Environmental Dependency of Inbreeding Depression: Implications for Conservation Biology

Inbreeding depression is environmentally dependent, such that a population may suffer from inbreeding depression in one environment but not another. We examined the phenotypic responses of 35 inbred ( F = 0.672) lineages of the red flour beetle Tribolium castaneum in two different climatic environments. We found a significant environmental effect on males but not females. More important, we found that the rank fitness order of lineages differs between environments; lineages of high fitness in one environment may have low fitness in another environment. This change in rank is evident in a significant genotype-by-environment interaction for inbreeding depression for both females and males. These results suggest that even if we know the average environmental effect of inbreeding depression in a population, for any particular lineage measurements of inbreeding depression in one environment may not predict the level of inbreeding depression in another environment. Conservation biologists need to be aware of the environmental dependency of inbreeding depression when planning wildlife refuges or captive propagation programs for small populations. Ideally, captive propagation programs should maintain separate lineages for release efforts. Refuge design programs should consider maintaining a range of habitat types.     

Changes in Extractable Metal Concentrations During Storage of Surface Water Samples Containing Sediments1

ABSTRACT: Changes in metal concentrations during storage of acidified water samples were studied. Water samples with high concentrations of suspended sediment were collected from the Fraser River, British Columbia. These samples were analyzed for “extractable” metals, which are defined to be the dissolved metals plus those metals extracted from suspended sediment by dilute mineral acid. Concentrations of extractable Cu, Fe, Pb, Zn, Ni, Co, Mn, and Cd were determined over time. Metal concentrations in these water samples were not stable and showed significant increases throughout the storage period. These results suggest that the extractable metal technique is inappropriate for the analysis of water samples containing suspended sediment.     

A High Performance Liquid Chromatographic Determination of Free Amino Acids in Natural Waters in the Picomolar (M X 10-12) Range Suitable for Shipboard Use

A reliable method for the determination of amino acids, suitable for routine shipboard use, is presented. Using reverse-phase high-performance liquid chromatography with computer-controlled gradient elution optimization, the amino acids commonly found in sea-water were clearly resolved and determined at the picomole level. A procedure was also developed to enable repeat injections of sea water samples to be made without deterioration of column material or performance. Thus the analysis was made more operator-independent and consequently more suitable for use at sea.     

UV light induces Ag nanoparticle formation: roles of natural organic matter,iron, and oxygen

Nanoparticles occurring in the environment originate either from engineered, synthetically produced nanoparticles, or from naturally produced nanoparticles. The latter can be formed in natural media by light-induced reduction of metal ions in presence of natural organic matter, such as humic substances occurring widely in waters, soils and sediments. There is actually few knowledge on the effect of sunlight and of the nature of organic matter on nanoparticle formation. Therefore, we studied here the photoreduction of silver(I) ion to silver nanoparticles with and without ferrous ion under oxic and anoxic conditions, using humic and fulvic acids as proxies of natural organic matter. UV light-induced formation of silver nanoparticles was monitored up to 60 min by measuring surface plasmon resonance in air-saturated mixture and nitrogen-saturated mixture of silver(I) ion–organic matter. Results show that the surface plasmon resonance intensity was about 2.5 times higher in the nitrogen-purged solution mixture than the air-saturated solution. This finding suggests the oxygen-containing species had no major role in forming silver nanoparticles. Therefore, photo-driven formation of silver nanoparticles most likely involved photoactivation of silver(I) ion and natural organic matter complexes. We observed also that both iron(II) and iron(III) ions highly modified the surface plasmon resonance spectra of the particles with broader features. Results also reveal that in the presence of humic acid, the intensity of the surface plasmon resonance peak decreased by at least 50 %, while almost no change in the intensity was seen when fulvic acid was used. Overall, our findings demonstrate that the ligand–metal charge transfer process, affected by the nature of organic matter, i.e., humic acid versus fulvic acid, was influenced by redox iron species.     

Validation and use of in vivo solid phase micro-extraction (SPME) for the detection of emerging contaminants in fish

A variety of emerging chemicals of concern are released continuously to surface water through the municipal wastewater effluent discharges. The ability to rapidly determine bioaccumulation of these contaminants in exposed fish without sacrificing the animal (i.e. in vivo) would be of significant advantage to facilitate research, assessment and monitoring of their risk to the environment. In this study, an in vivo solid phase micro-extraction (SPME) approach was developed and applied to the measurement of a variety of emerging contaminants (carbamazepine, naproxen, diclofenac, gemfibrozil, bisphenol A, fluoxetine, ibuprofen and atrazine) in fish. Our results indicated in vivo SPME was a potential alternative extraction technique for quantitative determination of contaminants in lab exposures and as well after exposure to two municipal wastewater effluents (MWWE), with a major advantage over conventional techniques due to its ability to non-lethally sample tissues of living organisms.     

