Human behaviour in emergency situations: comparisons between aviation and rail domains

This article presents a comparative review of the knowledge base regarding human behaviour in emergencies for both aviation and rail domains. Generic models of human behaviour in emergency situations are introduced and specific attention is then focussed on methods of behaviour prediction, exhibited behaviours in emergencies and methods of aiding evacuation across both modes of transport. Using established knowledge from the aviation domain, it has been possible to make observations and comparisons about the rail domain. Traditionally, the aviation domain has been a major focus of research attention and this is used to inform and interpret the rail domain. By drawing comparisons across these domains for human behaviour in emergency situations, the observations are discussed along with recommendations for future policies/planning for emergencies and future research areas

Adaptation and Mal-Adaptation to Ambient Hypoxia; Andean, Ethiopian and Himalayan Patterns

The study of the biology of evolution has been confined to laboratories and model organisms. However, controlled laboratory conditions are unlikely to model variations in environments that influence selection in wild populations. Thus, the study of “fitness” for survival and the genetics that influence this are best carried out in the field and in matching environments

Assessing reconstruction techniques of the Atlantic Ocean circulation variability during the last millennium

We assess the use of the meridional thermal-wind transport estimated from zonal density gradients to reconstruct the oceanic circulation variability during the last millennium in a forced simulation with the ECHO-G coupled climate model. Following a perfect-model approach, model-based pseudo-reconstructions of the Atlantic meridional overturning circulation (AMOC) and the Florida Current volume transport (FCT) are evaluated against their true simulated variability. The pseudo-FCT is additionally verified as proxy for AMOC strength and compared with the available proxy-based reconstruction. The thermal-wind component reproduces most of the simulated AMOC variability, which is mostly driven by internal climate dynamics during the preindustrial period and by increasing greenhouse gases afterwards. The pseudo-reconstructed FCT reproduces well the simulated FCT and reasonably well the variability of the AMOC strength, including the response to external forcing. The pseudo-reconstructed FCT, however, underestimates/overestimates the simulated variability at deep/shallow levels. Density changes responsible for the pseudo-reconstructed FCT are mainly driven by zonal temperature differences; salinity differences oppose but play a minor role. These results thus support the use of the thermal-wind relationship to reconstruct the oceanic circulation past variability, in particular at multidecadal timescales. Yet model-data comparison highlights important differences between the simulated and the proxy-based FCT variability. ECHO-G simulates a prominent weakening in the North Atlantic circulation that contrasts with the reconstructed enhancement. Our model results thus do not support the reconstructed FC minimum during the Little Ice Age. This points to a failure in the reconstruction, misrepresented processes in the model, or an important role of internal ocean dynamics

Relationship between bacterial and primary production in a newly filled reservoir: temporal variability over 2 consecutive years

International audienceSeasonal and spatial variations in bacterial abundance, biomass and production in a recently flooded reservoir were followed for 2 consecutive years, in conjunction with phytoplankton biomass (chlorophyll a) and activity (primary production). Between the 2 years of the study, the mean value of primary production remained constant, while those of the chlorophyll a concentration, bacterial abundance (BA), bacterial biomass (BB) and bacterial production (BP) decreased. The observed trends of the bacterial variables were linked to changes in the relative importance of allochthonous dissolved organic matter. Moreover, this factor would explain discrepancies observed between the slope of the model II regression equations established from results of the present study and those of the predictive models from the literature, relating to bacterial and phytoplankton variables. An estimate of the carbon budget indicated that 22 and 5% of the ambient primary production in the Sep Reservoir might be channeled through the microbial loop via BP during the 1st and 2nd year of the study, respectively. We conclude that heterotrophic BP in the Sep Reservoir may, on occasion, represent a significant source of carbon for higher order consumers

Guidance for the model developer on representing human behavior in egress models

Structures are currently designed and typically constructed in accordance with prescriptive and performance-based methodologies to ensure a certain level of safety. The performance-based approach requires the quantification of both available safe egress time (ASET) and required safe egress time (RSET) to determine the degree of safety provided. This article focuses on the RSET side of the equation, for which an engineer would use some type of egress modelling approach to estimate evacuation performance. Often, simple engineering equations are applied to estimate the RSET value; however, over time, more sophisticated computational tools have appeared. Irrespective of the approach adopted, appropriate and accurate representation of human behavior in fire within these approaches is limited, mainly due to the lack of a comprehensive conceptual model of evacuee decision-making and behavior during fire emergencies. This article initially presents a set of behavioral statements that represent the primary elements of current understanding regarding evacuee behavior. Once presented, guidance is provided on how these behavioral statements might be incorporated by the model developer into an egress model. The intent here is to assist in the advancement of current egress models by outlining the model structures required to represent the current understanding of egress behavior