significant changes between the type of shrubland and in the space between patches in each type (P<0.01). The highest value of the soil quality index was related to the under canopy in A. myriacanthus type and was equal to 0.87, and the lowest value was related to the central point of the open space in A. sieberi type and was equal to 0.22. The functional characteristics of plants such as biomass, height and canopy showed the highest correlation with the spatial distribution of elements and soil fertility factors in the open space areas (P<0.05).

Rangelands are ecosystems with various services and functions in addition to providing forage. Among the most important uses that can be made of rangeland are tourism, livestock grazing, and beekeeping. In this study, livestock grazing, tourism in customary systems, beekeeping, and exploitation of medicinal plants in the Lar Absar rangeland of Mazandaran were studied, and the suitability of the rangeland for each type of use was scored. Rangeland management methods and grazing systems were presented according to the condition and orientation of the rangeland and taking into account soil limiting factors. Then, the priority of using the rangelands was determined for each of them. Expenses, income, and net profit for each type of use were calculated based on market day conditions and the exchange rate in 1400 for 100 days. The results showed that livestock grazing is one of the appropriate exploitations in Lar Absar rangeland, and the best grazing livestock (according to vegetation and environmental factors) is sheep. Some types of plants can be well managed by using the natural grazing method and another part of the rangelands with the balanced grazing method and intermittent and delayed grazing systems in order to increase the level of productivity and improve the condition of the rangelands and with a plan for the productivity of the management. It is possible to properly and cheaply manage the rangelands of this system and improve its plant composition. The results showed that if livestock grazing is done in the rangelands, 42.7 million Tomans of income will be grazed, and tourism, beekeeping, and extraction of medicinal plants will be implemented. Around 380 million Tomans (15200 $) will be added to the ranger income. This increase in income can improve the livelihood of the user. In rangeland, fencing, beekeeping, the use of hives, and medicinal use, the machine for harvesting medicinal plants is recommended.

The object of this study was to compare predictive accuracy of some individual modeling methods versus ensemble modeling approach in estimating the spatial potential distribution and identifying ecological requirements of Artemisia sieberi in desert rangelands of Yazd province, Central Iran. For this purpose, the species presence data were collected using the random systematic sampling method in 2019. Individual modeling of the species distribution was performed using Random Forest, Classification and Regression Tree and Generalized Additive Model after preparing environmental variable maps using GIS and geostatistics. Predictive performance of individual models was evaluated using Area Under Curve and Root Mean Square Error statistics. Furthermore, the Ensemble model was used based on the weighted average AUC. The appropriate threshold limit value was calculated based on True Skill Statistic for conversion of continuous maps to binary ones of habitat suitability. Comparison of the performance of individual models showed that the RF model had a more accurate prediction compared to the other models (AUC= 0.971 and RMSE= 0.256). Evaluation of the models implemented using threshold-dependent metrics such as Sensitivity, Specificity, and Kappa index also confirmed this finding. The overall comparison of the results from the three models versus the Ensemble model also indicates the high performance of this model compared to the individual models. Based on Ensemble model results, 45.38% of the study area had a high suitability for the establishment of A. sieberi. Based on the analysis of the importance of variables in the RF model, elevation (42%), Clay (40.02%) and pH (38.97%) in 0-30 cm soil depth had the highest effect on the presence of species. In general, Ensemble modeling can reduce the uncertainty and provide more reliable results by combining the results of the different algorithms of individual modeling.

The main objectives of this study were to prepare a prediction map of the potential habitat of Agropyron intermedium and Find important factors influencing the establishment and distribution of this species and the preferred tendency of the species was relative to environmental factors Using the Maxent model. For modeling, region condition information was prepared including topography, climate, geology and soil, satellite images, digital elevation model (DEM), geology map, and climatology data. Then soil and plants sampling was performed and Soil samples were transferred to the lab. Soil properties were measured including gravel, pH, EC, lime, organic matter, N, K, P, sand, clay, and silt in the laboratory. Geostatistical methods were used for data analysis and mapping of environmental variables and the Maxent model was used for prediction maps. Kappa coefficient indicates that the Maxent model predicted A. intermedium habitat at a very good level (kappa = 0.85). Also, the accuracy of the classification of habitat maps predicted in the Maxent model is acceptable according to the analysis of the area under the curve (AUC = 0.771). The results showed that topographic variables and clay soil factor in the occurrence and distribution of A. intermedium has the greatest effect and increasing lime and ec have a negative influence on the presence of this species. A. intermedium is a desirable species that in addition to being used in creating hand-planted pastures, it is very important in improving and developing rangelands, especially in cold regions. Therefore, maintaining genetic and scientific,

