Environmental assessment of trace element bioaccumulation in sipunculan from seagrass and wetland sediments

This study is the first measurement of trace elements in sipunculan and their surrounding sediments. The bioaccumulation characteristics of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), and zinc (Zn) were analyzed and compared in two sipunculan species, Sipuncula nudus and Siphonosoma vastum, which were collected from seagrass beds and wetlands in Taiwan. The sipunculan and sediment samples were analyzed using an inductively coupled plasma mass spectrometer. Both sipunculan in the wetlands and seagrass beds had a high Cu bioaccumulation mechanism. Multivariate analysis, principle component analysis, and partial least squares for discriminant analysis of trace element levels and bioaccumulation factors were used to distinguish the element distributions that corresponded to the two habitats (seagrass beds and wetlands). Different levels of certain trace elements in these two sipunculan species may result not only from the environmental factors of various habitats but also from the accumulation characteristics of various species. The As, Cd, Cr, Cu, Hg, and Zn concentrations were markedly lower in sipunculan than in other invertebrates from the adjacent polluted regions. The public health issues regarding the consumption of sipunculan are also discussed.     

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.     

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.     

Sand as a relevant fraction in geochemical studies in intertidal environments

Soil and sediment samples from several intertidal environment exposed to different types of contamination were studied to investigate the importance of grain size in relation to the capacity of the substrates to retain trace metals. The unfractionated samples (referred to as bulk samples) were separated into the following grain/size fractions: fine–coarse sand (2?0.100 mm), very fine sand (0.100?0.050 mm), silt (0.050?0.002 mm), and clay (0.002 mm). The sample into its fractions was carried out was in a glove box under high-purity N₂ atmosphere in order to minimize any alterations to the samples. The bulk samples were characterized in terms of physicochemical properties such as pH, redox potential, and grain size. The total organic carbon (TOC), total sulfur (S), iron (Fe) pyrite, Fe, and manganese (Mn), and trace metals lead (Pb), mercury (Hg), chromium (Cr), and nickel (Ni) were analyzed in the bulk samples and in each fraction. The sand fractions were also examined by scanning electron microscopy (SEM). Comparisons of the above parameters were made between fractions and between each fraction and the corresponding bulk sample. The fine–coarse sand fraction contained high levels of the primary elements of the geochemical processes that occur in marine sedimentary environments such as TOC, total Fe, Mn, and S. The net concentrations of these four elements were higher in the fine-coarse sand fraction than in the very fine sand fraction and were similar to the net concentrations in the silt and clay fractions. Detailed SEM analysis of the sand coarse fraction revealed the presence of Fe and aluminum oxyhydroxide coatings in the oxic layers, whereas the framboidal pyrites and coatings observed in the anoxic layers were Fe sulfides. The presence of the various coatings explains why the trace metal concentrations in the sand fine–coarse fraction were similar to those in the clay fraction and higher than those in the very fine sand fraction. The present results highlight the importance of the sand fraction, which is generally disregarded in geochemical and environmental studies of sedimentary layers.     

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.     

Prediction of the solubility of zinc, copper, nickel, cadmium, and lead in metal-contaminated soils

Risk assessment of metal-contaminated soil depends on how precisely one can predict the solubility of metals in soils. Responses of plants and soil organisms to metal toxicity are explained by the variation in free metal ion activity in soil pore water. This study was undertaken to predict the free ion activity of Zn, Cu, Ni, Cd, and Pb in metal-contaminated soil as a function of pH, soil organic carbon, and extractable metal content. For this purpose, 21 surface soil samples (0–15 cm) were collected from agricultural lands of various locations receiving sewage sludge and industrial effluents for a long period. One soil sample was also collected from agricultural land which has been under intensive cropping and receiving irrigation through tube well water. Soil samples were varied widely in respect of physicochemical properties including metal content. Total Zn, Cu, Ni, Cd, and Pb in experimental soils were 2,015?±?3,373, 236?±?286, 103?±?192, 29.8?±?6.04, and 141?±?270 mg kg^?1, respectively. Free metal ion activity, viz., pZn²⁺, pCu²⁺, pNi²⁺, pCd²⁺, and pPb²⁺, as estimated by the Baker soil test was 9.37?±?1.89, 13.1?±?1.96, 12.8?±?1.89, 11.9?±?2.00, and 11.6?±?1.52, respectively. Free metal ion activity was predicted by pH-dependent Freundlich equation (solubility model) as a function of pH, organic carbon, and extractable metal. Results indicate that solubility model as a function of pH, Walkley–Black carbon (WBC), and ethylenediaminetetraacetic acid (EDTA)-extractable metals could explain the variation in pZn²⁺, pCu²⁺, pNi²⁺, pCd²⁺, and pPb²⁺ to the extent of 59, 56, 46, 52, and 51 %, respectively. Predictability of the solubility model based on pH, KMnO₄-oxidizable carbon, and diethylenetriaminepentaacetic acid-extractable or CaCl₂-extractable metal was inferior compared to that based on EDTA-extractable metals and WBC.     

Effect of a reservoir in the water quality of the Reconquista River, Buenos Aires, Argentina

The lower portion of the Reconquista River is highly polluted. However, little is known about the state of the high and middle basins. The aims of this work were to assess the water quality on the high and middle Reconquista River basins and to determinate if the presence of a reservoir in the river has a positive effect on the water quality. We conducted a seasonal study between August 2009 and November 2010 at the mouth of La Choza, Durazno, and La Horqueta streams at the Roggero reservoir—which receives the water from the former streams—at the origin of the Reconquista River and 17 km downstream from the reservoir. We measured 25 physical and chemical parameters, including six heavy metal concentrations, and performed a multivariate statistical analysis to summarize the information and allow the interpretation of the whole data set. We found that the Durazno and La Horqueta streams had better water quality than La Choza, and the presence of the reservoir contributed to the improvement of the water quality, allowing oxygenation of the water body and processing of organic matter and ammonia. The water quality of the Reconquista River at its origin is good and similar to the reservoir, but a few kilometers downstream, the water quality declines as a consequence of the presence of industries and human settlements. Therefore, the Roggero reservoir produces a significant improvement of water quality of the river, but the discharge of contaminants downstream quickly reverses this effect.