Southern Coast Of Caspian Sea Research Articles

Population structure of Caspian Kutum (Rutilus frisii, Nordmann, 1840) in the southern coast of Caspian Sea using Genome-wide single nucleotide polymorphism markers

The Caspian kutum (Rutilus frisii, Nordmann, 1840) is one of the most important semi-anadromous endemic fish species in the southern part of the Caspian Sea. The fisheries from wild populations of R. frisii are declined drastically due to variability of sea levels, overfishing, and illegal fishing. For this regard, genetic studies is very noticed to maintain of remained this endangered species. Here, we used restriction site-associated DNA sequencing (RAD-seq) approach to explore population structure, genetic variability, and single nucleotide polymorphisms (SNPs) from 146 individuals from eight rivers in Iran. In total 86,274 SNP loci were determined, and after filtering, 16,193 high-quality SNP markers were applied in statistical analyses. Twenty-eight percent of selected SNPs were located in genic regions and about 65% of these SNPs were in the coding sequence. Of the 102 SNP loci, 42 loci were found to be polymorphic and bi-allelic. The minor allele frequency (MAF) of these SNPs varied from 0.156 to 0.471. The observed heterozygosity (Ho) per locus ranged from 0.119 to 0.864, while the expected heterozygosity (He) per locus was from 0.142 to 0.569. Among these SNP loci, 22 SNP loci were significantly deviated from the Hardy–Weinberg equilibrium (P < 0.01) after Bonferroni correction. Both Principal coordinate analysis (PCA) and Bayesian clustering satisfyingly showed population genomic structure in Caspian kutum populations, indicating the description of distinct population segments. The first development of SNP markers in this study provides the better monitoring of population genetic variation in Caspian kutum at a more detailed level and in the scarce of genetic information about this species.

On the Indirect Estimation of Wind Wave Heights over the Southern Coasts of Caspian Sea: A Comparative Analysis

The prediction of ocean waves is a highly challenging task in coastal and water engineering in general due to their very high randomness. In the present case study, an analysis of wind, sea flow features, and wave height in the southern coasts of the Caspian Sea, especially in the off-coast sea waters of Mazandaran Province in Northern Iran, was performed. Satellite altimetry-based significant wave heights associated with the period of observation in 2016 were validated based on those measured at a buoy station in the same year. The comparative analysis between them showed that satellite-based wave heights are highly correlated to buoy data, as testified by a high coefficient of correlation r (0.87), low Bias (0.063 m), and root-mean-squared error (0.071 m). It was possible to assess that the dominant wave direction in the study area was northwest. Considering the main factors affecting wind-induced waves, the atmospheric framework in the examined sea region with high pressure was identified as the main factor to be taken into account in the formation of waves. The outcomes of the present research provide an interesting methodological tool for obtaining and processing accurate wave height estimations in such an intricate flow playground as the southern coasts of the Caspian Sea.

Analysis of the Genome D Polymorphism of Synthetic Wheat Obtained on the Basis of Ae. tauschii L.

An SNP analysis is performed using the iSelect90K SNP array to identify the genetic diversity of synthetic hexaploid wheat lines of Kyoto University (Japan) bred by crossing durum wheat variety Langdon (Triticum durum, 2n = 4x = 28, BBAA) with accessions of Aegilops tauschii (2n = 2x = 14, DD) of different ecological origin. The level of genomic variability is calculated by using the Emma approach (Efficient Mixed-Model Association) and genomic relationship matrix (G). The genetic diversity of the genome D of synthetic lines is greater than that of genomes A and B by 50%. The greatest genetic polymorphism is observed in the line Langdon/Ku-2105 from Pahlavi province on the southern coast of Caspian Sea and the line Langdon/Ig 131606 from Kyrgyzstan. Lines from India (Langdon/Ig 48042), Iranian provinces Sari and Babolsar (Langdon/Ku-2088, Langdon/Ku-2093, Langdon/Ku-2096), and Turkmenistan (Langdon/Ig 26387) are characterized by a lower genetic diversity of the genome D. Thus, the involvement of synthetic hexaploid wheat on the basis of Ae. tauschii accessions from the Caspian basin into hybridization will extend the genetic diversity of wheat varieties and increase the efficiency of genetic resources.

