https://envs.sbu.ac.ir/ Advanced Environmental Sciences en daily 1 Sat, 21 Mar 2026 00:00:00 +0330 Sat, 21 Mar 2026 00:00:00 +0330 https://envs.sbu.ac.ir/article_105999.html Introduction: Nowadays, conservation agriculture in dryland areas has gained great importance due to its potential to minimize climate hazards, reduce soil erosion, improve soil quality and increase available moisture. Few studies have been reported on genotype × tillage interaction for chickpea yield in dryland areas. The aim of this study was to evaluate the efficiency of the models used in stability analysis, including different AMMI indices, a combination of the two AMMI and BLUP methods, WAASB and WAASBY indices, and also to draw different diagrams to better understand the interaction of genotype × tillage (environment) and identify high-yielding chickpea genotypes adapted to the climatic conditions of rainfed regions in different tillage systems.Material and methods: Sixteen chickpea genotypes were evaluated under three tillage systems including conventional tillage with complete residue removal (CT), reduced tillage (ploughing with a chisel plough into the remaining vegetation cover at a depth of 10 to 15 cm of soil - RT), and no-till with vegetation remaining on the soil surface (CA) in farmer's fields in Delfan county, Lorestan province, during two cropping years (2019-2020). Statistical analyses were performed to determine the stability of genotypes in different tillage systems using the Metan and GGE multi-environmental experiment analysis packages in R software. AMMI statistical parameters as well as AMMI statistical-based parameters including ASV, SIPC, EV, ZA, SSI, WAASB, and WAASBY were used on the genotype × environment (tillage) interaction matrix obtained from the best linear unbiased prediction (BLUP).Results and discussion: The results of the likelihood ratio test showed that the effect of genotype and genotype × tillage interaction was significant on grain yield. Therefore, the unbiased best linear prediction (BLUP) analysis was considered appropriate for these data. Based on the AMMI Stability Value Index (ASV), genotypes 10, 4, 9, 14 and 12 had more stable yield. The simultaneous selection index (SSIASV) based on ASV identified genotypes 9, 4, 13, 10 and 6 as superior genotypes in terms of grain yield and yield stability. The AMMI2 biplot diagram based on the first two principal components identified genotypes 11, 2 and 6 as genotypes with yield stability. Considering that not all principal components contribute to the AMMI2 biplot calculation and only the first-two principal components are used, accounting for 18.47 and 25.26 percent of the genotype × tillage (environment) interaction, the WAASBY genotypic stability index was used, which allows simultaneous interpretation based on average yield and yield stability in a two-dimensional graph. Based on the WAASBY index based on BLUP analysis, genotypes 4, 5, 6, 8, 9, 11, and 15 were identified as high-yielding with stable yield. The results of the mosaic plot showed that the contribution of genotype and genotype × tillage (environment) interaction was 38.5 and 62.94 percent of the total variation, respectively.Conclusion: Overall, it seems that using the WAASBY chart with variable weighting from 0 to 100 for the WAASB index and average grain yield can lead to more reliable results from stability analysis using analyses such as factor analysis, BLUP, and AMMI in identifying selected genotypes. Considering that the mixed model and all components were used in calculating the WAASBY index, it seems that this index is superior to other indices. https://envs.sbu.ac.ir/article_105892.html Introduction: Given the growing and alarming trend of land cover changes-primarily driven by unsustainable Development in agricultural, urban, and industrial sectors-surface water resources, especially rivers, are increasingly threatened by various pollutants. Among the most critical of these are heavy and toxic metals, which pose serious risks to human and ecological health by directly or indirectly entering the food chain. As a vital transboundary water resource for the northwestern provinces of Iran, the Aras River is exposed to such threats. Accordingly, this study aims to perform a spatiotemporal analysis of land cover changes and investigate their relationship with variations in heavy metal concentrations in the Aras River. The primary focus is on identifying spatial patterns of overlap between land use transformation and chemically polluted hotspots, as well as evaluating the ecological risk potential of toxic elements entering the food web.Material and methods: To analyze land cover change trends from 2001 to 2024, time-series satellite imagery from the MODIS sensor (MCD12Q1 product) was utilized. Land cover dynamics were extracted and analyzed for three key years: 2001, 2012, and 2024. Concurrently, field sampling was conducted at 13 selected stations along the Aras River during two seasonal intervals (May and August 2024). The collected water samples were acidified and prepared following standard protocols, and were chemically analyzed using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). Target metals included lead (Pb), arsenic (As), nickel (Ni), cadmium (Cd), mercury (Hg), and chromium (Cr), which were evaluated in terms of concentration, spatial distribution, and compliance with national and international standards (FAO, WHO, EPA).Results and discussion: Land cover analysis revealed that rangelands and agricultural lands experienced the highest rates of change throughout the study period. Chemical analysis of the water samples in May showed that concentrations of lead, arsenic, and nickel exceeded international permissible limits in several stations. In August, although lead concentrations relatively decreased, other elements including arsenic, cadmium, mercury, nickel, and chromium maintained relatively uniform levels across most stations-often approaching ecological risk thresholds. While some metal concentrations remained within safe limits for agricultural irrigation, livestock consumption, and aquatic tissue accumulation, they were deemed unsuitable for aquatic life. Long-term human exposure through consumption of contaminated agricultural, livestock, or aquatic products could pose serious toxicological risks due to bioaccumulation.Conclusion: The results indicated a significant and meaningful correlation between land use change and increased concentrations of toxic heavy metals in surface waters. These findings underscore the urgent need to revise land management policies, enforce stricter controls on the discharge of untreated effluents, and enhance continuous water quality monitoring systems. By integrating remote sensing data with laboratory-based environmental assessments, this. https://envs.sbu.ac.ir/article_106000.html Introduction: Population growth and increasing human needs have led to a rise in fossil fuel consumption and land-use changes, resulting in climate change and global warming. Carbon sequestration has gained significant importance as a