Effects of global warming on animal distribution and performance become visible in many marine ecosystems. The present study was designed to develop a concept for a cause and effect understanding with respect to temperature changes and to explain ecological findings based on physiological processes. The concept is based on a wide comparison of invertebrate and fish species with a special focus on recent data obtained in two model species of fish. These fish species are both characterized by northern and southern distribution limits in the North Atlantic: eelpout (Zoarces viviparus), as a typical non-migrating inhabitant of the coastal zone and the cod (Gadus morhua), as a typical inhabitant of the continental shelf with a high importance for fisheries.Mathematical modelling demonstrates a clear significant correlation between climate induced temperature fluctuations and the recruitment of cod stocks. Growth performance in cod is optimal at temperatures close to 101C, regardless of the population investigated in a latitudinal cline. However, temperature specific growth rates decrease at higher latitudes. Also, fecundity is less in White Sea than in North and Baltic Sea cod or eelpout populations. These findings suggest that a cold-induced shift in energy budget occurs which is unfavorable for growth performance and fecundity. Thermal tolerance limits shift depending on latitude and are characterized by oxygen limitation at both low or high temperatures. Oxygen supply to tissues is optimized at low temperature by a shift in hemoglobin isoforms and oxygen binding properties to lower affinities and higher unloading potential. Protective stimulation of heat shock protein synthesis was not observed.According to a recent model of thermal tolerance the downward shift of tolerance limits during cold adaptation is associated with rising mitochondrial densities and, thus, aerobic capacity and performance in the cold, especially in eurythermal species. At the same time the costs of mitochondrial maintenance reflected by mitochondrial proton leakage should rise leaving a lower energy fraction for growth and reproduction. The preliminary conclusion can be drawn that warming will cause a northern shift of distribution limits for both species with a rise in growth performance and fecundity larger than expected from the Q 10 effect in the north and lower growth or even extinction of the species in the south. Such a shift may heavily affect fishing activities in the North Sea. r

The kinetics of the reaction of cytochrome c with solubilized mammalian cytochrome c oxidase (ferrocytochrome c:oxy en oxidoreductase, EC 1.9.3

A major challenge in evolutionary biology is to identify the genes underlying adaptation. The oxygentransporting haemoglobins directly link external conditions with metabolic needs and therefore represent a unique system for studying environmental effects on molecular evolution. We have discovered two haemoglobin polymorphisms in Atlantic cod populations inhabiting varying temperature and oxygen regimes in the North Atlantic. Three-dimensional modelling of the tetrameric haemoglobin structure demonstrated that the two amino acid replacements Met55b 1 Val and Lys62b 1 Ala are located at crucial positions of the a 1 b 1 subunit interface and haem pocket, respectively. The replacements are proposed to affect the oxygen-binding properties by modifying the haemoglobin quaternary structure and electrostatic feature. Intriguingly, the same molecular mechanism for facilitating oxygen binding is found in avian species adapted to high altitudes, illustrating convergent evolution in water-and air-breathing vertebrates to reduction in environmental oxygen availability. Cod populations inhabiting the cold Arctic waters and the low-oxygen Baltic Sea seem well adapted to these conditions by possessing the high oxygen affinity Val55-Ala62 haplotype, while the temperature-insensitive Met55-Lys62 haplotype predominates in the southern populations. The distinct distributions of the functionally different haemoglobin variants indicate that the present biogeography of this ecologically and economically important species might be seriously affected by global warming.

Adaptive Automation (AA) is a promising approach to keep the task workload demand within appropriate levels in order to avoid both the under- and over-load conditions, hence enhancing the overall performance and safety of the human-machine system. The main issue on the use of AA is how to trigger the AA solutions without affecting the operative task. In this regard, passive Brain-Computer Interface (pBCI) systems are a good candidate to activate automation, since they are able to gather information about the covert behavior (e.g., mental workload) of a subject by analyzing its neurophysiological signals (i.e., brain activity), and without interfering with the ongoing operational activity. We proposed a pBCI system able to trigger AA solutions integrated in a realistic Air Traffic Management (ATM) research simulator developed and hosted at ENAC (École Nationale de l'Aviation Civile of Toulouse, France). Twelve Air Traffic Controller (ATCO) students have been involved in the experiment and they have been asked to perform ATM scenarios with and without the support of the AA solutions. Results demonstrated the effectiveness of the proposed pBCI system, since it enabled the AA mostly during the high-demanding conditions (i.e., overload situations) inducing a reduction of the mental workload under which the ATCOs were operating. On the contrary, as desired, the AA was not activated when workload level was under the threshold, to prevent too low demanding conditions that could bring the operator's workload level toward potentially dangerous conditions of underload.

The directed transfer function (DTF) and the partial directed coherence (PDC) are frequency-domain estimators that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods is based on the multivariate autoregressive modelling (MVAR) of time series, which requires the stationarity of the signals. In this way, transient pathways of information transfer remains hidden. The objective of this study is to test a time-varying multivariate method for the estimation of rapidly changing connectivity relationships between cortical areas of the human brain, based on DTF/PDC and on the use of adaptive MVAR modelling (AMVAR) and to apply it to a set of real high resolution EEG data. This approach will allow the observation of rapidly changing influences between the cortical areas during the execution of a task. The simulation results indicated that time-varying DTF and PDC are able to estimate correctly the imposed connectivity patterns under reasonable operative conditions of signal-to-noise ratio (SNR) ad number of trials. An SNR of five and a number of trials of at least 20 provide a good accuracy in the estimation. After testing the method by the simulation study, we provide an application to the cortical estimations obtained from high resolution EEG data recorded from a group of healthy subject during a combined foot-lips movement and present the time-varying connectivity patterns resulting from the application of both DTF and PDC. Two different cortical networks were detected with the proposed methods, one constant across the task and the other evolving during the preparation of the joint movement.