نشریه مهندسی اکوسیستم بیابان
پیاپی 38 (بهار 1402)

 The conditions and performance of the ecosystem are affected by the changes made in some phenomena and conditions of the earth's surface (such as vegetation condition) over time due to various factors, including natural or human ones, making it necessary to identify, predict, and pay attention to such changes.
Considering the extreme vulnerability of arid and semi-arid regions to climate change worldwide, it is crucially important to investigate and evaluate climate change-induced alterations in vegetation in such regions. Therefore, this study sought to investigate the trend of vegetation changes in the three pastures of Farash Sardo, Kal-Bido, and Shoroiye located in Jiroft city with a dry and semi-arid climate, trying to examine the relationship between such changes and climatic factors. 

 The study area comprises three pastures, namely the Farash Sardo, Shoroiye, and Kal Bido, that were selected out of 375 pastures existing in Jiroft city, taking into account their significance for vegetation. To conduct the study, the monthly data of the Normalized Difference Vegetation Index (NDVI) and climatic data, including evaporation, average air pressure, average precipitation, relative humidity, sunny hours, dew point temperature, average maximum and minimum temperature rates, average temperature rate, and wind speed were used.
To this end, first, the long-term temporal changes in vegetation and climatic variables were evaluated using Mann-Kendall statistical test. Then, the most important climatic parameters affecting such changes were identified through multivariate regression, followed by the application of the root mean square error (RMSE) and the coefficient of determination (R2) to compare and assess the performance of the obtained models. Finally, the most important climatic factors involved in the changes made in the vegetation conditions of the study area were identified based on the selected model.

 The study’s findings revealed that vegetation changes had an increasing trend in Farash Sardo pasture at annual, winter, and spring time scales throughout the study period. Moreover, significant increasing trends were observed in the pasture of the Cal-Bido at annual, autumn, winter, and spring scales. However, no significant trend was found in the Shoroiye pasture.
On the other hand, the investigation of annual climatic factors indicated a significant increase and decrease in the wind speed and the dew point temperature in the Farash Sardo pasture, respectively. Also, while a significant increasing trend was found in evapotranspiration and average minimum temperature in the Cal-Bido pasture, the trend of changes was decreasing trend in the pasture in terms of air pressure, relative humidity, dew point temperature, average maximum temperature, and average temperature. As for the Shuroiye pasture, the results suggested a significant increasing trend in evapotranspiration and average minimum temperature, and a significant decreasing trend in the values of dew point temperature, relative humidity, air pressure, and average temperature.
Moreover, the modeling results showed that the most important climatic factors involved in NDVI changes in the Farash Sardo pasture were temperature, air pressure, spring evapotranspiration, and changes in winter air pressure and annual precipitation. On the other hand, the most important climatic factors affecting NDVI changes in the Cal-Bido pasture were identified as spring dew point temperature, air pressure, autumn air pressure, winter air pressure, maximum temperature, and annual air pressure. As for the Shoroiye pasture, the most important climatic factors involved in NDVI changes were found to be wind speed, precipitation, minimum and maximum temperature rate, average spring temperature, summer air pressure, autumn sunny hours, and winter sunny hours.
In general, the investigation of the relationship between drought and vegetation status of the pastures via land sampling and remote sensing data is suggested to be used for improving the results and increasing awareness concerning climate hazards for vegetation. Such a study together with the examination of the contribution of human interventions on vegetation changes can also be used for managing the environment during critical periods and setting appropriate plans.

Assessing precipitation alterations in a large area like Iran is required for the identification of those areas that are more vulnerable to changes in precipitation patterns, considering the fact that such changes may significantly influence water availability, agriculture, and other sectors that are dependent on water resources.  On the other hand, understanding the spatial variability of precipitation patterns can help develop purposive strategies, including drought or flood management in specific regions. Moreover, as severe weather events such as floods and droughts can devastate communities and their infrastructure, such an understanding can inform decisions made concerning disaster risk reduction efforts. Therefore, assessing precipitation variations is essential for the effective management of water resources and the reduction of disaster risks.
 

