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The Westerlund 1 (Wd1) cluster hosts a rich and varied collection of massive stars. Its dynamical youth and the absence of ongoing star formation indicate a coeval population. As such, the simultaneous presence of both late-type supergiants and Wolf-Rayet stars has defied explanation in the context of single-star evolution. Observational evidence points to a high binary fraction, hence this stellar population offers a robust test for stellar models accounting for both single-star and binary evolution. We present an optical to near-IR (VLT & NTT) spectroscopic analysis of 22 WR stars in Wd 1, delivering physical properties for the WR stars.
We discuss how these differ from the Galactic field population, and how they may be reconciled with the predictions of single and binary evolutionary models.
We analyse whether a stellar atmosphere model computed with the code CMFGEN provides an optimal description of the stellar observations of WR 136 and simultaneously reproduces the nebular observations of NGC 6888, such as the ionization degree, which is modelled with the pyCloudy code. All the observational material available (far and near UV and optical spectra) were used to constrain such models. We found that the stellar temperature T∗, at τ = 20, can be in a range between 70 000 and 110 000 K, but when using the nebula as an additional restriction, we found that the stellar models with T∗ ∼ 70 000 K represent the best solution for both, the star and the nebula.
Wolf-Rayet (WR) stars, as they are advanced stages of the life of massive stars, provide a good test for various physical processes involved in the modelling of massive stars, such as rotation and mass loss. In this paper, we show the outputs of the latest grids of single massive stars computed with the Geneva stellar evolution code, and compare them with some observations. We present a short discussion on the shortcomings of single stars models and we also briefly discuss the impact of binarity on the WR populations.
The interaction between massive star formation and gas is a key ingredient in galaxy evolution. Given the level of observational detail currently achievable in nearby starbursts, they constitute ideal laboratories to study interaction process that contribute to global evolution in all types of galaxies. Wolf-Rayet (WR) stars, as an observational marker of high mass star formation, play a pivotal role and their winds can strongly influence the surrounding gas. Imaging spectroscopy of two nearby (<4 Mpc) starbursts, both of which show multiple regions with WR stars, are discussed. The relation between the WR content and the physical and chemical properties of the surrounding ionized gas is explored.
Using ESPaDOnS optical spectra of WR6, we search variations on the stellar wind parameters during the different phases of the spectral variations. We use the radiative transfer code CMFGEN (Hillier & Miller 1998) to determine the wind parameters. Our work gives mean parameters for WR6, Teff = 55 kK, M = 2.7 × 10^-5 M⊙/yr and v∞ =1700 km/s. Furthermore the line profiles variations at different phases are the consequence of a variation of mass loss rate and temperature un the winds. Effective temperature reaches 59 kK at the highest intensity, whereas the mass-loss rate decreases to 2.5 × 10^-5 M⊙/yr in that case. On the other hand, effective temperature decreases to 52.5 kK and the mass-loss rate increases to 3 × 10^-5 M/⊙yr when the line profile reach its minimum intensity. Results confirm the variable nature of the stellar wind, presented in this case on two of its fundamental parameters: temperature and mass-loss; which could be used to constrain the nature of the instability at the basis of the wind.
Obtaining a complete census of massive, evolved stars in a galaxy would be a key ingredient for testing stellar evolution models. However, as the evolution of stars is also strongly dependent on their metallicity, it is inevitable to have this kind of data for a variety of galaxies with different metallicities. Between 2009 and 2011, we conducted the Magellanic Clouds Massive Stars and Feedback Survey (MSCF); a spatially complete, multi-epoch, broad- and narrow-band optical imaging survey of the Large and Small Magellanic Clouds. With the inclusion of shallow images, we are able to give a complete photometric catalog of stars between B ≈ 18 and B ≈ 19 mag.
These observations were augmented with additional photometric data of similar spatial res-
olution from UV to IR (e.g. from GALEX, 2MASS and Spitzer) in order to sample a large portion of the spectral energy distribution of the brightest stars (B < 16 mag) in the Magel- lanic Clouds. Using these data, were are able to train a machine learning algorithm that gives us a good estimate of the spectral type of tens of thousands of stars.
This method can be applied to the search for Wolf-Rayet-Stars to obtain a sample of candi- dates for follow-up observations. As this approach can, in principle, be adopted for any resolved galaxy as long as sufficient photometric data is available, it can form an effective alternative method to the classical strategies (e.g. He II filter imaging).
