A Sensitivity Analysis of an Integrated Modelling Approach to Assess the Risk of Wind-borne Spread of Foot-and-mouth Disease Virus from Infected Premises

The sensitivity of an integrated model to assess the potential for wind-borne spread of foot-and-mouth disease (FMD) to variations in key parameters controlling different physical and biological processes was evaluated. The estimated number of farms at risk is sensitive to the virus strain used and the accompanying effective contact rate. The C Noville strain increased the estimated number of exposed farms ranked as high and medium risk of being infected by a factor of 5, compared to the baseline, based on the O UKG 2001 strain. The inclusion of a model for biological ageing of the virus can also have a significant effect on the concentration patterns arising from transport and dispersion of the virus. Its inclusion has the practical advantage of markedly reducing the time required for the calculations. The estimated number of farms affected by exposure to high and medium virus concentrations is not grossly sensitive to attenuation caused by temperature or relative humidity effects. Changes in susceptibility to infection, as determined by the parameter θ in the exposure-risk model, does not change the configuration of the virus plumes, but it does change the distribution of farms at risk by risk category. These findings suggest that a good understanding of characteristics (excretion rates from infected animals, susceptibility of different species to infection, virus survival, etc.) of the virus strain involved in an FMD outbreak is necessary to provide a reliable assessment of the risk of wind-borne spread. In the event of an incursion of FMD, provision for laboratory studies on the virus will be an essential component of the disease response and should be factored into contingency plans.

Using environmental heterogeneity to plan for sea‐level rise

Environmental heterogeneity is increasingly being used to select conservation areas that will provide for future biodiversity under a variety of climate scenarios. This approach, termed conserving nature's stage (CNS), assumes environmental features respond to climate change more slowly than biological communities, but will CNS be effective if the stage were to change as rapidly as the climate? We tested the effectiveness of using CNS to select sites in salt marshes for conservation in coastal Georgia (U.S.A.), where environmental features will change rapidly as sea level rises. We calculated species diversity based on distributions of 7 bird species with a variety of niches in Georgia salt marshes. Environmental heterogeneity was assessed across six landscape gradients (e.g., elevation, salinity, and patch area). We used 2 approaches to select sites with high environmental heterogeneity: site complementarity (environmental diversity [ED]) and local environmental heterogeneity (environmental richness [ER]). Sites selected based on ER predicted present‐day species diversity better than randomly selected sites (up to an 8.1% improvement), were resilient to areal loss from SLR (1.0% average areal loss by 2050 compared with 0.9% loss of randomly selected sites), and provided habitat to a threatened species (0.63 average occupancy compared with 0.6 average occupancy of randomly selected sites). Sites selected based on ED predicted species diversity no better or worse than random and were not resilient to SLR (2.9% average areal loss by 2050). Despite the discrepancy between the 2 approaches, CNS is a viable strategy for conservation site selection in salt marshes because the ER approach was successful. It has potential for application in other coastal areas where SLR will affect environmental features, but its performance may depend on the magnitude of geological changes caused by SLR. Our results indicate that conservation planners that had heretofore excluded low‐lying coasts from CNS planning could include coastal ecosystems in regional conservation strategies.     

Alternative carbon dioxide modelling approaches accounting for high residual gases in LandGEM

High Canadian waste disposal rates necessitate landfill gas monitoring and accurate forecasting. CO₂ estimates in LandGEM version 3.02 currently rest on the assumptions that CO₂ is a function of CH₄, where the two gases make up nearly 100% of landfill gas content, leading to overestimated CO₂ collection estimates. A total of 25 cases (five formulas, five approaches) compared annual CO₂ collection at four western Canadian landfills. Despite common use in literature, the 1:1 ratio of CH₄ to CO₂ was not recommended to forecast landfill gas collection in cold climates. The existing modelling approach significantly overestimated CO₂ production in three of four sites, resulting in the highest residual sum of squares. Optimization resulted in the most accurate results for all formulas and approaches, which had the greatest reduction in residual sums of squares (RSS) over the default approach (60.1 to 97.7%). The 1.4 Ratio approach for L _o:L _o-CO2 yielded the second most accurate results for CO₂ flow (mean RSS reduction of 50.2% for all sites and subsection models). The annual k-modified LandGEM calculated k’s via two empirical formulas (based on precipitation) and yielded the lowest accuracy in 12 of 20 approaches. Unlike other studies, strong relationships between optimized annual k’s and precipitation were not observed.