This study suggests a new method for analyzing precipitation properties in Iran, using a mixture of Maximal Overlap Discrete Wavelet Transform (MODWT) and Multiscale Entropy (MDE) techniques. This approach allows for a more detailed and accurate assessment of the spatial and temporal characteristics of precipitation properties, preparing the ground for the development of appropriate strategies for different regions in Iran. To this end, annual precipitation data collected from fifty Iranian synoptic stations for 1980-2020 were analyzed. Then, after classifying the precipitation data into different subseries, the concept of entropy was used to measure precipitation variability. Moreover, MDE values were used as input data for clustering purposes, followed by the calculation of internal evaluation criteria to be used for the determination of the optimal number of clusters and the most suitable clustering method calculated.
 

The variations and trends of the precipitation data can be identified through the analysis of partial coefficients D1-D4 and the approximation coefficient. Accordingly, while the smaller partial sub-categories indicate more rapid variations at higher frequencies, the greater partial coefficients show more moderate variations at lower frequencies. Moreover, the approximation coefficient reveals the slightest variations at low frequencies in annual time series. The study’s results suggested that northern and northwestern Iranian regions that are primarily characterized by rainy, cold, and in some cases semi-arid climates experienced the greatest variations in terms of annual precipitation. On the other hand, the eastern and southern parts of Iran, which are mostly dry areas, experienced more moderate variations in annual precipitation rates. Therefore, according to the results found in this study, it could be argued that northern and northwestern Iran enjoy more precipitation variability than other parts of the country. Furthermore, the D3 sub-category (eight years) was found to have the greatest variations in terms of MWE. On the other hand, based on the values of Sci, DBi, and CH index, the k-means clustering method performed better than SOM (Sci=0.41, DBi= 1.22, and CH= 14.58). Finally, fifty Iranian synoptic stations were categorized into four clusters based on the MWE index, with Chabahar, Shahrud, Abadan, and Zanjan being selected as core clusters.
 

The current study proposed a methodology for analyzing and zoning Iran’s annual precipitation based on the multiscale entropy method, considering the fact that the period and trend of the annual time series could be identified via the analysis of the precipitation series. Following the analysis of the collected data, this study used the multiscale entropy method to record precipitation variability in each synoptic station. On the other hand, the determination of SOM and k-means input data based on MWE values helped reduce the input data, leading to an increase in the accuracy of the zoning method and the selection of the homogenous clusters based on the proposed methodology. The results of the study indicated that generally, the K-means method offered more homogeneous areas than the SOM method. Moreover, the homogeneous distribution of annual precipitation variations obtained based on the K-means-derived clusters confirmed the positive performance of the methodology proposed in this study, which involves the identification of hydrologic uncertainty and temporal-spatial variations of precipitation in those stations related to a specific cluster. The methodology seeks to create distinct clusters of stations that share common features. This approach can provide insights into the spatial variability of hydrological processes and help improve water resource management by identifying areas susceptible to hydrological extremes such as floods or droughts. Some studies have already been conducted on the spatial clustering of precipitation stations in Iran using different methods, including the application of geographical proximity or precipitation rate as criteria for clustering. However, the method used in the current study involved clustering based on similarity in hydrological uncertainty and temporal-spatial complexity, which is consistent with the findings of Roshangar and Alizadeh (2019), and Roshangar et al. (2019). Identifying hydrologically homogeneous regions and their associated precipitation characteristics can significantly enhance the effective management of water resources in terms of adapting to climate change, preventing damage to water environments, and mitigating the impact of climate-related disasters. Therefore, the proposed methodology for spatial clustering of synoptic stations could be useful in managing water resources and all precipitation-related sectors and variables such as runoff and soil moisture. However, this study faced some limitations such as the small number of synoptic stations and the short length of the statistical period. Therefore, it is recommended that the methodology be applied to more stations at more varied time scales.

