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This study was conducted to evaluate the ability of logistic regression to specify the environmental condition affecting the presence of selected plant species, and identifying suitable areas for the establishment of these species. Some sites with relatively homogeneous ecological conditions were identified by overlaying slope, aspect, elevation and geology maps (1: 25000 scales). Vegetation sampling was carried out using random- systematic method, and 60 plots were established along four transects with 200-1000 meters length in each site. The appropriate plot sizes were determined from 2 to 25 m² using Minimal Area Method. Soil samples were collected from eight soil profiles in each site from 0-30 cm and 30-80 cm depths from soil surface. Predictive maps of plant species habitats were produced using Logistic regression method. Optimal environmental condition of selected plant species were determined and predictive performance of the produced potential maps were assessed using kappa coefficient and the True skill Static. According to the results, geological formation, percent gravel, soil texture, acidity and lime contents were identified as the most important factors controlling distribution of plant communities in the study area. The accuracy of produced predictive maps for Amygdalus scoparia was very good, for Scariola orientalis- Stipa barbata and Pteropyrum olivieri- Stipa barbata were good and for Artemisia aucheri- Astragalus glaucacanthus vegetation habitats was moderate. The results showed that the logistic regression models, provides high accuracy predictive model for Amygdalus scoparia habitat due to its exclusive habitat conditions. The accuracies of the produced maps for other vegetation habitats were lower than Amygdalus scoparia because they had more wider ecological spectrum.

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The purpose of this study was to assess the logistic regression model capability to map the spatial distribution of plant species in Taleghan Miany rangelands. Systematic-random sampling method was used to collect vegetation and environmental data (such as topography and soil factors). Three transects with 150 m lengths were established in each sampling unit and the vegetation cover percentage were determined in 15 plots along each transect. Soil samples were collected from the two sampling plots in each transect randomly. Geo-statistical methods were used to produce the environmental maps. Topographic maps were also produced using digital elevation model. Species distribution models were prepared using logistic regressions equations in Geographic Information System (GIS). Kappa index (k) was used to evaluate the agreement between prediction models and field data. According to the results, kappa index obtained for Agropyron intermedium habitat model was 0.83. The calculated Kappa for Stipa barbata and Astragalus gossypinus habitat models were 0.79 and 0.80 respectively. This index for Thymus kotschyanus habitat was 0.68. This study indicated that logistic regression model could predict the habitat suitability of the four studied species appropriately. The produced logistic regression model for predicting Agropyron intermedium habitat was more efficient because this species has more specific habitat requirements. The results of this study can be used in rehabilitation, conservation and management programs in rangeland ecosystems.

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This study aimed to investigate the effects of some environmental factors on the distribution of Ferula gummosa and Ferula ovina in Shilander rangelands - Zanjan province. Two Ferula habitats were selected and their environmental characteristics were compared with control sites (no Ferula species present). Three transects with 150 meters lengths were established in each site and data were collected along the transects in seven plots of 4 m² (with 20 meters interval each). Composite soil samples from 0-30 cm of soil surface were collected from the starting point, middle and end part of the established transects and analyzed in soil laboratory. Slope percentage and direction, and elevation from sea level for all plots were also recorded. Canonical Correspondence Analysis (CCA) and Redundancy Analysis (RDA) were used to explore the relationships of Ferula species with environmental variables. According to the results, slope direction and degree, gravel and silt percentage, neutralizing substance percentage and soil saturation percentage were identified as the most important factors in characterizing Ferula species habitats. Comparing the environmental characteristics of Ferula habitats with control sites revealed that sand percentage, slope, silt percentage and elevation from sea level were different statistically between these sites (p ˂ 0.05). Logistic regression analysis indicated that soil pH (p ˂ 0.01) and neutralizing substance percentage (p ˂ 0.05) were the most important discriminating factors in Ferula habitats with the control sites.

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This study investigated the effects of seasonal changes and different soil conditions on  proline, soluble sugars, and ion content of Hammada salicornica in Bafgh area, Yazd province. Three Hammada salicornica habitats with various environmental conditions were selected. The first habitat had salty soil and hardpan (Hamada habitat), the second habitat located next to playa with saline soil and high groundwater table, and the third habitat characterized by sandy soil. The plant samples were collected in four seasons with five replications. The highest Proline content in the species was observed (2.5 mg/gwt) in autumn in sandy habitat and its lowest value was found (1 mg/gwt) in Hamadat habitat. The highest amounts of soluble sugar (2.5 mg/gwt) were measured in summer in sandy and playa habitats and its lowest amount (0.87 mg/gwt) was observed in winter in sandy habitat. The highest amounts of sodium content (42 Meq/l) measured in winter in Hamada habitat and its lowest amount (.64 Meq/l) found in winter in sandy habitat. The highest amounts of potasium (31 Meq/l) were measured in winter in Hamada and sandy habitats and its lowest amount (0.6 Meq/l) were found in all habitats in winter. The highest amounts of nitrogen content (2.6 percent) were measured in Hamada habitat and its lowest amount (1.1 percent) was also found in winter in Hamada habitat. It is concluded that hammada salicornica can adjust its osmotic potential with absorbing and increasing its sodium and potassium content. This study showed that physiological responses of hammada salicornica to environmental conditions depend mostly on plant phenology and the kind of stress as well as their interactions.

