Wetland ecosystems around the world are of great importance in terms of providing valuable ecological services to people and wildlife. According to the Montreux Record, there is a list of wetlands which failed to fulfill the Ramsar Convention’s criteria. The Shadegan international site, registered in 1975 as a Ramsar Convention member, has been subjecting to the Montreux record since 1993 owning to the conditions change. The purpose of this study was to apply linear programming (LP) to measure the status of Criterion IV of the Ramsar Convention over the extent of Shadegan Wetland. Accordingly, Criterion IV was defined in mathematical language and run by the Excel software. The Lingo software was also used to verify the previously retrieved linear model by defining constraints for X variables. The constraints of this model were chosen based on the extreme events (i.e. evaporation threshold was determined based on water and energy limitations) of each variable during the study period considering the trend effect of each variable.

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Although there are considerable profits in dam projects, they contribute to significant environmental changes. Landscape patterns are influenced by human pressure and are altered continuously. This study investigated the changes in the landscape pattern of Jask’s coastal area in Iran due to the Jagin River dam’s construction. A proposed methodology employed satellite images from 1987 to 2018 and classified them by multiple approaches to make LULC maps. Eight information categories were evaluated after classification. The accuracy of the classification was determined using the error matrix and kappa index. FRAGSTATS software was applied to calculate several landscape metrics such as edge density (ED), largest patch index (LPI) and Shannon’s diversity index (SHDI). The study reported that water right especially in the recent years, because of excessive use of reserve water, decreased and downstream of Jagin River was dried. The landscapes were continuously characterized by anthropogenic pattern features (agriculture land, aquaculture land, built-up land and residential land) after the dam’s construction. Rangeland cover and riparian vegetation decreased, and agriculture land increased with in filling pattern. The sand dune area has been spread to the residential area and roots of mangrove forests, because of this reason some parts of mangrove forest dried and roads are covered by sand dune. Their temporal comparison allowed us to localize the change in landscape patterns under the study time. The results can help decision-makers to evaluate the net benefits acquired as a result of the dam projects.

The genus Avicennia with eight species grow in intertidal zones of tropical and temperate regions, ranging in distribution from West Asia, to Australia, and Latin America. These mangroves have several medicinal applications for mankind. Many genetic and phylogenetic studies have been carried out on mangroves, but none is concerned with geographical adaptation of SNPs. We therefore, used ITS sequences of about 120 Avicennia taxa growing in different parts of the world and undertook computational analyses to identify discriminating SNPs among these species and to study their association with geographical variables. A combination of multivariate and Bayesian approaches such as CCA, RDA, and LFMM were conducted to identify the SNPs with potential adaptation to geographical and ecological variables. Manhattan plot revealed that many of these SNPs are significantly associated with these variables. The genetic changes accompanied by local and geographical adaptation were illustrated by skyline plot. These genetic changes occurred not under a molecular clock model of evolution, and probably under a positive selection pressure imposed in different geographical regions in which these plants grow.