Colliding Wolf-Rayet (WR) winds produce thermal X-ray emission widely observed by X-ray telescopes. In wide WR+O binaries, such as WR 140, the X-ray flux is tied to the orbital phase, and is a direct probe of the winds’ properties. In the Galactic center, ~30 WRs orbit the super massive black hole (SMBH) within ~10”, leading to a smorgasbord of wind-wind collisions. To model the X-ray emission of WR 140 and the Galactic center, we perform 3D hydrodynamic simulations to trace the complex gaseous flows, and then carry out 3D radiative transfer calculations to compute the variable X-ray spectra. The model WR 140 RXTE light curve matches the data well for all phases except the X-ray minimum associated with periastron, while the model spectra agree with the RXTE hardness ratio and the shape of the Suzaku observations throughout the orbit. The Galactic center model of the Chandra flux and spectral shape match well in the region r ≤ 3”, but the model flux falls off too rapidly beyond this radius.
Ring Nebulae
(2015)
Preliminary results are presented from spectroscopic data in the optical range of the Galactic ring nebulae NGC 6888, G2:4+1:4, RCW 58 and Sh2-308. Deep observations with long exposure times were carried out at the 6.5m Clay Telescope and at the 10.4m Gran Telescopio Canarias. In NGC 6888, recombination lines of C ii, O ii and N ii are detected with signal-to-noise ratios higher than 8. The chemical content of NGC 6888 is discussed within the chemical enrichment predicted by evolution models of massive stars. For all nebulae, a forthcoming work will content in-depth details about observations, analysis and final results (Esteban et al. 2015, in prep.).
We present results of investigation of spectral variability of one of the most interesting massive stars, Romano's star (M33/V532 or GR290), located in the M33 galaxy. Brightness of the star changes together with its spectral class, which varies from WN11 to WN8. Using CMFGEN code we estimated parameters of stellar atmosphere and found that during last ten years bolometric luminosity of the star changed synchronously with stellar magnitude. Our calculations argue in favor of the hypothesis of a post-LBV status of GR290.
Key physical ingredients governing the evolution of massive stars are mass losses, convection and mixing in radiative zones. These effects are important both in the frame of single and close binary evolution. The present paper addresses two points: 1) the differences between two families of rotating models, i.e. the family of models computed with and without an efficient transport of angular momentum in radiative zones; 2) The impact of the mass losses in single and in close binary models.
We present results of full 3D hydrodynamical and radiative transfer simulations of the colliding stellar winds in the massive binary system η Carinae. We accomplish this by applying the SimpleX algorithm for 3D radiative transfer on an unstructured Voronoi-Delaunay grid to recent 3D smoothed particle hydrodynamics (SPH) simulations of the binary colliding winds. We use SimpleX to obtain detailed ionization fractions of hydrogen and helium, in 3D, at the resolution of the original SPH simulations. We investigate several computational domain sizes and Luminous Blue Variable primary star mass-loss rates. We furthermore present new methods of visualizing and interacting with output from complex 3D numerical simulations, including 3D interactive graphics and 3D printing. While we initially focus on η Car, the methods employed can be applied to numerous other colliding wind (WR 140, WR 137, WR 19) and dusty `pinwheel' (WR 104, WR 98a) binary systems. Coupled with 3D hydrodynamical simulations, SimpleX simulations have the potential to help determine the regions where various observed time-variable emission and absorption lines form in these unique objects.
HD5980
(2015)
HD5980 is a multiple system containing at least 3 very massive and luminous stars. Located in the Small Magellanic Cloud, it is an ideal system for studying the massive star structure and evolutionary processes in low-metallicity environments. Intensely observed over the past few decades, HD5980 is a treasure trove of information on stellar wind structure, on wind-wind collisions and on the formation of wind-blown circumstellar structures. In addition, its characteristics suggest that the eclipsing WR+LBV stars of the system are the product of quasihomogeneous chemical evolution, thus making them candidate pair production supernovae or GRB progenitors. This paper summarizes some of the outstanding results derived from half a century of observations and recent theoretical studies.
We present the first physical characterization of the young open cluster VVVCL041. We spectroscopically observed the cluster main-sequence stellar population and a very-massive star candidate: WR62-2. CMFGEN modelling to our near-infrared spectra indicates that WR62-2 is a very luminous (10^6.4±0.2 L⊙)and massive (∼ 80M⊙) star.
