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This study analyzes the trophic structure of fish assemblages in a well-mixed tropical estuary, Zuari, located in southwest coast of India. A total of 224 fish species were collected between September 2013 and August 2016 from 324 sampling events from 9 sampling stations using surface and bottom set gillnets. The sampling events were designed to cover three major seasons such as the pre-monsoon, monsoon, and post-monsoon. For each sampling event, abiotic variables such as temperature, salinity, dissolved oxygen, and transparency of the water were recorded. The data obtained for abundance of fish species was subjected to cluster analysis and non-metric multidimensional scaling. The results defined six spatio-temporally varying groups (clusters) within Zuari estuary. Canonical correspondence analysis demonstrated that temperature, salinity, dissolved oxygen, and transparency were important in determining the fish assemblages in Zuari. The estuarine resident species were abundant in the inner zone (riverine side) of the estuary, where the salinity and temperature recorded lower dimensions compared to middle and outer zones (marine side). However, the inner shallow zone of the estuary was not a preferred habitat for the migrating marine species. Majority of the fish species preferred middle and outer zones and post-monsoon and pre-monsoon seasons for inhabiting the estuary. The present study furnishes a reference data for the spatio-temporal dynamics of fish assemblages in tropical monsoonal estuaries.

Expression of the stress biomarkers 70-kDa heat shock proteins (Hsp70) and manganese superoxide dismutase (MnSOD) was measured as the molecular basis of adaptive response against increased experimental temperatures (32-40 °C for a span of 24-72 h) on the fresh water molluscan species, Bellamya bengalensis (Lamark 1882). The experimental snail specimens were collected during summer and winter seasons from two contrasting wetlands: an ecorestored (free from human interference) site (SI) and other experiencing anthropogenic stresses (SII). The mortality rate of the B. bengalensis and the immunoblotting of MnSOD and Hsp70 of their digestive glands were performed at regular intervals during the period of heat stress. The SI provided a lower stress environment based on physicochemical parameters such as pH, dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), and alkalinity for the survival of test species, although both sites experienced mortality due to thermal stresses. The parity in protein expressions displayed a uniform mode of adaptive impact to temperature elevations in both field and laboratory exposure. The Hsp70 expression was minimal at lower thermal stress, but increased with a rise in temperature. It is very likely that higher Hsp70 levels are not directly related to survival or adaptation. In contrast, MnSOD levels appeared to be an indicator of adaptive responses vis-a-vis survival of the animals. So, the expression levels of a universal free radical scavenger like MnSOD are recognized as a potential biomarker in a bioindicator species like Bellamya.

The major objective of the investigation was to evaluate the road traffic noise and its likely impacts on the local community of Asansol city (West Bengal, India) by monitoring and modeling. The attitudinal response of local population due to existing vehicular noise is presented in the paper. Noise and Attitudinal Survey was conducted at 25 locations. A total of 869 individuals were surveyed. The relationship between traffic noise levels and annoyance was studied using correlation, linear and multiple linear regressions analysis. The average L(dn) value was 73.28 +/- 8.51 dB(A) (55.1-87.3); The Traffic Noise Index (TNI) was 80.62 +/- 15.88 dB(A) (49.4-115.8). The mean value of percent of population Highly Annoyed (%HA) due to road traffic noise was 26.50 +/- 3.37 (19.44-33.2), whereas the mean dissatisfaction score (MDS) was 2.96 +/- 0.90 (1.04-4.45). Annoyance modeling was also performed based on field data. It can be said that Noise values gives desirable annoyance predicting values in comparison to vehicular data.