An updated synthesis of the observed and projected impacts of climate change on the chemical, physical and biological processes in the oceans

The 5th Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) states with very high certainty that anthropogenic emissions have caused measurable changes in the physical ocean environment. These changes are summarized with special focus on those that are predicted to have the strongest, most direct effects on ocean biological processes; namely, ocean warming and associated phenomena (including stratification and sea level rise) as well as deoxygenation and ocean acidification. The biological effects of these changes are then discussed for microbes (including phytoplankton), plants, animals, warm and cold-water corals, and ecosystems. The IPCC AR5 highlighted several areas related to both the physical and biological processes that required further research. As a rapidly developing field, there have been many pertinent studies published since the cut off dates for the AR5, which have increased our understanding of the processes at work. This study undertook an extensive review of recently published literature to update the findings of the AR5 and provide a synthesized review on the main issues facing future oceans. The level of detail provided in the AR5 and subsequent work provided a basis for constructing projections of the state of ocean ecosystems in 2100 under two the Representative Concentration Pathways RCP4.5 and 8.5. Finally the review highlights notable additions, clarifications and points of departure from AR5 provided by subsequent studies.

Qualitative Distinction of Autotrophic and Heterotrophic Processes at the Leaf Level by Means of Triple Stable Isotope (C–O–H) Patterns

Foliar samples were harvested from two oaks, a beech, and a yew at the same site in order to trace the development of the leaves over an entire vegetation season. Cellulose yield and stable isotopic compositions (δ13C, δ18O, and δD) were analyzed on leaf cellulose. All parameters unequivocally define a juvenile and a mature period in the foliar expansion of each species. The accompanying shifts of the δ13C-values are in agreement with the transition from remobilized carbohydrates (juvenile period), to current photosynthates (mature phase). While the opponent seasonal trends of δ18O of blade and vein cellulose are in perfect agreement with the state-of-art mechanistic understanding, the lack of this discrepancy for δD, documented for the first time, is unexpected. For example, the offset range of 18 permil (oak veins) to 57 permil (oak blades) in δD may represent a process driven shift from autotrophic to heterotrophic processes. The shared pattern between blade and vein found for both oak and beech suggests an overwhelming metabolic isotope effect on δD that might be accompanied by proton transfer linked to the Calvin-cycle. These results provide strong evidence that hydrogen and oxygen are under different biochemical controls even at the leaf level.

Inhibition of photosynthesis by high temperature in oak (Quercus pubescens L.) leaves grown under natural conditions closely correlates with a reversible heat-dependent reduction of the activation state of ribulose-1,5-bisphosphate carboxylase/oxygenase

Inhibition of the net photosynthetic CO2 assimilation rate (Pn) by high temperature was examined in oak (Quercus pubescens L.) leaves grown under natural conditions. Combined measurements of gas exchange and chlorophyll (Chl) a fluorescence were employed to differentiate between inhibition originating from heat effects on components of the thylakoid membranes and that resulting from effects on photosynthetic carbon metabolism. Regardless of whether temperature was increased rapidly or gradually, Pn decreased with increasing leaf temperature and was more than 90% reduced at 45 °C as compared to 25 °C. Inhibition of Pn by heat stress did not result from reduced stomatal conductance (gs), as heat-induced reduction of gs was accompanied by an increase of the intercellular CO2 concentration (Ci). Chl a fluorescence measurements revealed that between 25 and 45 °C heat-dependent alterations of thylakoid-associated processes contributed only marginally, if at all, to the inhibition of Pn by heat stress, with photosystem II being remarkably well protected against thermal inactivation. The activation state of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) decreased from about 90% at 25 °C to less than 30% at 45 °C. Heat stress did not affect Rubisco per se, since full activity could be restored by incubation with CO2 and Mg2+. Western-blot analysis of leaf extracts disclosed the presence of two Rubisco activase polypeptides, but heat stress did not alter the profile of the activase bands. Inhibition of Pn at high leaf temperature could be markedly reduced by artificially increasing Ci. A high Ci also stimulated photosynthetic electron transport and resulted in reduced non-photochemical fluorescence quenching. Recovery experiments showed that heat-dependent inhibition of Pn was largely, if not fully, reversible. The present results demonstrate that in Q. pubescens leaves the thylakoid membranes in general and photosynthetic electron transport in particular were well protected against heat-induced perturbations and that inhibition of Pn by high temperature closely correlated with a reversible heat-dependent reduction of the Rubisco activation state.

