Gorgan Bay:a microcosm for study on macrobenthos species-environment relationships in the southeastern Caspian Sea

The relationship between spatial patterns of macrobenthos community characteristics and environmental conditions(salinity, temperature, dissolved oxygen, organic matter content, sand, silt and clay) was investigated throughout the Gorgan Bay in June 2010. Principal components analysis(PCA) based on environmental data separated eastern and western stations. The maximum(4500 ind./m²) and minimum(411 ind./m²) densities were observed at Stas 1 and 6, respectively. Polychaeta was the major group and Streblospio gynobranchiata was dominant species in the bay. According to Distance Based Linear Models results, macrofaunal total density was correlated with silt percentage and salinity and these two factors explaining 64% of the variability while macrofaunal community structure just correlated with salinity(22% total variation). In general, western part of the bay showed the highest number of species and biodiversity while, the highest density was found at Sta. 1 and in the middle part of the bay. Furthermore, relationship between diversity indices and macrobenthic species with measured factors is also discussed. Our results confirm the effect of salinity as an important factor on distribution of macrobenthic fauna in south Caspian brackish waters.     

Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models

This study attempts to identify and forecast future land cover (LC) by using the Land Transformation Model (LTM), which considers pixel changes in the past and makes predictions using influential spatial features. LTM applies the Artificial Neural Networks algorithm) in conducting the analysis. In line with these objectives, two satellite images (Spot 5 acquired in 2004 and 2010) were classified using the Maximum Likelihood method for the change detection analysis. Consequently, LC maps from 2004 to 2010 with six classes (forest, agriculture, oil palm cultivations, open area, urban, and water bodies) were generated from the test area. A prediction was made on the actual soil erosion and the soil erosion rate using the Universal Soil Loss Equation (USLE) combined with remote sensing and GIS in the Semenyih watershed for 2004 and 2010 and projected to 2016. Actual and potential soil erosion maps from 2004 to 2010 and projected to 2016 were eventually generated. The results of the LC change detections indicated that three major changes were predicted from 2004 to 2016 (a period of 12 years): (1) forest cover and open area significantly decreased at rates of almost 30 and 8 km², respectively; (2) cultivated land and oil palm have shown an increment in sizes at rates of 25.02 and 5.77 km², respectively; and, (3) settlement and Urbanization has intensified also by almost 5 km². Soil erosion risk analysis results also showed that the Semenyih basin exhibited an average annual soil erosion between 143.35 ton ha^?1 year^?1 in 2004 and 151 in 2010, followed by the expected 162.24 ton ha^?1 year^?1. These results indicated that Semenyih is prone to water erosion by 2016. The wide range of erosion classes were estimated at a very low level (0–1 t/ha/year) and mainly located on steep lands and forest areas. This study has shown that using both LTM and USLE in combination with remote sensing and GIS is a suitable method for forecasting LC and accurately measuring the amount of soil losses in the future.     

Optimal fusion of optical and SAR high-resolution images for semiautomatic building detection

Building detection from different high-resolution aerial and satellite images has been a notable research topic in recent decades. The primary challenges are occlusions, shadows, different roof types, and similar spectral behavior of urban covers. Integration of different data sources is a solution to supplement the input feature space and improve the existing algorithms. Regarding the different nature and unique characteristics of optical and radar images, there are motivations for their fusion. This paper is aimed to identify an optimal fusion of radar and optical images to overcome their individual shortcomings and weaknesses. For this reason, panchromatic, multispectral, and radar images were first classified individually, and their strengths and weaknesses were evaluated. Different feature-level fusions of these data sets were then assessed followed by a decision-level fusion of their results. In both the feature and decision levels of integration, artificial neural networks were applied as the classifiers. Several post-processing methods using normalized different vegetation index, majority filter, and area filter were finally applied to the results. Overall accuracy of 92.8% and building detection accuracy of 89.1% confirmed the ability of the proposed fusion strategy of optical and radar images for building detection purposes.     

Spatial distribution and biodiversity of macrofauna in the southeast of the Caspian Sea, Gorgan Bay in relation to environmental conditions

Spatial distribution and biodiversity of macrofauna in the Gorgan Bay, southeast of the Caspian Sea, were studied at fifteen stations in June 2010. Also, depth, temperature, salinity, dissolved oxygen, total organic matter content and sediment particle size were measured in each station. A total 3,356 individuals belonged to eight families and ten species were identified. Polychaeta were numerically dominated groups and Streblospio gynobranchiata, was constant and dominant species with 60.28% of total individuals but Bivalvia with four species had highest species number, though the density of them were low. The maximum density (4,500 ind/m²) was obtained at station 1 while the minimum (411 ind/m²) was observed at station 6. There was not significant correlation between the density of macrofauna with all environmental conditions. In total, six feeding group were considered but surface deposit feeder and deposit feeder were dominant in all stations. The maximum mean species number, diversity, richness, and evenness were obtained, 6.33, 1.46, 1.38 and 0.87, respectively. Based on the M-AMBI and the AMBI classification it seems that bentic environment in Gorgan Bay was not bad but the results of Shannon-Wiener, Margalef and Simpson indices the results were vice versa. In general, the values of the mentioned indices decreased from the western to the eastern part of the bay. Furthermore, the nonmetric multidimensional scaling (nMDS) showed that the structure of the macrofaunal assemblages was divides to six groups.     

