Phytoplankton assemblage in relation to physical and chemical characteristics of water in Al-Auda marsh of Maysan province southern Iraq was assessed from November 2012 to July 2013. Six sampling sites were chosen to examine all phytoplankton species in the study area. A total of 246 species and seventy-five genera have been recognized belonging to twelve phytoplankton classes as follows: Bacillariophyceae (106 taxa), Chlorophyceae (34 taxa), Euglenophyceae (29 taxa), Cyanophyceae (29 taxa), Conjugatophyceae (19 taxa), Mediophyceae (10 taxa), Cryptophyceas (5 taxa), Coscinodiscophyceae (4 taxa), Chrysophyceae (4 taxa), Dinophyceae (3 taxa), Trebouxiophyceae (2 taxa) whereas Compsopogonophyceae recorded only (one taxon).The finding showed class Bacillariophyceae dominated with (43.09%), followed by Chlorophyceae of (13.82%), then (11.79%) for each of Cyanophycean and Euglenophyceae. Mean ± standard deviation for water temperature was ranged between (14.3±1.6°C) during winter to (35.6±1.81°C) during summer, electrical Conductivity (2020±186μ.s/cm) during autumn to (6390±875μ.s/cm) during summer, total Phosphate 0.01±0.0 µg/l during winter to 0.3±0.08 µg/l during spring, and total nitrogen varied from 1.8±0.8 µg/l during winter to 6.9±0.5 µg/l during autumn. Seasonal distribution indicated that phytoplankton flourished predominantly during the summer and spring. The diversity index (H) recorded the highest value in spring and lowest value in autumn, Richness (D) and Evenness (E) indices achieved the highest values in spring, the lowest values in autumn. The Jaccard index (Ss%) recorded the highest similarity between autumn and winter, the lowest similarity was between autumn and spring. The results revealed Al-Auda marsh is mesotrophic according to phytoplankton composition.
This paper deals the prediction of the process of random spatial data of two properties, the first is called Primary variables and the second is called secondary variables , the method that were used in the prediction process for this type of data is technique Co-kriging , the method is usually used when the number of primary variables meant to predict for one of its elements is measured in a particular location a few (because of the cost or difficulty of obtaining them) compare with secondary variable which is the number of elements are available and highly correlated with primary variables, as was the&nbs
... Show MoreContracaecum rudolphii Hartwich, 1964 is a nematode which causes major concerns to human and wildlife animal’s health. However, the population genetics of C. rudolphii has been poorly studied in Iraq. In order to gain a deeper understanding in the outline of the genetic diversity of the nematode C. rudolphii that were isolated from its host cormorant Phalacrocorax carbo (Linnaeus, 1758), in the middle areas of Iraq, twenty specimens of C. rudolphii adults were isolated from nine individuals of P. carbo. The first (ITS-1) internal transcribed spacers (ITS) of ribosomal DNA (rDNA) of C. rudolphii were amplified using conventional polymerase chain reaction (PCR); then, the amplicons were subjected to sequencing. Concatenation of ITS
... Show MoreThe study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge
... Show MoreIt is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i
... Show MoreThis research paper is about synoptic climate specifically with in the upper air layers
using upper air layers maps analysis which are maps of thickness for the level 1000 – 500
MB, that their high average ranges between 100 – 5600 M above surface. This research paper
focuses on studying special and temporal variations of the atmosphere thickness above Iraqaccording
to this study, it is concluded that atmosphere thickness above Iraq increases
towards south with an average of 100 M as compared with north of Iraq. Regarding the
temporal variations, it is concluded that atmosphere thickness during hot months. In July, for
example, the atmosphere thickness becomes thicker than in January with an average of
(250)M