What do brain network interactions tell about cognitive processes? How to seek causality?

Optimal adjustment of brain networks allows the biased processing of information in response to the demand of environments and is therefore prerequisite for adaptive behaviour. It is widely shown that a biased state of networks is associated with a particular cognitive process. However, those associations were identified by backward categorization of trials and cannot provide a causal association with cognitive processes. This problem still remains a big obstacle to advance the state of our field in particular human cognitive neuroscience. In my talk, I will present two approaches to address the causal relationships between brain network interactions and behaviour. Firstly, we combined connectivity analysis of fMRI data and a machine leaning method to predict inter-individual differences of behaviour and responsiveness to environmental demands. The connectivity-based classification approach outperforms local activation-based classification analysis, suggesting that interactions in brain networks carry information of instantaneous cognitive processes. Secondly, we have recently established a brand new method combining transcranial alternating current stimulation (tACS), transcranial magnetic stimulation (TMS), and EEG. We use the method to measure signal transmission between brain areas while introducing extrinsic oscillatory brain activity and to study causal association between oscillatory activity and behaviour. We show that phase-matched oscillatory activity creates the phase-dependent modulation of signal transmission between brain areas, while phase-shifted oscillatory activity blunts the phase-dependent modulation. The results suggest that phase coherence between brain areas plays a cardinal role in signal transmission in the brain networks. In sum, I argue that causal approaches will provide more concreate backbones to cognitive neuroscience.

State Capture from Below? The Contradictory Effects of Decentralisation on Public Spending

This study analyses the contradictory effects of decentralisation on public spending. We distinguish three dimensions of decentralisation and analyse their joint and separate effects on public spending in the Swiss cantons over 20 years. We find that overall decentralisation has a strong, significant and negative effect on the size of the public sector, thus confirming the Leviathan hypothesis. The same holds for fiscal and institutional decentralisation. However, the extent to which political processes and actors are organised locally rather than centrally actually increases central and decreases local spending. This suggests that actors behave strategically when dealing with the centre by offloading the more costly policies. The wider implication of our study is that the balance between self-rule and shared rule has implications also for the size of the overall political system.

Modeling asteroid collisions and impact processes

As a complement to experimental and theoretical approaches, numerical modeling has become an important component to study asteroid collisions and impact processes. In the last decade, there have been significant advances in both computational resources and numerical methods. We discuss the present state-of-the-art numerical methods and material models used in "shock physics codes" to simulate impacts and collisions and give some examples of those codes. Finally, recent modeling studies are presented, focussing on the effects of various material properties and target structures on the outcome of a collision.

Unistructed BIAT faking when ego depleted or in normal state: Differential effect on brain and behavior

Background: Deception can distort psychological tests on socially sensitive topics. Understanding the cerebral processes that are involved in such faking can be useful in detection and prevention of deception. Previous research shows that faking a brief implicit association test (BIAT) evokes a characteristic ERP response. It is not yet known whether temporarily available self-control resources moderate this response. We randomly assigned 22 participants (15 females, 24.23 ± 2.91 years old) to a counterbalanced repeated-measurements design. Participants first completed a Brief-IAT (BIAT) on doping attitudes as a baseline measure and were then instructed to fake a negative doping attitude both when self-control resources were depleted and non-depleted. Cerebral activity during BIAT performance was assessed using high-density EEG. Results: Compared to the baseline BIAT, event-related potentials showed a first interaction at the parietal P1, while significant post hoc differences were found only at the later occurring late positive potential. Here, significantly decreased amplitudes were recorded for ‘normal’ faking, but not in the depletion condition. In source space, enhanced activity was found for ‘normal’ faking in the bilateral temporoparietal junction. Behaviorally, participants were successful in faking the BIAT successfully in both conditions. Conclusions: Results indicate that temporarily available self-control resources do not affect overt faking success on a BIAT. However, differences were found on an electrophysiological level. This indicates that while on a phenotypical level self-control resources play a negligible role in deliberate test faking the underlying cerebral processes are markedly different. Electronic supplementary material: The online version of this article (doi:10.1186/s12868-016-0249-8) contains supplementary material, which is available to authorized users.