management strategy for controlling atmospheric carbon levels. The objective of this study is to evaluate carbon sequestration rates and soil characteristics in rangeland and agricultural land uses in the Chatāl region of Golestan Province.Material and methods: This study was conducted in the Chatal village watershed in Golestan Province, covering an area of 3000 hectares. Soil sampling was performed at 100 points at a depth of 0-30 cm. Parameters including bulk density, organic carbon, pH, electrical conductivity, soil texture, and aggregate stability were measured using standard methods. After determining and calculating all parameters, data normality was first examined using the Shapiro-Wilk test, and a t-test was used to compare the rangeland and agricultural land uses. Additionally, the correlation of the studied parameters was performed using the Pearson's correlation coefficient test using R software.Results and discussion: The results indicated that the mean organic carbon content in rangeland land use (1.42%) was higher than in agricultural land use (0.79%). Additionally, the mean bulk density in agricultural land use (1.51 g/cm³) was lower than in rangeland (1.06 g/cm³). Soil aggregate stability in rangeland land use (8.51) was significantly higher than in agricultural land use (4.3). A significant positive correlation was observed between organic matter and carbon sequestration in both land uses, with correlation coefficients of 0.84 in rangeland and 0.77 in agricultural land use. Furthermore, electrical conductivity exhibited a negative impact on carbon sequestration in agricultural land use (correlation coefficient of -0.22).Conclusion: The results of this study highlight the challenges in maintaining soil quality and carbon sequestration capacity in agricultural lands. Based on the comparison between rangeland and agricultural land uses, it is evident that rangeland land use plays a more significant role in carbon sequestration. This is due to the presence of more stable vegetation cover and better management of organic matter in rangelands. In agricultural land uses, common farming practices such as plowing and the use of chemical fertilizers can lead to a decrease in soil organic carbon content. In contrast, rangeland use, which typically includes more stable vegetation cover, can contribute to maintaining and increasing carbon sequestration. To enhance carbon sequestration capacity in both land use types, the following recommendations are proposed: Promote sustainable agricultural practices that help maintain soil structure and reduce soil compaction, Preserve and expand rangelands by preventing their conversion to agricultural lands, Provide necessary training to farmers about the importance of organic matter and methods to increase it in the soil, Conduct further research to identify best practices for increasing carbon storage in both land use types across different regions. These recommendations can contribute to effective management policies for mitigating the negative effects of climate change and emphasize the need for sustainable agricultural practices. Rangeland land use plays a greater role in carbon sequestration compared to agriculture. These findings emphasize that proper management of natural resources and preservation of vegetation cover can contribute to increasing carbon sequestration capacity. It is recommended to promote sustainable agricultural practices and prevent the conversion of rangelands to agricultural lands. https://envs.sbu.ac.ir/article_106003.html Introduction Waste management is a fundamental challenge in urban communities, particularly in developing cities. Khorramabad, like many other cities in developing regions, faces the issue of improper waste disposal, leading to significant negative impacts on both the environment and public health. The aim of this research was to assess the environmental impacts of various waste disposal methods and identify the most appropriate option for waste management in Khorramabad.Material and methods: In this study, four waste disposal methods were evaluated: sanitary landfilling, unhygienic landfilling, recycling, and composting. The evaluation was conducted using the Rapid Impact Assessment Matrix (RIAM), which allows for a structured and comprehensive analysis of the environmental, economic, and social impacts of each method. This tool facilitates the identification of the strengths and weaknesses of each waste disposal method, providing valuable insights for decision-makers in choosing the most suitable waste management strategy based on local conditions.Results and discussion: The results indicated that composting, with a score of -182 in the RIAM matrix, emerged as the most sustainable and efficient waste management solution. Composting offers significant environmental and economic benefits, particularly in cities with a high proportion of biodegradable waste. This method not only reduces the volume of waste sent to landfills but also transforms organic waste into valuable products for agriculture or green spaces, thus contributing to local economic development. Additionally, composting reduces the environmental burden associated with waste disposal, such as greenhouse gas emissions and contamination of soil, water, and air, which are commonly associated with unhygienic landfilling. When compared to other waste management methods, particularly unhygienic landfilling, composting demonstrated a clear advantage. Unhygienic landfilling, which received the lowest score of -620, was found to have detrimental environmental and economic impacts. This method contributes to pollution in the form of greenhouse gases, hazardous pollutants, and leachate, posing significant risks to public health and the environment. Moreover, unhygienic landfilling is economically inefficient due to the high costs associated with land acquisition, long-term waste management, and environmental monitoring. In contrast, composting offers a more cost-effective solution by reducing landfill reliance and creating new opportunities in the green economy. The study also highlighted the value of the RIAM matrix as an effective analytical tool for assessing the environmental and economic impacts of different waste management strategies. This matrix provides a comprehensive framework for decision-makers to systematically compare the trade-offs between various waste management methods. It proved particularly useful in providing a rapid and systematic evaluation of the environmental and economic implications of each method, aiding in the selection of the most appropriate strategy for the specific needs of Khorramabad.Conclusion: In conclusion, the findings of this research suggest that composting is the most viable and sustainable waste management option for Khorramabad. By reducing landfill waste, minimizing environmental pollution, and creating economic opportunities, composting presents a highly effective solution for managing biodegradable waste. Although the implementation of composting requires significant initial investment, its long-term benefits, including