Antibiotic resistance and plasmid profiling of <Emphasis Type="Italic">Vibrio</Emphasis> spp. in tropical waters of Peninsular Malaysia

Vibrio species isolated from four different sampling stations in the west coast of Peninsular Malaysia were screened for their antimicrobial resistance and plasmid profiles. A total of 138 isolates belonging to 15 different species were identified. Vibrio campbellii, V. parahaemolyticus, V. harveyi, and V. tubiashii were found to predominance species at all stations. High incidence of erythromycin, ampicillin, and mecillinam resistance was observed among the Vibrio isolates. In contrast, resistance against aztreonam, cefepime, streptomycin, sulfamethoxazole, and sulfonamides was low. All the Vibrio isolates in this study were found to be susceptible to imipenem, norfloxacin, ofloxacin, chloramphenicol, trimethoprim/sulfamethoxazole, and oxytetracycline. Ninety-five percent of the Vibrio isolates were resistant to one or more different classes of antibiotic, and 20 different resistance antibiograms were identified. Thirty-two distinct plasmid profiles with molecular weight ranging from 2.2 to 24.8 kb were detected among the resistance isolates. This study showed that multidrug-resistant Vibrio spp. were common in the aquatic environments of west coast of Peninsular Malaysia.     

A moving target—incorporating knowledge of the spatial ecology of fish into the assessment and management of freshwater fish populations

Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.     

Spatial and temporal variability of metals in inter-tidal beach sediment of Mumbai, India

Nine metals were monitored in the beach sediment in Mumbai from May 2011 to March 2012 to evaluate the spatial and temporal distributions. The average heavy metal concentrations exhibited the following order: Fe > Mn > Cr > Co > Ni > Pb > Zn > Cu > Cd for the four sampling sites. The mean concentrations (± SD) of Fe, Mn, Cr, Co, Ni, Pb, Zn, Cu and Cd were estimated to be 31.15?±?10.02 g kg^?1, 535.04?±?76.42, 151.98?±?97.90, 92.76?±?14.18, 67.52?±?11.32, 59.57?±?15.19, 54.65?±?15.01, 32.24?±?8.07 and 18.75?±?1.76 mg kg^?1, respectively. The results indicated that the sediments were polluted with Cd, Cr, Co and Pb due to high anthropogenic influences. Spatial variation of metals revealed that most of the metals were high in Dadar beach and low in Aksa beach. Cd was the highest contaminant metal studied with a mean contamination factor of 93.75. The pollution load indices of the studied beaches ranged from 1.63 (Aksa) to 1.91 (Dadar) and indicated that the beach sediments were polluted with heavy metals. The heavy metal contents increased in relation to monsoon, and most of the heavy metals showed significantly high concentrations in November during the post-monsoon. The statistical analysis revealed significant effect of study site on all the metals studied. Further, there was a significant difference on metal accumulation on bimonthly basis in relation to weather pattern in Mumbai beaches.     

Characterizing spatial structure of sediment E. coli populations to inform sampling design

Escherichia coli can persist in streambed sediments and influence water quality monitoring programs through their resuspension into overlying waters. This study examined the spatial patterns in E. coli concentration and population structure within streambed morphological features during baseflow and following stormflow to inform sampling strategies for representative characterization of E. coli populations within a stream reach. E. coli concentrations in bed sediments were significantly different (p?=?0.002) among monitoring sites during baseflow, and significant interactive effects (p?=?0.002) occurred among monitoring sites and morphological features following stormflow. Least absolute shrinkage and selection operator (LASSO) regression revealed that water velocity and effective particle size (D ₁₀) explained E. coli concentration during baseflow, whereas sediment organic carbon, water velocity and median particle diameter (D ₅₀) were important explanatory variables following stormflow. Principle Coordinate Analysis illustrated the site-scale differences in sediment E. coli populations between disconnected stream segments. Also, E. coli populations were similar among depositional features within a reach, but differed in relation to high velocity features (e.g., riffles). Canonical correspondence analysis resolved that E. coli population structure was primarily explained by spatial (26.9–31.7 %) over environmental variables (9.2–13.1 %). Spatial autocorrelation existed among monitoring sites and morphological features for both sampling events, and gradients in mean particle diameter and water velocity influenced E. coli population structure for the baseflow and stormflow sampling events, respectively. Representative characterization of streambed E. coli requires sampling of depositional and high velocity environments to accommodate strain selectivity among these features owing to sediment and water velocity heterogeneity.     

Seasonal characteristics of SO2, NO2, and CO emissions in and around the Indo-Gangetic Plain

Anthropogenic emissions of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) exert significant influence on local and regional atmospheric chemistry. Temporal and spatial variability of these gases are investigated using surface measurements by the Central Pollution Control Board (India) during 2005–2009 over six urban locations in and around the Indo-Gangetic Plain (IGP) and supported using the satellite measurements of these gases. The stations chosen are Jodhpur (west of IGP), Delhi (central IGP), Kolkata and Durgapur (eastern IGP), Guwahati (east of IGP), and Nagpur (south of IGP). Among the stations studied, SO₂ concentrations are found to be the highest over Kolkata megacity. Elevated levels of NO₂ occur over the IGP stations of Durgapur, Kolkata, and Delhi. Columnar NO₂ values are also found to be elevated over these regions during winter due to high surface concentrations while columnar SO₂ values show a monsoon maximum. Elevated columnar CO over Guwahati during pre-monsoon are attributed to biomass burning. Statistically significant correlations between columnar NO₂ and surface NO₂ obtained for Delhi, Kolkata, and Durgapur along with very low SO₂ to NO₂ ratios (≤0.2) indicate fossil fuel combustion from mobile sources as major contributors to the ambient air over these regions.