The role of self‐regulation in the relationship between abusive supervision and job tension

Trait and state self‐regulation both have critical influences on workplace behavior, but their influences are thought to operate quite differently. We draw from social exchange and ego depletion theories to investigate the relationship between trait and state self‐regulation, as well as how they differentially affect the relationship between subordinates' perceptions of abusive supervision and job tension. Specifically, we examine (a) how the interaction between abusive supervision and trait self‐regulation affects job tension and (b) how state self‐regulation mediates the relationship between abusive supervision and job tension. Using 3 studies that include an experiment (n = 81) and 2 field studies with cross‐sectional (n = 157) and time‐separated (n = 109) data, we demonstrate that the interaction between abusive supervision and trait self‐regulation increases experienced job tension for subordinates who report higher levels of abusive supervision and trait self‐regulation than others. Also, we provide evidence that abusive supervision is indirectly associated with job tension through state self‐regulation. This study's findings have important implications for abusive supervision and self‐regulation research, as well as social exchange and ego depletion theories, because we extend our understanding of how trait and state self‐regulation affect cognitive responses associated with abusive supervision.     

Cropland patchiness strongest agricultural predictor of bird diversity for multiple guilds in landscapes of Ontario,Canada

The potential for agricultural landscapes to support biodiversity may vary greatly based on agricultural land use. Current knowledge suggests that agricultural composition and intensity are dominant drivers of biodiversity in agricultural landscapes, with variable effects of agricultural configuration and landscape diversity. The aim of this study was to determine the relative effects of agricultural composition, intensity, configuration, and landscape diversity on the species diversity of six distinct bird guilds on the landscape scale in a large and complex landscape in Ontario, Canada. We found that agricultural configuration, specifically patchiness of croplands, and to a lesser degree forage lands, was the strongest predictor of bird diversity for three of the six bird guilds considered (forest, shrubland, and town). The effects of increased cropland patchiness were variable, with forest and shrubland bird diversity increasing from small to moderate patchiness, and town bird diversity declining from moderate to high patchiness. Grassland birds, a group of considerable conservation concern, increased near linearly with increased agricultural land cover in the landscape, highlighting the need to consider agricultural lands in conservation planning for this species group. Woodland bird diversity declined significantly with all increasing measures of agricultural intensity, including the proportion of high-intensity agriculture and larger patches of agricultural land. Wetland birds were unique from the other guilds, showing primarily a strong association between diversity of land cover types and guild-level bird diversity. Surprisingly, increased cover of agricultural lands, which we predicted to be a dominant driver of guild-level bird diversity declines due to habitat loss, had weak, non-significant effects relative to the other land use variable being tested, except for the positive association with grassland birds. Our findings suggest that a mix of management strategies should be employed to consider the varying effects of agricultural lands on different bird guilds, such as the inclusion of agricultural land in conservation strategies for grassland species and further managing the configuration of agricultural lands to enhance biodiversity of agricultural landscapes.     

CO2 transportation for carbon capture and storage: Sublimation of carbon dioxide from a dry ice bank

Climate change is being caused by greenhouse gases such as carbon dioxide (CO₂). Carbon capture and storage (CCS) is of interest to the scientific community as one way of achieving significant global reductions of atmospheric CO₂ emissions in the medium term. CO₂ would be captured from large stationary sources such as power plants and transported via pipelines under high pressure conditions to underground storage. If a downward leakage from a surface transportation system module occurs, the CO₂ would undergo a large temperature reduction and form a bank of “dry ice” on the ground surface; the sublimation of the gas from this bank represents an area source term for subsequent atmospheric dispersion, with an emission rate dependent on the energy balance at the bank surface. Gaseous CO₂ is denser than air and tends to remain close to the surface; it is an asphyxiant, a cerebral vasodilator and at high concentrations causes rapid circulatory insufficiency leading to coma and death. Hence a subliming bank of dry ice represents safety hazard. A model is presented for evaluating the energy balance and sublimation rate at the surface of a solid frozen CO₂ bank under different environmental conditions. The results suggest that subliming gas behaves as a proper dense gas (i.e. it remains close to the ground surface) only for low ambient wind speeds.     

