The hypoxia avoidance behaviour of juvenile Atlantic cod (<Emphasis Type="Italic">Gadus morhua</Emphasis> L.) depends on the provision and pressure level of an O<Subscript>2</Subscript> refuge

The frequency of low O₂ (hypoxia) has increased in coastal marine areas but how fish avoid deleterious water masses is not yet clear. To assess whether the presence and oxygen pressure (PO₂) level of an O₂ refuge affects the hypoxia avoidance behaviour of fish, individual Atlantic cod (Gadus morhua L.) were exposed to a range of O₂ choices in a 2-way choice chamber at 11.4°C over two different experiments. Cod in the first experiment were allowed access to a fixed O₂ refuge (fully air-saturated seawater) whilst oxygen pressure (PO₂) on the other side was reduced in steps to a critically low level, i.e. 4.3 kPa—a point where cod can no longer regulate O₂ consumption. Under these conditions, cod did not avoid any level of hypoxia and fish swimming speed also remained unchanged. In contrast, strong avoidance reactions were exhibited in a second experiment when fish were again exposed to 4.3 kPa but the safety, i.e. PO₂, of the refuge was reduced. Fish not only spent less time at 4.3 kPa as a result of fewer sampling visits but they also swam at considerably slower speeds. The presence of an avoidance response was thus strongly related to refuge PO₂ and it is unlikely that cod, and possibly other fish species, would enter low O₂ to feed in the wild if a sufficiently safe O₂ refuge was not available. It is therefore hypothesized that the feeding range of fish may be heavily compressed if hypoxia expands and intensifies in future years.     

On risk governance deficits

The International Risk Governance Council (IRGC) has recently presented a report comprising an analysis and illustration of the most common deficits in risk governance. The work covers issues related to both assessments and management of risk. In this paper we take a closer look into this report. We acknowledge the work as an important contribution to the risk governance field, how risk decision-makers and practitioners in government and industry can improve the risk governance, but we also point to some weaknesses in the analysis, which are critical for the understanding and use of the IRGC document. Most of these relate to the understanding of fundamental ideas and phenomena, in particular risk and uncertainty. The rationale for several defined deficits is questioned, including “missing, ignoring or exaggerating early signals of risk” and “failure of managers to respond and take action when risk assessors have determined from early signals that a risk is emerging”. Simple examples are used to illustrate the problems and show how they can be rectified.     

A new method for spatially moving correlation analysis in geomedicine

A method of correlation analysis within a spatially moving window was applied to two sets of epidemiological/geochemical data in Norway, (1) mortality/disability rates of multiple sclerosis (MS) versus atmospheric fallout of Mg and concentrations of Se in overbank sediment, and (2) incidence rates of malignant melanoma of the skin (MM) versus concentrations of Ca and K in overbank sediment. It appears that n = 17 observation sites within the moving window is a practical compromise between noise in the data at small values of n and a spatial resolution good enough to detect trends in the distribution patterns of the correlation coefficient. For MS versus Mg, MS versus Se and MM versus Ca the correlation coefficients are generally negative and depict systematic distribution patterns with anomalous clusters of sites with good correlation. For MS versus Se the correlation coefficients also form an additional cluster of positive coefficients. Tests with permutated data show that more than 70% of the negative correlation coefficients for MS versus Mg and for MM versus Ca are both significantly different from zero at p<0.05, while less than 15% of those for MS versus Se are significant at the same level. For MM versus K the correlation coefficients are randomly distributed and not significantly different from zero. The described correlations may be effects of confounders and do not per se indicate any causal relationships. However, further research based on these results may well lead to the identification of possible aetiological factors.     

In the mixed world of predictive biology—Contradiction or support

Statistical prediction is a tool and aim in ecology and wildlife management and conservation. A prediction may either be supported by or contradicted by observations of an unknown set of observations. A contradiction occurs if the prediction is not included within the range of the unknown observations, i.e. the prediction misses the cloud of observations completely. Mixed-effects models, frequently used for statistical assessment of clustered data, carry information needed for calculating the probability of such contradictions. Here we present a new versatile statistic, the probability of contradiction (P (Contra)), that describes how often we would anticipate a new cluster of observations contradicting our predictions. Some benefits of P (Contra) are: (1) easy to calculate and intuitive interpretation, (2) comparability between datasets, (3) inclusion of residual correlation, (4) summary of the multitude of information from mixed models into one statistics, and (5) applicable to local mixed-effect models.     

Industrial disasters: Extreme events,extremely rare. Some reflections on the treatment of uncertainties in the assessment of the associated risks

This paper addresses the issue of risk from disasters occurring due to accidents in high-consequence technologies, e.g., nuclear and oil and gas. The focus is on the challenges posed to the representation and treatment of uncertainties in the assessment of such risk, given that the occurrence of such extreme disasters is extremely unlikely, and yet they occur. A general framework of analysis is proposed.     