Point wise Determination of Vertical Deformation at southern Coastal Areas of Caspian Sea by Combination of Satellite Altimetry and Tide Gauge Observations

In this paper, a combination of satellite altimetry (SA) and tide-gauge (TG) observations is used to determine the pattern of vertical deformation at southern coasts of Caspian Sea. Satellite altimetry measures the variations of sea water surface with a respect to a reference ellipsoid, while tide gauge data gives the sea level relative to a particular ground station; consequently, the difference between these two observations will give the vertical motion at the ground station. However, altimeter satellites still have problems at shallow waters or coastal areas which leads to inaccurate and corrupted sea surface height at tide gauge stations. To minimize this imprecision, two strategies are applied for the selection of the suitable SA points near the TG stations. The First one is to choose those close passes to the TG stations, provided that the SA data is not corrupted (range observation is available). The second strategy is to extrapolate the SA points at TG stations using Spatio- Temporal Kriging method. In both point of views, use is made of re-tracking methods to improve the ranges of SA observations near the coast. Amplitudes of tidal components are removed from both SA and TG observations to derive the residual tide free signals. Afterward, a linear trend is fitted to the residual signals in the sense of least square; the difference between these two, supplies the vertical deformation of the ground station. The results illustrate that the average vertical crustal motion at Anzali, Noshahr and Neka are -1.387, -1.903 and -3.14 mm/year, respectively.

Factors affecting microplastic retention and emission by a wastewater treatment plant on the southern coast of Caspian Sea

Understanding how wastewater treatment plants (WWTPs) process microplastics (MPs) will help informing management practices to reduce MP emissions to the environment. We show that composite 24 h samples taken at three replications from the outflow of the grit chamber, primary settling tank and clarifier of the WWTP of Sari City, on the southern coast of the Caspian Sea, contained 12667 ± 668, 3514 ± 543 and 423 ± 44.9 MP/m3, respectively. Fibers accounted for 94.9%, 89.9% and 77.5% of the total number of MPs, respectively. The MP removal efficiency was 96.7%. MP shape (fiber, particle), size and structure were the most important factors determining their removal in different steps of the wastewater treatment process. The structure of microfibers (polyester, acrylic and nylon) and the consequent higher density than water explained their high removal (72.3%) in the primary settling tank. However, size was more important in microparticle removal with particles ≥500 μm being removed in the primary settling tank and <500 μm in the clarifier unit. The smallest particles (37–300 μm) showed the lowest removal efficiency. The predominant types of fibers and particles were polyester and polyethylene, respectively, which are likely to originate from the washing of synthetic textiles and from microbeads in toothpaste and cosmetics. Despite the efficiency of the Sari WWTP in removing MPs, it remains a major emission source of MPs to the Caspian Sea due to its high daily discharge load.

An Analytical Study on the Formation of Submerged Bars in the Southern Coasts of Caspian Sea

An Analytical Study on the Formation of Submerged Bars in the Southern Coasts of Caspian Sea

Geospatial modeling of surface soil texture of agricultural land using fuzzy logic, geostatistics and GIS techniques

ABSTRACTSoil texture is a key controlling factor of soil properties and its functions include water and nutrient holding capacity, retention of pollutants, root development, soil biodiversity, and biogeochemical cycling. From the geotechnical standpoint, it is interesting to analyze the soil texture in regions due to its relation with the infiltration and runoff processes and, consequently, the effect on erosion processes. The purpose of this study is to present a methodology that provides the soil texture spatial variation by using Fuzzy logic theory and geostatistical technique in Geographic Information System (GIS) platform. A total of 140 soil samples were taken from topsoil (0–30 cm) in the study area located in the north of Guilan Province, the southern coast of Caspian Sea, Northern Iran. The soil textural classes were converted to numerical values (fuzzy values) using the fuzzy logic concept. The fuzzy values were spatially interpolated by ordinary kriging method such that the fitted model on experimental semi-variogram was exponential with moderate structure. The results showed the accuracy of soil texture predictive map was acceptable according to the values of normalized root-mean-square error for train data set (0.182) and test data set (0.179). The knowledge of the spatial variability of soil properties such as the soil texture can be an important tool for land-use planning in order to reduce the potential soil losses during rainy seasons. The results indicated that the integration of fuzzy logic, geostatistics, and GIS can improve the interpolation process.