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Determining the recreational appropriatness of rangeands based on their ecological potentials is vital for ecotourism management. Ecological potentials should be evaluated to achieve an appropriate ecotorism planning. This study aimed to provid a model for evaluating ecotourim suitability using GIS in Venae basin, Boroujerd County, Lorestan province, Iran. The effective sub-criteria on ecotorism suitability were identified using literature review, questioners from exporters and tourists. Analytical Hierarchy Process (AHP) was used to weight and evaluate these factors or sub-criteria on rangeland recreational appropriateness. Expret Choice software was used to conduct AHP. Digital information map, slope, aspect, satellite map and so on were overlaid by ArcGIS^© software.  The ecotourism suitability sub-criteria were categorized into two main physical and biotic criteria.  Twenty two sub-criteria were evaluated based on the specific ecotourism type, and their spatial maps were produced and combined. According to the AHP synthesis, sensitivity to soil erosion was identified as the most important sub-criteria (with relative weight of 0.431) from physical criteria for ecotourism suitability and distance from city and camping were not identified as important sub-criteria with relative weight as low as 0.028. Security and residents charcteristics were also identified as the most and least important sub-criteria for ecotourism suitability among biotic criteria  with relative weight of 0.56 and 0.33  respectively. Results indicated that 1457 hectares (24.85 percent) of the study area was classified as highly suitable for eotourism (S1), 1751 hectares (29.86 percent) classified as S2, 1200 hectares (20.46 percent) classified as S3 and 1456 hectares (24.85 percent) were classified as unsuitable (N) for ecotourism purposes. In summary, the physiographic condition of the study area such as high slope and mountainous land units were identified as the most limiting factors of ecotourim suitability. Specific landscape, high mountain peaks, plant diversity, gardens, orchards and plantation were aslo identified as sub-criteria that improve ecotourim suitability in the study area. The limitation of slope sub-criteria for ecotourism suitability can be decreased by providing walking trails appropriate for tourists in the area.

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Geno Biospher is in cross two Khalig- Omani & Iran –Torani region cross together. It has lots of rangelands with trees and with more than 60% plant species of Hormozgan. In this study, the original goal is evaluating potential of Geno rangelands for ecotourism use to preventing degrade. In every special region in every type, we use 4 transects with 200 meter and we put 15 plot 1*1 m² with 100 meter distance. Then production was estimated with cut & weight method and final plant cover map was prepared. Map rules was based according life-environment units and with using systemic method in Arc GIS9.2 environment, all data layers overlay together and ecotourism ecologic potential map was prepared with Makhdom ecological models. Finally results show that 10.84% or 61.04ha is proper for concentrated recreation 1& 2 levels and 40.64% or18067.01 ha is proper for open recreation. According research result and attention to 40.64% of range surface that protect and they has open recreation potential too, this rangeland can use for ecotourism, plant and animal researching, mountain climbing, looking bird, looking at wild animal and paraglider for scientific and public tourisms.
 

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This study was conducted to model the distribution of two species: Limonium iranicum (Bornm.) Lincz. and Aeluropus littoralis (Gouan) Parl. Logistic regression was the method and surrounding rangelands of Meighan playa the study area. Samples were taken through random- systematic method with 2 to 4 square meters plots. For each plots, density and canopy cover were measures and recorded. Within the vegetation types, soil samples were taken from the beginning and the end of each transect at two depth levels, 0-30 (1^st depth) and 30-80 cm (2^nd depth). Notes were also taken from habitat factors such as topography and soil data. Maps of environmental variables were prepared using geographic information system (GIS) and geostatistical methods. Spatial distribution maps of the species were drawn using logistic regression by SPSS. GIS. Kappa coefficient was used to verify the accuracy of the map V.S. the real world. According to the results, for the second depth lime and silt are important factors on the growth of L. iranicum, while sand was mostly important in the first depth. The most important variables in the A. littoralis habitat preference were lime of the first depth and elevation. Moreover, the map of the model was well plotted for A. littoralis habitat (kappa = 0.65) and much better for the L. iranicum habitat (kappa = 0.83). In conclusion, this model has the ability to predict the distribution of species in the halophyte habitats.