Diagnosis of dissolved organic matter removal by GAC treatment in biologically treated papermill effluents using advanced organic characterisation techniques

Granular activated carbon (GAC) exhaustion rates on pulp and paper effluent from South East Australia were found to be a factor of three higher (3.62 cf. 1.47 kg m⁻³) on Kraft mills compared to mills using Thermomechanical pulping supplemented by Recycled Fibre (TMP/RCF). Biological waste treatment at both mills resulted in a final effluent COD of 240 mg L⁻¹. The dissolved organic carbon (DOC) was only 1.2 times higher in the Kraft effluent (70 vs. 58 mg L⁻¹), however, GAC treatment of Kraft and TMP/RCF effluent was largely different on the DOC persisted after biological treatment. The molecular mass (636 vs. 534 g mol⁻¹) and aromaticity (5.35 vs. 4.67 L mg⁻¹ m⁻¹) of humic substances (HS) were slightly higher in the Kraft effluent. The HS aromaticity was decreased by a factor of 1.0 L mg⁻¹ m⁻¹ in both Kraft and TMP/RCF effluent. The molecular mass of the Kraft effluent increased by 50 g mol⁻¹ while the molecular mass of the TMP/RCF effluent was essentially unchanged after GAC treatment; the DOC removal efficiency of the GAC on Kraft effluent was biased towards the low molecular weight humic compounds. The rapid adsorption of this fraction, coupled with the slightly higher aromaticity of the humic components resulted in early breakthrough on the Kraft effluent. Fluorescence excitation-emission matrix analysis of the each GAC treated effluent indicated that the refractory components were higher molecular weight humics on the Kraft effluent and protein-like compounds on the TMP/RCF effluent. Although the GAC exhaustion rates are too high for an effective DOC removal option for biologically treated pulp and paper mill effluents, the study indicates that advanced organic characterisation techniques can be used to diagnose GAC performance on complex effluents with comparable bulk DOC and COD loads.     

Prediction of Traffic Noise: A Screening Technique

Abstract

Traffic noise is ubiquitous in many communities and is an important environmental concern, especially for persons located near major roadways. Several different methods are available to estimate noise levels resulting from roadway traffic. These include computational, graphical, and computer modeling techniques.

The prediction methodology presented here is a simplified technique that can be used for estimating noise resulting from traffic and for screening traffic noise impacts. This Traffic Noise Screening (TNS) approach consists of a series of traffic noise level prediction graphs developed for different roadway configurations. The graphs are based on the results from using the Federal Highway Administration (FHWA) STAMINA2.0 computerized noise prediction model for various scenarios. Data inputs to the TNS approach include roadway geometries, traffic volumes, vehicle travel speed, and centerline distance to the receptors.

The TNS graphs allow easy estimation of traffic noise levels for use in predicting traffic-related noise impacts. This TNS approach is not intended as a substitute for detailed modeling, such as with STAMINA2.0, but as a screening tool to aid in determining when detailed modeling may be necessary. If screening results indicate that noise estimates are significant, or if the scenario is rather complex, then additional, more detailed modeling can be performed.     

A Comparison of Nonlinear Regression and Neural Network Models for Ground-Level Ozone Forecasting

ABSTRACT

A hybrid nonlinear regression (NLR) model and a neural network (NN) model, each designed to forecast next-day maximum 1-hr average ground-level O₃ concentrations in Louisville, KY, were compared for two O₃ seasons—1998 and 1999. The model predictions were compared for the forecast mode, using forecasted meteorological data as input, and for the hindcast mode, using observed meteorological data as input. The two models performed nearly the same in the forecast mode. For the two seasons combined, the mean absolute forecast error was 12.5 ppb for the NLR model and 12.3 ppb for the NN model. The detection rate of 120 ppb threshold exceedances was 42% for each model in the forecast mode. In the hindcast mode, the NLR model performed marginally better than the NN     

The Development of a Charging/Collecting Device for High Resistivity Dust Using Cooled Electrodes

A charging/collecting device for high-resistivity fly ash has been developed which controls back ionization by cooling the collector electrode internally with water. The device consists of parallel 6.0 cm pipes with corona wires suspended between the pipes. The pipes provide a simple means of interfacing with a cooling water system and also minimizing the collector area needing to be cooled. By cooling the pipes with 38°C (100°F) water, back ionization is eliminated and average field strengths of 7 kV/cm can be achieved with fly ash having a resistivity > 10¹² ω-cm. Results of tests on an actual flue gas stream and plans for future testing are described. Initial tests using heated instead of cooled electrodes are described as well as other tests that lead to the present design. The results of tests with the heated electrode show the kind of improvements in performance that can be obtained when resistivity is controlled in only a small collection area.