This study was conducted to evaluate the effect of polymer mulches and plant mulch on some soil physical properties. For this purpose, effects of synthetic polymer, natural polymer, natural - synthetic polymer, and litter, On some physical properties of soil at two depths (0-5 cm and 5-30 cm) and two time periods in a completely randomized design with four replications was studied. 10*10 meter experimental plots were considered and mulches covered 2 cm of the soil surface in each plot. The results showed that the use of mulches in the first week of applying, affected the bulk density (3.6% increase in synthetic polymer), porosity (6.01% increase in synthetic polymer), temperature (2.52% increase in litter and 1.85 decrease in natural polymer) and humidity (16.67% increase in synthetic polymer) at the layer of 0-5 cm, Soil moisture (16.67% increase in synthetic polymer) was also affected at the depth of 5-30 cm. Six months after the experiment began, mulches were applied, made a significant difference compared to control in the bulk density (4.81% and 2.12% decrease in synthetic polymer for 1st and 2nd layers respectively), porosity (8.23% increase in synthetic polymer for 1st layer and 4.12% increase in natural - synthetic polymer for 2nd layer) and moisture content of both surface and beneath soil (103.53% and 48.6% increase in natural - synthetic polymer for 1st and 2nd layers respectively), also the electrical conductivity of the first depth of soil (6.23% decrease in natural - synthetic polymer) was affected.

The use of biochar as a soil amendment is one of the new methods to improve soil properties and increase plant yield. In this study, in order to evaluate the effect of adding natural biochar on soil properties and yield of Pamirian winterfat (Eurotia ceratoides) plant, an experiment in a completely randomized design were performed with 11 treatments by different levels of biochar (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10% by weight) and three replications in greenhouse conditions. After the end of the growing season, some physical and chemical properties of the soil (pH, EC, organic matter (%), lime, bulk deisty, particle density, and porosity percentage), germination percentage, and yield of E. ceratoides were measured. In all the studied traits of the soil (except for the particle density), and the characteristics of the E. ceratoides plant, the statistical difference between the various levels of biochar was significant (a = 0.01). Adding different levels of biochar increased pH, ECy, soil porosity percentage, soil organic matter, whereas decrased bulk density, lime percentage, clay percentage, sand, and silt.

The present study aimed to model potential habitat distribution of A. sieberi, and its ecological requirements using generalized additive model (GAM) and classification and regression tree (CART) in in the Poshtkouh rangelands of Yazd province. For this purpose, pure habitats of the species was delineated and the species presence data was recorded by the systematic-randomize sampling method. Using DEM and geostatistical method, digital layers of environmental variables (soil and physiographic variables) were prepared with the same spatial resolution (pixel size 30×30 meter). Plant distribution modeling was conducted using CART and GAM models in the R.3.3.1 software environment. The prediction performance of the models was evaluated by the AUC (Area Under the Curve) In addition, The TSS (True Skill Statistic) was used to determine the optimal threshold limitof species presence. The classification accuracy of the presence/ absence map was investigated using the Kappa index. Based on the results, The CART model had a better predictive performance than the GAM models (AUC=0.97 and 0.89, respectively). Furthermore, the Kappa coefficient of the CART model was higher than GAM, based on the obtained Kappa coefficient values (0.97 and 0.89, respectively). This study concludes that the CART model were more accurate in estimating the distribution range of A. sieberi in comparison with the GAM model. The analysis of the importance of variables showed that the electrical conductivity (EC) and acidity (pH) of the first soil depth had the highest effect on the distribution of A. sieberi. In general, it can be concluded that application of data-driven methods, such as CART model, can be useful for accurate estimation of the potential habitat distribution of plant species on a local scale. Therefore, the application of these models to introduce the suitable species in vegetation reclamation plans of Iran's desert rangelands is recommended.

