The art of measuring nothing: The paradox of measuring safety in a changing civil aviation industry using traditional safety metrics

Measuring safety as an outcome variable within the ultra-safe civil aviation industry during periods of deliberate organizational change is a difficult, and often fruitless, task. Anticipating eroding safety processes, based on measuring nothing happening over time, does not adequately capture the true state of an evolving safe system, and this is particularly relevant for leaders and managers in a civil aviation industry responsible for maintaining and improving ultra-safe performance while simultaneously managing demanding strategic business goals.In this paper, I will look at the difficulties of measuring safety as an outcome measure in high reliability organizations (HROs) using the traditional measures of incident and accident reporting during periods of deliberate organizational change inspired by the results from a 3 year longitudinal case study of the Norwegian Air Navigation Services provider – Avinor. I will first review the current safety literature relating to safety management systems (SMSs) used in the civil aviation industry. I will then propose a more holistic model that shifts the focus from the traditional safety monitoring mechanisms of risk analysis and trial and error learning, to the natural interactivity within socio-technical systems as found in high reliability organizations. And finally, I will present a summary of the empirical results of an alternate methodology for measuring perceived changes in safety at the operational level as leading indicators of evolving safety at the organizational level.     

Detecting pattern in biological stressor response relationships using model based cluster analysis

Environmental monitoring of aquatic systems is needed to estimate the quality of the systems, to evaluate standards and to study stressor–response relationships. Monitoring programs often focus on the collection of biological, chemical and physical measures of the system. An important concern is the effect of chemical and physical stressors on the biological community. Evaluation of relationships may be difficult as the extent of the relationship is not known. From a management perspective, interest is on what factors affect the biological community and where these factors have an influence. The focus of this paper is on the use of regression based cluster analysis as a tool for finding relationships between a single biological response and a suite of environmental stressors. The approach to cluster analysis uses a penalized regression classification likelihood and Markov Chain Model Composition Monte Carlo. This approach allows for simultaneous development of regression models and clustering of the regression models. The method is applied to the analysis of a data set describing stressors/response relationship in Ohio.     

Sterol production and phytosterol bioconversion in two species of heterotrophic protists, Oxyrrhis marina and Gyrodinium dominans

The kinetics and efficiency of sterol production and bioconversion of phytosterols in two heterotrophic protists Oxyrrhis marina and Gyrodinium dominans were examined by feeding them two different algal species (Rhodomonas salina and Dunaliella tertiolecta) differing in sterol profiles. R. salina contains predominantly brassicasterol (?99%) and <2% cholesterol. The major sterols in D. tertiolecta are ergosterol (45–49%), 7-dehydroporiferasterol (29–31%) and fungisterol (21–26%). O. marina fed R. salina metabolized dietary brassicasterol to produce 22-dehydrocholesterol and cholesterol. O. marina fed D. tertiolecta metabolized dietary sterols to produce cholesterol, 22-dehydrocholesterol, brassicasterol and stigmasterol. G. dominans fed either R. salina or D. tertiolecta metabolized dietary sterols to make cholesterol, brassicasterol and a series of unknown sterols. When protists were fed R. salina, which contains cholesterol, the levels of cholesterol were increased to a magnitude of nearly 5- to 30-fold at the phytoplankton-heterotrophic protist interface, equivalent to a production of 172.5 ± 16.2 and 987.7 ± 377.7 ng cholesterol per mg R. salina carbon consumed by O. marina and G. dominans, respectively. When protists were fed D. tertiolecta, which contains no cholesterol, a net production of cholesterol by the protists ranged from 123.2 ± 30.6 to 871.8 ± 130.8 ng per mg algal C consumed. Cholesterol is not only the dominant sterol, but a critical precursor for many physiologically functional biochemicals in higher animal. As intermediates, these heterotrophic protists increase the amount of cholesterol at the phytoplankton–zooplankton interface available to higher trophic levels relative to zooplankton feeding on algae directly.     

Spatial selection and inheritance: applying evolutionary concepts to population dynamics in heterogeneous space

Organisms in highly suitable sites generally produce more offspring, and offspring can inherit this suitability by not dispersing far. This combination of spatial selection and spatial inheritance acts to bias the distribution of organisms toward suitable sites and thereby increase mean fitness (i.e., per capita population increase). Thus, population growth rates in heterogeneous space change over time by a process conceptually analogous to evolution by natural selection, opening avenues for theoretical cross-pollination between evolutionary biology and ecology. We operationally define spatial inheritance and spatial selective differential and then combine these two factors in a modification of the breeder's equation, derived from simple models of population growth in heterogeneous space. The modified breeder's equation yields a conservative criterion for persistence in hostile environments estimable from field measurements. We apply this framework for understanding gypsy moth population persistence amidst abundant predators and find that the predictions of the modified breeder's equation match initial changes in population growth rate in independent simulation output. The analogy between spatial dynamics and natural selection conceptually links ecology and evolution, provides a spatially implicit framework for modeling spatial population dynamics, and represents an important null model for studying habitat selection.     