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The transformation of rangelands into dryland farming in vast areas and relatively short time regardless of certain roles and methods, leads to soil erosion and loss of productivity of the lands. Land abandonment is the final step of the process. For future generation needs however these lands should be converted into pasture or its original form. For this purpose, finding suitable places for rehabilitation projects, especially at macro level, is inevitable. In this regard, the hierarchical analysis process (AHP) was used. In this model, five main criteria including physiographic, climatic, soil, geomorphology and land use types plus 14 sub-criteria were selected. Physiography components such as elevation, slope angle and aspect were in one category. For climate, precipitation and temperature were the sub-criteria. For soil factors, texture, depth, Ec, pH and organic matter were used as sub-criteria. Geomorphology has geology and erosion components. And land use with 11 elements took part in the model. The results of the calculations showed that the most influential criteria were physiography and climate with the weight of 0.426 and 0.270 respectively. Soil and land use factors were the next in terms of importance value. The geomorphology stood at the lowest priority with the weight of 0.055. The results also showed that 26437 hectares of eligible land (low yield and abandoned land) equivalent to 44.62% of this land (highest level) are moderately suitable for the restoration. The small piece of lands equal to 3603 hectares (6.08%) are unsuitable for reclamation. Also, 1983 ha (3.35%) of dry farms are very unsuitable for restoration while 15780 ha (26.63%) are very suitable. In general, the use of the hierarchical analysis method is a cost-effective way to determine the most/least suitable lands for restoration and/or conversion to the pasture.  And AHP can help managers and planners to make a better decision.

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Economic and therapeutic value of medicinal plants have encourage the people to increase cultivation of these plants in the world. Glycyrrhiza glabra is one of Iranian native plants which is used in the food, pharmaceutical and tobacco industries. The aim of this research is to identify suitable lands for cultivation of Glycyrrhiza glabra using ANP Fuzzy method in Ligvanchay watershed, Ardabil. Eleven criteria in four clusters including climate, soil, physiography and socio-economic were weighted using expert’s opinion in Super Decision software. Land use map was prepared using Landsat image and support vector machine method. Also, Fuzzy method was used to prepare same scale layers in Idrisi Selve software. Finally, potential map was prepared using weighted linear combination method in ArcGIS. Based on results, Altitude, slope, soil depth and soil fertility factors were the most important layers respectively. Results showed that 1936.85 ha (26.96%) of area have high or very high potential for the task. Based on results by changing the pattern of farming from cereal dryland to licorice can create a better economic benefits.  

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Cultivation and development of medicinal plants is an effective way to fulfil of medicinal plants demand and to protect natural habitat to over use. Ziziphora tenuior is one of the traditional medicinal plants in Iran, which has a substance called Pulegone with its analgesic and anti-inflammatory effects. The main purpose of this study is find suitable landfor the plant cultivation in Sabalan watershed using ANP Fuzzy method. Most of relevant criteria (14) such as topographic, Soil, Climate, Geological and Land use were weighed using Analytical Network Process method and Delphi expert’s opinions in Super Decision software environment. The make a Fuzzy method, Idrisi Selva software environment was used. Using the weighted linear combination method, desired layers were created and overlaid to make the land suitability map for the plant development.  The results showed that altitude, temperature, soil depth and slope percentage are the most important criteria in cultivation and development of this plant in the region, respectively. Based on the results, 4245 hectares (16.14%) of area has a high or very high, 4283 hectares (16.83%) has moderate, 4271.56 hectares (18.04%) has low potential for cultivation and development of Ziziphora tenuior. Also 12913 hectares (49.35%) of the area has found non suitable. The model was validated by matching the Ziziphora tenuior distribution boundary on the areas with the final potential classes map. Results showed that 88.6% of this boundaries are fitting to medium, high or very high potential classes. Thus it could be concluded that ANP Fuzzy model is well able to identify suitable areas for the development of this plant cultivation.