reduced environmental impacts and enhanced economic growth, justify the investment. This study provides valuable insights for urban managers to make informed and optimal decisions regarding sustainable waste management strategies for the future of Khorramabad. https://envs.sbu.ac.ir/article_106002.html Introduction: Oil, as the most important economic resource in the country, not only generates income but also inevitably causes environmental pollution during the stages of extraction, refining, distribution, and storage. Microorganisms utilize degrading enzymes of petroleum compounds to break down hydrocarbons as a carbon source in environmental stress. Enzymes usage, due to their lack of pollution and controllability, is the best method for cleaning up environmental pollutants. One of the best enzymes for degrading oil compounds is ligninolytic enzymes produced by fungi. The aim of this study is to optimize the production of enzymes that degrade petroleum compounds for oil pollution cleanup.Material and methods: In this study, the fungal strain 2E, which was preserved in the microorganism bank of Academic Center for Education, Culture and Research (ACECR) of Shahid Beheshti University, was utilized, and its ability to produce ligninolytic enzymes was investigated. The experimental design was carried out with the Minitab 22.2.1 software for optimizing enzyme production, and the environment that had the highest protein level was identified using spectrophotometry and Bradford method. Enzymatic assays were performed at wavelengths of 420 and 595 nanometers for laccase and peroxidases, respectively, using suitable substrates. The concentration of protein in each of the specified environments was determined, and the degradation of crude oil was measured using lignin-degrading enzymes.Results and discussion: Fungus was identified as a producer of ligninolytic enzymes. Decomposition of guaiacol and the color change of the culture medium to brown indicated the activity of the laccase enzyme and the reaction on substrate was confirmed by formation of red color in the presence of manganese peroxidase and decolorization of azure in the presence of lignin peroxidase. Using Minitab 22.2.1 software and cultivation results in 12 culture media from the experimental design with the aforementioned software, the stirring and inducing factors showed the greatest effect. The highest protein concentration was obtained under conditions of 5 grams per liter of glucose, 0.02 grams per liter of ammonium sulfate, 0.1 millimolar of copper sulfate, 4% crude oil, pH 7, temperature at 30 degrees Celsius, 15 milliliters of inoculum, and a stirring speed of 150 rpm. Three media with high protein concentration were tested for enzyme activity, and a direct relationship between protein concentration and the activity of ligninolytic enzymes was observed, leading to the selection of the optimal environment. The supernatant obtained from the fungal culture in the optimal condition was concentrated using ammonium sulfate precipitation and chromatography, with enzyme activity measured at 128.32 U/ml for laccase and 59.4 U/ml for peroxidases. The enzymatic biodegradation ability in the presence of crude oil was investigated, and based on the results of gas chromatography, the degradation rate of crude oil was calculated to be 88.3± 2.17 percent, which indicates a high degradation capability compared to other scientific reports regarding petroleum compounds. Ligninolytic enzymes, due to their wide substrate range and high structural flexibility, can react with petroleum compounds as pseudo-substrates and can lead to biodegradation and environmental cleanup.Conclusion: Based on the results of this research, ligninolytic enzymes can be considered a powerful option for petroleum compounds biodegradation as a pseudo-substrate. From an economic perspective, optimizing ligninolytic enzymes production in an appropriate environment for practical use is important. It is hoped that the use of hydrocarbon-degrading enzymes as an environmentally friendly method will pave a new path for addressing oil pollution. https://envs.sbu.ac.ir/article_105973.html Introduction: The mining industry is a major contributor to environmental pollution, exerting a direct Impact on the three pillars of sustainable development: the economy, the environment, and society. Consequently, it is imperative to integrate the principles of sustainability into the operations of industrial and mining companies.The implementation of sustainability principles ensures the economic viability, environmental sustainability, and social responsibility of mineral resource exploitation and processing.This business tool necessitates the introduction of clean or green technologies and is highly dependent on knowledge. The objective of this study was to evaluate the impact of knowledge management practices on green innovation and sustainable business practices, as well as their relationship with sustainability in Iranian mining companies.Material and methods: The present study employed a questionnaire-based approach, which was conducted between April and the end of September of 2022. The survey was distributed to employees of six mining companies in the country, and a total of 647 questionnaires were completed online.A structural equation modeling approach was employed to assess the causal relationship between knowledge management, green innovation, and sustainable operations in the mining industry. The indirect effects of the dimensions of knowledge management on the dimensions of sustainable development were investigated using the bootstrap method, with the dimensions of green innovation serving as the mediating variable.Results and discussion: The findings indicate that knowledge management exerts a direct and significant positive influence on green innovation (β=0.80, P-value<0.01) and sustainable business (β=0.34, P-value<0.01). Conversely, the findings revealed a direct and significant positive effect of green innovation on sustainable business (β=0.65, P-value<0.01). Additionally, the indirect effects of knowledge management dimensions on sustainable business dimensions, in the presence of intermediaries, were found to be significant. The findings of the research indicated that knowledge management is a crucial factor in the development of green innovation and sustainable business practices in mining companies. Additionally, green innovation was identified as a crucial predictor of sustainable business practices. Both dimensions of green innovation, namely green technology innovation and green management innovation, can be considered mediators of the relationship between knowledge management dimensions (namely, creation, acquisition, sharing, and application of knowledge) and sustainable business dimensions.Conclusion: This study indicate that the sustainable business of the country's mining companies can be enhanced through the influence of knowledge management and green innovation. Furthermore, it is crucial to incorporate all facets of knowledge management and green innovation in order