Temporal evolution of headwall erosion rates derived from cosmogenic nuclide concentrations in the medial moraines of Glacier d'Otemma, Switzerland

Climate change affects the stability and erosion of high‐alpine rock walls above glaciers (headwalls) that deliver debris to glacier surfaces. Since supraglacial debris in the ablation zone alters the melt behaviour of the underlying ice, the responses of debris‐covered glaciers and of headwalls to climate change may be coupled. In this study, we analyse the beryllium‐10 (10Be)‐cosmogenic nuclide concentration history of glacial headwalls delivering debris to the Glacier d'Otemma in Switzerland. By systematic downglacier‐profile‐sampling of two parallel medial moraines, we assess changes in headwall erosion through time for small, well‐defined debris source areas. We compute apparent headwall erosion rates from 10Be concentrations ([10Be]), measured in 15 amalgamated medial moraine debris samples. To estimate both the additional 10Be production during glacial debris transport and the age of our samples we combine our field‐based data with a simple model that simulates downglacier debris trajectories. Furthermore, we evaluate additional grain size fractions for eight samples to test for stochastic mass wasting effects on [10Be]. Our results indicate that [10Be] along the medial moraines vary systematically with time and consistently for different grain sizes. [10Be] are higher for older debris, closer to the glacier terminus, and lower for younger debris, closer to the glacier head. Computed apparent headwall erosion rates vary between ~0.6 and 10.8 mm yr−1, increasing over a maximum time span of ~200 years towards the present. As ice cover retreats, newly exposed headwall surfaces may become susceptible to enhanced weathering and erosion, expand to lower elevations, and contribute formerly shielded bedrock of likely different [10Be]. Hence, we suggest that recently lower [10Be] reflect the deglaciation of the debris source areas since the end of the Little Ice Age

Assessing the Disruptiveness of New Energy Technologies - An Ex-Ante Perspective

For those organizations that experience disruption, they usually understand the situation when it is already too late. The real challenge to any theory, especially if it is of high relevance for managers, is how it performs predictively. Can the theory of disruptive technologies be used not only to analyze cases ex post but to predict the potential disruptive technologies ex ante? Established companies are skeptical of the idea of disruptiveness, because of the difficulty of making predictions given the ex post nature of the theory. In this regard the goal of this report is to provide a general measure of disruptiveness and develop a framework that can assess technologies whether they have the potential to be proven disruptive. The developed assessment framework captures the essential characteristic and holistic success factors for disruptive technologies based on the theory of Christensen and a number of clarifications as seen in the literature. The framework is applied and validated by assessing the disruptive potential of five renewable energy technologies (wind energy, solar energy, biomass, hydro power, geothermal) in the power generation, heating and transportation sectors of four European countries (Austria, Bulgaria, Germany and Romania). The results show the applicability of the framework and give insights into technology and country specific determinants of energy market sector disruptions. (authors' abstract)Series: Working Papers / Institute for Strategic Management / Energy & Strategy Think Tan

Glycolytic Shunts Replenish the Calvin-Benson-Bassham Cycle as Anaplerotic Reactions in Cyanobacteria

The recent discovery of the Entner-Doudoroff (ED) pathway as a third glycolytic route beside Embden-Meyerhof-Parnas (EMP) and oxidative pentose phosphate (OPP) pathway in oxygenic photoautotrophs requires a revision of their central carbohydrate metabolism. In this study, unexpectedly, we observed that deletion of the ED pathway alone, and even more pronounced in combination with other glycolytic routes, diminished photoautotrophic growth in continuous light in the cyanobacterium Synechocystis sp. PCC 6803. Furthermore, we found that the ED pathway is required for optimal glycogen catabolism in parallel to an operating Calvin–Benson–Bassham (CBB) cycle. It is counter-intuitive that glycolytic routes, which are a reverse to the CBB cycle and do not provide any additional biosynthetic intermediates, are important under photoautotrophic conditions. However, observations on the ability to reactivate an arrested CBB cycle revealed that they form glycolytic shunts that tap the cellular carbohydrate reservoir to replenish the cycle. Taken together, our results suggest that the classical view of the CBB cycle as an autocatalytic, completely autonomous cycle that exclusively relies on its own enzymes and CO2 fixation to regenerate ribulose-1,5-bisphosphate for Rubisco is an oversimplification. We propose that in common with other known autocatalytic cycles, the CBB cycle likewise relies on anaplerotic reactions to compensate for the depletion of intermediates, particularly in transition states and under fluctuating light conditions that are common in nature

