Heavy metals contamination in water and three species of most consumed fish sampled from Caspian Sea, 2011

The present study is an attempt to evaluate the heavy metal contamination in the marine environment of the Caspian Sea of Iran. The concentrations of zinc, chromium, cadmium, and lead were measured in water and dorsal muscle of fish sampled from 10 selected stations along Gorgan coast using atomic absorption spectrophotometry during summer of 2011. The average concentrations of lead in water and fish samples (115.29?±?14.78 and 113.23?±?27.01 μg/L) were significantly higher than that of cadmium and chromium (P?<?0.05). The highest heavy metals content was observed in Cyprinus carpio samples. The heavy metals concentrations in the samples were within the acceptable recommended standards. But, elevating levels of heavy metals in water and fish made a serious concern about ecosystem and food chain contamination. It is recommended that protective authorities should carry out a continual assessment on the levels of pollutants in the sea.     

Assessment and monitoring of long-term forest cover changes in Odisha, India using remote sensing and GIS

Deforestation and fragmentation are important concerns in managing and conserving tropical forests and have global significance. In the Indian context, in the last one century, the forests have undergone significant changes due to several policies undertaken by government as well as increased population pressure. The present study has brought out spatiotemporal changes in forest cover and variation in forest type in the state of Odisha (Orissa), India, during the last 75 years period. The mapping for the period of 1924–1935, 1975, 1985, 1995 and 2010 indicates that the forest cover accounts for 81,785.6 km² (52.5 %), 56,661.1 km² (36.4 %), 51,642.3 km² (33.2 %), 49,773 km² (32 %) and 48,669.4 km² (31.3 %) of the study area, respectively. The study found the net forest cover decline as 40.5 % of the total forest and mean annual rate of deforestation as 0.69 %?year^?1 during 1935 to 2010. There is a decline in annual rate of deforestation during 1995 to 2010 which was estimated as 0.15 %. Forest type-wise quantitative loss of forest cover reveals large scale deforestation of dry deciduous forests. The landscape analysis shows that the number of forest patches (per 1,000) are 2.463 in 1935, 10.390 in 1975, 11.899 in 1985, 12.193 in 1995 and 15.102 in 2010, which indicates high anthropogenic pressure on the forests. The mean patch size (km²) of forest decreased from 33.2 in 1935 to 5.5 in 1975 and reached to 3.2 by 2010. The study demonstrated that monitoring of long term forest changes, quantitative loss of forest types and landscape metrics provides critical inputs for management of forest resources.     

Delineating shallow saline groundwater zones from Southern India using geophysical indicators

A geophysical survey was conducted over an industrial belt encompassing 80 functional leather factories in Southern India. These factories discharge untreated effluents which pollute shallow groundwater where electrical conductivity (EC) value had a wide range between 545 and 26,600 μS/cm (mean, 3, 901 μS/cm). The ranges of Na⁺ and Cl^? ions were from 46 to 4,850 mg/L (mean, 348 mg/L) and 25 to 10,390 mg/L (mean, 1,079 mg/L), respectively. Geoelectrical layer parameters of 37 vertical electrical soundings were analyzed to demarcate fresh and saline water zones. However, the analysis not did lead to a unique resolution of saline and fresh waters. It was difficult to assign a definitive value to the aquifer resistivity of any area. Thus, geophysical indicators, namely longitudinal unit conductance (S), transverse unit resistance (T), and average longitudinal resistivity (R _s), were calculated for identifying fresh and saline waters. Spatial distributions of S, T, and R _s reflected widely varying ranges for the saline and fresh water zones. Further, the empirical relation of formation factor (F) was established from pore-water resistivity and aquifer resistivity for fresh and saline aquifers, which may be used to estimate local EC values from the aquifer resistivity, where well water is not available.     