to achieve comprehensive business sustainability. https://envs.sbu.ac.ir/article_106563.html Introduction: Forecasting the trend of storms provides the possibility of planning to control the dust crisis for managers and officials. Artificial neural network patterns are among the most widely used methods for prediction. In most studies, researchers form several models to find the most suitable artificial neural network model that is more accurate in order to choose the model that has the most accuracy. The aim of this research is to combine the multivariate regression model and ANFIS fuzzy neural network in order to achieve the appropriate model faster.Material and methods: In this research, the data of dusty days, temperature, rainfall, relative humidity taken from Zabol synoptic station, statistical yearbooks and statistics related to Hirmand river flow have been used. At first, using rainfall data to check the drought situation, the value of SPI index was calculated in R-Studio programming software. Then, the multivariable regression model was estimated using temperature data, maximum wind speed, Hirmand river flow, SPI index and the number of dusty days with the help of Eviews software. Finally, two ANFIS neural-fuzzy network models with different inputs were developed in MATLAB software. In this way, the input variables to the first model were randomly selected and the output of the regression model was used to determine the input variables of the second model.Results and discussion: The results showed that dusty days have the highest correlation with the Hirmand river with a coefficient of -0.70 and then with the drought index (SPI) with a coefficient of -0.65. The SPI index includes positive and negative values, in the years when the value of the SPI index has decreased and indicates drought, dusty days have increased. After that, the correlation coefficient of temperature with the number of dusty days is 0.56 and finally the correlation coefficient of wind speed with dusty days is 0.45. The results of multivariate regression estimation showed that the variables of Hirmand river flow, SPI index, temperature and wind speed have a significant effect on the number of dusty days and their coefficient sign is as expected. Finally, using MATLAB software and ANFIS model, two models with different inputs were checked. In the first model, the variables of temperature, relative humidity and rainfall were used as inputs. In the second model, the variables of Hirmand river flow, SPI index and temperature, which according to the results of correlation coefficients and regression modeling had the greatest impact on dusty days, were determined as inputs. The results of the evaluation of two models showed that the second model, which is based on the results of regression modeling and examining correlation coefficients, has less error.Conclusion: Predicting incidents is very effective in informing managers and planners in order to manage risks. Artificial neural networks are among the most important methods for prediction. But it is very important to choose the right inputs in order to increase the prediction accuracy with artificial neural network. In some studies, researchers have to build several neural networks to choose the one with the least error, which requires spending a lot of time. In the present research, firstly, the correlation coefficients between all the considered variables were calculated and the influence of the selected variables on the dependent variable was evaluated by estimating the multivariate regression model. The results showed that if variables with the highest correlation and significant impact on the dependent variable are selected as inputs to the fuzzy neural network, the accuracy of the ANFIS neural-fuzzy network increases. https://envs.sbu.ac.ir/article_105996.html Introduction: One of the main problems associated with mining activities is run-off, which adversely effects the quality of surface and underground waters. Golestan province has various mines and since that most of these are located in forest areas, monitoring their effects on neighboring ecosystems is essential. Due to the abundance in every ecosystem, short life cycle, and quick response to the environmental changes, diatoms are considered as suitable bioindicators and extensively have been used for water quality assessment. These organisms can serve as good Indicators in heavily polluted areas affected by mining. This survey studied the effects of the mining drainage from the Zemestan Yurt and Razi mines in East Golesta on diatom assemblages. No studies have been conducted on the relationship between diatoms and coal mines in Iran. This survey specifically examined the impact of drainage from Zemestan Yurt and Razi coal mines on diatom assemblages.Material and methods: In this study in each mine two sites werer selected: the first site in the outlet of mine and the second downstream form the outlet where the drainage flows into the Khormarud (in Zemestan Yurt Mine) and Ghareh Cheshmeh Rivers (in Razi Mine). Sampling was carried out during the winter season from stony substrates. The sampling stations were located downstream from the outlets of the Zemestan Yurt (Azadshahr City) and Razi (East Alborz, Ramian City) coal mines, where the drainage flows into the Khormarud and Ghareh Cheshmeh Rivers. Alongside algal samples, water samples were also collected and in darkness with ice were carried out to the laberatory for further analysis. Diatom samples were studied and identified under a light microscope after preparation and the production of permanent slides. Water parameters were measured both in situ and in the laboratory.Results and discussion: In total 27 diatom taxa belonging to 16 genera were identified in this study; these taxa have also been reported from other aquatic ecosystems in Golestan Province. The most abundant taxa included Achnanthidium minutissimum, Diatoma moniliformis and Gomphonema pumilum which more or less were among the most abundant taxa in other studied ecosystems of Golestan Province. Hydrochemical results showed that the pH was alkaline and greater than 8, which aligns with the identified diatom taxa, as 60.71% of which were alkalifilous which are found in pH more than 7 and the last are taxa which are found in pH 7. Although salinity levels increased as one moved away from the mines, however its level was in the freshwater range and this increase was not significant enough to have a remarkable effect on the diatom assemblage. In terms of tolerance to organic pollution, most of the identified taxa in both mines were found to be pollution-tolerant. Regarding tropHic status, most species were indicators of eutropHic waters, followed by species capable of surviving in various tropHic conditions.Conclusion: Among the effects of mining which can remarkably affect the diatom assemblages is the obvious change in water pH and salinity; according to findings of this study no significant change were observed in terms of the mentioned parameters and the identified taxa were also reported from other