The Modeling of Future Precipitation Changes, under Climate Change in the Southern Coasts of Caspian Sea.

The Modeling of Future Precipitation Changes, under Climate Change in the Southern Coasts of Caspian Sea.

Spectral Wave Modeling in Very Shallow Water at Southern Coast of Caspian Sea

This study evaluates the capability of the Simulating WAves Nearshore (SWAN) wave model (version 41.01) in predicting significant wave height and spectral peak energy content for swell waves in very shallow water of surf zone during depth-induced wave breaking and dissipation. The model results were compared with field measurements at five nearshore stations. The results demonstrated that some breaker index formulations were successful for significant wave height prediction in surf zones. However, an incorrect shape of the energy spectrum and overestimated near spectral peak energy content at shallow water stations were obtained using all of the embedded depth-induced wave breaking formulations in SWAN. The dependent breaker index on relative depth (Kpd) formulation, which was successful in predicting near spectral peak energy content, resulted in an average error of 30%. Finally, this formulation was modified to enhance the model performance in reproducing the spectral peak energy content.

Mapping the Spatial Distribution of Rice Fields in Southern Coast of Caspian Sea Using Landsat 8 Time-series Images

Since rice is one of the important crops not only in Iran but also in the world, it is vital to determine the paddy rice field as accurately as possible using fast and economical methods such as remote sensing and GIS. Accurate and timely rice paddy field maps with a fine spatial resolution would greatly improve our understanding of the effects of paddy rice agriculture on greenhouse gases missions, food and water security, and human health. In the past, the accuracy and efficiency for rice paddy field mapping at fine spatial resolutions were limited by the poor data availability and image-based algorithms. The unique physical features of rice paddy fields during the flooding/open-canopy period were captured with the dynamics of vegetation indices, which are then used to identify rice paddy fields. In order to prepare information about spatial distribution of rice fields, Multi-Spectral and Multi-Temporal data can be helpful because in addition to the rice, all fields could be covered by mixture of water and soil regarding the time of crop calendar. The Landsat 8 data with 11 bands has visible, near infrared, shortwave infrared as well as thermal bands; and therefore, different vegetation indices can be calculated, including Normalized Difference Vegetation Index (NDVI) and Land Surface Water Index (LSWI2105) which is sensitive to leaf water and soil moisture. In this study, special mapping algorithm that uses NDVI and LSWI2105 time series data derived from LANDSAT8 16-days 30-meter vegetation indices product of LANDSAT imagery developed to identify paddy rice fields. This algorithm works based on the sensitivity of LSWI2105 to the surface moisture and NDVI to the vegetation chlorophyll content. In this research method has been developed to define the relationship between the NDVI and LSWI2105 to detect the location of paddy rice fields in North part of Iran in 2014-15. The results, a validated with ground field works data at 56 well-distributed sample points. The overall accuracy of the method was 69.0909%.

The prevalence of heavy metals in Cladophora glomerata L. from Farahabad Region of Caspian Sea – Iran

ABSTRACTThe presence of toxic heavy metals in the environment is considered as a risk factor for adverse human and environmental health effects. Farahabad Region is a tourist center in the southern coast of Caspian Sea in Mazandaran Province of Iran. Environmental monitoring of this site is important for public health for individuals visiting and residing in this region. Although numerous biomonitoring data are available globally, very few if any apparent investigations have been conducted in this region. In this study, concentration of three heavy metals chromium (Cr), lead (Pb), and cadmium (Cd) was determined for one year in Cladophora glomerata, the predominant macroalga species present in this region. Detection of heavy metals was performed with atomic absorption spectrophotometer using standard methods. Results showed that the range of Cr metal in various algal samples was 29–55 ppm/g dry weight. The levels of Pb in algal samples (Cladophora) ranged from 2 to 8 ppm/g dry weight. The Cd concentrations in C. glomerata biomass ranged from 1.5 to 8.2 ppm/g dry biomass. In view of potential threats of such high metal concentrations in coastal waters and in algal tissues, it is necessary to adopt conservation measures to ensure public health safety.