Accuracy and uncertainty assessment on geostatistical simulation of soil salinity in a coastal farmland using auxiliary variable

Understanding the spatial soil salinity aids farmers and researchers in identifying areas in the field where special management practices are required. Apparent electrical conductivity measured by electromagnetic induction instrument in a fairly quick manner has been widely used to estimate spatial soil salinity. However, methods used for this purpose are mostly a series of interpolation algorithms. In this study, sequential Gaussian simulation (SGS) and sequential Gaussian co-simulation (SGCS) algorithms were applied for assessing the prediction accuracy and uncertainty of soil salinity with apparent electrical conductivity as auxiliary variable. Results showed that the spatial patterns of soil salinity generated by SGS and SGCS algorithms showed consistency with the measured values. The profile distribution of soil salinity was characterized by increasing with depth with medium salinization (EC_e 4–8 dS/m) as the predominant salinization class. SGCS algorithm privileged SGS algorithm with smaller root mean square error according to the generated realizations. In addition, SGCS algorithm had larger proportions of true values falling within probability intervals and narrower range of probability intervals than SGS algorithm. We concluded that SGCS algorithm had better performance in modeling local uncertainty and propagating spatial uncertainty. The inclusion of auxiliary variable contributed to prediction capability and uncertainty modeling when using densely auxiliary variable as the covariate to predict the sparse target variable.     

Sediment fluxes and the littoral drift along northeast Andhra Pradesh Coast, India: estimation by remote sensing

The littoral drift regime along the northeastern coast of India was investigated by analyzing coastal drift indicators and shoreline changes based on multitemporal satellite images. The study of offshore turbidity patterns and quantitative estimation of suspended sediments was undertaken to understand the magnitude and direction of movement of sediment fluxes. The study revealed that: (1) the character of coastal landforms and sedimentation processes indicate that the sediment transport is bidirectional and monsoon dependent; (2) multidate, multitemporal analysis of satellite images helps to show the nature of sediment transport along the coast. The dominant net sediment transport is in a NE direction along the eastern coast of India. Finally, this assessment demonstrates the potential of remote sensing technology in understanding the coastal morphometric changes, long-term sediment transport, shoreline changes, and offshore turbidity distribution pattern and the implications for the transport of sediment-associated pollutants.     

Estimation of chlorpyriphos and cypermethrin residues in chilli (Capsicum annuum L.) by gas–liquid chromatography

Dissipation of chlorpyriphos and cypermethrin in chilli was studied following three applications of a combination formulation of Nurelle-D 505 (chlorpyriphos 50 %?+?cypermethrin 5 %) at 1 and 2 L?ha^?1 at an interval of 15 days. Residues of chlorpyriphos and cypermethrin in chilli were estimated by gas–liquid chromatography and confirmed by gas chromatography–mass spectrometry. Half-life periods for chlorpyriphos were found to be 4.43 and 2.01 days, whereas for cypermethrin these values were observed to be 2.51 and 2.64 days at single and double the application rates, respectively. Residues of chlorpyriphos dissipated to more than 80 % after 10 days at both the dosages. However, residues of cypermethrin dissipated to the extent of more than 70 % in 7 days. Soil samples collected after 15 days of the last application did not show the presence of chlorpyriphos and cypermethrin at their respective determination limit of 0.01 mg?kg^?1. The use of chlorpyriphos and cypermethrin mixture at the recommended dosage does not seem to pose any hazards to the consumers, and a waiting period of 1 day is suggested to reduce the risk before consumption of green chilli.     

Alteration of antioxidant enzymes and impairment of DNA in the SiO2 nanoparticles exposed zebra fish (Danio rerio)

The incorporation of nanoparticles in industrial and biomedical applications has increased significantly in recent years, yet their hazardous and toxic effects have not been studied extensively. While standard toxicological test methods are generally capable of detecting the toxic effects, the choice of relevant methods for nanomaterials is still discussed. Among the various oxide nanomaterials, silica nanoparticles are widely used in biological applications that include nano-medicine. But studies on adverse effects of silica nanoparticle exposure to fish remain unclear. Therefore, the present study was designed to investigate the oxidative toxic effects of silicon dioxide nanoparticles using fish model. The size of the SiO₂ nanoparticles was between 68 and 100 nm which was confirmed by X-ray diffractometer, dynamic light scattering, scanning electron microscope and transmission electron microscope. The zebra fish were exposed to sub-lethal concentrations (5 and 2.5 mg/L) of characterized SiO₂ nanoparticles for a period of 7 days. After 7 days, SiO₂ nanoparticle-treated fishes were sacrificed, and tissues such as liver, muscle and gill were dissected out for the analysis of antioxidant enzymes and DNA fragmentation. The DNA profiles were analysed in the tissues of zebra fish that treated with SiO₂ nanoparticles. Tissues of fish from clean water were used as control, and DNA profiles were analysed. It is found that DNA from control tissues was intact, whereas the tissues treated with SiO₂ were all fragmented. SiO₂ nanoparticle-mediated antioxidant enzymes activities, such as catalase, superoxide dismutase, glutathione (GSH)-S-transferase, glutathione reductase and GSH, in the tissues of zebra fish were measured. The results revealed that alteration of antioxidant enzymes due to SiO₂ nanoparticle can be considered as a biomarker to SiO₂-mediated oxidative stress in biological samples.     

