• Energy Research
• Open Access close
• Restricted close
• Open Source close
• Persian close

The Study of phytoplankton in the Caspian Sea was substantially started in the 1990s with the aim to produce and record data. phytoplankton study in this area became more important because of the occurance of some ecological events in recent years (such as bloom and arrival invader species). The study was seasonally conducted in western (Giulan province) to eastern coast (Golestan province) at 8 transects (Astra, Anzali, Sefidrud, Tonekabon, Nowshahr, Babolsar, Amirabad and Bandar Turkman) from inshore (5 m depth) to offshore (100 m). 476 samples were collected to study quantification and qualification of phytoplankton in 2009-2010. Results showed that 195 species of phytoplankton were identified in 8 phylums which were classified to Bacillariophyta (81 species), Pyrrophyta (33 species), Cyanophyta (28 species), Chlorophyta (38 species), Euglenophyt (11 species), Xantophyta (1 species), Chrysophyta (2 species) and Haptophyta (1 species). Abundance and biomass of phytoplankton were significantly different between euphotic layer (0 to 20m depths) and aphotic layer (50 to 100m depths) (p0.05). In spring, Bacillariophyta and Pyrrophyta with 40% and 29% of total abundance were dominant phylum at euphotic layer. In fall, Bacillariophyta (57% of total abundance) and Cyanophyta (28% of total abundance) were the first and second dominant phyla. While in summer and winter the predominant phyla was made by Cyanophyta (92% of total abundance) and Bacillariophyta (94% of total abundance) respectively. Species richness in western, central and eastern regions was 119, 141 and 147 respectively. Shannon index was 2.39 and 2.04 at euphotic layer and below photic layer, respectively. Shannon and evenness indices in eastern region was lower than western and central regions. Meanwhile, Shannon index in spring and autmn (2.50 and 2.39) was higher than summer and winter (0.21 and 0.36). In photic layer, dominant species were Stephanodiscus hantzschii Chrysochromulina sp. and Exuviaella cordata in spring. While Oscillatoria sp. was the predominant species in summer. In fall, dominant species contained Thalassionema nitzschioides and Oscillatoria sp. Finally, Pseudonitzschia seriata and Cerataulina pelagica made the most abundance species in winter. The dominant species in the below phoyic layer was very similar to photic layer. The mean abundance of Pseudonitzschia seriata , Oscillatoria sp. and Dactyliosolen fragilissima was higher than other species in all regions of study area (west, middle and east). Seasonal succession of dominant species were under the influence of natural factors such as sunlight, heat, river currents, wind and vertical mixing of water. However it seems that the invasion of ctenophore into Caspian Sea (with change in nutrient levels and decline of phytoplankton predator) and also human activities (i.e. water balance of ships and discharge of sewage) are severely impact on seasonal dominant species, pattern of species composition and relative abundance of species. These changes mainly accompany with appearance of new and harmful species (with the ability of severe proliferation) and displacement of native and dwell species.