 Considered two important contributing factors in reducing biodiversity in rangelands, drought, and grazing influence the performance of natural ecosystems. Moreover, plant communities respond variously to drought periods under different management conditions. However, while many studies have so far been conducted on the response of plant communities to drought, it is not clear whether the ecosystems are more resistant or more vulnerable to drought. Therefore, this study sought to examine the impact of grazing intensity (including lenient, moderate, and heavy grazing) on vegetation characteristics (such as canopy cover, forage production, and species diversity) of semi-desert ecosystems of South Khorasan province under normal, wet, and drought conditions.

 This study attempted to investigate the structural properties of Salsola richteri and Artemisia sieberi- Zygophyllum eurypterum communities in the grazing and enclosed rangelands under short-term wet and drought conditions. To this end, canopy cover, density, forage production, and the richness and diversity of species were measured according to the Guidelines set by the Iranian National Program for Monitoring Rangeland Quality. Moreover, the species abundance index was used to assess plant diversity indices. Accordingly, after recording the plant density values and converting them to abundance ones, the species richness, dominance, diversity, and evenness were calculated using the adiv package. On the other hand, the Standard Precipitation Index (SPI) was used to assess the drought. Finally, the statistical analysis of the data was performed using the Wilcoxon signed-rank test and permutation test. 

 The results of the SPI analysis indicated that the Salsola richteri community experienced normal and very dry years in 2019-2020 and 2020-2021, whose SPI value was found to be 0.097 and 1.6, respectively. As for the Artemisia sieberi- Zygophyllum eurypterum community, the years 2019-2020 and 2020-2021 fell under relatively humid and normal classes, respectively, with their SPI values being 1.14 and -0.70, respectively. Moreover, it was found that annual species were eliminated by drought, especially Salsola richteri and Ammothamnus lehmanii which were affected the most among other species. Accordingly, the production of Salsola richteri was reduced from 800 kg/ha to 60 kg/ha and Ammothamnus lehmanii was completely dried. However, the results showed that canopy cover and density of perennial species were not significantly influenced by drought (p≥0.05). For instance, Ammodendrom persicum and Stipagrostis pennata, which had the highest density in this region, were less affected by drought. On the other hand, in the enclosed rangeland, the species diversity of the Salasola community was higher in the normal year (1-D = 0.15) than in the dry one (1-D = 0.105). It was also found that in the Artemisia sieberi- Zygophyllum eurypterum community, decreased precipitation rate was more influential in reducing forage production than other vegetation properties. In this regard, the production of all plant species was approximately zero in the normal year, with the grazing capacity being impossible to determine. 

 As found by the current study, drought exerted a significantly negative influence on the density, richness, and diversity of species in the Salsola community, with species dominance being greater in the dry year than the normal one. Therefore, it appears that compared to the Artemisia sieberi- Zygophyllum eurypterumcommunity, the Salsola community enjoys a higher species diversity.
On the other hand, 2020 and 2021 were determined as the wet and the normal years based on SPI, respectively. However, although 2021 was identified as a normal year, the increased temperature and decreased precipitation rate during the sampling period so negatively affected the vegetation that the year was practically considered a dry year. Moreover, the comparison of the wet and normal years suggested that the density, canopy cover percentage and forage production of annual species had turned to zero throughout the normal year. However, the Artemisia sieberi- Zygophyllum eurypterum community experienced much worse conditions than the Salsola community, where the species richness in both grazing and enclosed rangelands decreased from 25 species to 4 and 7 species, respectively. It was also found that all annuals and herbaceous species had been eliminated from the region and only perennial plants and shrubs had survived. This study examined biodiversity as one of the most important characteristics of plant communities that could be affected by drought, as biodiversity is believed to be involved in improving the performance of natural ecosystems. Furthermore, biodiversity can protect an ecosystem's performance against severe weather events. Considering the response of plant species to drought, Ammodendrom persicum is recommended as a drought-resistant plant to be planted in areas that are subject to the programs dedicated to the revival of dry and desert regions. On the other hand, being generally defined in terms of different aspects, drought is classified into various types, including meteorological, hydrological, agricultural, economic, and social. In this regard, ecological drought is also recommended to be added to such a classification.

