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Otoliths are commonly used to discriminate between fish stocks, through both elemental composition and otolith shape. Typical studies also have a large number of elemental compositions and shape measures relative to the number of otolith samples, with these measures exhibiting strong mean–variance relationships. These properties make otolith composition and shape data highly suitable for use within a multivariate generalised linear model (MGLM) framework, yet MGLMs have never been applied to otolith data. Here we apply both a traditional distance based permutational multivariate analysis of variance (PERMANOVA) and MGLMs to a case study of striped snakehead (Channa striata) in India. We also introduce the Tweedie and gamma distributions as suitable error structures for the MGLMs, drawing similarities to the properties of Biomass data. We demonstrate that otolith elemental data and combined otolith elemental and shape data violate the assumption of homogeneity of variance of PERMANOVA and may give misleading results, while the assumptions of the MGLM with Tweedie and gamma distributions are shown to be satisfied and are appropriate for both otolith shape and elemental composition data. Consistent differences between three groups of C. striata were identified using otolith shape, otolith chemistry and a combined otolith shape and chemistry dataset. This suggests that future research should be conducted into whether there are demographic differences between these groups which may influence management considerations. The MGLM method is widely applicable and could be applied to any multivariate otolith shape or elemental composition dataset. [ABSTRACT FROM AUTHOR]

In order to evaluate the exposure of the northern India rural population to polyaromatic hydrocarbon (PAH) inhalation, indoor pollution was assessed by collecting and analyzing the respirable particulate matter PM and PM in several homes of the village Bhithauli near Lucknow, UP. The home selection was determined by a survey. Given the nature of biomass used for cooking, homes were divided into two groups, one using all kinds of biomass and the second type using plant materials only. Indoor mean concentrations of PM and associated PAHs during cooking ranged from 1.19 ± 0.29 to 2.38 ± 0.35 and 6.21 ± 1.54 to 12.43 ± 1.15 μg/m, respectively. Similarly, PM and total PAHs were in the range of 3.95 ± 1.21 to 8.81 ± 0.78 and 7.75 ± 1.42 to 15.77 ± 1.05 μg/m, respectively. The pollutant levels during cooking were significantly higher compared to the noncooking period. The study confirmed that indoor pollution depends on the kind of biomass fuel used for cooking. [ABSTRACT FROM AUTHOR]

Two PCP-degrading bacterial strains, Bacillus cereus (ITRC-S6) and Serratia marcescens (ITRC-S7) were used for the treatment of pulp and paper mill effluent at conditions; 1.0% glucose and 0.5% peptone at 30 ± 1°C at 120 rpm for 168 h of incubation. These two bacterial strains effectively reduced colour (45–52%), lignin (30–42%), BOD (40–70%), COD (50–60%), total phenol (32–40%) and PCP (85–90%) within 168 h of incubation. However, the highest reduction in colour (62%), lignin (54%), BOD (70%), COD (90%), total phenol (90%) and PCP (100%) was recorded by mixed culture treatment. The bacterial mechanism for the degradation of pulp and paper mill effluent may be explained by an increase in the cells biomass using added co-substrates resulting liberation of significant amount of chloride due to bacterial dechlorination of chlorolignins and chlorophenols this showed reduction in colour, lignin and toxicity in the effluent. Further, GC-MS analysis of ethyl acetate-extractable compounds from treated pulp paper mill effluent reinforces the bacterium capability for the degradation of lignin and pentachlorophenol, as many aromatic compounds such as 2-chlorophenol, 2, 4, 6-trichlorophenol and tetrachlorohydroquinone, 6-chlorohydroxyquinol and tetrachlorohydroquinone detected which were not present in the untreated effluent. [ABSTRACT FROM AUTHOR]