studied ecosystems of Golestan Province. However the studied sites exhibited low taxonomic richness, which is characteristic ecosystems affected by mining; all identified taxa were either pollution-tolerant or taxa with extensive ecological niches. Therefore more experiments on rivers pollution are suggested specially in terms of possible heavy metals that may have entered this rivers through mine runoffs. https://envs.sbu.ac.ir/article_105998.html Introduction: Land use changes are one of the important issues in regional and development planning. Considering the advantages and capabilities of satellite data, this technology can be of great help in identifying and discovering these changes; In this study, land use changes in the Ghaemshahr region were evaluated over a 22-year period.To  conduct this research, images from the 2001 ETM+ sensor, 2014 and 2023 OLI sensor of the Landsat satellite were used. The main goal of this research is to investigate and reveal land use changes in the city of Ghaemshahr, located in Mazandaran province, between 2001 and 2023, where a large part of its forests have been destroyed for various reasons in recent years; since at least two data series from different time periods are required to monitor land use changes using satellite images.Material and methods: In this study, data from the ETM+ and OLI sensors of the Landsat satellite were used to monitor the trend of land use and land cover changes in Ghaemshahr County in three time periods: 2001 to 2014, 2014 to 2023, and finally to examine the 22-year changes from 2001 to 2023. The images presented in this system were atmospherically, radiometrically, and geometrically corrected, and the Jeffreys-Matousita criterion, which is a type of test to ensure the separation of classes defined using ground control samples, was used. And the samples were re-corrected and the best band combination was selected, and the study area was classified into six land use classes. In addition, the minimum separability using the Jeffreys-Matuseita criterion is zero and its maximum is 2. The results of class separability were extracted for the years 2001, 2014 and 2023.Results and discussion: Based on the results of the matrix table, the overall classification accuracy obtained from the ETM+ sensor data for the year 2001 was calculated to be 89.2 and for the OLI sensor data for the years 2014 and 2023 it was calculated to be 90.3 and 95.8. Also, the kappa coefficient for the years 2001, 2014 and 2023 is 0.85, 0.88 and 0.91, respectively. In terms of the area changed over the 22-year period, the garden and residential land classes have increased the most, so that the area of ​​these classes has increased from 22.5 and 12 percent of the total area of ​​the study area in 2001 to 43.5 and 20.8 percent in 2023, respectively, which means an increase of more than 7,694 hectares in garden lands and 3,139 hectares in residential lands. Also, the agricultural land class had the largest decrease with a decrease of 11,102 hectares and 29.1 percent. This decrease is due to the conversion of agricultural land to garden and residential land in the study area. Other classes of water, barren areas and forests decreased by 0.3, 0.2, and 0.4 percent, respectively. In general, the use of satellite images to prepare maps of land use and their changes is essential in environmental resource management planning.Conclusion: The results of this study indicate that the area of ​​forested lands has decreased and over time, the land cover pattern and consequently land use have undergone fundamental changes and transformations, and human factors have played the largest role. In Qaemshahr County, a significant portion of the conversion of garden and agricultural lands is related to the replacement of residential use in place of these lands. https://envs.sbu.ac.ir/article_106996.html Introduction: Plant diseases are responsible for at least 10% of global crop losses, costing the agricultural sector Billions of dollars in economic losses each year. This issue is all the more important when we consider that the world’s population is rapidly increasing and the need to provide sufficient, safe and sustainable food is felt more than ever. Plant pathogens, including fungi, bacteria and viruses, can severely reduce the quality and quantity of crops and pose a serious threat to food security. On the other hand, given climate change and increasing temperatures and humidity in many regions, the conditions for the spread and severity of these diseases have become more favorable. In response to these challenges, farmers have relied mainly on the use of pesticides and chemical compounds in recent decades, which, although effective in the short term, have been severely questioned due to the development of resistance in pathogens, the persistence of chemical residues in the environment and the threat to human and other living organisms. Therefore, attention to new and environmentally friendly methods for disease control has become an inevitable necessity. One important and promising solution is the use of biological control agents such as beneficial microorganisms, antagonistic fungi, and beneficial bacteria, which can help reduce and eliminate pathogens through competition, production of antimicrobial substances, and stimulation of the plant defense system.Material and methods: In order to investigate the effect of volatile compounds and Bacillus subtilis on the Sclerotinia Sclerotiorum fungus, cross-peer test was used. In the present study, Bacillus subtilis beneficial bacteria volatile compounds were identified using mass spectrometric-mass spectrometry analysis.Results and discussion: The compounds of Decane, Undecane, Tridecane and their derivatives, Octadecane, Eicosane and Hexadecane are the most important compounds produced by this bacterium. After detecting bacterial Volatile compounds B. subtilis. To investigate the inhibitory nature of the volatile compounds from Mycelium growth of Sclerotinia sclerotiorum, cross cross-peer tests were used. This pathogen is one of the most common pathogenic agents in the greenhouse and field plants, which has remained in soil for a long time and causes contamination. The fungus S. sclerotiorum was exposed to B. subtilis bacterial volatile compounds. Studies show that B. subtilis antagonist was able to prevent 95.93% of the growth of fungi and has the ability to control biological activity.Conclusion: This bacterium can be used as a non-chemical and effective method against Sclerotia caries in different hosts in a long-term future and can be used widely in commercial scale. Also, due to the fact that bacterial volatile compounds are also responsible for inducing resistance and change of essential oils in plants, the simultaneous effect of volatile compounds B. antagonist B. subtilis on essential oil changes of Satureja rechingeri was investigated. The plant exhibits antimicrobial, anti-cancer, anti-inflammatory and anticoagulant properties of the blood through its essential components. During the interaction, the bacterial and plant volatile compounds