The Japanese medaka (Oryzias latipes) model: applicability for investigating the immunosuppressive effects of the aquatic pollutant benzo[a]pyrene (BaP)

Despite the fact that BaP is a carcinogen, mammalian immunosuppressant, and ubiquitous aquatic pollutant, knowledge regarding the effects of BaP on the immune system of fish is still lacking. To begin to fill this gap, studies were conducted in medaka to examine the effects and mechanisms by which BaP exposure might alter host immunocompetence. Fish, exposed by IP injection of BaP (2-600 microg/g BW), were examined after 48 h for effects upon immune function and CYP1A expression/activity. Benzo[a]pyrene, at a concentration below that which increased levels of CYPIA expression/activity (2 microg BaP/g BW) suppressed lymphocyte proliferation. Concentrations of BaP at 20 and 200 microg/g BW. suppressed antibody-forming cell (AFC) numbers, superoxide production, and host resistance against bacteria. In contrast, exposure to the low affinity aryl hydrocarbon receptor (AhR) agonist, benzo[e]pyrene (BeP), neither induced CYP1A expression nor altered immune function. Given the lack of immunosuppressive effects produced by BeP, and the fact that exposure to the AhR antagonist (and CYP1A inhibitor) alpha-naphthoflavone (ANF) ameliorated the suppressive effects of BaP upon AFC numbers, the AhR pathway (including CYP1A-mediated production of reactive BaP metabolites) appears important in mediating BaP-induced immunotoxicity in fish, as in mammals. In the past, the medaka has proven a successful model for assessing carcinogenic agents. These studies have demonstrated its utility for also determining the immunosuppressive effects of an important aquatic contaminant.     

A First Comparison of the Surface Brightness Fluctuation Survey Distances with the Galaxy Density Field: Implications for H0 and Omega

We compare the peculiar velocities measured in the surface brightness fluctuation survey of galaxy distances with the predictions from the density fields of the IRAS 1.2 Jy flux-limited redshift survey and the optical redshift survey (ORS) to derive simultaneous constraints on the Hubble constant H0 and the density parameter beta=Omega0.6&solm0;b, where b is the linear bias. We find that betaI=0.42+0.10-0.06 and betaO=0.26+/-0.08 for the IRAS and ORS comparisons, respectively, and that H0=74+/-4 km s-1 Mpc (with an additional 9% uncertainty due to the Cepheids themselves). The match between predicted and observed peculiar velocities is good for these values of H0 and beta, and although there is covariance between the two parameters, our results clearly point toward low-density cosmologies. Thus, the unresolved discrepancy between the "velocity-velocity" and "density-density" measurements of beta continues.     

The inhibition of marine nitrification by ocean disposal of carbon dioxide

In an attempt to reduce the threat of global warming, it has been proposed that the rise of atmospheric carbon dioxide concentrations be reduced by the ocean disposal of CO2 from the flue gases of fossil fuel-fired power plants. The release of large amounts of CO2 into mid or deep ocean waters will result in large plumes of acidified seawater with pH values ranging from 6 to 8. In an effort to determine whether these CO2-induced pH changes have any effect on marine nitrification processes, surficial (euphotic zone) and deep (aphotic zone) seawater samples were sparged with CO2 for varying time durations to achieve a specified pH reduction, and the rate of microbial ammonia oxidation was measured spectrophotometrically as a function of pH using an inhibitor technique. For both seawater samples taken from either the euphotic or aphotic zone, the nitrification rates dropped drastically with decreasing pH. Relative to nitrification rates in the original seawater at pH 8, nitrification rates were reduced by ca. 50% at pH 7 and more than 90% at pH 6.5. Nitrification was essentially completely inhibited at pH 6. These findings suggest that the disposal of CO2 into mid or deep oceans will most likely result in a drastic reduction of ammonia oxidation rates within the pH plume and the concomitant accumulation of ammonia instead of nitrate. It is unlikely that ammonia will reach the high concentration levels at which marine aquatic organisms are known to be negatively affected. However, if the ammonia-rich seawater from inside the pH plume is upwelled into the euphotic zone, it is likely that changes in phytoplankton abundance and community structure will occur. Finally, the large-scale inhibition of nitrification and the subsequent reduction of nitrite and nitrate concentrations could also result in a decrease of denitrification rates which, in turn, could lead to the buildup of nitrogen and unpredictable eutrophication phenomena. Clearly, more research on the environmental effects of ocean disposal of CO2 is needed to determine whether the potential costs related to marine ecosystem disturbance and disruption can be justified in terms of the perceived benefits that may be achieved by temporarily delaying global warming.     

A hybrid artificial neural network-numerical model for ground water problems

Numerical models constitute the most advanced physical-based methods for modeling complex ground water systems. Spatial and/or temporal variability of aquifer parameters, boundary conditions, and initial conditions (for transient simulations) can be assigned across the numerical model domain. While this constitutes a powerful modeling advantage, it also presents the formidable challenge of overcoming parameter uncertainty, which, to date, has not been satisfactorily resolved, inevitably producing model prediction errors. In previous research, artificial neural networks (ANNs), developed with more accessible field data, have achieved excellent predictive accuracy over discrete stress periods at site-specific field locations in complex ground water systems. In an effort to combine the relative advantages of numerical models and ANNs, a new modeling paradigm is presented. The ANN models generate accurate predictions for a limited number of field locations. Appending them to a numerical model produces an overdetermined system of equations, which can be solved using a variety of mathematical techniques, potentially yielding more accurate numerical predictions. Mathematical theory and a simple two-dimensional example are presented to overview relevant mathematical and modeling issues. Two of the three methods for solving the overdetermined system achieved an overall improvement in numerical model accuracy for various levels of synthetic ANN errors using relatively few constrained head values (i.e., cells), which, while demonstrating promise, requires further research. This hybrid approach is not limited to ANN technology; it can be used with other approaches for improving numerical model predictions, such as regression or support vector machines (SVMs).     