Introduction: FAO AquaCrop model (Raes et al., 2009a; Steduto et al., 2009) is a user-friendly and practitioner oriented type of model, because it maintains an optimal balance between accuracy, robustness, and simplicity; and it requires a relatively small number of model input parameters. The FAO AquaCrop model predicts crop productivity, water requirement, and water use efficiency under water-limiting and saline water conditions. This model has been tested and validated for different crops such as maize, sunflower and wheat (T. aestivum L.) under diverse environments. In most of arid and semi-arid regions water shortage is associated with reduction in water quality (i.e. increasing salinity). Plants in these regions in terms of water quality and quantity may be affected by simultaneous salinity and water stress. Therefore, in this study, the AquaCrop model was evaluated under simultaneous salinity and water stress. In this study, AquaCrop Model (v4.0) was used. This version was developed in 2012 to quantify the effects of salinity. Therefore, the objectives of this study were: i) evaluation of AquaCrop model (v4.0) to simulate wheat yield and water use efficiency under simultaneous salinity and water stress conditions in an arid region of Birjand, Iran and ii) Using different treatments for nested calibration and validation of AquaCrop model. Materials and Methods: This study was carried out as split plot design (factorial form) in Birjand, east of Iran, in order to evaluate the AquaCrop model.Treatments consisted of three levels of irrigation water salinity (S1, S2, S3 corresponding to 1.4, 4.5, 9.6 dS m-1) as main plot, two wheat varieties (Ghods and Roshan), and four levels of irrigation water amount (I1, I2, I3, I4 corresponding to 125, 100, 75, 50% water requirement) as sub plot. First, AquaCrop model was run with the corresponding data of S1 treatments (for all I1, I2, I3, and I4) and the results (wheat grain yield, average of soil water content, and ECe) were considered as the “basic outputs”. After that and in the next runs of the model, in each step, one of the inputs was changed while the other inputs were kept constant. The interval of variation of the inputs was chosen from -25 to +25% of its median value. After changing the values of input parameters, the model outputs were compared with the “basic outputs” using the sensitivity coefficient (Sc) of McCuen, (1973). Since there are four irrigation treatments for each salinity treatment, the model was calibrated using two irrigation treatments for each salinity treatment and validated using the other two irrigation treatments. In fact, six different cases of calibration and validation for each salinity treatment were [(I3 and I4), (I2 and I4), (I1 and I4), (I2 and I3), (I1 and I3), and (I1 and I2) for calibration and (I1 and I2), (I1 and I3), (I2 and I3), (I1 and I4), (I2 and I4), and (I3 and I4) for validation, respectively]. The model was calibrated by changing the coefficients of water stress (i.e. stomata conductance threshold (p-upper) stomata stress coefficient curve shape, senescence stress coefficient (p-upper), and senescence stress coefficient curve shape) for six different cases. Therefore, the average relative error of the measured and simulated grain yield was minimized for each case of calibration. After calibrating the model for each salinity treatment, the model was simultaneously calibrated using six different cases for three salinity treatments as a whole. Results and Discussion: Results showed that the sensitivity of the model to crop coefficient for transpiration (KcTr), normalized water productivity (WP*), reference harvest index (HIo), θFC, θsat, and maximum temperature was moderate. The average value of NRMSE, CRM, d, and R2 for soil water content were 11.76, 0.055, 0.79, and 0.61, respectively and for soil salinity were 24.4, 0.195, 0.72, and 0.57, respectively. The model accuracy for simulation of soil water content was more than for simulation of soil salinity. In general, the model accuracy for simulation yield and WP was better than simulation of biomass. The d (index of agreement) values were very close to one for both varieties, which means that simulated reduction in grain yield and biomass was similar to those of measured ones. In most cases the R2 values were about one, confirming a good correlation between simulated and measured values. The NRMSE values in most cases were lower than 10% which seems to be good. The CRM values were close to zero (under- and over-estimation were negligible). Based on higher WP under deficit irrigation treatments (e.g. I3) compared to full irrigation treatments (e.g. I1 and I2), it seems logical to adopt I3 treatment, especially in Birjand as a water-short region, assigning the remaining 25% to another piece of land. By such strategy, WP would be optimized at the regional scale. Conclusion: The AquaCrop was separately and simultaneously nested calibrated and validated for all salinity treatments. The model accuracy under simultaneous case was slightly lower than that for separate case. According to the results, if the model is well calibrated for minimum and maximum irrigation treatments (full irrigation and maximum deficit irrigation), it could simulate grain yield for any other irrigation treatment in between these two limits. Adopting this approach may reduce the cost of field studies for calibrating the model, since only two irrigation treatments should be conducted in the field. AquaCrop model can be a valuable tool for modelling winter wheat grain yield, WP and biomass. The simplicity of AquaCrop, as it is less data dependent, made it to be user-friendly. Nevertheless, the performance of the model has to be evaluated, validated and fine-tuned under a wider range of conditions and crops. Keywords: Biomass, Plant modeling, Sensitivity analysis