Full identification of hazards and prioritizing them for non-harm to nature is one of the first steps in natural resource management. Therefore, introducing a comprehensive system of evaluation, understanding, and evaluation is essential for controlling hazards. This study aimed to model and predict environmental hazards following increased degradation in natural environments by ANN. Thus, 600 soil and vegetation samples were collected from inhomogeneous ecological units. Soil samples were prepared by strip transect method according to soil depth in four profiles (5, 10, 15, 20 cm). Vegetation samples were also collected using a minimum level method using 2 2 square plots according to the type, density, and distribution of vegetation. Sampling was done in two safe zones and other uses were modeled using ANN in MATLAB environment. The optimal model of multilayer perceptron with two hidden layers, sigmoid tangent function and 19 neurons per layer and coefficient of determination of 0.90. The results of sensitivity analysis showed that soil moisture content would be effective in decreasing biodiversity and flood risk as well as increasing the risk of extinction of endemic species in the region, and then the apparent and true gravity and soil porosity and distance from the road play a key role in the degradation of cover. Vegetation has increased flooding and extinction risk. Therefore, it is recommended that measures related to soil and vegetation restoration in this park be taken to reduce future damages as soon as possible.
 

The establishment of vegetation is the best way to manage degraded and at risk of degradation lands. Considering that the planting in arid lands is very costly because of ecological restrictions, so experts are looking for methods that increase the percentage of the seedlings establishment and reduce the cost of planting, in this regard the correct use of amendments is very important. The study area is located in Nazarabad City in southwest of Alborz province. In this study, the amendments including mineral biochar, arbuscular mycorrhiza fungi and acrylic resin polymer each in four levels were used at the base of Nitraria schoberi seedlings. The soil characteristics of the area was determined at the start of planting. After one year with counting the number of live seedlings, the percentage of establishment for each treatment was calculated. Economical estimates were calculated based on cost-benefit and calculated separately for each treatment. The results showed that there was a significant difference at the 5% level between the amendments and the control. Mycorrhizae had the highest (70%) and the control and biochar 4 treatments had the least (40%) percent of establishment. Economically, mycorrhizal 2, polymer 2 and biochar 1 treatments were the most optimal treatments for each amendment, respectively. The used amendments had different effects on the establishment of seedlings, so that the percentage of establishment increased with increasing level of mycorrhiza use, but with increasing level of polymer and biochar use, negative effects were observed and the percentage of seedling establishment decreased.

In this study, the prediction of Thymus kotschyanus habitat distribution was investigated using two methods of generalized additive regression model (GAM) and Boosted regression trees (BRT) in central part of Taleghan rangelands. Data on vegetation and habitat factors such as topography, climate, geology and soil were collected. For data preparation, samples were taken from the field to record the presence/absence of the species using 735 plots of 1m2 and random-systematic method. Topography information’s, like slope, elevation and slope direction of sampling points were extracted from digital elevation map. In addition, on each site five soil samples were taken to the laboratory for the following tests: gravel content, soil texture, organic matter, caco3, phosphorus and potassium. The results showed that the probability of presence of T. kotschyanus increases as caco3, potassium and silt are more available and decreases when phosphorus and clay are increasing. Also, its relationship with elevation and gravel is gaussian. Results showed that both methods (GAM and GBM) are able to predict the distribution of T. kotschyanus habitat meaningfully.

Over the past two decades, degradation damage has increased in natural ecosystems. This research focuses solely on the degradation of soil and vegetation cover in Sorkheh Eshpar National Park. For this purpose, some physical properties of the soil (specific gravity and true porosity, moisture content, a percentage of pebbles, acidity and conductivity and soil texture) were measured. Also, the diversity and density of the crop in two safe zones and other uses were calculated. Soil sampling was carried out in the form of strip transects at the beginning and the end of each joint unit and excavation of four soil profiles at a depth of 5-5 cm. The crown cover was taken with 2 × 2 squares throughout each transect and 30 plots per unit. A total of 600 plots and 480 soil profiles were taken from the study area. Shannonchr('39')s biodiversity index was selected as an output variable and soil characteristics, ecological factors, and human factors as inputs of the model. Normality of data was confirmed by Shapiro-Wilk test. SPSS software was used for soil degradation regression and vegetation cover. The combined, removable, and retrograde method was chosen with a value of = 422.0. With the MATLAB software, the artificial neural network was created with a multi-layered perceptron, with a secret layer, and 18 neurons, and a sigmoid tangent function, and a value of R = 0.5065. Considering the amount of R in the artificial neural network model, this model was selected as the optimum model for estimating and predicting soil degradation and vegetation cover in Sorkho-e Hesar National Park.

