Effects of Two Amphibian Pathogens on the Developmental Stability of Green Frogs

Abstract: Developmental instability, measured as fluctuating asymmetry (FA), is often used as a tool to measure stress and the overall quality of organisms. Under FA, it is assumed that control of symmetry during development is costly and that under stress the trajectory of development is disturbed, resulting in asymmetric morphologies. Amphibian emergent infectious diseases (EIDs), such as Ranavirus and chytrid fungus, have been involved in several mortality events, which makes them stressors and allows for the study of FA. We analyzed nine populations of green frogs (Rana clamitans) for the presence or absence of Ranavirus and chytrid fungus. Individuals were measured to determine levels of FA in seven traits under the hypothesis that FA is more likely to be observed in individuals infected by the pathogens. Significantly higher levels of FA were found in individuals with Ranavirus compared with uninfected individuals among all populations and all traits. We did not observe FA in individuals infected with chytrid fungus for any of the traits measured. Additionally, we observed a significant association between Ranavirus infection and levels of FA in both males and females, which may indicate this viral disease is likely to affect both sexes during development. Altogether, our results indicate that some EIDs may have far‐reaching and nonlethal effects on individual development and populations harboring such diseases and that FA can be used as a conservation tool to identify populations subject to such a stress.     

Exploring Environmental Data in a Highly Immersive Virtual Reality Environment

Geography inherently fills a 3D space and yet we struggle with displaying geography using, primarily, 2D display devices. Virtual environments offer a more realistically-dimensioned display space and this is being realized in the expanding area of research on 3D Geographic Information Systems (GISs). Traditionally, a GIS has only limited tools for statistical analysis, and 3D GIS research has concentrated on the visualization of the geographical terrain. Here we discuss linking multivariate statistical graphics to geography in the highly immersive C2 virtual reality environment at Iowa State University using mid-Atlantic streams data.     

Models predicting the fate of pollutants in rivers

The spill of 2,4,‐D in the Rhine river was used to show the evolution from simple to sophisticated models. The first simulation was done with an analytical solution of the dispersion‐advection equation without elimination. Elimination was introduced in a second simulation. The third simulation was carried out with a numerical model. This included elimination and variable dispersion. The lack of data limited the use of very detailed models.     

Note on In-Traffic Measurement of Airborne Tire-Wear Participate Debris

Measuring greenhouse gas (GHG) source emissions provides data for validation of GHG inventories, which provide the foundation for climate change mitigation. Two Toyota RAV4 electric vehicles were outfitted with high-precision instrumentation to determine spatial and temporal resolution of GHGs (e.g., nitrous oxide, methane [CH₄], and carbon dioxide [CO₂]), and other gaseous species and particulate metrics found near emission sources. Mobile measurement platform (MMP) analytical performance was determined over relevant measurement time scales. Pollutant residence times through the sampling configuration were measured, ranging from 3 to 11 sec, enabling proper time alignment for spatial measurement of each respective analyte. Linear response range for GHG analytes was assessed across expected mixing ratio ranges, showing minimal regression and standard error differences between 5, 10, 30, and 60 sec sampling intervals and negligible differences between the two MMPs. GHG instrument drift shows deviation of less than 0.8% over a 24-hr measurement period. These MMPs were utilized in tracer-dilution experiments at a California landfill and natural gas compressor station (NGCS) to quantify CH₄ emissions. Replicate landfill measurements during October 2009 yielded annual CH₄ emissions estimates of 0.10 ± 0.01, 0.11 ± 0.01, and 0.12 ± 0.02 million tonnes of CO₂ equivalent (MTCO₂E). These values compare favorably to California GHG Emissions Inventory figures for 2007, 2008, and 2009 of 0.123, 0.125, and 0.126 MTCO₂E/yr, respectively, for this facility. Measurements to quantify NGCS boosting facility-wide emissions, during June 2010 yielded an equivalent of 5400 ± 100 TCO₂E/yr under steady-state operation. However, measurements during condensate transfer without operational vapor recovery yield an instantaneous emission rate of 2–4 times greater, but was estimated to only add 12 TCO₂E/yr overall. This work displays the utility for mobile GHG measurements to validate existing measurement and modeling approaches, so emission inventory values can be confirmed and associated uncertainties reduced.

Implications:?Measuring greenhouse gas (GHG) source emissions provides data and validation for GHG inventories, the foundation for climate change mitigation. Mobile measurement platforms with robust analytical instrumentation completed tracer-dilution experiments in California at a landfill and natural gas compressor station (NGCS) to quantify CH₄ emissions. Data collected for landfill CH₄ agree with the current California emissions inventory, while NGCS data show the possible variability from this type of facility. This work displays the utility of mobile GHG measurements to validate existing measurement and modeling approaches, such that emission inventory values can be confirmed, associated uncertainties reduced, and mitigation efforts quantified.     