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This study aims at comparing the performance of MaxEnt and logistic regression in preparing the predictive habitat distribution map of Thymus kotschyanus and determining the factors affecting in the northern of Ardabil Province rangelands. 28 sites were selected and at each site, three transects with a length of 100 m and on each transect ten 1m2 plots were established. Soil samples were taken digging of nine soil profiles and samples taked from 0-15 and 15-30 cm depths. Geostatistical techniques were used to provide the soil maps. Digital elevation model was used to prepare the topography maps as a data layer. The Landscape metrics using Fragstats was calculated. Model accuracy in MaxEnt method was evaluated by using the AUC. By jackknife method and response curve, the most important environmental predictor variables were found. Model accuracy in logistic regression method is evaluated by using Hosmer and Lemshow Statistic and ROC. Then predictive distribution maps were produced. The Kappa coefficient index was used to evaluate the accuracy of the distribution maps. Based on logistic regression model, potassium of the 2th depth, aggregation index (positive correlation), slope and bare soil were the negative correlations and based on MaxEnt model, clay of the first depth, patch area (coefficient of variation), slope are the most influential factors affecting the presence of this species in this habitat. T.kotschyanus is widespread on light-textured soils (clay<15%), potassium (<18 meq/L), Silt (<20%) and high elevation (300-2700 meters above sea level), and slope (35-55%). Based on kappa coefficient, logistic regression model was able to predict the habitat distribution of studied species at the good level (kappa= 0.64) and MaxEnt had in intermediate level (kappa 0.42). These results indicate that the logistic regression model is more accurate.

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To assess the potential habitat of plants and appropriate planning for conservation and restoration policies the best fitted method should be used. In order to model the habitat distribution of the rare species of Vaccinium arctostaphyllus L., within the eight habitats of the plant, two place, with and without the species, were selected. Random-systematic method in the growing season was used. Data on different factors such as latitude and longitude, physiography of each habitat were recorded using GPS at 40 point. Soil samples were collected from a depth of 0-30 cm (active rooting depth). Then some physical and chemical properties of soil such as pH, electrical conductivity, soil texture, lime, soluble potassium, magnesium, soluble sodium, particulate organic matter, absorbable phosphorus, soluble bicarbonate and percentage of clay, silt and sand were measured in the laboratory. In the next step, logistic regression was used to determine the relationship between environmental factors and the distribution of V. arctostaphyllus L. Map of environmental factors affecting the distribution of the species was prepared using IDW spatial statistics to evaluate the interpolation methods. The Kappa index was used to assess the matching of forecasted map and the ground truth. The results of logistic regression showed that the most important factors affecting the distribution of V. arctostaphyllus L. were slope, geographical direction, phosphorus and silt. Presence of the species negatively is related to the geographical direction. Overlapping of the areas showed that these species are distributed in high slope and west and southwest direction. Also, the compliance of the forecast map with the actual habitat map was assessed at a good level (Kappa index: 0.65). In general, the results showed that the logistic regression method is able to give a good prediction for the habitat of the V. arctostaphyllus L. species. The results of this study could be used to identify and evaluate the susceptible habitats of this species and the possibility of conservation, reproduction and breeding as a rare and native medicinal plant.

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Background and objectives: The conservation and management of endangered medicinal and industrial plants in rangelands are essential for the economic and social benefits they provide. Dorema ammoniacum D. DON. is an important fodder, medicinal, and industrial plant that is threatened due to over-exploitation. This study aimed to predict the potential habitat of D. ammoniacum using logistic regression analysis and to identify the environmental factors that influence its distribution in the Nadoushan rangelands of Yazd province.
Methodology: We collected data on environmental factors, including topography, climate, soil, and vegetation, from the rangelands of Nadushan. Vegetation sampling was conducted in six homogeneous units using the random-systematic method. Soil samples were collected from the beginning and end of each transect at depths of 0-30 and 30-60 cm. We used variogram analysis to investigate the spatial structure between soil factors, and kriging interpolation and inverse distance weighting methods were used to prepare soil characteristic maps. The logistic regression model was used to predict the potential distribution of D. ammoniacum, using presence/absence data and environmental data.
Results: The results showed that the variables of saturated moisture, sodium and calcium percentage of the first soil depth, organic carbon percentage of the second soil depth, and nitrate of the first soil depth were the most important environmental factors affecting the distribution of D. ammoniacum. The presence of D. ammoniacum had a positive relationship with the percentage of saturated moisture and sodium of the first soil depth, organic carbon of the second depth, and calcium of the first soil depth, and a negative relationship with nitrate of the first soil depth. The logistic regression model predicted that 20% of the studied area had excellent suitability and 24% had suitable habitat for D. ammoniacum.
Conclusion: Logistic regression analysis was useful for predicting the potential habitat of D. ammoniacum in the Nadoushan rangelands, and the results can guide conservation efforts and management decisions. The study identified the significant environmental factors that influence the distribution of D. ammoniacum and provided a useful tool for identifying potential areas for sustainable exploitation and restoration of the species.