moslem Rostampour; Reza Yari; Samaneh Mohammadi moghaddam
Volume 33, Issue 1 , May 2026, Pages 1-10
Abstract
Abstract
Background and objectives
Plants 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 ...
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Abstract
Background and objectives
Plants 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.
Methodology
Habitats 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.
Result
Based 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.
Conclusion
In 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.
Iman Islami; Farhad Khabazi; Elmira Asadi-Fard; Mohammad Reza Kargar
Volume 33, Issue 1 , May 2026, Pages 11-20
Abstract
Extended Abstract
Background and Objectives: One of the major contemporary challenges in the field of natural resources is their degradation and decline, a process that has unfortunately accelerated with population growth and increasing human pressures. Furthermore, many national and regional development ...
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Extended Abstract
Background and Objectives: One of the major contemporary challenges in the field of natural resources is their degradation and decline, a process that has unfortunately accelerated with population growth and increasing human pressures. Furthermore, many national and regional development programs have been implemented without due consideration for strengthening governance structures in natural resource management. In this context, the role of governmental organizations and institutions in mitigating these damages is undeniable. One powerful tool for understanding the governance network and the behavioral patterns of such organizations is Social Network Analysis (SNA), which facilitates a deeper understanding of inter-organizational relations and their respective roles. Accordingly, the main objective of this study is to map the hybrid or inter-organizational network of key decision-making actors in the governance and management of natural resources in Fars Province (including governmental and non-governmental organizations), visualize their relationships, and identify their structural patterns within the natural resource governance framework of the region.
Materials and Methods: The research was conducted in three main stages. The first stage involved identifying organizational stakeholders, while the second involved analyzing their functional roles using the UCINET 6.0 software and the core–periphery index. Stakeholder identification was carried out through snowball sampling, and data collection was based on a structured SNA questionnaire and in-depth interviews with 25 key actors involved in natural resource governance in Fars Province. The questionnaires aimed to identify key stakeholders and their communication patterns in the governance network. The second stage focused on the analysis of inter-organizational interactions and the identification of the nature of these collaborations. Functional roles were analyzed using the core–periphery structure, in which nodes (organizations) were classified into core and peripheral categories. Core organizations were characterized by strong, frequent connections and high density across the network, while peripheral organizations displayed weak ties and lower network density.
Results: The study identified 25 key actors in the participatory natural resource governance network in Fars Province. These were classified into two main categories: 17 actors in the core group and 8 in the periphery. The core group included key players responsible for planning and enhancing the coherence of the governance network. The Fars Natural Resources and Watershed Management Organization emerged as the most central and influential node in the network. Additionally, six organizations with intermediary roles and six with developmental roles were identified as important actors in the network. For example, organizations such as Rural Cooperatives and County Governorates contributed to local empowerment and capacity building. Similarly, village councils and rural municipalities served as intermediaries for promoting public participation and monitoring natural resources. The findings emphasize the significance of inter-organizational collaboration and the pivotal role of local actors in achieving participatory natural resource governance. According to the results of the core–periphery index, the actors were categorized into two groups: Group 1 (Core), with a density index of 0.713, included key organizations playing major roles in resource management and regional development. Group 2 (Periphery), with a lower density of 0.196, consisted of organizations that contributed less significantly to governance and coordination.
Conclusion: The findings reveal that 17 core actors maintain high levels of interaction in the natural resource governance network of Fars Province. Other identified actors demonstrated weaker collaborative ties and lower network dynamism. The Natural Resources and Watershed Management Organization remains the central institution with the most influential role, followed by the Fars Provincial Government and the Agricultural Jihad Organization, both of which play key roles in coordination and supervision. In contrast, organizations such as the Railway Administration, Civil Registration Organization, and Cultural Heritage Department were identified as having minimal connectivity within the governance network.A noteworthy phenomenon in this assessment was the emergence of hybrid organizational communities within the institutional decision-making network of natural resource governance in Fars. These hybrid structures consist of clusters of 2 to 5 organizations that jointly execute key management functions.The formed hybrid governance model revolves around the Natural Resources Organization and includes interconnected communities with 2 to 6 members, whose collaborations are based on shared goals or complementary functions. These hybrid networks are understood as relational structures shaped by organizational pathways and governance objectives. Thus, by identifying and defining the hybrid network governance model in Fars Province, this study has revealed the trajectory of organizational collaboration in natural resource management and provided a targeted framework for improving governance. The findings can inform policy formulation to enhance the efficiency, agility, and cohesion of governance components and offer a more robust response to the ongoing challenges in the region's natural resource management.
Nasim Shaabani; Farhad Aghajanloo; Nafiseh Salahi Moghadam; Peyman Akbarzadeh; Mehdi Khoshbakht
Volume 33, Issue 1 , May 2026, Pages 21-30
Abstract
Abstract
Background and Objectives
Climate change is emerging as one of the main threats to the habitats and distribution of native plants. These changes can have widespread effects on the distribution of plant species. The T. persicus species T. persicus is found only in certain areas of northwestern ...
