Assessing the status and trend of bat populations across broad geographic regions with dynamic distribution models

Bats face unprecedented threats from habitat loss, climate change, disease, and wind power development, and populations of many species are in decline. A better ability to quantify bat population status and trend is urgently needed in order to develop effective conservation strategies. We used a Bayesian autoregressive approach to develop dynamic distribution models for Myotis lucifugus, the little brown bat, across a large portion of northwestern USA, using a four-year detection history matrix obtained from a regional monitoring program. This widespread and abundant species has experienced precipitous local population declines in northeastern USA resulting from the novel disease white-nose syndrome, and is facing likely range-wide declines. Our models were temporally dynamic and accounted for imperfect detection. Drawing on species-energy theory, we included measures of net primary productivity (NPP) and forest cover in models, predicting that M. lucifugus occurrence probabilities would covary positively along those gradients. Despite its common status, M. lucifugus was only detected during -50% of the surveys in occupied sample units. The overall naive estimate for the proportion of the study region occupied by the species was 0.69, but after accounting for imperfect detection, this increased to -0.90. Our models provide evidence of an association between NPP and forest cover and M. lucifugus distribution, with implications for the projected effects of accelerated climate change in the region, which include net aridification as snowpack and stream flows decline. Annual turnover, the probability that an occupied sample unit was a newly occupied one, was estimated to be low (-0.04-0.14), resulting in flat trend estimated with relatively high precision (SD = 0.04). We mapped the variation in predicted occurrence probabilities and corresponding prediction uncertainty along the productivity gradient. Our results provide a much needed baseline against which future anticipated declines in M. lucifugus occurrence can be measured. The dynamic distribution modeling approach has broad applicability to regional bat monitoring efforts now underway in several countries and we suggest ways to improve and expand our grid-based monitoring program to gain robust insights into bat population status and trend across large portions of North America.     

Climate change and the cost of conserving species in Madagascar

We examined the cost of conserving species as climate changes. We used a Maxent species distribution model to predict the ranges from 2000 to 2080 of 74 plant species endemic to the forests of Madagascar under 3 climate scenarios. We set a conservation target of achieving 10,000 ha of forest cover for each species and calculated the cost of achieving this target under each scenario. We interviewed managers of projects to restore native forests and conducted a literature review to obtain the net present cost per hectare of management actions to maintain or establish forest cover. For each species, we added hectares of land from lowest to highest cost per additional year of forest cover until the conservation target was achieved throughout the time period. Climate change was predicted to reduce the size of species' ranges, the overlap between species' ranges and existing or planned protected areas, and the overlap between species' ranges and existing forest. As a result, climate change increased the cost of achieving the conservation target by necessitating successively more costly management actions: additional management within existing protected areas (US$0-60/ha); avoidance of forest degradation (i.e., loss of biomass) in community-managed areas ($160-576/ha); avoidance of deforestation in unprotected areas ($252-1069/ha); and establishment of forest on nonforested land within protected areas ($802-2710/ha), in community-managed areas ($962-3226/ha), and in unprotected areas ($1054-3719/ha). Our results suggest that although forest restoration may be required for the conservation of some species as climate changes, it is more cost-effective to maintain existing forest wherever possible.     

Regeneration of used sand with sodium silicate binder by wet method and their core manufacturing

Journal of Material Cycles and Waste Management - Organic binders that are used in sand casting emit high amounts of hazardous pollutants and volatile organic compounds during the casting process....     

Tertiary recycling of plastics waste: an analysis of feedstock,chemical and biological degradation methods

Journal of Material Cycles and Waste Management - Globally, there is rising awareness of the severity of the plastic waste problem, and the implications of plastics accumulation in the environment....     

Recovery of Pd as PdO from Pd/SiO2 catalyst by leaching using hydrochloric acid

Journal of Material Cycles and Waste Management - The recovery of Pd from spent catalysts has been gaining attention due to its high economic value and limited availability in nature. To recover...     

Safety management in a relationship-oriented culture

A relationship-oriented culture predominates in the Greater China region, where it is more important than in Western countries. Some characteristics of this culture influence strongly the organizational structure and interactions among members in an organization. This study aimed to explore the possible influence of relationships on safety management in relationship-oriented cultures. We hypothesized that organizational factors (management involvement and harmonious relationships) within a relationship-oriented culture would influence supervisory work (ongoing monitoring and task instructions), the reporting system (selective reporting), and teamwork (team communication and co-ordination) in safety management at a group level, which would in turn influence individual reliance complacency, risk awareness, and practices. We distributed a safety climate questionnaire to the employees of Taiwanese high-risk industries. The results of structural equation modeling supported the hypothesis. This article also discusses the findings and implications for safety improvement in countries with a relationship-oriented culture.     