In Memoriam

ABSTRACT

A feasibility study of polychlorinated biphenyl (PCB) removal from contaminated soils using microwave-generated steam (MGS) was performed. Initial experimental results show that MGS effectively removed PCBs from contaminated soil with an overall removal efficiency of greater than 98% at a steam-to-soil mass ratio of 3:1. Removal efficiency was found to be dependent upon the amount of steam employed, expressed as a mass ratio of steam applied to soil mass. Evaporation was identified as a major mechanism in removing PCBs from the soil. Rapid expansion and evaporation of pore water by microwave dielectric heating accelerated evaporation rates of PCB molecules. Increased solubility of PCBs into the heated aqueous phase is also hypothesized. Together these effects increase mass-transfer rates, thus enhancing removal of PCBs from the soil.     

Phosphorus losses from grasslands fertilized with broiler litter: EPIC simulations

Broiler litter, a mixture of poultry excreta and bedding material, is commonly used to fertilize grasslands in the southeastern USA. Previous work has shown that under certain situations, application of broiler (Gallus gallus domesticus) litter to grasslands may lead to elevated levels of phosphorus (P) in surface runoff. The EPIC simulation model may be a useful tool to identify those situations. This work was conducted to evaluate EPIC's ability to simulate event and annual runoff volume and losses of dissolved reactive phosphorus (DRP) from tall fescue (Festuca arundinacea Schreb.)-bermudagrass [Cynodon dactylon (L.) Pers.] paddocks fertilized with broiler litter. The EPIC simulations of event runoff volume showed a trend toward underestimation, particularly for runoff events >30 mm. On an annual basis, EPIC also tended to underestimate runoff, especially at runoff volumes > 100 mm. Both event and annual runoff estimations were strongly associated with observed values, indicating that model calibration could improve the simulation of surface runoff volume. The relationship between simulated and observed values of DRP loss was relatively poor on an event basis (r=0.65), but was stronger (r=0.75) on an annual basis. In general, EPIC tended to underestimate annual DRP losses. This underestimation was apparently caused by the lack of an explicit mechanism to model broiler litter on the soil surface. These results suggested that additional work on the EPIC P submodel would be warranted to improve its simulation of surface application of broiler litter to grasslands.     

MODELING THE HYDROCHEMISTRY OF THE CANNONSVILLE WATERSHED WITH GENERALIZED WATERSHED LOADING FUNCTIONS (GWLF)1

ABSTRACT: A previous modeling study used the Generalized Watershed Loading Functions (GWLF) model to simulate stream‐flow, and nutrient and sediment loads to Cannonsville Reservoir from the West Branch Delaware River (WBDR). We made several model revisions, calibrated key parameters, and tested the original GWLF model and a revised GWLF model using more recent data. Model revisions included: addition of unsaturated leakage between unsaturated and saturated subsurface reservoirs; revised timing of sediment export; inclusion of urban sediments and dissolved nutrients; tracking of particulate nutrients from point sources; and revised timing of septic system loads. The revision of sediment yield timing resulted in significant improvements in monthly sediment and particulate phosphorus predictions as compared to the original model. Addition of unsaturated leakage improved hydrologic predictions during low flow months. The other model changes improve realism without adding significant model complexity or data requirements. Goodness of fit of revised model predictions versus stream measurements, as measured by the Nash‐Sutcliff coefficient of model efficiency, exceeded 0.8 for streamflow‐0.7 for sediment yield and dissolved nitrogen (N) and 0.6 for particulate and dissolved phosphorus (P). The revised GWLF model, with limited calibration, provides reasonable estimates of monthly streamflow, and nutrient and sediment loads in the Cannonsville watershed.     

Streamflow Responses to Climate Change: Analysis of Hydrologic Indicators in a New York City Water Supply Watershed

Recent works have indicated that climate change in the northeastern United States is already being observed in the form of shorter winters, higher annual average air temperature, and more frequent extreme heat and precipitation events. These changes could have profound effects on aquatic ecosystems, and the implications of such changes are less understood. The objective of this study was to examine how future changes in precipitation and temperature translate into changes in streamflow using a physically based semidistributed model, and subsequently how changes in streamflow could potentially impact stream ecology. Streamflow parameters were examined in a New York City water supply watershed for changes from model‐simulated baseline conditions to future climate scenarios (2081‐2100) for ecologically relevant factors of streamflow using the Indicators of Hydrologic Alterations tool. Results indicate that earlier snowmelt and reduced snowpack advance the timing and increase the magnitude of discharge in the winter and early spring (November‐March) and greatly decrease monthly streamflow later in the spring in April. Both the rise and fall rates of the hydrograph will increase resulting in increased flashiness and flow reversals primarily due to increased pulses during winter seasons. These shifts in timing of peak flows, changes in seasonal flow regimes, and changes in the magnitudes of low flow can all influence aquatic organisms and have the potential to impact stream ecology.