Rostam Moslempour; Samira Hossein Jafari; Reza Yari
Volume 33, Issue 2 , July 2026, , Pages 101-121
Abstract
Extended Abstract Background and objectives: Iran has a high potential in carbon storage due to the large extent of rangelands. Rangeland ecosystems are atmospheric carbon sinks. Soil is an important source of carbon storage and it has been proved that carbon storage in soil is more than three times ...
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Extended Abstract Background and objectives: Iran has a high potential in carbon storage due to the large extent of rangelands. Rangeland ecosystems are atmospheric carbon sinks. Soil is an important source of carbon storage and it has been proved that carbon storage in soil is more than three times the storage in the atmosphere and vegetation. Knowing the amount of soil carbon sequestration and storage can be used as a useful and practical tool to better understand soil carbon cycle. Therefore, the purpose of this research is to investigate and determine the most important soil factors affecting the amount of soil carbon storage in Zirkouh and Ferdows habitats in South Khorasan with different plant types.Methodology: The present research was carried out in South Khorasan province in rangeland habitats of Zirkouh, including Artemisia sieberi, Zygophyllum eurypterum, and Tamarix stricta plant types, and in the desert areas of Ferdows, including Calligonum polygonoides, Seidlitzia rosmarinus, Stipagrostis pennata, and Zygophyllum eurypterum types. 60 squares of 4×4 meters were established in the representative area of each habitat by random-systematic method, and, canopy cover percentage and plant density was estimated in each plot. Then, 10 plants were randomly selected. Soil samples were taken to a depth of 70 cm in the plots, under the canopy cover of the plant. Soil physical and chemical properties were determined in the laboratory. The correlation diagram (Pearson correlation coefficient) between environmental characteristics and carbon storage was drawn. First, ordinary multiple linear regression (OLS) analysis was used to examine the relationships, and the multiple collinearity between environmental characteristics and organic carbon storage was examined by the variance inflation factor (VIF) criterion. Since normality and multiple collinearity are assumptions of ordinary regression, two regression models: Partial Least Squares (PLS) and Principal Component Regression (PCR), were used in the present study.Results: The results of descriptive statistics showed that in Zirkouh habitat, the highest and lowest changes in soil carbon storage are in Tamarix habitat (Mean=20.77, SD=11.66) and Artemisia habitat (Mean=13.83, SD=1.81), respectively. In Ferdows region, the highest and lowest changes in the amount of soil carbon storage were observed in Calligonum (Mean=6.96, SD=1.57) and Zygophyllum (Mean=5.36, SD=0.80) habitats, respectively. In Zirkouh habitat, carbon storage had a significant negative correlation with sand (p≤0.05) and a significant positive correlation with canopy cover percentage, N, P, silt, EC (p≤0.01), lime and K (p≤0.05). Interestingly, sand percentage had a significant negative correlation with all measured soil properties in this diagram. In Ferdows region, carbon storage had a significant negative correlation with gypsum and potassium (p≤0.05) and a significant positive correlation with N. In the present study, two models of partial least square regression (PLS) and principal component regression (PCR) were used. In PLS regression method as the best model, in Zirkouh habitat, the parameters such as sand, silt, phosphorus and canopy cover percentages remained as significant variables in the model and among them, silt percentage had the most impact in predicting carbon storage. In Ferdows habitat, the parameters including organic carbon, silt, nitrogen, potassium and gypsum remained as significant variables in the model.Conclusion: Investigating the effective factors on carbon storage can help managers and decision makers in choosing management methods and modifying existing methods in order to reduce atmospheric carbon density. The results of this research showed that among the two models of partial least square regression (PLS) and principal component regression (PCR), PLS model is the best model to determine the factors affecting carbon storage. There was a positive relationship between vegetation cover and soil nutrients (N, P, K) and carbon storage in the Zirkouh habitat, which emphasizes the role factors related to fertility in carbon storage. By implementing appropriate range management strategies—such as protection, improvement, and restoration of vegetation cover—we can increase soil organic carbon storage. This approach can help prevent air pollution, reduce vegetation degradation, and ultimately mitigate the harmful effects of climate change.
moslem Rostampour; Reza Yari; Samaneh Mohammadi moghaddam
Volume 33, Issue 1 , May 2026, , Pages 1-10
Abstract
AbstractBackground and objectivesPlants distribution pattern is one of the most important features of plant communities whose concept is related to the condition of a species and its distribution in a plant community. Awareness of the spatial distribution pattern of plants in each region is one of the ...