Investigation of the relationship between plant species and environmental factors plays an important role in plant ecology. The present study aimed to develop the best predicting model for distribution of Prangos uloptera DC. using logistic regression (LR) and Maximum Entropy Methods (MaxEnt) in its habitat in the southern rangeland of Ardabil province, Iran. Vegetation data (presence and absence of P. uloptera) and environmental factors (including soil, topography and climatic variables) were collected. The original vegetation type map was prepared using slope and elevation maps (1: 25000 scale) and satellite imagery (Landsat). Vegetation samples were collected in 2016. In each site, three transects of 100 m length were deployed (two transects in the direction of a gradient and one transect perpendicular to the slope direction). On each transect, ten 4m2 plots were placed along each transect, and the total canopy cover and plant density were recorded. Overall, 180 plots were sampled in six sites. Soil samples were collected at a depth of 0-30 cm at the beginning and end of each transect. The LR method was performed in the SPSS Ver. 19 software, and the Maximum Entropy method was carried out in the MaxEnt Ver. 3.1 software. The LR model showed that rainfall had the highest effect on the distribution of the P. uloptera habitat. The accuracy of the LR method for the prediction map was good (Kappa index= 0.65). The MaxEnt method showed that variables, including sand, nitrogen (N), silt, and potassium (K) had the highest effect on distribution of P. uloptera habitat. However, the accuracy of the MaxEnt method was low (Kappa index=0.35). It was concluded that modeling methods could be used as a prediction tool to determine the location of plant species. This may lead to better rangelands management and improvement in areas with similar conditions.

Haloxylon is one of the resistant plants in desert areas, which has always been considered by researchers and practitioners since controlling sandy soils as one of the solutions to erosion and sand fixation by biological methods. In this study was conducted in forest plantations eshtehard, Bases of haloxylon thate wilting and drying effects are visible, was chosen and pruning them. This factorial experiment based on completely randomized design with four treatments, pruning time (September, October, December, February) and four sub-plots pruning height (Complete pruning, 25 cm, 50 and 75 cm) were implemented. Before applying pruning, for homogeneous and the same size the bases, Variable height, canopy cove diameter and crown diameter was measured on every base. The end of July condition bases was investigated in terms of Tillering and not tillering. Results showed that pruning stimulates been tillering. Because 97.5 percentage of bases was tillering. Pruning in January from height of 75 cm with 100 tiller hade the greatest number tiller. The lowest tiller regarding of November with 5 tiller. There is no significant difference between treatments in term of tiller diameter, but in general thickest tiller was for pruning in January. Therefore, it can be said that pruning is about 75 centimeters in December as the best pruning time and heigh.

Salvia limbata is an herbaceous plant which belongs to Lamiaceae family and is native to Iran. In this study, essential oils and variety of chemical compounds of Salvia limbata in flowering stage in different altitudes in July were studied. In order to study the active ingredients of plant in studied sites in flowering stage nine plant samples were examined for phytochemical analysis. Identification of the basic constituents (quantity and quality) with GC / MS and GC-FID (gas chromatography coupled to mass spectrometer) has been done. The yield of essential oils in flowering stage in Paeein Taleghan 0.34% in Mian Taleghan 0.34% and in Bala Taleghan is 0.46%. According to the results, difference in altitudes in three habitats shows a significant difference among the percentages of the obtained compounds. The most important constituents of essential oil include α-Pinene, β-Pinene, allo-aromadendrene and Spathulonol. Also, Salvia is reported as one of the sources for the extraction of α -pinene.