Speciation of selected heavy metals geochemistry in surface sediments from Tirumalairajan river estuary, east coast of India

Surface sediment samples from the Tirumalairajan river estuary were studied for grain size pattern, organic matter, and heavy metals (Fe, Mn, Zn, and Pb) using the sequential and bulk metal extraction methods to evaluate metal behavior. Ten surface sediment samples were collected during the monsoon and summer seasons of the year 2009. The observed orders of concentrations of heavy metals in the sediments were as follows: Fe?>?Mn?>?Zn?>?Pb. The results obtained from sequential extraction showed that, among the metals studied, a larger portion of the metals were associated with the residual phase, although they are available in other fractions. The low concentration of metals available in bioavailable phases indicated that the sediments of Tirumalairajan river estuary were relatively unpolluted. Correlation analysis was also carried out to understand the associations of metals in different phases with sand, silt, clay, and organic matter. To understand the risk of heavy metals to sediment-dwelling organisms, the data were compared with risk assessment code and sediment quality values using the screening quick reference table. The main source of metals to the estuary is from the irrigation field and its associated activities in the study area.     

An assessment of the optimal scale for monitoring of MODIS and FIA NPP across the eastern USA

Robust monitoring of carbon sequestration by forests requires the use of multiple data sources analyzed at a common scale. To that end, model-based Moderate Resolution Imaging Spectroradiometer (MODIS) and field-based Forest Inventory and Analysis (FIA) data of net primary productivity (NPP) were compared at increasing levels of spatial aggregation across the eastern USA. A total of 52,167 FIA plots and colocated MODIS forest cover NPP pixels were analyzed using a hexagonal tiling system. A protocol was developed to assess the optimal scale as an optimal size of landscape patches at which to map spatially explicit estimates of MODIS and FIA NPP. The optimal mapping resolution (hereafter referred to as optimal scale) is determined using spatially scaled z-statistics as the tradeoff between increased spatial agreement as measured by Pearson’s correlation coefficient and decreased details of coverage as measured by the number of hexagons. Spatial sensitivity was also assessed using land cover assessment and forest homogeneity using spatially scaled z-statistics. Pearson correlations indicate that MODIS and FIA NPP are most highly correlated when using large hexagons, while z-statistics indicate an optimal scale at an intermediate hexagon size of 390 km². This optimal scale had more spatial detail than was obtained for larger hexagons and greater spatial agreement than was obtained for smaller hexagons. The z-statistics for land cover assessment and forest homogeneity also indicated an optimal scale of 390 km².     

Automated riverine landscape characterization: GIS-based tools for watershed-scale research, assessment, and management

River systems consist of hydrogeomorphic patches (HPs) that emerge at multiple spatiotemporal scales. Functional process zones (FPZs) are HPs that exist at the river valley scale and are important strata for framing whole-watershed research questions and management plans. Hierarchical classification procedures aid in HP identification by grouping sections of river based on their hydrogeomorphic character; however, collecting data required for such procedures with field-based methods is often impractical. We developed a set of GIS-based tools that facilitate rapid, low cost riverine landscape characterization and FPZ classification. Our tools, termed RESonate, consist of a custom toolbox designed for ESRI ArcGIS®. RESonate automatically extracts 13 hydrogeomorphic variables from readily available geospatial datasets and datasets derived from modeling procedures. An advanced 2D flood model, FLDPLN, designed for MATLAB® is used to determine valley morphology by systematically flooding river networks. When used in conjunction with other modeling procedures, RESonate and FLDPLN can assess the character of large river networks quickly and at very low costs. Here we describe tool and model functions in addition to their benefits, limitations, and applications.