Feasibility of resting-state microstates neurofeedback

Despite major progress, currently available treatment options for patients suffering from schizophrenia remain suboptimal. Antipsychotic medication is one such option, and is helpful in acute phases of the disease. However, antipsychotics cause significant side-effects that often require additional medication, and can even trigger the discontinuation of treatment. Taken together, along with the fact that 20-30% of patients are medication-resistant, it is clear that new medical care options should be developed for patients with schizophrenia. Besides medication, an emerging option to treat psychiatric symptoms is through the use of neurofeedback. This technique has proven efficacy for other disorders and, more importantly, has also proven to be feasible in patients with schizophrenia. One of the major advantages of this approach is that it allows for the influence of brain states that otherwise would be inaccessible; i.e. the physiological markers underlying psychotic symptoms. EEG resting-state microstates are a very interesting electrophysiological marker of schizophrenia symptoms. Precisely, a specific class of resting-state microstates, namely microstate class D, has consistently been found to show a temporal shortening in patients with schizophrenia compared to controls, and this shortening is correlated with the presence positive psychotic symptoms. Under the scope of biological psychiatry, appropriate treatment of psychotic symptoms can be expected to modify the underlying physiological markers accompanying behavioral manifestations of a disease. We reason that if abnormal temporal parameters of resting-state microstates seem to be related to positive symptoms in schizophrenia, regulating this EEG feature might be helpful as a treatment for patients. The goal of this thesis was to prove the feasibility of microstate class D contribution self-regulation via neurofeedback. Given that no other study has attempted to regulate microstates via neurofeedback, we first tested its feasibility in a population of healthy subjects. In the first paper we describe the methodological characteristics of the neurofeedback protocol and its implementation. Neurofeedback performance was assessed by means of linear mixed effects modeling, which provided a complete profile of the neurofeedback’s training response within and between-subjects. The protocol included 20 training sessions, and each session contained three conditions: baseline (resting-state) and two active conditions: training (auditory feedback upon self-regulation performance) and transfer (self-regulation with no feedback). With linear modeling we obtained performance indices for each of them as follows: baseline carryover (baseline increments time-dependent) and learning and aptitude for each of the active conditions. Learning refers to the increase/decrease of the microstate class D contribution, time-dependent during each active condition, and aptitude refers to the constant difference of the microstate class D contribution between each active condition and baseline independent of time. The indices provided are discussed in terms of tailoring neurofeedback treatment to individual profiles so that it can be applied in future studies or clinical practice. In our sample of participants, neurofeedback proved feasible, as all participants at least showed positive results in one of the aforementioned learning indices. Furthermore, between-subjects we observed that the contribution of microstate class D across-sessions increased by 0.42% during baseline, 1.93% during training trials, and 1.83% during transfer. This range is expected to be effective in treating psychotic symptoms in patients. In the second paper presented in this thesis, we explored the possible predictors of neurofeedback success among psychological variables measured with questionnaires. An interesting finding was the negative correlation between “motivational incongruence” and some of the neurofeedback performance indices. Even though this finding requires replication, we discuss it in terms of the interfering effects of incompatible psychological processes with neurofeedback training requirements. In the third paper, we present a meta-analysis on all available studies that have related resting-state microstate abnormalities and schizophrenia. We obtained medium effect sizes for two microstate classes, namely C and D. Combining the meta-analysis results with the fact that microstate class D abnormalities are correlated with the presence of positive symptoms in patients with schizophrenia, these results add further support for the training of this precise microstate. Overall, the results obtained in this study encourage the implementation of this protocol in a population of patients with schizophrenia. However, future studies will have to show whether patients will be able to successfully self-regulate the contribution of microstate class D and, if so, whether this regulation will have an impact on symptomatology.