The calculation of the grazing capacity requires the consideration of factors affecting it. Due to the effective factors, the long-term grazing capacity model was designed, and then the capacity of the rangelands was calculated. Grazing capacity was calculated by the proposed model in four steps including estimating the average good production, calculation of available metabolic energy, the daily requirement of the animal unit and grazing capacity. Due to the drought condition of habitats and fluctuation of forage production in different years, one cannot calculate grazing capacity with once production measurement for the long-term. Hence, the average good production of habitats was determined and based on that, long-term grazing capacity was calculated. The average good production of Golestan Kouh, Vardast, and Pashmakan habitats in the statistical period of 6-7 years was estimated to be 425, 233.8 and 343.3 kg/ha, which are related to normal years in terms of rainfall. The grazing capacity of habitats in a quarterly period of four months was calculated to be 0.8, 0.3 and 0.5 animal unit per hectare so that if there is a drought for 12 consecutive months, there will be no damage to vegetation. Meanwhile, there is not much damage to the beneficiary and he will not have to sell too much of his livestock. The area needed for grazing of an animal unit in the rangelands was suggested to be 1.3, 3.3 and 2 hectare. This amount is recommended to be one hectare for a 30-year period based on a common method in range management plans. This indicates the need to pay attention to the factors affecting the grazing capacity and emphasizes the application of the proposed model in order to calculate the rangeland capacity.

This study was conducted to investigate the effect of ecological factors on distribution, presence and absence of species Ferula ovina and F. persica in the semi-arid rangelands of Zanjan province, Iran in 2015. The locations of ten 4m2 plots with 15m spacing on three 150 m long transects were systematically randomized and determined in each key area within each habitat. The soil surface features including total canopy cover, canopy cover of target species, bare soil and stone and gravel on the soil surface were estimated. Three mixed soil samples from the locations at the beginning, middle, and end of each transect from depth of 0-30 cm were collected to determine soil properties. Physiographic and climate factors of each selected site were determined. Independent sample t-test and one-way analysis of variance were conducted to compare the related parameters and the discriminant analysis was also performed to determine the importance of environmental variables on the presence and absence of the target species. The results showed that in F. persica habitat, the percentage of total neutralizing value and silt was less than that in the absence area of the species. In contrast, in F. ovina habitat, the amount of these variables was significantly higher than that in the absence area of the specie. The results of discriminant analysis showed that temperature parameters, altitude, sand and gravel percent on the soil surface, electrical conductivity, total neutralizing value and rainfall in the first canonical function had the highest value and they were the first factors affecting species distribution and location differentiation. However, presence and absence of species in the target habitats are often dependent on some variables such as pH, soil silt percent, aspect, precipitation and minimum temperature..

Rheum ribes species is one of the important medicinal plants in the world. In this study were used maximum entropy method (Maxent) and the MAXENT software to this prediction habitat map. Measure environmental variables was soil variables including gravel percentage, pH, electrical conductivity, percent lime, gypsum, organic matter, soluble salts (Ca+, Na+, K+, Mg2+, CL, HCO3, SM and SO2), sand, clay and silt and variable topography (slope, aspect and elevation) and rainfall variable. Those were effective variables on the presence of species. The model classification accuracy using the area under the curve (AUC) was 95% (good Level), and kappa coefficient was obtained 0.92 that measuring from the agreement of prediction maps with ground truth, which is at a high level. The results of this study showed that the habitat of this species is in the soils with low pH (less than 8), clay Low (less than 40%), coarse texture and organic matter more than 4.0 percent. And the presence of this species has inverse relationship with a pH of both the depth and the clay first depth and with has directly relationship to organic matter of both depths.

This study was conducted to analysis the changes in plant group species (PGS) in relation to environmental and management factors in mountain rangelands of Baneh-Kurdestan, Iran. For this purpose 4 plant group species: shrub, forb, grass and shrub-forb (3sites for each PGS) were defined in the study area. There were established 30 plots (2m2) in each site via classified random method. Also in the center of plots we had 10 soil profiles into sampling in each site. All of vegetation, soil and topography and management (grazing intensity) factors were measured in the plots (in total, 90 plots and 30 soil samples for each PGS). Principal component analysis (PCA) showed that first and second axes, in total, explain 73% of changes in the traits of plant group species. Two PGS of forb and shrub-forb are directly related to clay, organic matter, nitrogen, soil depth, potassium, silt 1th, and the first depth and electrical conductivity 2th and northern aspect. Grasses affected by silt 2th, pH, CaO 2th, southern aspect and shrubs are related to sand, gravel (surface and below ground), southern aspect and grazing intensity. On the other word, topography, grazing intensity, nitrogen, organic matter and soil physical factors were the most important factors in the separation of plant group species. The plant group species that had different functional groups (Shrub and forb) had more production and coverage.