Uncertainty in epidemiology and health risk and impact assessment

Environmental epidemiology and health risk and impact assessment have long grappled with problems of uncertainty in data and their relationships. These uncertainties have become more challenging because of the complex, systemic nature of many of the risks. A clear framework defining and quantifying uncertainty is needed. Three dimensions characterise uncertainty: its nature, its location and its level. In terms of its nature, uncertainty can be both intrinsic and extrinsic. The former reflects the effects of complexity, sparseness and nonlinearity; the latter arises through inadequacies in available observational data, measurement methods, sampling regimes and models. Uncertainty occurs in three locations: conceptualising the problem, analysis and communicating the results. Most attention has been devoted to characterising and quantifying the analysis—a wide range of statistical methods has been developed to estimate analytical uncertainties and model their propagation through the analysis. In complex systemic risks, larger uncertainties may be associated with conceptualisation of the problem and communication of the analytical results, both of which depend on the perspective and viewpoint of the observer. These imply using more participatory approaches to investigation, and more qualitative measures of uncertainty, not only to define uncertainty more inclusively and completely, but also to help those involved better understand the nature of the uncertainties and their practical implications.     

Numerical and field investigation of enhanced in situ denitrification in a shallow-zone well-to-well recirculation system

This study investigated efficiency of in situ enhanced biological denitrification of nitrate-contaminated groundwater which employs a well-to-well circulation in a shallow zone where oxygen might give an adverse affect on the denitrification processes. The numerical model developed for the efficiency test included sequential aerobic and nitrate-based respiration, multi-Monod kinetics of reactive components, growth and decay of biomass, and denitrification inhibition associated with the presence of oxygen. Moreover, reaction kinetics for production of toxic intermediates such as nitrite and nitrous oxide were also included in the model. The developed model was applied to the analysis of enhanced in situ denitrification using an injection/extraction well pair. To evaluate the relative remediation effectiveness, comparisons were made between a continuous fumarate injection test (CFIT) system and a pulsed fumarate injection test (PFIT) system, where both systems had the same total fumarate mass injected into the aquifer. The PFIT system was preferable to the CFIT system because of the high possibility of occurrence of clogging in the latter case at the injection well, with no other significant advantages found in either the CFIT or the PFIT system. Accordingly, this developed numerical model is useful to predict and evaluate an in situ bioremediation by denitrification in aquifers.     

Performance evaluation of NOAA-EPA developmental aerosol forecasts

To aid air quality model development and assess air quality forecasts, the Meteorological Development Laboratory (MDL) provided categorical verification metrics for developmental aerosol predictions. The National Air Quality Forecasting Capability (NAQFC) generated 48 h (of) gridded hourly developmental predictions for the lower 48 states (CONUS) domain in 12 km horizontal spacing. The NAQFC uses the North American Mesoscale (NAM) model with EPA’s Community Multiscale Air Quality (CMAQ) model to produce predictions of ground level aerosol concentrations. We used bilinear interpolation to calculate predicted daily maximum values at the location of the observation sites. We compared these interpolated predicted values to the observed daily maximum to produce 2 × 2 contingency tables, with a threshold of 40 μg/m³ during the months of March–August, 2007. The model showed some degree of skill in predicting aerosol exceedances. These results are preliminary as the NAQFC model for aerosol prediction is in the developmental stage. A more comprehensive performance evaluation will be accomplished in 2008, when more data become available. Our verification metrics included categorical analyses for Fraction Correct (FC) or percent correct (FC × 100), Threat Score (TS) or Critical Success Index (CSI), Probability of Detection (POD), and the False Alarm Rate (FAR), Mean Absolute Error (MAE) and mean algebraic error or bias, where bias is forecast minus observation. Graphic products included weekly statistics for the CONUS displayed in the form of bar charts, scatterplots, and graphs. In addition, we split the CONUS into six geographic regions and provided regional statistics on a monthly basis. MDL produced spatial maps of daily 1-h maximum predicted aerosol values overlaid with the corresponding point observations. MDL also provided spatial maps of the daily maximum of the 24-h running average. We derived the 24-h running average from the 1-h average predicted aerosol values and observations.