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.     

The use of sensory perception indicators for improving the characterization and modelling of total petroleum hydrocarbon (TPH) grade in soils

This paper proposes a multistep approach for creating a 3D stochastic model of total petroleum hydrocarbon (TPH) grade in potentially polluted soils of a deactivated oil storage site by using chemical analysis results as primary or hard data and classes of sensory perception variables as secondary or soft data. First, the statistical relationship between the sensory perception variables (e.g. colour, odour and oil–water reaction) and TPH grade is analysed, after which the sensory perception variable exhibiting the highest correlation is selected (oil–water reaction in this case study). The probabilities of cells belonging to classes of oil–water reaction are then estimated for the entire soil volume using indicator kriging. Next, local histograms of TPH grade for each grid cell are computed, combining the probabilities of belonging to a specific sensory perception indicator class and conditional to the simulated values of TPH grade. Finally, simulated images of TPH grade are generated by using the P-field simulation algorithm, utilising the local histograms of TPH grade for each grid cell. The set of simulated TPH values allows several calculations to be performed, such as average values, local uncertainties and the probability of the TPH grade of the soil exceeding a specific threshold value.     

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.     

Evaluation of metals in several varieties of sweet potatoes (Ipomoea batatas L.): comparative study

Sweet potatoes are a staple in the diet of some people and an excellent source of minerals. Metal monitoring in food, like sweet potatoes, provides basic information on safety aspects in regulatory processes as well as nutritional values. One hundred five samples of three varieties of sweet potatoes were randomly obtained from supermarkets, farmers markets, and farmers' plots in Tenerife (Canary Islands, Spain). The edible portion (pulp) was the only part considered for analysis. Flame atomic absorption spectrometry was used to determine the contents of sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), copper (Cu), iron (Fe), manganese (Mn), and zinc (Zn), while the levels of chromium (Cr), nickel (Ni), cadmium (Cd), and lead (Pb) were determined using graphite furnace atomic absorption spectrometry. The mean concentrations were 500 Na, 4409 K, 564 Ca, 609 Mg, 1.291 Cu, 6.554 Fe, 2.324 Mn, 2.348 Zn, 0.028 Cr, 0.048 Ni, 0.001 Cd, and 0.003 Pb mg/kg, respectively. Potassium presented the highest contents in all varieties of sweet potatoes. Iron was the most abundant microelement. The orange fleshed sweet potato variety offered greater nutritional contributions to the recommended intakes than the rest of the varieties studied. The estimated mean daily intake of Ni (0.72 mg/day) detected in our samples was highly consistent with other studies. Average daily intakes of Cd (0.015 μg/day) and Pb (0.045 μg/day) were below toxicological reference values. In conclusion, the levels of Cd and Pb detected in the sweet potatoes analyzed do not represent any toxicological risk to consumers.