Low rainfall with poor temporal and spatial distribution, scarcity of water resources, and the increasing demand for water are major problems in arid and semiarid regions. The efficient use of water resources and efforts to achieve new water sources are two main solutions to slightly overcome these problems. Among these, rainwater harvesting is one of the most prominent methods for rainwater management to confront the scarcity of water that is rapidly developing in many areas. Due to the variety and extent of rainwater harvesting methods, characteristics such as the amount of rainfall and its distribution, topography, soil type, soil depth, social and economic factors, as well as the water consumption in each area must be considered when selecting the appropriate method. In this paper, firstly, the factors affecting the selection and design of each rainwater harvesting method is studied that includes natural factors such as weather conditions, topography, runoff, and the technical, economic, social, and organisational factors. Then, the different methods of rainwater harvesting systems including microcatchment, macrocatchment, and rooftop rainwater harvesting systems are expressed in detail.

Species diversity, richness and biomasses (aboveground biomass) and their relationships are the key variables of ecosystems. This study was conducted to determine the relationship of Species Diversity (SD) and Species Richness (SR) with Above-Ground Biomass (AGB) at a local scale at 5 different habitats (shrubland, forbland, grassland, shrub-forbland and forb-shrubland) in Zagros mountains in west of Iran (2015). For each habitat, 50 plots (2m2) were determined. SD was estimated by Shannon–Wiener’s index, SR was defined as the number of species per plot and AGB was detected per unit of area (gm-2). Results indicated that all of relationship patterns existed in these habitats. The unimodal relationship was found in shrub-forbland and forb-shrubland whereas the relationship of SD/SR vs.AGB in shrubland was linear and negative, and in forbland and grassland, it was positive. There were many complex and variable mechanisms dealing with the SD/SR vs. AGB relationship. The unimodal relationship indicates that SR and SD peaked at intermediate levels of AGB, and it is an inherent attribute of the spatially heterogeneous habitats affected by life forms, micro-sites, facilitation and competition. The positive linear was related to positive response of SD, SR and AGB to environmental factors or because of any reason (grazing, disturbance level…), the AGB may not reach to the highest possible level; thus, it may only show a positive relationship. When SD and AGB are affected in the opposite directions by environmental factors such as soil fertility, negative patterns may be caused. The negative pattern represents short gradients indicating a similar species composition among plots. Greater R2 in SD vs. AGB than SR vs. AGB at all habitats showed that evenness and richness (components of SD) are more important than just SR; thus, SD vs. AGB relationship is better and more reliable to predict the variations (SD and AGB).

The most important factor affecting forage quality is phenological stage, that recognizing it be determined the appropriate time grazing in pasture. In this study, four species including Artemisia sieberi, Salsola kerneri, Aelienia subaphylla and Eurotia ceratoides were sampled in different phenological stages (vegetative, flowering and seedling). Samples were taken from the rangelands of Nodooshan-Yazd in 1389 and 1390. At each stage, five replicates for each plant species were selected at least five vegetable base from different locations of vegetation type in the region for each replicates Year growth of shrub species were harvested. Samples grinding after drying and to separate the different parts (Flower, leaf and stem) and were analyzed using infrared spectroscopy in the laboratory. important indicators of quality such as crude protein (CP), acid detergent fiber (ADF), dry matter digestibility (DMD) and metabolic energy (ME) were determined. Results showed that the highest percentage of crude protein is related to in leaves of A. subaphylla and in vegetative stage (9.19%), highest percentage of ADF in shoot of and in seedling stage (53.42%) and highest percentage of DMD (48.13%) and highest amount of metabolic energy (6.18 MJ/KgDM) in leaves of A. sieberi and in vegetative stage. The end of the vegetative period can be considered the best time for grazing.