While Iran’s soil is considered one of the richest soils in terms of mineral deposits worldwide, it is contaminated with heavy metals. On the other hand, some studies have recommended the use of native plants as a sustainable strategy to resolve the environmental problems caused by mining. In this regard, phytoremediation can be regarded as an economical, effective, economical, biological, and practical method for removing heavy metals from contaminated sites. Therefore, this study sought to investigate the potential of Seidlitzia Rosmarinus and Haloxylon Aphyllum desert species for the phytoremediation of heavy metals (i.e., Ni, Co, As, Cr, and V) found around the bauxite crusher of Jajarm alumina mine in the direction of the prevailing wind. 

Soil sampling was performed at distances of 450-700, 800-1200, 1400-2000, and 2500-5000 meters away from the center of the bauxite crusher and the control site. To this end, the seeds of the above-mentioned species were planted in pots with a 3:1:1 ratio of sand, dung, and soil, respectively. Then, the planted seeds were transferred, after two months, to the pots containing the soils sampled from target distances. Finally, upon the completion of the vegetative period, phytoremediation was carried out on the potential species using a factorial experiment in a greenhouse located at Gorgan University of Agricultural Sciences and Natural Resources, applying a completely randomized block design with three replications. The data analysis was then performed using the SPSS software, and Duncan's test was used to compare the obtained means for the significant results at the 5% level. To check the normality of the data, the Kolmogorov-Smirnov test. Moreover, the homogeneity of variances was checked via the Lyon test.

The results indicated that S. Rosmarinus and H. Aphyllum contained various amounts of heavy metals, with the amount of absorbed Arsenic (As), Chromium (Cr), and Cobalt (Co) being greater in aerial and underground tissues of the H. Aphyllum species than those of the S. Rosmarinus. However, the case was reversed in terms of Nickel (Ni) and Vanadium (V), that is, the number of such metals was greater in aerial and underground tissues of S. Rosmarinus tissues compared with H. Aphyllum.
 
On the other hand, while the transfer rate of As, Cr, and Co was higher in H. Aphyllum than that of S. Rosmarinus, the transfer rate of Ni and V was greater in S. Rosmarinus compared to H. Aphyllum. The results of the study also suggested that whereas the rates of Ni, As, Cr, and Co bioaccumulation factor was higher in S. Rosmarinus than those of H. Aphyllum, it was the bioaccumulation rate of Co that was greater in H. Aphyllum compared to the S. Rosmarinus.
In this regard, the average amount of Ni, Co, As, Cr, and V in H. Aphyllum were found to be 469.19, 172.74, 9.51, 21.59, and 23.07 mg/kg in the intended intervals, respectively. Moreover, the average transfer rates of such heavy metals in the species were reported as 1.09, 1.21, 1.08, 1.21, and 1.02, respectively, and the average bioaccumulation rate of metals was found to be 0.53, 0.26, 0.66, 0.50, and 0.30 mg/kg, respectively.
On the other hand, the study found that the average amount of Ni, Co, As, Cr, and Vanadium in S. Rosmarinus was 479.31, 169.34, 9.42, 21.18, and 30.85 mg/kg, respectively. Furthermore, the average rates of the transfer factor in the species were 1.20, 1.05, 1.01, 1.05, and 1.05, respectively, and the average rates of bioaccumulation were reported as 0.55, 0.24, 0.68, 0.54, and 0.39 mg/kg, respectively.
The results of the study also indicated a significant difference between the aerial and underground tissues of the intended species in terms of vanadium accumulation at a 1% significance level. Moreover, the transfer and bioaccumulation rates of Ni, Co, As, Cr, and V were greater and less than 1 in S. Rosmarinus and H. Aphyllum, respectively, indicating that the species had transferred metals to their aerial tissues. Therefore, as S. Rosmarinus and H. Aphyllum have low biochemical rates, they are appropriate for phytoextraction purposes in the phytoremediation process.