Transport impacts on atmosphere and climate: Land transport

Emissions from land transport, and from road transport in particular, have significant impacts on the atmosphere and on climate change. This assessment gives an overview of past, present and future emissions from land transport, of their impacts on the atmospheric composition and air quality, on human health and climate change and on options for mitigation.In the past vehicle exhaust emission control has successfully reduced emissions of nitrogen oxides, carbon monoxide, volatile organic compounds and particulate matter. This contributed to improved air quality and reduced health impacts in industrialised countries. In developing countries however, pollutant emissions have been growing strongly, adversely affecting many populations. In addition, ozone and particulate matter change the radiative balance and hence contribute to global warming on shorter time scales. Latest knowledge on the magnitude of land transport's impact on global warming is reviewed here.In the future, road transport's emissions of these pollutants are expected to stagnate and then decrease globally. This will then help to improve the air quality notably in developing countries. On the contrary, emissions of carbon dioxide and of halocarbons from mobile air conditioners have been globally increasing and are further expected to grow. Consequently, road transport's impact on climate is gaining in importance. The expected efficiency improvements of vehicles and the introduction of biofuels will not be sufficient to offset the expected strong growth in both, passenger and freight transportation. Technical measures could offer a significant reduction potential, but strong interventions would be needed as markets do not initiate the necessary changes. Further reductions would need a resolute expansion of low-carbon fuels, a tripling of vehicle fuel efficiency and a stagnation in absolute transport volumes. Land transport will remain a key sector in climate change mitigation during the next decades.     

The link between 'green' and economic success: environmental management as the crucial trigger between environmental and economic performance

The link between environmental and economic performance has been widely debated in the literature for the last ten to fifteen years. One view is that improved environmental performance mainly causes extra costs for the firm and thus reduces profitability. However, also the opposite has been argued for: improved environmental performance would induce cost savings and increase sales and thus improve economic performance. Theoretical and empirical research have provided arguments for both positions and have not been conclusive so far. This article discusses reasons for the different views and the differences in empirical research and presents a theoretical framework to explain the coexistence of the conflicting views. It is argued that not merely the level of environmental performance, but mainly the kind of environmental management with which a certain level is achieved, influences the economic outcome. The model presented provides implications for both empirical research and company management in practice. Research and business practice should focus less on general correlations and more on causal relationships of eco-efficiency, i.e. the effect of different environmental management approaches on economic performance.     

Climate and air quality-driven scenarios of ozone and aerosol precursor abatement

In addition to causing domestic and regional environmental effects, many air pollutants contribute to radiative forcing (RF) of the climate system. However, climate effects are not considered when cost-effective abatement targets for these pollutants are established, nor are they included in current international climate agreements. We construct air pollution abatement scenarios in 2030 which target cost-effective reductions in RF in the EU, USA, and China and compare these to abatement scenarios which instead target regional ozone effects and particulate matter concentrations. Our analysis covers emissions of PM (fine, black carbon and organic carbon), SO₂, NO_x, CH₄, VOCs, and CO. We find that the effect synergies are strong for PM/BC, VOC, CO and CH₄. While an air quality strategy targeted at reducing ozone will also reduce RF, this will not be the case for a strategy targeting particulate matter. Abatement in China dominates RF reduction, but there are cheap abatement options also available in the EU and USA. The justification for international cooperation on air quality issues is underlined when the co-benefits of reduced RF are considered. Some species, most importantly SO₂, contribute a negative forcing on climate. We suggest that given current knowledge, NO_x and SO₂ should be ignored in RF-targeted abatement policies.     

Evaluation of measures of impairment in real and simulated driving: Results from a randomized,placebo-controlled study

Objective: Standard deviation of lateral position (SDLP) is often the primary outcome in experimental studies on impaired driving. However, other measures may be easier and more practical to obtain and reflect a broader range of driving-related behaviors. We wanted to assess the validity and sensitivity of a range of measures in a driving simulator as well as during real driving and compare these to SDLP.

Methods: Twenty healthy male volunteers undertook 6 driving trials each, 3 in a regular car on a closed track resembling rural road conditions and 3 in a simulator with an identical driving scenario. Ethanol was used as impairing substance due to its well-characterized effects on driving. The subjects were tested sober and at blood alcohol concentrations (BAC) of approximately 0.5 and 0.9 g/L. We explored dose–response relationships between BAC and a range of driving-related measures, as well as their BAC-dependent effect sizes.

Results: In simulator driving, ethanol intake increased steering wheel reversal frequency, steering wheel movement measures, average speed, standard deviation of speed, and pedal use frequency. At the test track, only steering wheel movement and standard deviation of speed were significantly correlated to BAC. Likewise, reaction to unexpected incidents and observance of red traffic lights were adversely affected by ethanol in the simulator but not at the test track. Whereas SDLP showed a relatively large effect size that was similar in simulated and real driving, all other measures demonstrated smaller effect sizes, with less pronounced BAC effects on the test track than in the simulator.

Conclusions: The results suggest that the driving-related measures explored in this study are less sensitive to alcohol-mediated driving impairment than SDLP, especially during real (test track) driving. The discrepancy in effect sizes between simulated and real driving may imply low external validity of these measures in simulator studies.