Antibacterial activity of different extracts of prawn shell (Macrobrachium nipponense) against human bacterial pathogens

Aims: Bioactive compounds existing in crustacean shells have the potential to inhibit the growth of some pathogenic microorganism. The purpose of this study is to evaluate the antibacterial effects of different extracts of prawn shells (Macrobrachium nipponense) on some human pathogenic bacteria. Materials and Methods: Sampling (prawn) was conducted in summer 2014 from Anzali wetland in southern coast of Caspian Sea. Then, the hydroalcoholic, methanolic, and acetone extracts of prawn shells were applied for this purpose. Two Gram-positive (Bacillus subtilis Staphylococcus aureus) and three Gram-negative (Klebsiella pneumoniae, Vibrio cholerae, and Escherichia coli) were used as test organisms. The antibacterial activity was determined by paper disk diffusion. Results: The prawn shell extracts showed activity against pathogenic bacteria. The highest antibacterial activities were measured in B. subtilis, S. aureus, and V. cholerae with the zone of inhibition being 12.12 ± 0.32 mm, 12.51 ± 0.14 mm, and 12.35 ± 0.27 mm, respectively. Among all the strains, S. aureus exhibits a significant zone of inhibition against all extracts (P

Hydrothermal gasification performance of Enteromorpha intestinalis as an algal biomass for hydrogen-rich gas production using Ru promoted Fe–Ni/γ-Al2O3 nanocatalysts

Supercritical water gasification (SCWG) of Enteromorpha intestinalis (E. intestinalis) as a major algal biomass of southern coast of Caspian Sea was investigated in a batch reactor with and without the catalyst, to determine its potential for hydrogen production. The highest hydrogen yield of 5.25 (mmol H2/g of E. intestinalis) was observed for the noncatalytic test in the temperature of 440°C, water loading of 6g, E. intestinalis loading of 0.06g and reaction time of 10min. All catalytic tests were performed in this condition in the presence of unpromoted and ruthenium promoted Ni–Fe/γ-Al2O3 nanocatalysts. Catalysts were prepared with 12wt.% of Ni and 6wt.% of Fe in the active phase and 0.5–2wt.% of Ru as a promoter via microemulsion technique. Nanocatalysts were characterized by ICP, BET, XRD, H2 chemisorption, and TEM techniques to recognize their physicochemical properties. According to catalyst characterizations, the promoted Ni–Fe/γ-Al2O3 with 2wt.% Ru with higher dispersion and smaller size of nickel on γ-Al2O3, showed the best performance during SCWG of E. intestinalis. The maximum H2 yield of 12.28 (mmol H2/g of E. intestinalis) and hydrogen selectivity of 0.74, were obtained by using this optimized catalyst.

Simulation of rice production under climate change scenarios in the Southern coasts of Caspian Sea

Climate change has direct and indirect consequences on crop production and food security. Agriculture and cropproduction is one of the factors which depend on the weather conditions and it provides the human requirements inmany aspects. The objective of this study is to assess the impacts of future climatic change on irrigated rice yieldusing the CERES-Rice model in the Southern Coast of Caspian Sea under three climate change scenarios of Sra1b,Sra2 and Srb1. Required data for this research includes the meteorological, soil and crop management data. Themeteorological data include the daily data of minimum temperature, maximum temperature, solar radiation andprecipitation during 1981-2010 and Global Climate Models (HADCM3, ECHAM5, IPCM4, GFCM2, NCCCSM andINCM3) during 1971-2000. Soil and product management data provided from field experiment was conducted from2008 to 2009 at the Rice Research Institute in Rasht. Validating of Global Climate Models show that ECHAM5climate model has the highest correlation with the lowest error to simulate the future temperature and precipitation.We used ECHAM5 climate model coupled with a crop growth model for simulating of the effects of climate changeon rice protection. The results of prediction of climate change scenarios show that minimum and maximumtemperature will be ascending and precipitation will be decreasing in the Rasht station. Results of simulated yield andbiomass of the rice crop base on scenarios of Sra1b, Sra2 and Srb1 show that rice crop yield and biomass decreasewith increasing of mean temperature and decreasing of precipitation.