Ventromedial Prefrontal Cortex Activation Is Associated with Memory Formation for Predictable Rewards

During reinforcement learning, dopamine release shifts from the moment of reward consumption to the time point when the reward can be predicted. Previous studies provide consistent evidence that reward-predicting cues enhance long-term memory (LTM) formation of these items via dopaminergic projections to the ventral striatum. However, it is less clear whether memory for items that do not precede a reward but are directly associated with reward consumption is also facilitated. Here, we investigated this question in an fMRI paradigm in which LTM for reward-predicting and neutral cues was compared to LTM for items presented during consumption of reliably predictable as compared to less predictable rewards. We observed activation of the ventral striatum and enhanced memory formation during reward anticipation. During processing of less predictable as compared to reliably predictable rewards, the ventral striatum was activated as well, but items associated with less predictable outcomes were remembered worse than items associated with reliably predictable outcomes. Processing of reliably predictable rewards activated the ventromedial prefrontal cortex (vmPFC), and vmPFC BOLD responses were associated with successful memory formation of these items. Taken together, these findings show that consumption of reliably predictable rewards facilitates LTM formation and is associated with activation of the vmPFC

From 13C-lignin to 13C-mycelium: Agaricus bisporus uses polymeric lignin as a carbon source

Plant biomass conversion by saprotrophic fungi plays a pivotal role in terrestrial carbon (C) cycling. The general consensus is that fungi metabolize carbohydrates, while lignin is only degraded and mineralized to CO2. Recent research, however, demonstrated fungal conversion of 13C-monoaromatic compounds into proteinogenic amino acids. To unambiguously prove that polymeric lignin is not merely degraded, but also metabolized, carefully isolated 13C-labeled lignin served as substrate for Agaricus bisporus, the world's most consumed mushroom. The fungus formed a dense mycelial network, secreted lignin-active enzymes, depolymerized, and removed lignin. With a lignin carbon use efficiency of 0.14 (g/g) and fungal biomass enrichment in 13C, we demonstrate that A. bisporus assimilated and further metabolized lignin when offered as C-source. Amino acids were high in 13C-enrichment, while fungal-derived carbohydrates, fatty acids, and ergosterol showed traces of 13C. These results hint at lignin conversion via aromatic ring-cleaved intermediates to central metabolites, underlining lignin's metabolic value for fungi

Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance

Background: Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are small hematophagous insects responsible for the transmission of bluetongue virus, Schmallenberg virus and African horse sickness virus to wild and domestic ruminants and equids. Outbreaks of these viruses have caused economic damage within the European Union. The spatio-temporal distribution of biting midges is a key factor in identifying areas with the potential for disease spread. The aim of this study was to identify and map areas of neglectable adult activity for each month in an average year. Average monthly risk maps can be used as a tool when allocating resources for surveillance and control programs within Europe. Methods : We modelled the occurrence of C. imicola and the Obsoletus and Pulicaris ensembles using existing entomological surveillance data from Spain, France, Germany, Switzerland, Austria, Denmark, Sweden, Norway and Poland. The monthly probability of each vector species and ensembles being present in Europe based on climatic and environmental input variables was estimated with the machine learning technique Random Forest. Subsequently, the monthly probability was classified into three classes: Absence, Presence and Uncertain status. These three classes are useful for mapping areas of no risk, areas of high-risk targeted for animal movement restrictions, and areas with an uncertain status that need active entomological surveillance to determine whether or not vectors are present. Results: The distribution of Culicoides species ensembles were in agreement with their previously reported distribution in Europe. The Random Forest models were very accurate in predicting the probability of presence for C. imicola (mean AUC = 0.95), less accurate for the Obsoletus ensemble (mean AUC = 0.84), while the lowest accuracy was found for the Pulicaris ensemble (mean AUC = 0.71). The most important environmental variables in the models were related to temperature and precipitation for all three groups. Conclusions: The duration periods with low or null adult activity can be derived from the associated monthly distribution maps, and it was also possible to identify and map areas with uncertain predictions. In the absence of ongoing vector surveillance, these maps can be used by veterinary authorities to classify areas as likely vector-free or as likely risk areas from southern Spain to northern Sweden with acceptable precision. The maps can also focus costly entomological surveillance to seasons and areas where the predictions and vector-free status remain uncertain