Water quality and presence of pesticides in a tropical coastal wetland in southern Mexico

The water quality of the Pozuelos-Murillo lagoon system in southern Mexico was evaluated during three periods between March and October 2002, with particular emphasis on the detection of organochlorine and organophosphorous pesticide residues in water and sediments. Physicochemical and microbiological parameters of water were also measured and integrated in a water quality index (WQI). Multivariate analysis was used to regionalise the lagoon system as a function of the behaviour of all measured parameters. Solid phase micro-extraction followed by gas chromatography (SPME-GC) was used for pesticide analysis. The concentration of phosphorous was found to be higher than that of nitrogenous compounds. This, besides a deficiency in dissolved oxygen and a high organic matter concentration (as COD), reflects eutrophication processes in some areas of the system. Measured levels of faecal coliforms and oils and greases were above the limits established by Mexican law and comparable to the concentrations reported for other highly polluted systems in Mexico. Residues of DDD (2.0 microg L(-1)) in water and DDE (247 ng g(-1)) and endosulfan I (814 ng g(-1)) sediments were detected by SPME-GC. The spatial distribution of these contaminants implies major potential risks because the most polluted sites were found to be those with the highest fishing activity. Although in general the WQI is on acceptable levels (65-80%), some contamination problems are evident.     

The synergistic powers of AEM and GIS geodatabase models in water resources studies

Comprehensive studies of water resources systems require integration of modeling tools and data associated with individual processes. An object-oriented approach is presented here that associates ground water models based upon the analytic element method (AEM) with geographic information system (GIS) geodatabase features using an AEM Model Interface. Each aquifer object contains a prescribed geometry, a mathematical representation in the AEM, and GIS hydrogeologic data. The synergistic understanding inherent in such an approach is illustrated by a study linking local AEM model predictions of water elevation with ground water geodatabase objects. This AEM Model Interface provides a key component in establishing a common object-oriented geodatabase modeling approach linking ground water to a variety of natural and social processes.     

Transition probability/Markov chain analyses of DNAPL source zones and plumes

At sites where a dense nonaqueous phase liquid (DNAPL) was spilled or released into the subsurface, estimates of the mass of DNAPL contained in the subsurface from core or monitoring well data, either in the nonaqueous or aqueous phase, can be highly uncertain because of the erratic distribution of the DNAPL due to geologic heterogeneity. In this paper, a multiphase compositional model is applied to simulate, in detail, the DNAPL saturations and aqueous-phase plume migration in a highly characterized, heterogeneous glaciofluvial aquifer, the permeability and porosity data of which were collected by researchers at the University of Tübingen, Germany. The DNAPL saturation distribution and the aqueous-phase contaminant mole fractions are then reconstructed by sampling the data from the forward simulation results using two alternate approaches, each with different degrees of sampling conditioning. To reconstruct the DNAPL source zone architecture, the aqueous-phase plume configuration, and the contaminant mass in each phase, one method employs the novel transition probability/Markov chain approach (TP/MC), while the other involves a traditional variogram analysis of the sampled data followed by ordinary kriging. The TP/MC method is typically used for facies and/or hydraulic conductivity reconstruction, but here we explore the applicability of the TP/MC method for the reconstruction of DNAPL source zones and aqueous-phase plumes. The reconstructed geometry of the DNAPL source zone, the dissolved contaminant plume, and the estimated mass in each phase are compared using the two different geostatistical modeling approaches and for various degrees of data sampling from the results of the forward simulation. It is demonstrated that the TP/MC modeling technique is robust and accurate and is a preferable alternative compared to ordinary kriging for the reconstruction of DNAPL saturation patterns and dissolved-phase contaminant plumes.     

Electrical resistance sensors record spring flow timing, Grand Canyon, Arizona

Springs along the south rim of the Grand Canyon, Arizona, are important ecological and cultural resources in Grand Canyon National Park and are discharge points for regional and local aquifers of the Coconino Plateau. This study evaluated the applicability of electrical resistance (ER) sensors for measuring diffuse, low-stage (<1.0 cm) intermittent and ephemeral flow in the steep, rocky spring-fed tributaries of the south rim. ER sensors were used to conduct a baseline survey of spring flow timing at eight sites in three spring-fed tributaries in Grand Canyon. Sensors were attached to a nearly vertical rock wall at a spring outlet and were installed in alluvial and bedrock channels. Spring flow timing data inferred by the ER sensors were consistent with observations during site visits, with flow events recorded with collocated streamflow gauging stations and with local precipitation gauges. ER sensors were able to distinguish the presence of flow along nearly vertical rock surfaces with flow depths between 0.3 and 1.0 cm. Laboratory experiments confirmed the ability of the sensors to monitor the timing of diffuse flow on impervious surfaces. A comparison of flow patterns along the stream reaches and at springs identified the timing and location of perennial and intermittent flow, and periods of increased evapotranspiration.