are increased in the compounds effective in plant resistance, including β-Pinene, α-Pinene, β-Myrcene, α-Terpinene, p-Cymene, γ-terpinene, Carvacrol methyl ether, Trans-Caryophyllene, α- Thujone, Thymol, and Carvacrol have significantly changed their control status. https://envs.sbu.ac.ir/article_107000.html Introduction: Landscape of an area consists of uniform parts of that land that have components of Patchs,passages and bed of land landscape. Since the density and distribution of vegetation in the landscape of the land of the passage of time is affected by many variables and changes. Variety and uniformity of plants studies the effectiveness of the indicators of richness, diversity and uniformity of vegetation from the structure of the landscape.Material and methods: In this study, two variables of size and shape of patchs on the structure of the Adoroshk watershed were selected because these two variables are known as important components in the planning of areas for conservation purposes. For this purpose, first the identification and preparation of the map of the structure of the land address of Adoroshk was performed and then the desired map in Arc GIS 10.3 software with suitable image format and ready to enter FRAGSTATS 4.2 software and then two variables of ratio of environment to area and size The patchs in the structure of Adoroshk land were calculated. Data obtained from identification and counting of vegetation in the area, which were the result of linear transect and plot method, were also entered in SPSS software environment and through Shannon-Wiener, Simpson, Hill, Brillouin and MacArthur Plant diversity was measured using the Margalf, Mann-Henick index of plant richness in each spot of the habitat. The Pilo, Alatalo and Hip indices were also used to measure species uniformity. The correlation between the variables was determined from Pearson correlation.Results and discussion: In this study, 60 plant species were identified and counted in 338 plots and the findings of this study indicate a significant relationship between the two physical variables of size and shape of habitat spots and richness. The diversity and uniformity of rangeland plant species in the Adoroshk watershed.Conclusion: The priority of paying attention to circular patchs that have a minimum ratio of environment to area in the design and management of Adoroshk watershed was proven during the planning and protection of vegetation. https://envs.sbu.ac.ir/article_106998.html Introduction: Public participation as one of the pillars of sustainable development has been the focus of international institutions such as the World Bank and UNDP since the 1970s, especially in developing countries. This new perspective is a response to the failure of centralized development approaches and emphasizes the role of local communities in resource management. Agenda 21 and the 2030 Sustainable Development Agenda have also highlighted the importance of public participation in environmental governance. In Iran, despite the legal status of environmental protection, challenges such as inappropriate policies, unsustainable exploitation, and lack of attention to the role of local communities have exacerbated environmental crises. In the meantime, the Sorkhrud Wetland, as a sensitive habitat in the north of the country, is of great importance and its protection is not possible without the effective cooperation of fishermen, farmers, and indigenous residents. This study aimed to identify the factors affecting the participation of local stakeholders in the protection of this wetland and analyze the impact of these factors in strengthening participatory approaches.Material and methods: The present study was descriptive-analytical and was conducted in the Sorkhroud region of Mazandaran province. The statistical population included fishermen, farmers, and other residents related to the wetland ecosystem. A researcher-made questionnaire was used to collect data, whose validity was confirmed by experts and its reliability was confirmed by Cronbach's alpha of 0.84. Sampling was carried out using stratified random sampling with a sample size of 350 people. The data were analyzed using statistical tests such as Kolmogorov-Smirnov, Pearson correlation, and the logit model. Descriptive statistics were also used to analyze the variables of awareness and social norms more accurately.Results and discussion: The results showed that public participation in the protection of the Sorkhroud wetland is influenced by several factors. Based on descriptive analyses, social norms (mean=3.95) and social capital (mean=3.93) had the highest effect and physical assets (mean=3.15) had the lowest effect on participation. The Kolmogorov-Smirnov test showed that the data distribution was normal and the Levene test confirmed the homogeneity of variances. In Pearson correlation analysis, the level of awareness (0.475) and social norms (0.438) had the highest correlation with participation. Also, in the logit model, the variables of income, cultivated area, membership in social institutions, number of household members and trust in protective institutions were significant at the 99% level and had a positive effect on the probability of participation; the highest effect was related to income (0.877) and the lowest effect was related to the number of household members (0.079). These findings confirm the importance of economic and social factors in active public participation. In examining the attitudes of the users, wetland conservation as a source of income and preventing soil and water degradation were prioritized, while less well-known environmental functions such as carbon storage were given the lowest priority. This highlights the need for targeted education based on explaining ecosystem functions. Also, in the social norms dimension, the highest agreement was observed on items such as “the need for people to make decisions in conservation” and “the need for unity to combat illegal hunting”. In contrast, the item “wetland conservation does not benefit the people” had the lowest acceptance. Comparing the results with similar studies in the country also showed that successful participatory conservation models have always been associated with knowledge enhancement, reduced livelihood dependence, and continuous interaction with the local community.Conclusion: The present study showed that raising awareness, institutionalizing social norms, and strengthening livelihood infrastructure are the main prerequisites for effective participation in the conservation of the Sorkhroud Wetland. Therefore, designing integrated policies centered on environmental education, creating economic incentives, and building trust can provide a suitable platform for the development of participatory conservation. https://envs.sbu.ac.ir/article_106004.html Introduction:Macrobenthos are a key part of aquatic ecosystems, serving as a food source for demersal predators and improving the structure of the environment. They play an important role in marine food webs and are essential for the functioning of coastal