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The aim of the study is to address the issues and associated health risks due to consumption of high-fluoride water supplied for drinking in a rural part of Shanmuganadhi River basin, Tamil Nadu, India. In this study, 61 groundwater samples were gathered from various tube and open wells and analysed for fluoride and other physicochemical parameters. The abundance of cations is Na+ > Ca2+ > Mg2+ > K+, and that of anions is HCO3− > SO42− > Cl− > F−. The fluoride concentration in drinking groundwater varied from 0.10 to 3.3 mg/l. According to the WHO standards, about 26% of the samples were unfit for drinking requirements (16 out of 61 samples) Water quality index (WQI) method was adopted to categorize the water into different classes to understand its suitability for drinking requirements. WQI signified that nearly 52% of the samples denoted poor, very poor and not suitable categories, whereas 48% of samples denoted good and excellent categories for consumption. Health risks associated with high-fluoride drinking water were assessed for various age groups of inhabitants such as children, teens and adults. The hazard quotient estimated based on the oral intake ranged from 0.00E+00 to 5.50E+00, from 0.00E+00 to 4.22E+00 and from 0.00E+00 to 3.45E+00 for children, teens and adults, respectively. It suggested that the health risks are associated with 75%, 59% and 43% of samples, respectively, among children, teens and adults. Therefore, children are more inclined towards risk than teens and adults in this region based on the intake of fluoride-rich drinking water. To improve the present scenario, groundwater should be either treated before drinking water supply or must be artificially recharged to lower the concentration of ions. [ABSTRACT FROM AUTHOR]

ABSTRACT Muthusankar, G.; Proisy, C.; Balasubramanian, D.; Bautès, N.; Bhalla, R S.; Mathevet, R.; Ricout, A.; Senthil Babu, D., and Vasudevan, S., 2018. When socio-economic plans exacerbate vulnerability to physical coastal processes on the south east coast of India. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 1446–1450. Coconut Creek (Florida), ISSN 0749-0208. Industrial and urban development along the coast may exacerbate the changes induced by oceano-climatic processes to such an extent that the coast becomes uninhabitable. This paper presents a baseline study carried out on the 360 km-long Coromandel coast of Tamil Nadu's (TN) Bay of Bengal coast, Southeast India. About 30% of the 72 million inhabitants of the state of TN live in low-lying coastal areas within a variety of ecosystems such as sandy beaches and dunes, wetlands, mudflats and mangroves. Exponential demographic growth combines with dense urban agglomerations, ever-growing industrial and harbour areas, aquaculture and luxury tourism expansion increasing vulnerabilities to coastal erosion and extreme meteorological events. We report here how very high spatial resolution satellite (VHSRS) images, freely provided by Google Earth® engine or from the public database offered by GIS software, may be used to impartially and significantly survey coastal land cover (LC) transformations at fine scales over a number of years using preliminary visual interpretation. The study also gathered demographic data, historical records on strength and trajectories of the cyclones that have hit the TN coast since 1900, and decadal series of daily ERA-Interim/ECMWF waves and Mercator-Ocean oceanic currents. Our results demonstrate a tangle of environmental and human activities and situations subject to specific coastal hazards, particularly severe during the Northeast monsoon season. The potential risks for coastal ecosystems and local communities are finally discussed. [ABSTRACT FROM AUTHOR]

In spatial ecology, detailed covariance analyses are useful for investigating the influences of landscape properties on fauna and/or flora species. Such ecological influences usually operate at multiple scales, involving biological levels from individual to group, population or community and spatial units from field to farms and regions. The aim of this work was to analyze possible multiscale influences of some landscape properties on elephant distribution in the Western Ghats, India, by applying a recent and simple mathematical method to quantify such ecological relationships across space and scales. This method combines a moving window with various correlation indices to investigate the relationship between two mapped variables. Maps of landscape heterogeneity (quantified here at all locations of the landscape with a modified Shannon index) and Asian elephant presence (a two-dimensional presence probability) were significantly correlated. This correlation systematically decreased with increasing scales (i.e. sizes of the reference moving window). Yet, this global relationship includes both positive and negative correlations located at distinct places. We documented a positive feedback (reinforcement) because elephants appeared to seek greater habitat heterogeneity, in heterogeneous areas, such as along the interface between natural and a human-disturbed habitat or in the natural part of the studied landscape. In parallel, we observed a negative feedback (compensation) making elephants seeking more homogeneous places in some relatively heterogeneous zones. Such negative feedbacks corresponded to higher than average probabilities of elephant presence. Finally, when elephant density varied according to landscape heterogeneity (corresponding to significant correlations), it pointed towards swamps and grasslands, but not towards semi-evergreen or secondary forests (as it may have been expected). Land cover information appeared to be less relevant than an integrated heterogeneity index computed at all scales. [ABSTRACT FROM AUTHOR]

Data acquired during soil resource inventory of central Western Ghats, India, were supplemented with other available environmental data to estimate/map soil organic carbon (SOC) stock at the regional level. For an area (about 88,000 sq. km) stretching between Goa and the Palghat Gap, a model was developed linking SOC stock to the different environmental parameters known to control SOC levels, particularly type of land cover. Forests of different status, presenting varying stages of degradation, still occupy 43,000 sq. km in this area. This can explain the higher SOC stock (0.44 Pg) estimated compared to figures published earlier. [ABSTRACT FROM AUTHOR]