Decomposition of diverse litter mixtures in streams

In view of growing interest in understanding how biodiversity affects ecosystem functioning, we investigated effects of riparian plant diversity on litter decomposition in forest streams. Leaf litter from 10 deciduous tree species was collected during natural leaf fall at two locations (Massif Central in France and Carpathians in Romania) and exposed in the field in litter bags. There were 35 species combinations, with species richness ranging 1-10. Nonadditive effects on the decomposition of mixed-species litter were minor, although a small synergistic effect was observed in the Massif Central stream where observed litter mass remaining was significantly lower overall than expected from data on single-species litter. In addition, variability in litter mass remaining decreased with litter diversity at both locations. Mean nitrogen concentration of single- and mixed-species litters (0.68-4.47% of litter ash-free dry mass) accounted for a large part of the variation in litter mass loss across species combinations. For a given species or mixture, litter mass loss was also consistently faster in the Massif Central than in the Carpathians, and the similarity in general stream characteristics, other than temperature, suggests that this effect was largely due to differences in thermal regimes. These results support the notion that decomposition of litter mixtures is primarily driven by litter quality and environmental factors, rather than by species richness per se. However, the observed consistent decrease in variability of decomposition rate with increasing plant species richness indicates that conservation of riparian tree diversity is important even when decomposition rates are not greatly influenced by litter mixing.     

Heterogeneity in social network connections is density-dependent: implications for disease dynamics in a gregarious ungulate

Behavioral Ecology and Sociobiology - Individual animals across all taxa differ consistently in behaviour, i.e. they show personality traits. This inter-individual variability has significant...     

An implicit wetting–drying algorithm for the discontinuous Galerkin method: application to the Tonle Sap,Mekong River Basin

Environmental Fluid Mechanics - The accurate simulation of wetting–drying processes in floodplains and coastal zones is a challenge for hydrodynamic modelling, especially for long time...     

Assessment of temporal and spatial water quality in international Gomishan Lagoon,Iran, using multivariate analysis

Coastal lagoon ecosystems are vulnerable to eutrophication, which leads to the accumulation of nutrients from the surrounding watershed over the long term. However, there is a lack of information about methods that could accurate quantify this problem in rapidly developed countries. Therefore, various statistical methods such as cluster analysis (CA), principal component analysis (PCA), partial least square (PLS), principal component regression (PCR), and ordinary least squares regression (OLS) were used in this study to estimate total organic matter content in sediments (TOM) using other parameters such as temperature, dissolved oxygen (DO), pH, electrical conductivity (EC), nitrite (NO₂), nitrate (NO₃), biological oxygen demand (BOD), phosphate (PO₄), total phosphorus (TP), salinity, and water depth along a 3-km transect in the Gomishan Lagoon (Iran). Results indicated that nutrient concentration and the dissolved oxygen gradient were the most significant parameters in the lagoon water quality heterogeneity. Additionally, anoxia at the bottom of the lagoon in sediments and re-suspension of the sediments were the main factors affecting internal nutrient loading. To validate the models, R², RMSECV, and RPDCV were used. The PLS model was stronger than the other models. Also, classification analysis of the Gomishan Lagoon identified two hydrological zones: (i) a North Zone characterized by higher water exchange, higher dissolved oxygen and lower salinity and nutrients, and (ii) a Central and South Zone with high residence time, higher nutrient concentrations, lower dissolved oxygen, and higher salinity. A recommendation for the management of coastal lagoons, specifically the Gomishan Lagoon, to decrease or eliminate nutrient loadings is discussed and should be transferred to policy makers, the scientific community, and local inhabitants.     

Biomarker responses of <Emphasis Type="Italic">Peromyscus leucopus</Emphasis> exposed to lead and cadmium in the Southeast Missouri Lead Mining District

Biomarker responses and histopathological lesions have been documented in laboratory mammals exposed to elevated concentrations of lead and cadmium. The exposure of white-footed mice (Peromyscus leucopus) to these metals and the potential associated toxic effects were examined at three contaminated sites in the Southeast Missouri Lead Mining District and at a reference site in MO, USA. Mice from the contaminated sites showed evidence of oxidative stress and reduced activity of red blood cell δ-aminolevulinic acid dehydratase (ALAD). Histological examinations of the liver and kidney, cytologic examination of blood smears, and biomarkers of lipid peroxidation and DNA damage failed to show indications of toxic effects from lead. The biomagnification factor of cadmium (hepatic concentration/soil concentration) at a site with a strongly acid soil was 44 times the average of the biomagnification factors at two sites with slightly alkaline soils. The elevated concentrations of cadmium in the mice did not cause observable toxicity, but were associated with about a 50% decrease in expected tissue lead concentrations and greater ALAD activity compared to the activity at the reference site. Lead was associated with a decrease in concentrations of hepatic glutathione and thiols, whereas cadmium was associated with an increase. In addition, to support risk assessment efforts, we developed linear regression models relating both tissue lead dosages (based on a previously published a laboratory study) and tissue lead concentrations in Peromyscus to soil lead concentrations.