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AbstractBackground and objectivesPlants distribution pattern is one of the most important features of plant communities whose concept is related to the condition of a species and its distribution in a plant community. Awareness of the spatial distribution pattern of plants in each region is one of the basics and requirements for measuring and evaluating vegetation that is important in determining management practices. This study carried out in order to analyze and investigate the distance indices, probability distribution and regression in order to determine the distribution pattern of 17 rangeland species from the dominant species of Southern and Razavi province.MethodologyHabitats of 17 plant species were identified in four sub-regions: semi-desert, steppe, semi-steppe, and dry forests located in the Irani-Torani vegetation zone in South Khorasan and Khorasan Razavi province. In each habitat, 40 plots of 1×1 m for herbs, 2×2 m for shrubs, 4×4 m for shrubs, and 10×10 m for trees were established along 2 transects (total of 80 plots per habitat). The distribution of species was determined by calculating quadratic indices including Index of Dispersion (ID), Lexis’s Index (IL), Charlier’s Index (ICh) Index of Cluster Size (ICS). Green’s Index (GI), Index of Cluster Frequency (ICF), Index of Mean Crowding (IMC), Index of Patchiness (IP), Morisita’s Index, (IM) and Standardized Morisita (Ip) and probability distribution indices. including Poisson distribution (ID), positive and negative binomial distribution, and Taylor and Iwao’s patchiness regression and Taylor’s power law indices.ResultBased on the results indices of Morisita’s Index of Cluster Frequency. Standardized Morisita index and Lexis’s Index are close to each other. Stipagrostis, Bromus tomentellus, Acantholimon scirpinum, Stipa barbata, Festuca ovina, Rhamnus pallasii and Cornulaca monacantha species have clumped pattern based on all quadratic indices. Berberis vulgaris, Onobrychis cornuta and Acantholimon scirpinum species have a random distribution pattern based on Green's index and Stachys inflata based on spot and Green's indices. Based on the probability distributions studied on the density data of Festuca ovina, Cornulaca monacantha, Tamarix ramosissima , Astragalus gossypinus and Juniperus polycarpos species, they were following the Poisson distribution which represents a random pattern. Stipa barbata, Festuca ovina and Astragalus squarrosus were the only species that follow only the positive binomial distribution which indicates a uniform pattern. Based on the regression methods, the distribution pattern of the studied plants was clumped. Stachys inflata had a clustered distribution based on all indices. Caligonium polygonoide had a clustered distribution based on all indices except Z and Charlier’s Index (random and uniform, respectively). The results of Morista index, cluster frequency index (ICF), standard Morista index and Lexis index (IL) were close to each other.ConclusionIn the present study, quadratic indices, regression, and probability distributions were used. Among the methods, quadratic indices predicted 65 % of species clumped, 32 % uniform, and 3 % random distribution. Since the standard Morrisita and Morrisita index are not dependent of N and n, there are better indicators to determine the distribution pattern.
Reza Yari; Seyedeh Mahbubeh Mirmiran; Yaser Ghasemi Aryan; Esfandiar Jahantab
Volume 32, Issue 4 , December 2025, , Pages 337-351
Abstract
Background and ObjectiveExcessive, unprincipled, and over-capacity use has resulted in the destruction and gradual reduction of rangeland productive capacity. Consequently, the diverse and multi-functional utilization of rangelands reduces livestock pressure, preserves and restores vegetation cover, ...
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Background and ObjectiveExcessive, unprincipled, and over-capacity use has resulted in the destruction and gradual reduction of rangeland productive capacity. Consequently, the diverse and multi-functional utilization of rangelands reduces livestock pressure, preserves and restores vegetation cover, creates employment opportunities, and increases the income of rangeland users. Beekeeping represents an important aspect of the multi-purpose use of rangelands, which, in addition to producing honey and a variety of other by-products, plays a significant ecological role in pollination and in supporting the survival of agricultural, forest, and rangeland products. It also contributes to increasing beneficiaries' income and improving the overall economic situation of rural residents.MethodologyThis research was conducted to assess the ecological and economic potential of beekeeping within the Jahannama rangelands of Golestan Province. After gathering baseline information, a systematic inventory of plant species was conducted during the entire growing season. The family, scientific name, Persian name, and flowering duration of all identified species were determined using available botanical resources. The research type was applied, and the research approach was quantitative. The data collection instrument consisted of a structured questionnaire, relying on available sources and direct interviews with all beekeepers in the region, numbering 15 individuals. The questionnaire included variables related to inputs consumed, labor (person-days), consumption quantity (kilograms), production input prices (rials), income, production costs, production quantity and price, the number of days and months of rangeland usage, and the beneficiaries’ satisfaction with the vegetation cover of the rangelands for beekeeping purposes. The questionnaire's validity was verified through the opinions of specialists and experienced experts; however, the questionnaire's reliability was estimated using the Cronbach’s alpha method (0.81) in SPSS. Finally, to estimate the profit obtained from rangelands for beekeeping, the indexing method based on the marginal product value approach and the relationship between the number of days of rangeland use, the release of honeybees, and honey production was applied.ResultsAltogether, 134 species of nectar-producing and pollen-producing plants from 80 genera and 31 families were identified in the area. The families Asteraceae (29 species), Lamiaceae (23 species), and Fabaceae (19 species) exhibited the highest abundance. Regarding attractiveness classes, 28, 39, 43, 21, and 3 species were assigned to attractiveness classes 1-5, respectively. More than 64 percent