According to the results of the current study, S. Rosmarinus and H. Aphyllum are highly applicable for the extraction of Ni, Co, As, Cr, and V in the phytoremediation of the study area. On the other hand, as the intended species are indigenous to the study area, they can be planted in the area for clearance purposes. Moreover, after removing the aerial parts of S. Rosmarinus and H. Aphyllum for the preservation and clearance of the ecosystem, their remaining parts could be collected and burned under controlled conditions, using their ashes (as biological ore) for the re-extraction of metals or other economic purposes.
Therefore, the species are recommended for clearing the study area and similar areas of heavy metals. However, to conduct more comprehensive studies on the potential phytoremediation applicability of S. Rosmarinus and H. Aphyllum, it is necessary to necessary examine the species grown in pots in terms of field studies so that they can be used as a suitable model for phytoextraction and the revival of the lands contaminated with heavy metals.

Remote sensing science has been increasingly used throughout recent years in natural resources studies, especially for assessing and preparing vegetation maps. Moreover, aerial photography is widely used as a remote sensing tool, especially the ones taken by quadcopters in inaccessible areas, which could be effective, useful, and innovative. On the other hand, digital observation of the earth is an observed data-based approach in which photos are used to study natural resources. In many cases, using photos in time-specific and comparative studies is highly effective, taking into account the largeness of the area, inaccessibility, and lack of roads. Therefore, this study used a quadcopter to take photos from various points at different altitudes and compared them with aerial images to determine which type of photo from which height provides the best information concerning the investigated land and vegetation. Therefore, the purpose of this study is to investigate the possibility of using a quadcopter in preparing a vegetation percentage map.
 

Considering the costly and time-consuming nature of ground sampling of vegetation, this study used vegetation photography, digitizing and analyzing the collected photos after transferring them into computer systems. To this end, first, the intended photography centers were selected in the study area at different altitudes, from 10 meters high to 100 meters. Then, a quadcopter was sent to the area, taking photos from each selected center.
 In this regard, in a single center selected as the indicator within a kilometer radius of the study area, the required images were taken at each altitude class from four main directions, moving from the 100-meter height class to the ten-meter height one. The images were used to calibrate the collected photos and the numerical values of the calculated vegetation percentage. Then, the intended maps were extracted based on image dimensions and the coordinates of the selected points in Google Earth. Finally, the phases passed for the photos taken by the quadcopter were repeated for photos obtained from the maps so that vegetation percentage could be calculated based on the prepared maps.
 

The analysis of the study’s results suggested that the variations of vegetation percentage occurred at a slower pace in the western direction at 90 meters height and above, indicating that the height is the best altitude for determining the region’s vegetation percentage. However, a direct relationship was found between elevation and the changes in vegetation percentage in the eastern and northern directions at 90 meters height and above, with the vegetation percentage remaining unchanged with an increase in elevation. In other words, from 90 meters height beyond, the elevation exerts no influence on the calculated vegetation percentage, making it optimal for photography.
As for the southern direction, the vegetation variations remain unchanged from 40 meters height beyond, with the increase in elevation not affecting the calculated vegetation percentage. On the other hand, an extremely high correlation (99%) was found between the data collected in the western direction, indicating a very close relationship between the vegetation percentage values collected from different altitudes by the quadcopter and Google Earth.
In the eastern direction, the first flight level lies at 20 meters high. Probably, due to the low density of the vegetation, the larger size of the shrubs, and the small surface shown in the images, the vegetation percentage is considerably different from other points, thus making it unreliable.
 

This study found that the images cover a greater surface of the intended area with an increase in elevation. However, as the pixels become larger in such as process, fewer details are available. Therefore, the scope of the studies becomes limited, and the possibility of error increases. On the other hand, fewer areas were observed, and studies in those photos were taken from low altitudes, whose resolution was higher, though.
The study also found that the more uniform range of variations in the vegetation percentage at different elevations indicates a uniform density, and the more non-uniform density leads to abnormal changes in vegetation percentage as the elevation varies.
According to the study’s results, the best elevation for investigating vegetation in terms of the existing plants in the area was 90 meters in height. Moreover, the error percentage was revealed to be too high at 20 meters elevation due to the small dimensions covered by the images, thus making the altitude unreliable for any such study.
Generally, it can be concluded that the useful elevation for photography depends on the type of vegetation under study and that the optimal height should be determined based on the type of vegetation and its minimum dimensions. Moreover, taking into account the vegetation percentage and the quality of the images taken by quadcopter and Google Earth, it could be argued that the photos taken by the quadcopter enjoy more accuracy, providing higher coverage percentage and more precision in recording greater details.