Iran is located in the North Temperate Zone from 25 to 40 degrees latitude and 44 to 63 degrees longitude, with a total area of approximately 1,650,000 Km2. A 50% of total lands area is covered with high mountain ranges. Elevations range from 26 meters below sea level on the shores of the Caspian Sea to 5860 meters above sea level at the pick of the Mt. Damavand. Drought or water deficiency is one of the most critical climatic factors in Iran. About 50% of Iran can be classified as arid or semi-arid zones. Climate parameters, particularly precipitation varies significantly in different parts of the country. There is not a good annual rainfall distribution in most regions of Iran, which limits the plant development and growth. Not only high temperature in southern, central and lowlands of Iran is a limiting factor, but also low temperature in northern, western and highlands is another limiting factor too. The Caspian region receives the largest part of the country’s precipitation while the central desert (Dasht-e-Lut) is faced with permanent drought. Forest ecological zones in Iran could be categorized as: a) North, Caspian forest, b) West, Zagros forest, c) North West, Arasbaran forest, d) South, Subtropical forest in Persian Gulf areas, and e) Central, Scattering forests. Some of the main tree species of Caspian forests: Fagus orientalis, Carpinus betulus, Acer velutinum, Quercus castaneifolia, Fraxinus excelsior. In this study, whole forest areas in southern part of Caspian Sea were monitored by study on vegetation map and visiting field. Three points representing major part of Hyrcanian Forests were selected from wet part in west to drier part in east. Four meteorological stations data used for investigation. Most of climatic factors including maximum, minimum and mean annual temperature; daily and annual precipitations were investigated. Mainly trends of mean annual temperature and annual precipitations were used for conclusion. It can clearly be concluded that during last half century climate in forest area in Caspian region become warmer. Precipitation trends especially in Anzali station that has highest precipitation records in Iran and also in Gorgan station have decreased. Precipitation trends in Rasht and Baboulsar stations have shown positive change. During last 49 years in Rasht station mean annual temperature increased about 1.28 °C and even its minimum temperature shows 2.45 °C increases. Increase mean annual temperature in Baboulsar station in last 54 yeas is about 1.44 °C and its minimum temperature shows 1.80 °C increases. Decrease of annual precipitation in Anzali station during last 54 years of records is about 409.4 mm and amount of decrease of precipitation for the period of last 53 years in Gorgan station is about 55.6 mm. Distribution of plants are directly depends upon temperature and precipitation conditions in each climatic zone. Generally with increasing about 100 meter of elevation amount of temperature will decrease by one degree of centigrade. In study zones especially in Gilan and Gorgan areas temperatures shown more than one degree increases and main species of vegetation cover moved upward about 100 meters. All data statistically were analyzed.

Since the importance of water in the durability and survival of life is clear to everyone, water issue has always been the focus of researchers and experts. Iran, having its own geographical and climatic location, has a small share of rainfall. Therefore, having an average annual rainfall of about 240 millimeters, one-third of the global average (860 millimeters), it is part of the dry and semi-arid climate (Alizadeh, 1997). Due to the lack of statistics, complexity of hydrological ecosystems and the impossibility of full recognition of the conditions in many catchment areas of the country, the use of methods that measure the amount of runoff from rainfall in non-statistical basins or those with incomplete statistics are of prime importance. One of these methods is the use of the capabilities of hydrological models in the simulation of hydrological processes which is one of the initial stages of water resources management and planning, and also the study of the hydrological effects of land use change and the way of exploitation of natural resources in a basin, where it is possible to simulate the hydrological processes, such as runoff, in the basins with complete statistics with the lowest cost and minimum time, and then use the information to estimate runoff in similar basins with no statistical data or incomplete statistics (Namdorost, 2002). LARS-WG5 is one of the generators of meteorological accidental data that is used to generate daily rainfall data, daily irradiance and maximum and minimum daily temperatures in a station under present and future climate conditions (Semenov and .Brooks., 1998). Zarghami et al (2001) reported a 2.3 degree increase in temperature and a 3 percent reduction in rainfall over the years 2020-2090 for East Azarbaijan province with the LRS-WG Exponential Meteorological Scale under the A1B, A2 and B1 scenarios using HADCM3 output.