Source identification of perylene in surface sediments and waterbird eggs in the Anzali Wetland, Iran

Following the marked increase of perylene concentration in southern coast of Caspian Sea, waterbird eggs were used as biomonitoring agents. Surface sediments and eggs of five bird species were collected from colonies in Anzali Wetland in the above coast for perylene analysis. The perylene concentrations in sediment and egg samples ranged within 70.6–204.4 and 25.5–43.2 ng/g dw, respectively. Diagnostic perylene ratios showed that the perylene found in all samples was of biogenic origin, possibly developing from terrestrial materials. The combination pattern of perylene was found to be similar in all samples. Conclusively, perylene observed in the area was transmitted from sediments in breeding areas into the eggs, so the eggs are biomonitoring agents and the prevalence of oxic conditions in surface sediments limits formation of perylene, reflecting perylene formation in the catchment area. We found that perylene distribution in surface sediments follows irregular patterns, representing significant effects from local inputs.

Chemical Composition of the Essential Oil of Convolvulus persicus L.

Convolvulus persicus L. (Convolvulaceae) is distributed in the Southern coasts of Caspian Sea. The aerial parts of this species were collected from Sari (Mazandaran, Iran) in July 2012. The chemical composition of the essential oil obtained by hydrodistillation of the aerial parts of C. persicus was investigated by GC and GC-MS. Twenty components, representing 89.0 % of the total oil, were characterized with β-caryophyllene (47.0 %), dodecanal (8.8 %), caryophyllene oxide (5.7 %), tetradecanal (4.4 %) and dihydroedulan I (4.4 %) as the major components. This is the first report on the analysis of the essential oil from a species of Convolvulus genus.

Climatology ofCyclones and TheirTracking over Southern Coasts ofCaspian Sea

The southern coasts of Caspian Sea is subjected to synoptic/mesoscale weather systemsranging from locally enhanced sea breeze formation and small local front systems to synoptic scale cyclones.This study presents climatology of cyclones over the southern coasts of Caspian Sea covering a ten year period1996-2005. Altogether 57 cyclones were formed during the ten year period. Anoticeable seasonality is observedin evolution of cyclones over the entire Caspian region, a majority of the 57 cyclones (73.7%) were developedduring winter and fall seasons while the remaining (26.3%) occurred during spring and summer seasons.Most ofthe cyclones were of low intensity, out of 57 cyclones observed during the ten year period 16 (28%) were deepdepressions and 24 (42.1%) were cyclonic storms. Altogether 5 super cyclonic storms were observed during theperiod, out of which 4 were observed during winter and fall seasons. Mid-tropospheric, large-scale processes andlocal features were responsible for the initial development of all weather systems. The Mediterranean Sea playsa significant role in cyclogenesis and propagation of the systems the Caspian region. Further, a Mediterraneancyclonic system formed during October 2001 was studied in detail using backward trajectory Lagrangian model:Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT). The HYSPLIT model outputs confirmedthe observed synoptic features for the weather system of the case study.