of the identified species were both nectar and pollen producers. Based on regular field observations, the flowering period of plant species ranged from May to September. The majority of plant species (52 species) flowered from June to August, while 20 species flowered from July to August. Therefore, the months of June through August constitute the most suitable period for establishing beehives in these rangelands. The findings revealed that, because the flowering duration of most nectar- and pollen-producing species in the rangelands is 93 days (June–August) and the average number of rangeland utilization days is 74 days, the total economic value of the rangeland—which includes the combined value of all ecosystem services and goods provided by the rangeland system, such as forage, medicinal plants, ecotourism, regulatory services, and other benefits, of which the economic value derived specifically from beekeeping constitutes just one part—was considerable. Therefore, the total value of the rangelands for beekeeping, considering the number of exploitation days and the daily price of honey based on 2023 rates (645,000 Tomans), was calculated to be 13,754,560,500 Rials, and the economic value of beekeeping was estimated as 1,551,438.9 Rials per hectare.ConclusionIn general, the results demonstrate that these rangelands, due to the presence of numerous plant species, predominantly fall within attractiveness classes I through III, possess suitable and substantial potential for the development of beekeeping activities and for the consequent increase in economic income. This valuable natural resource can be utilized, along with providing forage for livestock, thereby contributing to improved livelihoods and enhanced economic well-being for beneficiaries.
Rostam Moslempour; Reza Yari; Seyedeh Mahboubeh Mirmiran
Volume 31, Issue 4 , January 2025, , Pages 347-362
Abstract
Background and objectives: Desert ecosystems usually receive less attention in carbon sequestration studies due to their low vegetation cover and limited carbon sequestration. However, since more than a third of the earth's surface covers 55% of the total area of Iran and more than 50% of the area of ...
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Background and objectives: Desert ecosystems usually receive less attention in carbon sequestration studies due to their low vegetation cover and limited carbon sequestration. However, since more than a third of the earth's surface covers 55% of the total area of Iran and more than 50% of the area of South Khorasan province, so they can be a significant carbon storage place. This research was conducted with the aim of investigating the carbon sequestration by six desert species: Calligonum polygonoides, Seidlitzia rosmarinus, Artemisia sieberi, Stipagrostis pennata, Salsoa richteri and Zygophyllum eurypterum in the rangeland of Ferdows.Methodology: In this Study, 30 plots of four square meters were randomly established in Calligonum polygonoides, Seidlitzia rosmarinus, Zygophyllum eurypterum and Salsoa richteri and in Artemisia sieberi and Stipagrostis pennata habitats, 30 plots of two square meters were randomly established and the canopy percentage and plant density were estimated in each plot. Vegetation cover and plant density were estimated in each plot. In the same plots, the soil profile was dredged down to a depth of 70 cm under the canopy, and the soil sample was taken and transported to the laboratory. By estimating the percentage of soil organic carbon (using the Walkley-Black method) and bulk density of the soils (using the paraffin method), the amount of soil carbon sequestration was finally measured. The data was used in the form of a completely random design, and Tukey's test was used to compare the means at the five percent probability level. The Shapiro-Wilk and Bartlett tests were used to check whether residual value variances were normal and homogeneous. The data obtained from the results of the experiments were analyzed using R software.Results: In general, the results showed that the highest amount of soil organic carbon was observed in Salsoa richteri and Artemisia sieberi habitats and the lowest amount was observed in Seidlitzia rosmarinus habitat. The highest amount of bulk density was observed in Calligonum polygonoides habitats. The results of the analysis of variance showed that the effect of the habitat on soil carbon sequestration is significant (p<0.01) and the amount of this effect is moderate to high (ηp2 between 0.10 and 0.47). The highest and lowest amount of carbon sequestration was observed in Zygophyllum eurypterum (28.66 tons per hectare) and Seidlitzia rosmarinus (12.80 tons per hectare habitats, respectively. Also, in terms of the percentage of vegetation, a significant difference was observed between habitats. The highest and lowest of vegetation cover percentage was obtained in Zygophyllum eurypteru (36.84%) and Seidlitzia rosmarinus (10.15%) habitats, respectively. Seidlitzia rosmarinus habitat had the lowest amount of soil organic carbon and also the highest percentage of vegetation, and compared to other plants, it produced the lowest amount of carbon sequestration. The highest and lowest plant density was obtained in the Stipagrostis pennata and Zygophyllum eurypterum habitats, respectively. Despite the high organic carbon in the soil of its habitat, Salsoa richteri plant also had low carbon sequestration due to the low density and percentage of vegetation cover. The results of correlation analysis show that there is a positive and significant relationship between vegetation percentage and carbon sequestration (p<0.01), but no significant relationship was observed between plant density and carbon sequestration (p>0.05).Conclusion: The amount of carbon sequestration was different depending on the percentage of vegetation and there was a positive and significant relationship between the percentage of vegetation and the amount of carbon sequestration, while no relationship was observed between the amount of vegetation density and carbon sequestration. So, in this study, Zygophyllum eurypterum habitat produced the highest percentage of vegetation cover and carbon sequestration, and Seidlitzia rosmarinus habitat had the lowest percentage of vegetation cover and carbon sequestration. Therefore, the vegetation percentage parameter can be used to estimate carbon sequestration. In other words, in the habitats that have bushy and shrubby plants, it is possible to estimate the amount of carbon sequestration based on the canopy percentage.