     

Supporting Diverse Data Providers in the Open Water Data Initiative: Communicating Water Data Quality and Fitness of Use

Shared, trusted, timely data are essential elements for the cooperation needed to optimize economic, ecologic, and public safety concerns related to water. The Open Water Data Initiative (OWDI) will provide a fully scalable platform that can support a wide variety of data from many diverse providers. Many of these will be larger, well‐established, and trusted agencies with a history of providing well‐documented, standardized, and archive‐ready products. However, some potential partners may be smaller, distributed, and relatively unknown or untested as data providers. The data these partners will provide are valuable and can be used to fill in many data gaps, but can also be variable in quality or supplied in nonstandardized formats. They may also reflect the smaller partners' variable budgets and missions, be intermittent, or of unknown provenance. A challenge for the OWDI will be to convey the quality and the contextual “fitness” of data from providers other than the most trusted brands. This article reviews past and current methods for documenting data quality. Three case studies are provided that describe processes and pathways for effective data‐sharing and publication initiatives. They also illustrate how partners may work together to find a metadata reporting threshold that encourages participation while maintaining high data integrity. And lastly, potential governance is proposed that may assist smaller partners with short‐ and long‐term participation in the OWDI.     

3D numerical investigation of thermally assisted high efficiency ductile machining of nanocrystalline hydroxyapatite

This study investigates the effects of four different variables (initial workpiece temperature, side rake angle, edge radius/feed rate, and nose radius/depth of cut) on ductile regime machining of a bioceramic material known as nanohydroxyapatite (nano-HAP) using 3D numerical simulation. AdvantEdge FEM Version 5.9 is used to conduct turning simulations of the nano-HAP workpiece. Tecplot 360 is used to analyze the results of the simulations. Because the workpiece is thin, the entire workpiece is set to a uniform initial temperature to simulate laser preheating of the material. Initial workpiece temperature, rake angle (side rake angle), edge radius, and nose radius are varied, and the effects of these operating conditions on critical feed are investigated. It is found that critical feed increases as initial workpiece temperature increases, and also as negativity of rake angle increases. For the edge radius, it is concluded that an initial increase causes an increase in critical feed – however, at some value of edge radius, critical feed shows no further increase; for the nose radius, critical feed appears to show no significant dependence.     

Nuptial coloration of red shiners (<Emphasis Type="Italic">Cyprinella lutrensis</Emphasis>) is more intense in turbid habitats

Communication is shaped and constrained by the signaling environment. In aquatic habitats, turbidity can reduce both the quantity and quality of ambient light and has been implicated in the breakdown of visual signaling. Here, we examined the relationship between turbidity (quantified with long-term data) and the expression of carotenoid-based nuptial coloration in the red shiner (Cyprinella lutrensis), a small-bodied cyprinid. Males in more turbid habitats displayed redder fins, and an experimental manipulation of adult diet suggested that carotenoid intake alone did not explain among-population color differences. These results run counter to similar studies where signal expression decreased in turbid conditions, and may be explained by the non-territorial red shiner mating system, interactions between the mechanism of coloration and the signaling environment, or reduced cost of color expression in turbid habitats (e.g., reduced predation risk). Our results highlight how the behavioral and ecological contexts in which signals function can shape evolutionary responses to the environment.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Remote sampling of a CO2 point source in an urban setting

High frequency CO₂ and wind speed measurements were used to examine the urban baseline eddy covariance CO₂ flux and analyse the CO₂ rich plume from a local power station. A reliable relationship between high frequency CO₂ maxima and the rate of CO₂ emission at the power station was established. This relationship was shown to be highly dependant on wind speed. The ensemble mean plume was found to be Gaussian in horizontal profile with a width dependant on wind speed. The relationship between peak CO₂ mixing ratio and averaging time was shown to be a simple power law with a time exponent of approximately 0.5. The large, short pulses in CO₂ mixing ratio in the power plant plume were found to have an approximately Lorentzian shape. These pulses generated negative vertical eddy flux measurements so data from the plume sector were necessarily excluded from the flux baseline results. The plume-excluded flux had a similar magnitude and variability to those reported in other urban CO₂ flux studies despite this site not being ideal due to the proximity of roughness elements to the measurement point.