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.     

Assessment of heavy metal enrichment in the offshore fine-grained sediments of the Caspian Sea

Sampling of the offshore seabed sediments of southwestern part of the Caspian Sea was carried out by gravity corer in order to study heavy metal concentration and the physicochemical factors controlling their distribution in the fine-grained fraction. The grain size distribution, amount, and type of clay minerals, total organic carbon (TOC) content, and Eh–pH of the sediments were determined. The average concentrations of the heavy metals in ppm are Mn (563), Cu (207.5), Sr (187), Zn (94), Pb (26.3), Ni (14.5), Co (11.5), Cd (2.56), and Ag (1.04) in their order of abundances. Co and Zn mostly indicate increase in silt-size fraction of the sediments suggesting their probable detrital provenance but the Mn, Ni, Cu, Sr, Pb, Cd, and Ag concentrations show a similar trend to distribution of the clay-size fraction. The concentrations of Mn, Co, and Cd increase with increase in the TOC content but the Cu, Pb, Ni, Ag, and Sr concentrations decrease with increase of the TOC content. The amounts of Zn, Cu, Sr, Pb, Cd, and Ag increase with increase in the CaCO₃ content. The calculated enrichment factor indicates that the sediments are very strong to extremely enriched in Ag, significantly enriched in Cu and Cd, and depleted to mineral for Pb, Sr, Co, Ni, and Zn. Variations of the Cu, Sr, Cd, Ag, and Pb concentrations are similar to the clay and CaCO₃ distributions.     

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.     

Advantages of Geographically Weighted Regression for Modeling Benthic Substrate in Two Greater Yellowstone Ecosystem Streams

Stream habitat assessments are commonplace in fish management, and often involve nonspatial analysis methods for quantifying or predicting habitat, such as ordinary least squares regression (OLS). Spatial relationships, however, often exist among stream habitat variables. For example, water depth, water velocity, and benthic substrate sizes within streams are often spatially correlated and may exhibit spatial nonstationarity or inconsistency in geographic space. Thus, analysis methods should address spatial relationships within habitat datasets. In this study, OLS and a recently developed method, geographically weighted regression (GWR), were used to model benthic substrate from water depth and water velocity data at two stream sites within the Greater Yellowstone Ecosystem. For data collection, each site was represented by a grid of 0.1 m² cells, where actual values of water depth, water velocity, and benthic substrate class were measured for each cell. Accuracies of regressed substrate class data by OLS and GWR methods were calculated by comparing maps, parameter estimates, and determination coefficient r ². For analysis of data from both sites, Akaike’s Information Criterion corrected for sample size indicated the best approximating model for the data resulted from GWR and not from OLS. Adjusted r ² values also supported GWR as a better approach than OLS for prediction of substrate. This study supports GWR (a spatial analysis approach) over nonspatial OLS methods for prediction of habitat for stream habitat assessments.     

Characterization of As and trace metals embedded in PM10 particles in Puebla City, México

Forty-eight air-filter samples (PM₁₀) were analysed to identify the concentration level of partially leached metals (PLMs; As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and V) from Puebla City, México. Samples were collected during 2008 from four monitoring sites: (1) Tecnológico (TEC), (2) Ninfas (NIN), (3) Hermanos Serdán (HS) and (4) Agua Santa (AS). The results indicate that in TEC, As (avg. 424 ng m^?3), V (avg. 19.2 ng m^?3), Fe (avg. 1,202 ng m^?3), Cu (avg. 86.6 ng m^?3), Cr (41.9 ng m^?3) and Ni (18.6 ng m^?3) are on the higher side than other populated regions around the world. The enrichment of PLMs is due to the industrial complexes generating huge dust particles involving various operations. The results are supported by the correlation of metals (Mn, Cd and Co) with Fe indicating its anthropogenic origin and likewise, As with Cd, Co, Fe, Mn, Pb and V. The separate cluster of As, Fe and Mn clearly signifies that it is due to continuous eruption of fumaroles from the active volcano Popocatépetl in the region.     

Temperature inversion characteristics in relation to synoptic circulation above Athens,Greece

In this paper, the characteristic properties of inversions formed inside the lower boundary layer over Athens, Greece, were studied using 35-year radiosonde measurements of temperature, humidity, and atmospheric pressure. The analysis revealed that the inversion parameters demonstrate considerable seasonal variation. Specifically, inversions associated with weak anticyclonic conditions are more frequent during the winter and summer months, while during spring, weak lows are more probable to produce inversions. Some theoretically expected associations between synoptic circulation patterns and certain inversion parameters were also identified.     

The distribution and extent of heavy metal accumulation in song sparrows along Arizona’s upper Santa Cruz River

Heavy metals are persistent environmental contaminants, and transport of metals into the environment poses a threat to ecosystems, as plants and wildlife are susceptible to long-term exposure, bioaccumulation, and potential toxicity. We investigated the distribution and cascading extent of heavy metal accumulation in southwestern song sparrows (Melospiza melodia fallax), a resident riparian bird species that occurs along the US/Mexico border in Arizona’s upper Santa Cruz River watershed. This study had three goals: (1) quantify the degree of heavy metal accumulation in sparrows and determine the distributional patterns among study sites, (2) compare concentrations of metals found in this study to those found in studies performed prior to a 2009 international wastewater facility upgrade, and (3) assess the condition of song sparrows among sites with differing potential levels of exposure. We examined five study sites along with a reference site that reflect different potential sources of contamination. Body mass residuals and leukocyte counts were used to assess sparrow condition. Birds at our study sites typically had higher metal concentrations than birds at the reference site. Copper, mercury, nickel, and selenium in song sparrows did exceed background levels, although most metals were below background concentrations determined from previous studies. Song sparrows generally showed lower heavy metal concentrations compared to studies conducted prior to the 2009 wastewater facility upgrade. We found no cascading effects as a result of metal exposure.     

A new sampler for stratified lagoon chemical and microbiological assessments

A sampler was needed for a spatial and temporal study of microbial and chemical stratification in a large swine manure lagoon that was known to contain zoonotic bacteria. Conventional samplers were limited to collections of surface water samples near the bank or required a manned boat. A new sampler was developed to allow simultaneous collection of multiple samples at different depths, up to 2.3 m, without a manned boat. The sampler was tethered for stability, used remote control (RC) for sample collection, and accommodated rapid replacement of sterile tubing modules and sample containers. The sampler comprised a PVC pontoon with acrylic deck and watertight enclosures, for a 12 VDC gearmotor, to operate the collection module, and vacuum system, to draw samples into reusable autoclavable tubing and 250-mL bottles. Although designed primarily for water samples, the sampler was easily modified to collect sludge. The sampler held a stable position during deployment, created minimal disturbance in the water column, and was readily cleaned and sanitized for transport. The sampler was field tested initially in a shallow fresh water lake and subsequently in a swine manure treatment lagoon. Analyses of water samples from the lagoon tests showed that chemical and bacterial levels, pH, and EC did not differ between 0.04, 0.47, and 1.0 m depths, but some chemical and bacterial levels differed between winter and spring collections. These results demonstrated the utility of the sampler and suggested that future manure lagoon studies employ fewer or different depths and more sampling dates.