In order to study the effect of water and nitrogen stress on biomass in Maize variety KSC704, an experiment was conducted at Agricultural and Natural Resources Research Center of Neyshabour city in year 2013. The experimental design was randomized complete block with three replications. The main treatments consisted of two levels of water stress 80 and 60 percent of water requirement in each of the three stages of growth vegetative, reproductive and grain filling and secondary treatments of two levels of 100 and 50 percent nitrogen. Most of biomass was produced in the control (no stress) equal to 22.8 ton/ha. Water and nitrogen stress applied at different stages of growth, has decreased final biomass. Water and nitrogen stress at vegetative growth stage had highest effect on biomass and lowest biomass was measured in IR60N50 equal to 13.2 ton/ha. Statistical analysis of results also showed that effects of water and nitrogen stress and interaction effects of irrigation and nitrogen had significant effect on biomass and water use efficiency at 1 percent level. The highest water use efficiency were obtained in control (I100N100) treatment with 1.77 kilograms per cubic meter. According to the results, it is recommended to maximize water use efficiency, water and nitrogen use completely done.

Dear Editor, Climate change is one of the most important challenges of the current century. High temperatures, ice melting, sea level rise, floods, droughts and wildfires are the consequences of climate change. Climate change affects human health directly by changing weather patterns (extreme heat, floods, hurricanes, storms and droughts) and indirectly by changing the quality of water, air and food. Climate change increases the risk of respiratory and cardiovascular diseases; food, water and vector borne illnesses; infectious diseases, injuries and premature deaths. Iran is very vulnerable to climate change due to its geographical location, dry and semi-arid weather conditions (80%) and economic structure. Iran's health system is facing the double challenge of dealing with the human impacts of climate change and reducing its significant contribution to the country's carbon footprint. As a result, the country's health system should be adaptive and resilient to climate change to decrease vulnerability and increase adaptive capacity and ensure continued health services. Therefore, Ministry of Health should formulate national strategic and operational plans to strengthen the adaptability and resilience of the country's health system to climate change. Such plans provide a roadmap for healthcare policymakers, managers and employees to protect and improve people's health in unstable and changing weather conditions.

Pumpkin is one of the valuable medicinal plants which have high oil content in its seeds. The response of pumpkin was examined against controlled water deficiency with spraying salicylic acid under field conditions in 2015 and 2016 in split plot experiment based on complete randomized block design. The plants sprayed with 0, 0.5, 1 and 1.5 mM concentrations of salicylic acid at 5-6 leaf stages. After 15 days plants exposed to -0.3, -1.2 and -1.8 MPa water deficiency. Increasing water deficiency reduced RWC, chlorophyll and carotenoids content, plant height, number of nodes and branches per plant, fruit yield, fruit diameter, seed yield, number of seed per fruit and weight of 1000 seeds while it and also increased the diameter of mesocarp especially in -1.8 MPa treated plants. On the contrary, spraying with salicylic acid resulted in significant increase in RWC, chlorophyll and carotenoids contents, plant height, number of nodes and branches per plant, fruit yield, diameter of fruit, seed yield, number of seed per fruit and weight of 1000 seeds. Haghest salicylic acid effect observed at 1.5 mM concentration. Most of traits under study depicated their significant reduction at -1.8 MPa water deficiency, while other traits like leaf water content, plant height, chlorophyll a, b and total chlorophyll content, nodes per plant, number of branches and mesocarp diameter were reduced at -1.2 MPa. On the other hand, seed per fruit was increased significantly at -1.2 MPa as compared to -0.3 MPa water deficiency. The main reason for increment of seed number per fruit was due to reduction in mesocarp diameter and its weight. It seems that water deficiency changed the partitioning pattern of assimilates from fruit and shifted them to seeds against mesocarp or other parts of fruit. Among the yield components, seed number per fruit and number of fruit per land area had the most effect on yield formation. The variation in seed weight was not significant. According to results, pumpkin may considered as a tolerant plant to soil suction till -1.2 MPa, without a significant reduction in seed yield.