ecosystems. Due to their high sensitivity to environmental changes, they serve as key indicators for assessing the health of aquatic habitats. The Caspian Sea, as the largest enclosed water body in the world, hosts a unique biodiversity that is influenced by various factors such as climate change, invasive species, pollution, and human exploitation. Previous studies indicate that the species composition of macrobenthos in this sea has changed over time. However, the lack of a comprehensive and updated database on the biodiversity status of this group poses challenges for conservation efforts and sustainable resource management. Therefore, the present study aims to compile and provide a comprehensive and updated checklist of macrobenthic species in the Caspian Sea, serving as a valuable reference for biodiversity monitoring, environmental management, and conservation planning.Material and methods: The checklist of macrobenthos was compiled using peer-reviewed articles, books, and various reports related to the Caspian Sea. Data on macrobenthos were collected from reliable scientific sources, including published studies, taxonomic keys, reports, and online databases from 1994 to 2023. The identified species were validated using international standard databases such as WORMS and GBIF. Finally, all taxonomic classifications were updated according to the WORMS database.Results and discussion: A total of 584 species of macrobenthos were identified in this study, belonging to 240 genera, 112 families, 55 orders, and 27 classes. The highest species diversity was observed in arthropods (323 species, 55.31%), followed by mollusks (190 species, 32.53%), while other groups, such as nematodes, comprised a smaller proportion of the community. Approximately 80% of these benthic species are endemic to the Caspian Sea. This high level of endemism highlights the unique biodiversity of the region and highlight the importance of conservation efforts to protect these species from environmental threats. Previous studies reported significantly fewer macrozoobenthic species, likely due to their limited geographic study area at a local scale. The present study, by providing a comprehensive checklist, offers valuable insights into the biodiversity of the Caspian Sea ecosystem. Accurate data on macrobenthic diversity is crucial in marine resource management and ecosystem health conservation. This checklist not only serves as a reference tool for biodiversity assessments but also supports the monitoring of ecological changes driven by natural factors, human activities, and climate change.Conclusion: The high number of species identified in this study highlights the biological richness and structural complexity of the Caspian Sea's benthic community. Arthropods were the dominant macrobenthic group, emphasizing their key role in the benthic ecosystem, followed by mollusks, which also significantly contribute to ecological balance. The findings of this study are valuable not only for research but also for environmental policymakers and natural resource managers, as they can aid in developing conservation strategies and sustainable management plans for marine ecosystems. https://envs.sbu.ac.ir/article_106997.html Introduction: Risk assessment, particularly in the environmental domain, serves as a fundamental tool for identifying, controlling, and mitigating the hazards associated with human and industrial activities. This process enables systematic management and prevention of adverse outcomes by conducting a comprehensive analysis of potential threats. Through the application of reduction, elimination, and substitution strategies, high-severity and high-likelihood risks can be identified and mitigated to lower levels. Such measures facilitate the balance between human activities and environmental protection, effectively preventing further ecosystem degradation. Integrating environmental risk assessment into various stages of project planning and implementation ensures that potential threats are identified and managed effectively, minimizing negative impacts. This approach plays a vital role in fostering sustainability and responsibly managing natural resources, ultimately enhancing the quality of life and preserving these resources for future generations.Material and methods: This study investigates environmental issues in the maintenance processes of Transmission and high-voltage electrical substations in Zanjan Province using two models: Failure Mode and Effects Analysis (FMEA) and Energy Trace and Barrier Analysis (ETBA). A total of 64 risks were identified in each model.Results and discussion: The integration of these two methods allowed for a comprehensive identification of environmental hazards, including risks such as energy losses, harm to birds and animals, and hazardous waste. Recommendations for risk control and management were provided, such as fencing the equipment and sealing canal entrances and exits to prevent animals from entering. The analysis outcomes included identifying energy types and their sudden or unwanted release, evaluating barriers and energy control systems, calculating risk numbers, assessing barrier efficiency, and proposing actions for risk reduction and the resulting residual risk.Conclusion: In this study, risk assessment was conducted using the Failure Modes and Effects Analysis (FMEA) and Energy Trace and Barrier Analysis (ETBA) methods, which demonstrated that the level and identification of risks were similar in both approaches. Among the most significant risks identified was energy loss, for which mitigation strategies such as network optimization, equipment upgrades, proper maintenance planning, and reducing leaks were recommended. For moderate risks, such as harm to animals and birds, solutions like fencing equipment, insulating busbars, and studying animal behavior in the region were suggested. In managing hazardous waste, such as mineral oils, the study recommended developing comprehensive guidelines, proper collection, and delivery to recycling centers. Additionally, reducing water and electricity consumption was emphasized through measures such as drip irrigation, energy-efficient equipment, and double-glazed windows. Finally, for managing administrative waste and minimizing paper use, the study advocated for the development of digital systems and promoting awareness and training in waste segregation, which significantly contribute to pollution reduction. https://envs.sbu.ac.ir/article_106999.html Introduction: Dust storms are atmospheric phenomena that create numerous problems and deficiencies. Some of these problems include environmental and ecosystem degradation in the region, the spread of various diseases, social and civic dissatisfaction, and reduced productivity and efficiency. The present study is a basic research investigation that examines the sources and environmental consequences of dust particles in the northern and northwestern parts of Mashhad.Material and methods: After conducting preliminary investigations and reviewing general concepts and previous studies, this research