Mineral chemistry of a Cenozoic igneous complex,the Urumieh–Dokhtar magmatic belt,Iran: Petrological implications for the plutonic rocks

The Niyasar plutonic complex, one of the Cenozoic magmatic assemblages in the Urumieh‐Dokhtar magmatic belt, was the subject of detailed petrographic and mineralogical investigations. The Niyasar magmatic complex is composed of Eocene to Oligocene mafic rocks and Miocene granitoids. Eleven samples, representing the major rock units in the Niyasar magmatic complex and contact aureole were chosen for mineral chemical studies and for estimation of the pressure, temperature, and oxygen fugacity conditions of mineral crystallization during emplacement of various magmatic bodies. The analyzed samples are composed of varying proportions of quartz, plagioclase, K‐feldspar, hornblende, biotite, titanite, magnetite, apatite, zircon, garnet, and clinopyroxene. Application of the Al‐in‐hornblende barometer indicates pressures of around 0.2 to 0.4 kbar for the Eocene–Oligocene mafic bodies and around 0.5 to 1.7 kbar for the Miocene granitoids. Hornblende‐plagioclase thermometry yields relatively low temperatures (661–780 °C), which probably reflect late stage re‐equilibration of these minerals. The assemblage titanite–magnetite–quartz as well as hornblende composition were used to constrain the oxygen fugacity and H₂O content during the crystallization of the parent magmas in the Miocene plutons. The results show that the Miocene granitoids crystallized from magmas with relatively high oxygen fugacity and high H₂O content (~5 wt% H₂O). The Miocene granitoids show similar range of oxygen fugacity, H₂O contents and mineral chemical compositions, which indicate a common source for their magmas. Although the crystallization pressures of the Miocene plutons discriminate various categories of plutonic bodies emplaced at depths of about 5.7–6.5 km (Marfioun pluton), about 4.2 km (Ghalhar pluton) and 1.9–2.3 km (Poudalg pluton), they were later uplifted to the same level by vertical displacement of faults. The emplacement depths of the Niyasar plutons suggest that the central part of the Urumieh‐Dokhtar magmatic belt has experienced an uplift rate of ca. 0.25–0.4 mm/yr from the Miocene onwards.     

Courage under fire: Seagrass persistence adjacent to a highly urbanised city–state

Due to increasing development Southeast Asia’s coastlines are undergoing massive changes, but the associated impacts on marine habitats are poorly known. Singapore, a densely populated island city–state, is a quintessential example of coastal modification that has resulted in the (hitherto undocumented) loss of seagrass. We reconstructed the historic extent and diversity of local seagrass meadows through herbarium records and backwards extrapolation from contemporary seagrass locations. We also determined the current status of seagrass meadows using long-term monitoring data and identified the main threats to their presence in Singapore. Results show that, even though ∼45% of seagrass has been lost during the last five decades, species diversity remains stable. The main cause of seagrass loss was, and continues to be, land reclamation. We conclude that strict controls on terrestrial runoff and pollution have made it possible for seagrass to persist adjacent to this highly urbanised city–state.     

Examination of chloritization of biotite as a tool for reconstructing the physicochemical parameters of mineralization and associated alteration in the Zafarghand porphyry copper system,Ardestan, Central Iran: mineral-chemistry and stable isotope analyses

Mineralogy and Petrology - The chloritization of biotite and stable isotopes of silicate have been studied for the Zafarghand porphyry copper deposit, Ardestan, Iran. The studied area, in the...     

Coastal Wave Height Prediction using Recurrent Neural Networks (RNNs) in the South Caspian Sea

The prediction of wave parameters has a great significance in the coastal and offshore engineering. For this purpose, several models and approaches have been proposed to predict wave parameters, such as empirical, soft computing, and numerical based approaches. Recently, soft computing techniques such as recurrent neural networks (RNN) have been used to develop sea wave prediction models. In this study, the RNN for wave prediction based on the data gathered and the measurement of the sea waves in the Caspian Sea, in the north of Iran is used for this study. The efficiency of RNNs for 3, 6, and 12 hourly and diurnal wave prediction using correlation coefficients is calculated to be 0.96, 0.90, 0.87, and 0.73, respectively. This indicates that wave prediction by using RNNs yields better results than the previous neural network approaches.