Ecological health analysis of Caspian marine environment based on the diversity and distribution pattern of meiofauna in the Mazandaran Province, Caspian Sea

Biodiversity and distribution of benthic meiofauna in the sediments of the Southern Caspian Sea (Mazandaran) was studied in order to introducing and determining of their relationship with the environmental factors. From 12 stations (ranging in depths 5, 10, 20 and 50 meters), sediment samples were gathered in 6 months (2012). Environmental factors of water near the bottom including temperature, salinity, dissolved oxygen and pH were measured during sampling with CTD and grain size and total organic matter percentage and calcium carbonate were measured in laboratory. In different months, the average water temperature (9.52-23.93), dissolved oxygen (7.71-10.53 mg/L), salinity (10.57±0/07 and 10.75±0/04 ppt), pH (7.44±0/29 and 7.41±0/22), EC (17.97±0/12 and 18.30±0/04μs/cm2), TDS (8.92±0/04 and 9.14±0/02 mg/L), total organic matter (5.83±1/43 and 6.25±0/97%) and calcium carbonate (2.36±0/36 and 1.68±0/19%) were measured respectively. Structure of the sediment samples mostly consisted of fine sand; very fine sand, silt and clay. From the 4 group animals (Foraminifera, Crustacea, Worms and Mollusca), there were identified 40species belong to 29 genera of 25 families. The cosmopolitan foraminifer, Ammonia beccarii caspica, was common in all sampling stations. Result showed that depth was important factor on distribution of meiofauna. Most density of foraminifera and crustacean was observed in depth of 20m and for mollusca and worms observed in 5m. Shannon diversity index decreased with depth that showed in shallow water diversity was higher than deep water. Mean of maximum and minimum Shannon index was obsorvers in depth of 5m and 50 m that was measured in order 0.93 and 0.43. Account of Shannon index showed that this area is under pressure. Account of peioleo index showed distribution in this area was not steady.

A social and gender analysis of Northern Province, Zambia: Qualitative evidence that supports the use of a gender transformative approach

A qualitative social and gender analysis was carried out in June 2015 in Luwingu and Mbala Districts in Northern Province, Zambia. The research explored the norms and power relations at various institutional levels that constrain certain social groups from benefiting from programmatic investments aimed at improving livelihoods, health status, and food and nutrition security within the Irish Aid Local Development Programme (IALDP). This technical paper provides a summary of the research findings, lessons learned and suggests options for action the IALDP could consider to help bring about gender transformative change in the lives and livelihoods of poor and vulnerable people.

Preparation of environmental monitoring plan pattern for surface water quality in Iran (Case study: Gharehsou River)

Using water quality management programs is a necessary and inevitable way for preservation and sustainable use of water resources. One of the important issues in determining the quality of water in rivers is designing effective quality control networks, so that the measured quality variables in these stations are, as far as possible, indicative of overall changes in water quality. One of the methods to achieve this goal is increasing the number of quality monitoring stations and sampling instances. Since this will dramatically increase the annual cost of monitoring, deciding on which stations and parameters are the most important ones, along with increasing the instances of sampling, in a way that shows maximum change in the system under study can affect the future decision-making processes for optimizing the efficacy of extant monitoring network, removing or adding new stations or parameters and decreasing or increasing sampling instances. This end, the efficiency of multivariate statistical procedures was studied in this thesis. Multivariate statistical procedure, with regard to its features, can be used as a practical and useful method in recognizing and analyzing rivers’ pollution and consequently in understanding, reasoning, controlling, and correct decision-making in water quality management. This research was carried out using multivariate statistical techniques for analyzing the quality of water and monitoring the variables affecting its quality in Gharasou river, in Ardabil province in northwest of Iran. During a year, 28 physical and chemical parameters were sampled in 11 stations. The results of these measurements were analyzed by multivariate procedures such as: Cluster Analysis (CA), Principal Component Analysis (PCA), Factor Analysis (FA), and Discriminant Analysis (DA). Based on the findings from cluster analysis, principal component analysis, and factor analysis the stations were divided into three groups of highly polluted (HP), moderately polluted (MP), and less polluted (LP) stations Thus, this study illustrates the usefulness of multivariate statistical techniques for analysis and interpretation of complex data sets, and in water quality assessment, identification of pollution sources/factors and understanding spatial variations in water quality for effective river water quality management. This study also shows the effectiveness of these techniques for getting better information about the water quality and design of monitoring network for effective management of water resources. Therefore, based on the results, Gharasou river water quality monitoring program was developed and presented.