In this study ichthyoplankton, phytoplankton, zooplankton, benthic and hydrochemistry parameters were studied. 9 out of 11 sampling stations were in the Gorgan Bay area and 2 of them were in the mouth of the Bay. Ichthyoplankton survey were carried out in 6 stations and the other surveys such as phytoplankton, etc were done in 11 stations in 2009. Gorgan Bay map and position of sampling sites are given at the end of material and methods section. Biomass and frequency of phytoplankton at different stations, months and seasons were calculated that are presented in Tables 1 to 3. Hydro-chemical parameters such as water temperature, air temperature, visibility, DO, BOD5, pH, Alkalinity (bicarbonate, carbonate and total), Hardness (calcium, magnesium), CL,EC, Salinity, N (nitrate, nitrite, NH_3), Phosphate were measured and results are shown Table 11. Biomass (mgr/m^3) and numbers (ind./m^3) of 47 genus of different phylum of phytoplanktons such as Cyanophyta, Chlorophyta, Pyrophyta, Chrysophyta and Euglenaphyta as well as different phylum of zooplanktons consist of Protozoa, Arthropoda, Rotifera and Cyliophora were estimated. Frequency of phytoplanktons (ind/m^3) was 131.2, 1.6, 65.3, 18.9 and 23.8 million respectively. Furthermore, their biomass was 308.4, 1.9, 1358.9, 295.1 and 124.7 mg/m^3, respectively. The maximum and minimum numbers were observed in Leptolingbaya belonged to Cyanophyta and Diatoms of Chrysophyta 84.3 and 0.025 million (ind/ m^3) respectively. The maximum and minimum biomass was observed in Gyrosigma (Chrysophyta) and Tetradron (Chloropyta), 12317.3 and 0.014 mg/m3 respectively. The average biomass of zooplankton was measured 531.74, 30.77, 225.07, and 96.26 mg/m^3 respectively and the total was attained 883.83 mg/m3 Table 5. The maximum and minimum biomass of all zooplanktons was estimated in November and July, 3446.23 and 6 mg/m^3 respectively. Furthermore, the maximum and minimum numbers of zooplanktons were found in September and July which were 48.4 and 0.002 millions respectively and the average number was 8.4 ind/m^3 Table 4. Also numbers and biomass (gr/m^2) of 11 families of benthos which inhabit Gorgan Bay such as Annelida, Mollusca and Arthropoda were investigated in separated stations and distinctive months. The maximum and minimum biomass of benthos was observed in January (42.91 gr/m^2) and March (0.6428 gr/m^2). The biomass was considerable in April, February, August and December (Tables: 4, 5 and 6).

Using of Nano-materials is one of the suitable ways for increasing of abiotic resistance in plants. In the current research, wild pear seedlings were irrigated with different concentrations of TiO2 and SiO2 NPs such as 0, 10, 100, 500 and 100 mgL-1. After this pretreatments, irrigation was stopped for 14 days to induce drought stress on the seedlings. At the end of the experiment, relative water content, xylem water potential, root biomass, electrolyte leakage rate, proline content and catalase enzyme activity were measured. The results showed that although both types of nanoparticles were differentially absorbed by roots of wild pear seedlings, the amelioration of water deficit in terms of all studied variables were observed for both of NPs with a slight differences between them. SiO2 NPs was more successful in improving root biomass and relative water content. On the other hand, TiO2 NPs was more successful in improving xylem water potential and catalase activity. Finally, amelioration effects of both NPs were clearly proved by the current research but further experiments are advised to find out involved mechanisms.