Risk assessment of the total mercury in Golden gray mullet (Liza aurata) from Caspian Sea

Mercury is the most toxic heavy metal in the aquatic ecosystems which originates both from natural and industrial resources and is ultimately deposited in sediments as methyl mercury. This metal is quickly transferred through the food chain and accumulated in organisms. In this study, the human health risk due to consumption of Mullet ( Liza aurata ) in the Caspian Sea, were evaluated by measuring the concentration of mercury in muscle samples using Atomic absorbtion spectrophotometer (Perkin Elmer FIAS-100) and cold vapor technique. A total of 60 fresh Mullet samples were collected by local fisherman from 12 stations on the southern coast of Caspian Sea in Mazandaran province situated in the north of Iran. The average concentration of mercury in Mullet muscle was 0.137 µg/g of fresh weight (0.432 µg/g dry weight) which was less than the allowable amount for human consumption determined by the international organizations such as United States Environmental Protection Agency, World Health Organization, Food and Agriculture Organizations and the Food and Drug Administration. The calculations indicated that daily and weekly mercury uptake for Iranian consumers is lower than the guide values (Acceptable Daily Intake and Provisional Tolerable Weekly Intake) provided by international organizations. Also, Hazard Quotient Index was below 1 (0.35). Therefore, the consumption of the Mullet is not a serious threat to the consumer’s health and a consumption permitted rate of 51 g per day is recommended.

Productivity and optimal management of the uneven-aged hardwood forests of Hyrcania

Hyrcania is a productive region near the southern coast of Caspian Sea. Her forests are mostly uneven-aged beach-dominated hardwood mixtures. There is increasing willingness to treat these forests without clear-felling, following the ideas of continuous cover management. However, lack of growth and yield models have delayed this endeavor, and no instructions for uneven-aged management have been issued so far. This study developed a set of models that enable the simulation of stand development in alternative management schedules. The models were used to optimize stand structure and the way in which various initial stands should be converted to the optimal uneven-aged structure. The model set consists of individual-tree diameter increment model, individual-tree height model, survival model, and a model for ingrowth. The models indicate that the sustainable yield of the forests ranges from 2.2 to 7 m3 ha−1 a−1 in uneven-aged management, depending on species composition. Better ingrowth would substantially enhance productivity. The optimal stand structure for maximum sustained yield has a wide descending diameter distribution, the largest trees of the post-cutting stand being 80–100 cm in dbh. If cuttings are conducted at 30- or 40-year intervals, they should remove 20–40 largest trees per hectare. Despite moderate growth rate, uneven-aged management produces high incomes, 850–1,000 UDS ha−1a−1, because the timber assortments that are obtained from the removed large trees have very high selling prices. Optimal conversion to uneven-aged structure showed that the steady-state stand structure depends on initial stand condition and discount rate when the length of the conversion period is fixed. Discount rates higher than 1 % lead to reduced wood production, heavy cuttings, and low basal areas of the steady-state forest.

A genetic algorithm approach for assessing soil liquefaction potential based on reliability method

Deterministic approaches are unable to account for the variations in soil’s strength properties, earthquake loads, as well as source of errors in evaluations of liquefaction potential in sandy soils which make them questionable against other reliability concepts. Furthermore, deterministic approaches are incapable of precisely relating the probability of liquefaction and the factor of safety (FS). Therefore, the use of probabilistic approaches and especially, reliability analysis is considered since a complementary solution is needed to reach better engineering decisions. In this study, Advanced First-Order Second-Moment (AFOSM) technique associated with genetic algorithm (GA) and its corresponding sophisticated optimization techniques have been used to calculate the reliability index and the probability of liquefaction. The use of GA provides a reliable mechanism suitable for computer programming and fast convergence. A new relation is developed here, by which the liquefaction potential can be directly calculated based on the estimated probability of liquefaction (P L ), cyclic stress ratio (CSR) and normalized standard penetration test (SPT) blow counts while containing a mean error of less than 10% from the observational data. The validity of the proposed concept is examined through comparison of the results obtained by the new relation and those predicted by other investigators. A further advantage of the proposed relation is that it relates P L and FS and hence it provides possibility of decision making based on the liquefaction risk and the use of deterministic approaches. This could be beneficial to geotechnical engineers who use the common methods of FS for evaluation of liquefaction. As an application, the city of Babolsar which is located on the southern coasts of Caspian Sea is investigated for liquefaction potential. The investigation is based primarily on in situ tests in which the results of SPT are analysed.