evaluated data and performed statistical analyses for the years 2015 and 2016 (1394–1395 in the Iranian calendar). It also examined the sources of pollution, the level of air pollution, and its consequences. Finally, based on statistics related to dust events, the study compared the two years and conducted zoning of dust concentration and identification of their sources.Results and discussion: The occurrence of dust particles is increasing worldwide, particularly in the Middle East and Iran, and the city of Mashhad is no exception. Measurements conducted over recent years indicate a continuous increase in dust particles, which unfortunately can be attributed to inadequate decision‑making and ineffective management strategies by responsible authorities, as well as insufficient environmental awareness and compliance among citizens. The results of this study, based on sampling from 40 locations, showed no significant difference between the years 2015 and 2016 in terms of air quality index, dust concentration, and their spatial distribution. According to the zoning map of the average PM concentration in northern Mashhad, the eastern part of the study area showed high pollution levels, while the northwestern part of Mashhad (western section of the study area) showed lower pollution levels. Other areas exhibited varying concentrations of dust depending on land use and other factors. According to existing standards, the air quality in the study area is considered clean. However, it should be noted that this result is based solely on samples collected on a single day and cannot be generalized to the entire year. Various factors affecting dust concentration (such as peak traffic hours, wind, temperature, etc.) may have had unexpected influences at the time of sampling.Conclusion: The results indicate that although the area falls within the clean air quality range, several relatively weak dust production centers can still be identified based on different PM levels. Each of these centers generates dust particles with specific PM characteristics depending on the type of monitoring station, which may be classified as traffic-related, industrial, residential, or construction-related. The types of dust particles present in the area also vary depending on the station type (residential, residential–educational, residential–medical, residential–commercial, and traffic). The use of public transportation is recommended to reduce pollution caused by vehicles. In this regard, several recommendations are proposed, including improving and standardizing factories and related industries, as well as enhancing vehicle manufacturing standards to reduce emissions. Proper irrigation practices in agricultural lands should be implemented to preserve soil structure and improve vegetation cover. Additionally, planting shrubs and vegetation compatible with the local climate is recommended to ensure greater ecological stability. To collect and store precipitation, which can increase soil moisture and support vegetation preservation, the construction of underground reservoirs is also suggested. https://envs.sbu.ac.ir/article_106339.html Extended AbstractIntroductionThe increasing strain on water and land resources, combined with recurring droughts and unsustainable farming practices, has posed serious challenges to agricultural sustainability in Iran’s semi-arid regions. Remote sensing techniques offer a powerful, cost-effective, and repeatable method for monitoring changes in cropping patterns. The Sentinel-2 satellite, with its high spectral resolution and five-day revisit time, provides an ideal data source for such studies. The Varamin Plain, located in southeastern Tehran, represents a critical agricultural zone affected by water scarcity and policy restrictions on crop cultivation. Understanding how cropping patterns have changed over time in this area can help inform adaptive agricultural planning. In recent years, intensive agricultural activities combined with climate fluctuations have significantly transformed cropping systems, especially in semi-arid regions such as Varamin Plain. Accurate monitoring of these changes using advanced satellite imagery is critical to ensure agricultural sustainability and effective water management at both local and regional scales.Materials and MethodsThis study utilized Sentinel-2 imagery from the years 2016, 2018, 2020, and 2022. Images were sourced from USGS and Copernicus databases and were preprocessed in ENVI 5.3 using QUAC atmospheric correction. Monthly NDVI maps were generated and stacked to form annual composites. Four crop classes were defined: Garden, rainfed, irrigated, and rice. Classification was performed using the Support Vector Machine (SVM) algorithm. Training data were derived from field surveys, Google Earth imagery, and local agricultural records. Accuracy assessments were carried out using confusion matrices, calculating user accuracy, producer accuracy, overall accuracy, and Kappa coefficient. GIS techniques were employed to calculate class areas and visualize transitions using Sankey diagrams.Results and DiscussionOverall classification accuracy was consistently above 80% in all four years, with Kappa values ranging from 0.74 to 0.77. The 2018 classification had the highest accuracy. Sankey diagrams revealed that the most significant transitions occurred between irrigated and rain fed lands, reflecting farmers’ adaptive responses to climatic variability and water availability. Notably, rice cultivation dropped significantly in 2020 due to groundwater depletion and local restrictions on high-consumption crops. These observations align with findings from other semi-arid areas of Iran, where reduced rainfall and policy interventions have led to shifts in cropping strategies. These outcomes correspond closely with similar studies in semi-arid regions, highlighting farmers’ common adaptive responses to drought conditions. However, limitations such as insufficient phenological ground data were also noted. Methodologically, Sentinel-2 imagery—particularly its Red-Edge bands—proved highly effective in distinguishing crop types, while SVM maintained robustness across datasets. However, some limitations were noted, including the absence of phenological ground truth data and the biennial analysis approach, which may overlook within-year crop changes or mixed cropping systems.ConclusionThe findings underscore the potential of combining Sentinel-2 imagery with SVM classification for effective agricultural monitoring in semi-arid regions. This approach can be effectively applied to similar semi-arid regions, potentially enhancing water management and agricultural policy decisions. This methodology can support evidence-based decision-making for water resource management, crop planning, and climate adaptation strategies. To further improve classification accuracy and temporal coverage, future studies should incorporate ground-based phenological data and higher-frequency satellite imagery.Keywords: Adaptation, Agricultural transition, Classification accuracy, Crop dynamics, Sustainability.