Jalil Farzadmehr; Yaser Ghasemi Aryan; Reza Yari
Volume 29, Issue 2 , July 2022, , Pages 156-165
Abstract
This study aimed to investigate the effect of restoration projects on soil surface indicators and performance characteristics in Taherabad rangelands of Ferdows. The Landscape Function Analysis method was used to determine soil surface properties and yield potentials. In this regard, in the representative ...
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This study aimed to investigate the effect of restoration projects on soil surface indicators and performance characteristics in Taherabad rangelands of Ferdows. The Landscape Function Analysis method was used to determine soil surface properties and yield potentials. In this regard, in the representative area of each treatment, three transects (each for 100-meter) were settled at specified distances along the main slope. Along each transect the length and width of plant spots and the length of the inter-spot distance were measured. Excel and LFA (Landscape Function Analysis) instructions were used to calculate the performance potentials. To examine the significance of the performance potentials, SAS software was used in this study. According to the results, there is a significant difference between the treatments. The highest percentage of stability was estimated in the arc basin + exclusion and the lowest was in the treatment of the control area; also, soil infiltration of different restorative treatments, significant differences, and the highest and lowest percentages of soil infiltration was estimated in the arc basin + exclusion and control projects, respectively. The results showed no significant difference in the Nutrient Cycling Index and soil mineral elements in different rangeland restoration projects. Landscape Organization Index for arc basin + exclusion, planting + exclusion, exclusion and control were estimated to be 0.33, 0.22, 0.18 and 0.14, respectively. The Kruskal–Wallis test showed a significant difference (at a 5% level) between the soil surface indicators at different rangeland restoration projects. It is concluded that there are significant differences among soil surface indicators, collar and canopy, litter, soil surface fragility, erosion type and intensity, eroded materials, nature of soil surface and wetting test at 5%, and texture at 1% in different restoration treatments. Different treatments have caused differences in these indicators. Also, there is no significant difference between cryptogam and microtopography indicators. In general, arc basin +exclusion construction in arid and semi-arid regions is a useful restoration activity and increases soil stability and infiltration.
Yaser Ghasemi Aryan; Hossein Arzani; Esmaiel Filekesh; Reza Yari
Volume 20, Issue 1 , June 2013, , Pages 1-10
Abstract
Determination of grazing capacity is considered as one of the most fundamental aspects of range management and understanding the effective factors on it is of utmost importance. Since the amount of forage production in a growth period is the basis for calculation of grazing capacity, in this research ...
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Determination of grazing capacity is considered as one of the most fundamental aspects of range management and understanding the effective factors on it is of utmost importance. Since the amount of forage production in a growth period is the basis for calculation of grazing capacity, in this research the estimation of production through the measurement of plant’s dimensions was investigated. For this purpose, the habitat of Artemisia siberi was determined and then 8 transects of 50 m length were established with 10 m intervals by random-systematic method. The height and diameter of 40 species of Artemisia siberi with different dimensions were recorded and the production of each species was clipped and weighted after drying. All data were analyzed by SPSS. Results showed that there was a significant linear correlation between production as a dependent variable and volume, canopy cover and height of Artemisia siberi as independent variables (R2= 0.88, 0.84, and 0.74, respectively) at 1% probability level. Finally, the relationship between production and volume was identified as the best linear relationship.