Protecting water, soil, and organisms, rangeland vegetation is naturally spread over the earth like an umbrella. On the other hand, vegetation changes either cause an improvement or irreparable damage to water and soil resources. Therefore, knowing the effect of vegetation changes on hydrological components of the watershed, including base and peak flow, is a prerequisite for any management planning at the watershed scale. However, the issue takes on particular significance in arid and semi-arid areas, where there is no sufficient quantitative data and the land cover and land use classes are widely dispersed. Therefore, this study sought to calibrate and validate a model for simulating runoff and sediment in the Sarbaz watershed using the soil and water assessment tools (SWAT). What follows presents a scenario concerning the simulation of the influence of improving rangeland vegetation on hydrological components of the Sarbaz basin using a recalibrated and validated model.

 This study used the SWAT hydrological model to investigate the effect of vegetation changes on discharge and sedimentation in the Sarbaz River watershed located in Sistan and Baluchistan province, enacting the scenario of improving rangeland conditions from poor to moderate. To this end, HRU was obtained from the combination of land use, soil, and slope class maps. Then, surface runoff, sediment, and chemical elements were calculated for each HRU, each sub-basin, and the watershed, respectively. On the other hand, ninety-seven hydrological response units were obtained based on digital height lines of 21 sub-basins after combining three maps. Then, following the preparation of the intended parameters and input data, the model was calibrated for 17 years from 1999 to 2016, and validated over a five-year period from 2017 to 2021. Finally, the model was implemented for the present time based on preliminary data, and then the scenario of improving the pasture conditions from poor to moderate was enacted to determine the influence of vegetation on runoff and sediment.

 The sensitivity analysis revealed that the alpha parameters in the return flow (v_ALPHA_BF) and the initial curve number of American soil conservation (CN-SCS) for medium humidity conditions exerted the greatest influence on the calibration and validation of the simulation. The results obtained from runoff calibration were found to be 0.76 Nash-Satkif coefficient and 0.86 explanation coefficient, and 0.53 and 0.58 for sediment, respectively, indicating acceptable rates for runoff (on a good floor) and sedimentation. Moreover, the results of the scenario concerning the improvement of pasture conditions from poor to moderate suggested a 46% and 15% reduction in the flood volume and total sediment, respectively, indicating the great influence of vegetation increase on Sarbaz River’s stability.

Preserving rangeland plants requires the protection of water and soil, and ultimately maintaining the balance of an ecosystem. However, quantifying the influence of vegetation on runoff and sediment requires modeling and simulation. Accordingly, the current study used water and soil assessment models to construct its intended scenarios. The area of poor pastures in the study area covers nearly 81% of the region. It should be noted that the status of the pastures could be improved through appropriate grazing methods such as modification and flooding, making the flow continue in dry periods and thus reducing the flood damage in the study area.
Generally, this study found that the average amount of surface runoff was decreased by 46.88%, indicating the effectiveness of the enacted scenario in reducing flood discharge. Moreover, the peaks of sediment in the diagram were decreased. Also, the average sediment was found to have decreased by 15.53% at the outlet of the basin, suggesting a significant reduction of sediment in the basin. Therefore, it could be argued that the scenario enacted in the current study worked well and that relevant organizations, especially the General Directorate of Natural Resources and Watershed Management of Sistan and Baluchistan province may play it out in the study area. Such a change could be made with suitable methods to improve the conditions of the pasture, including modification and flooding, leading to the continuation of the discharge flow in dry periods and the reduction in flood damage and loss of water and soil in the study area.