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Abstract
Background and Objectives
Climate change is emerging as one of the main threats to the habitats and distribution of native plants. These changes can have widespread effects on the distribution of plant species. The T. persicus species T. persicus is found only in certain areas of northwestern Iran and is at risk of extinction for unknown reasons. This study uses the maximum entropy (MaxEnt) model to predict the effects of climate change on the distribution of T. persicus in northwestern Iran. The aim of this research is to assess the possible effects of climate change on the habitats of this species and identify areas that may be under serious threats.
Materials and Methods
In this study, Mahneshan County, Zanjan Province and Takab County, West Azerbaijan Province, located in the northwest of Iran, were selected as study areas. To determine the locations of the T. persicus species, 70 presence sites were randomly classified and selected based on the vegetation typology map of the provinces, which were used as training data for modeling. Also, to evaluate the model, 70 actual presence sites were collected in the field using the Global Positioning System (GPS) in July 2024 in the Mahneshan areas of Zanjan Province (the area of the directions of the Belghis Peak) and Takab County, West Azerbaijan Province. To model the distribution of this species, 30 environmental variables including 19 climate variables were used in three time periods of the present 2024 (1990–2020), 2070 (2060–2080) and 2100 (2080–2100) under the SSP585 and SSP126 scenarios and the IPSL-CM6A-LR general circulation model, 3 physiographic variables (elevation, slope and slope direction) as well as 8 soil physical and chemical variables. All environmental data were prepared with ArcGIS 10.8 software at a scale of 30 seconds (about one square kilometer). Finally, the maximum entropy model (MaxEnt) was used to model the distribution of the T. persicus species.
Results
Current distribution maps of this species were prepared with climate data under the two SSP585 and SSP126 scenarios, along with soil and physiographic data. Comparison between the effect of soil and climate data on distribution prediction, using the AUC index, showed that soil data (AUC=0.85) have a lower effect on predicting the distribution of this species. This could be due to the lack of access to data such as lead and zinc contamination of the region, which did not enter this information into the model. However, these elements can have a great impact on the distribution of this species due to the location of the T. persicus species near the Angouran lead and zinc mine. Subsequently, future distribution maps of the species for the years 2070 and 2100 were prepared using climate and physiographic data. The model results showed that the most important variables affecting the distribution of the studied species include altitude, Bio1, Bio10, Bio11, Bio6, Bio12, Bio17, Bio18, Bio5, and slope. Also, according to the results obtained, T. persicus had a more effective distribution in areas with annual rainfall of 300 to 500 mm, altitudes above 2500 m, temperatures below 8 ° C and slopes above 20 °.
Conclusion
The results of modeling the distribution of the T. persicus species under the SSP126 and SSP585 scenarios indicate a significant reduction in the area of favorable areas for the growth of this species in the future. Currently, the area of the favorable area (with a best threshold of 0.3) is about 550.4 km2, which will decrease to 377.4 km2 under the SSP126 scenario and 252.2 km2 under the SSP585 scenario in 2070. In 2100, this decrease will be further and the area of the favorable area will reach 181.2 km2 (SSP126) and 93.9 km2 (SSP585). These changes indicate the negative effects of climate change on the distribution of the Persian thyme species and highlight the need for conservation measures to preserve this species against threats from climate change.
Mohebi Mohebbi; Alireza Eftekhari; Mahshid Souri; Saeedeh Nateghi
Volume 33, Issue 1 , May 2026, Pages 31-40
Abstract
Extended abstract
Background and objectives: Efforts for sustainable management of rangelands require evaluation and monitoring in different temporal and spatial scales. It is necessary to identify the most important climatic effects and how they affect vegetation factors in the field of optimal rangeland ...
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Extended abstract
Background and objectives: Efforts for sustainable management of rangelands require evaluation and monitoring in different temporal and spatial scales. It is necessary to identify the most important climatic effects and how they affect vegetation factors in the field of optimal rangeland management. Sablan peak is the third highest peak in the country and is known as the livestock hub of Ardabil province. Considering the importance of Sablan rangelands in the economy and livelihood of the residents of the region, maintaining water and soil and other important services, it is necessary to organize a suitable management plan for its long-term use and to determine a model to predict the percentage of canopy cover and its biomass rate.
Materials and methods: For this purpose, basic and annual information on canopy percentage, biomass and condition, and climatic information such as rainfall and temperature are needed. Also, obtaining a model that can estimate the percentage of canopy cover and biomass with acceptable accuracy and precision without visiting in person; it is one of the priorities of rangeland management in the region. Based on this, in order to identify the most effective climate factors and determine the relevant model, Shabil Sabalan site in Ardabil province was evaluated and monitored for 5 years (2017-2021). Vegetative factors, including crown percentage of total cover and biomass rate, and functional factors, including rangeland condition and tendency, were evaluated during a 5-year period. Evaluations were carried out in a 50-hectare site named Shabil at the foot of Sablan Mountains in Lahrood section of Meshginshahr city with Festuca ovina-Bromus tomentellus-Onobrychis cornuta plant type. This site is a representative area for rangelands in the north of Sablan in terms of plant and functional traits. The key area of two hectares with a height of 2805 meters inside the site was considered for the implementation of the plan and evaluation. The average long-term rainfall of 30 years leading to the year of its study is 460 mm. To analyze the data, General Linear Model test was used in Minitab 16 software. Pearson correlation test and stepwise regression were used to check and determine the correlation of environmental and vegetation data and to identify the most effective factors and predict the model.