This research was aimed to modeling the habitat suitability for plant species in southern rangelands of Golestan province by ENFA method with Biomapper software. For this purpose, the spatial data of species presence and environmental conditions were used to identify the suitable sites for the study species and their habitat requirements. For vegetation sampling in each vegetation type, three 50-meter transects were established, along which measurements were performed within 10 plots with five-meter intervals. The plot size was calculated to be 1m2. In each vegetation type, soil sampling was done at 0-30 cm depth. Then data were entered to the Biomapper software and the middle algorithm and harmonic algorithm were used to produce the habitat suitability map. The kappa coefficient was used to check the conformity of the predicted map with actual vegetation map. The kappa coefficient was calculated to be 0.57, 0.70, 0.58, and 0.50 for Artemisia aucheri, Festuca ovina-Astragalus gossypinus, Bromus tomentellus, and Bromus tomentellus- Festuca ovina, respectively. According to the obtained results, the most important environmental factors affecting plant species in the study vegetation types were as follows: clay content and slope (A. aucheri); sand content and altitude (F.ovina-A.gossypinus); sand content and northwest aspect (B.tomentellus); sand content, altitude and organic carbon (F.ovina-A.gossypinus). The models developed in this study can be used to identify suitable areas for range improvement practices.

Landscape ecology is one of theyoungest branches of ecology science, and especially deals on the study of landscape composition, structure and function. Landscape elements are such as patches, corridors, matrixalong the border and ecotons. Landscape metrics are algorithms for quantifying thespatial characteristics of patches, classes or entire landscape mosaics, and thebest way to compare different landscape requirements. Due to this, the aim of this study was to quantifylandscape patterns and the possibility of breakdown of plant communities usinglandscape metrics. Metrics that were used in this study thenumber of patch, class area proportion in the landscape, mean patch size, edge density, mean shape index, mean patch fractal dimension and total edgein the class level and Shannon diversity index in the landscape level. Metrics listed for vegetationmap and morphology units were calculated using the patch analyst extension for Poshtkooh rangelands of Yazd. Then, using the principal component analysis were determined the important metrics for the separation of plant communities. The resultsof the principal component analysis for the separation of class in morphology units map showed that edge density metric have thegreatest impact but in the vegetation map landscape metrics, were equally important and more importance metric could not be determined and compared to separation the units of land shape in the morphology units map were less separation. Finally, with using of discriminate analysis, wasdetermined thedifferentiation function and metrics that create separation between the plant communities and land classes. Discriminate analysis showed that thenumber of patch metric, edge density and mean patch fractal dimension can beseparated plant communities and classes in the map, units are less resolution.

Knowledge of the recent changes as an essential component of global environmental changes and sustainable part of the study emerged. The destruction of landscape, vegetation and land use changes and land cover change are those who constantly exert pressure on the country's environment. Land use change is a complex process and dynamic that natural and human systems linked together and make a direct impact on soil, water and atmosphere. The aim of this study was to investigate the possibility of using indicators of ecological landscape in the separation of land and plant communities in the study area is in the North East Semnan. To this end, there is need to the morphology of the land and vegetation maps. In this study, six metrics at class level and one metric at landscape-level for the study area were measured. These metrics using Patch analyst extension in ArcGIS was calculated. Then, using PCA important measures for separation plant communities were determined. Principal component analysis to determine the most important metrics in the resolution of the morphology map of land classes showed edge density, number of patches and mean patch size are the most important metrics, and in separate classes plant communities of this area the class area proportion, number of patches and mean patch fractal dimension are the most important metrics

Artificial Neural Network (ANN) is new information processing structures that uses special methods for biological neural networks. The main purpose of this study was to modeling of Seidlitzia rosmarinus distribution in northeast rangelands of Semnan by ANN model. For this purpose, vegetation sampling was carried out in each vegetation type along three transects of 750 m, on which 15 plots were established with an interval of 50 m. Soil samples were taken from two depths of 0-20 cm and 20-80 cm in starting and ending points of each transect. To provide the prediction map of plant species distribution, different layers of environmental factors used in the model are required. The geostatistics method was applied for mapping soil properties based on the prediction model obtained from ANN method for S. rosmarinus. The back-propagation neural network with three-layer- perceptron network was designed to generate the ANN model and seven neurons in the input layer, ten neurons in the hidden layer, and one neuron in the output layer were used. The accuracy of the prediction map was tested with actual vegetation maps and the Kappa coefficient was calculated to be 72%, indicating a very good agreement. Results showed that this species is distributed in rangelands with a pH of 8.1-8.3, an EC 0.22-0.26 dS/m, in a silty-sandy textured soil, and an altitude of 1600-1750 meters. it is highly correlated with lime and pH in two depths.