Climatology and forecast modeling of ambient carbon monoxide in Phoenix, Arizona

We perform a climatology of factors influencing ambient carbon monoxide (CO), in which we examine the relationships between meteorology, traffic patterns, and CO at seasonal, weekly, and diurnal time scales in Phoenix, Arizona. From this analysis we identify a range of potentially important variables for statistical CO modeling. Using stepwise multivariate regression, we create a suite of models for hourly and 8-h ambient CO designed for daily operational forecasting purposes. The resulting models include variables and interaction terms related to anticipated nocturnal atmospheric stability as well as antecedent and climatological CO behavior. The models are evaluated using a range of error statistics and skill measures. The most successful approach employs a two-stage modeling strategy in which an initial prediction is made that may, depending on the forecast value, be followed by a second prediction that improves upon the first. The best models provide accurate daily forecasts of CO, with explained variances approaching 0.9 and errors under 1 ppm.     

The Impact of Climate Change on Mammal Diversity in Canada

Current large-scale mammalian diversity patterns in Canada can be accurately explained using various measurements of heat energy. Unfortunately, climatic change is predicted to alter the fundamental climatic basis for contemporary diversity gradients, with the expected consequence that much of the Canadian biota will need to migrate in order to remain within climatically suitable regions. We make predictions regarding future mammal diversity patterns in Canada, and therefore provide a preliminary indication of where management intervention should be directed in order to conserve mammal diversity as climate changes. We also examine the current distributions of individual mammal species in Canada in order to determine which taxa cannot migrate farther north because of the Arctic Ocean barrier. Of the 25 species that fall into this category, we examine the predicted loss of habitat in one keystone species – Dicrostonyx groenlandicus, the collared lemming – and find that this taxon is likely to lose approximately 60% of its habitat with unpredictable but likely detrimental consequences for the arctic biota. We discuss the implications of our findings briefly.     

Belief Networks: A Framework for the Participatory Development of Natural Resource Management Strategies

Successful long-term management of natural resources requires the development of strategies which recognise the constraints pertaining to the environmental system and can therefore be realistically expected to work. This paper presents a new technique for strategy formulation using belief networks, a framework based on Bayesian probability calculus that supports the investigation of complex environmental systems by the user and analysis of all constraints. While mathematical in nature, belief networks are superficially simple and allow concepts to be expressed in terms with which a wide range of user will be familiar. This offers a participatory approach to the development of management strategies through consideration of the impact of potential management options with consequent benefits for strategy implementation.     

Promising synergies to address water, sequestration, legal, and public acceptance issues associated with large-scale implementation of CO2 sequestration

Stabilization of CO₂ atmospheric concentrations requires practical strategies to address the challenges posed by the continued use of coal for baseload-electricity production. Over the next two decades, CO₂ capture and sequestration (CCS) demonstration projects would need to increase several orders of magnitude across the globe in both size and scale. This task has several potential barriers which will have to be accounted for. These barriers include those that have been known for a number of years including safety of subsurface sequestration, pore-space competition with emerging activities like shale gas production, legal and regulatory frameworks, and public acceptance and technical communication. In addition water management is a new challenge that should be actively and carefully considered across all CCS operations. A review of the new insights gained on these previously and newly identified challenges, since the IPCC special report on CCS, is presented in this paper. While somewhat daunting in scope, some of these challenges can be addressed more easily by recognizing the potential advantageous synergies that can be exploited when these challenges are dealt with in combination. For example, active management of water resources, including brine in deep subsurface formations, can provide the additional cooling-water required by the CO₂ capture retrofitting process while simultaneously reducing sequestration leakage risk and furthering efforts toward public acceptance. This comprehensive assessment indicates that water, sequestration, legal, and public acceptance challenges ought to be researched individually, but must also be examined collectively to exploit the promising synergies identified herein. Exploitation of these synergies provides the best possibilities for successful large-scale implementation of CCS.