Results: The results of the evaluation of plant factors, the percentage of canopy coverage and biomass showed that the highest amount of coverage and biomass was obtained in one year after with the highest amount of rainfall. Therefore, the analysis of the variance of canopy percentage and biomass during the studied years was significant at the level of 1%. The results of the evaluation of the site-based or environmental factor of the rangeland condition also showed that the best amount of rangeland condition was obtained in years with more rainfall and more coverage and biomass. In examining the correlation between the studied indicators, the percentage of vegetation with autumn and winter rainfall showed a significant positive correlation at the level of 5%, but biomass was not correlated with any of the studied variables. The results of the step-by-step regression also showed that among the analyzed indicators, autumn and winter rainfall is the most effective factor in predicting the percentage of vegetation and total rainfall, and autumn and winter rainfall are also the most effective factors in predicting biomass at a probability level of 5% were in the region.
Conclusion: The three important indicators of canopy percentage, biomass and condition have performed well in showing the difference of different years, but the vegetation index has the highest correlation and due to the ease of vegetation evaluation compared to biomass evaluation, therefore the annual evaluation of canopy percentage Coverage as the most important factor can help in determining the prediction model. With the continuation of data collection, stronger and more accurate models can be obtained to estimate the canopy percentage and the amount of biomass
Maryam Salehi Lande; Maasoumeh Movaghari; Nafiseh Rang Zan; Leila Khalasi Ahvazi
Volume 33, Issue 1 , May 2026, Pages 41-50
Abstract
Abstract
Background and objectives
Monitoring and evaluating the effectiveness of implementing any type of project, including land reclamation projects, helps relevant managers in making better decisions for future projects. The present research aims to investigate the chemical, physical and hydrological ...
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Abstract
Background and objectives
Monitoring and evaluating the effectiveness of implementing any type of project, including land reclamation projects, helps relevant managers in making better decisions for future projects. The present research aims to investigate the chemical, physical and hydrological characteristics of planting with species Seidlitzia rosmarinus Boiss ex B., Tamarix passerinoides Delile ex Desv. and Prosopis juliflora SW. DC. in south and southeast of Ahvaz.
Methodology
Soil samples were collected in four areas (control (no planting), S. rosmarinus, T. passerinoides, and P.juliflora), at two distances (under the crown and outside the crown) and at two depths (0-30 and 30-60 cm). The collected soil samples were transferred to the laboratory and after preparing a composite soil sample; its properties were measured in three replicates. some physical properties (bulk density by clod method, soil aggregate stability by sieve method, penetration resistance by penetrometer), some chemical properties (soil pH using the saturated extract method and a pH meter, electrical conductivity using the saturated extract and EC meter, total soil nitrogen by Kjeldahl method, available phosphorus using the Olsen method with Spectrophotometr, soluble potassium in soil saturation extract by flame photometer, and organic matter by the ignition method), and some hydrological properties (soil moisture by weight percentage) were measured. In addition, the soil infiltration rate was compared by establishing two double cylinders in the control area and the planted area.
Results
The results of this study showed that nitrogen percentage and penetration resistance had significant differences between the control area and planting areas. Planting with each species reduced the soil penetration resistance, and the highest value of this index was related to the control area and the lowest value was related to the T. passerinoides and then P.juliflora. In addition, T. passerinoides and P.juliflora increased soil nitrogen content and reduced soil pH compared to the control area. Also, the results of comparing the average soil properties under the canopy and outside the canopy of the plants and in two studied depths showed that under the canopy of the T. passerinoides, the electrical conductivity of the first depth of the soil decreased and its organic carbon increased. Similar also S. rosmarinus, caused a decrease in the electrical conductivity of the soil and an increase in organic carbon under the canopy, with the difference that the increase in organic carbon also occurred outside the canopy. While P.juliflora increased the electrical conductivity and pH of the soil under the plant crown compared to outside the crown. Also, the results obtained from the Kostiakov infiltration equation comparing the infiltration rate between the control area and the planted area showed that planting in this area increased the infiltration rate by 124% compared to the control area.
Conclucion
In general, the results of this study on the non-native species of P.juliflora showed that despite the effect that this species had on reducing soil penetration resistance and increasing soil nitrogen content compared to the control area, but it also increased electrical conductivity and pH under the plant crown While the two native species, T. passerinoides and S. rosmarinus, led to a decrease in electrical conductivity and increase in soil organic carbon under the plant crown and even outside the plant crown (in the case of S. rosmarinus). Therefore, despite the positive effects of native species on soil properties in this study, planting of these plants is prioritized over the non-native species, P.juliflora.