We an optically-thick, transonic, steady wind model for a H-free Wolf-Rayet star. A bifurcation is found across a critical mass loss rate Mb. Slower winds M < Mb extend by several hydrostatic stellar radii, reproduce features of envelope in ation from Petrovic et al. (2006) and Gräfener et al. (2012), and are energetically unbound. This work is of particular interest for extended envelopes and winds, radiative hydrodynamic instabilities (eg. wind stagnation, clumping, etc.), and NLTE atmospheric models.
The evolution of massive stars is strongly influenced by their initial chemical composition. We have computed rapidly-rotating massive star models with low metallicity (∼1/50 Z⊙) that evolve chemically homogeneously and have optically-thin winds during the main sequence evolution. These luminous and hot stars are predicted to emit intense mid- and far-UV radiation, but without the broad emission lines that characterize WR stars with optically-thick winds. We show that such Transparent Wind UV-Intense (TWUIN) stars may be responsible for the high number of He ii ionizing photons observed in metal-poor dwarf galaxies, such as IZw 18. We find that these TWUIN stars are possible long-duration gamma-ray burst progenitors.
Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making.
Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop-and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.
The results of streamflow trend studies are often characterized by mostly insignificant trends and inexplicable spatial patterns. In our study region, Western Austria, this applies especially for trends of annually averaged runoff. However, analysing the altitudinal aspect, we found that there is a trend gradient from higher-altitude to lower-altitude stations, i.e. a pattern of mostly positive annual trends at higher stations and negative ones at lower stations. At midaltitudes, the trends are mostly insignificant. Here we hypothesize that the streamflow trends are caused by the following two main processes: on the one hand, melting glaciers produce excess runoff at higher-altitude watersheds. On the other hand, rising temperatures potentially alter hydrological conditions in terms of less snowfall, higher infiltration, enhanced evapotranspiration, etc., which in turn results in decreasing streamflow trends at lower-altitude watersheds. However, these patterns are masked at mid-altitudes because the resulting positive and negative trends balance each other. To support these hypotheses, we attempted to attribute the detected trends to specific causes. For this purpose, we analysed trends of filtered daily streamflow data, as the causes for these changes might be restricted to a smaller temporal scale than the annual one. This allowed for the explicit determination of the exact days of year (DOYs) when certain streamflow trends emerge, which were then linked with the corresponding DOYs of the trends and characteristic dates of other observed variables, e.g. the average DOY when temperature crosses the freezing point in spring. Based on these analyses, an empirical statistical model was derived that was able to simulate daily streamflow trends sufficiently well. Analyses of subdaily streamflow changes provided additional insights. Finally, the present study supports many modelling approaches in the literature which found out that the main drivers of alpine streamflow changes are increased glacial melt, earlier snowmelt and lower snow accumulation in wintertime.
The agricultural transition profoundly changed human societies. We sequenced and analysed the first genome (1.39x) of an early Neolithic woman from Ganj Dareh, in the Zagros Mountains of Iran, a site with early evidence for an economy based on goat herding, ca. 10,000 BP. We show that Western Iran was inhabited by a population genetically most similar to hunter-gatherers from the Caucasus, but distinct from the Neolithic Anatolian people who later brought food production into Europe. The inhabitants of Ganj Dareh made little direct genetic contribution to modern European populations, suggesting those of the Central Zagros were somewhat isolated from other populations of the Fertile Crescent. Runs of homozygosity are of a similar length to those from Neolithic farmers, and shorter than those of Caucasus and Western Hunter-Gatherers, suggesting that the inhabitants of Ganj Dareh did not undergo the large population bottleneck suffered by their northern neighbours. While some degree of cultural diffusion between Anatolia, Western Iran and other neighbouring regions is possible, the genetic dissimilarity between early Anatolian farmers and the inhabitants of Ganj Dareh supports a model in which Neolithic societies in these areas were distinct.
The role that climate and environmental history may have played in influencing human evolution has been the focus of considerable interest and controversy among paleoanthropologists for decades. Prior attempts to understand the environmental history side of this equation have centered around the study of outcrop sediments and fossils adjacent to where fossil hominins (ancestors or close relatives of modern humans) are found, or from the study of deep sea drill cores. However, outcrop sediments are often highly weathered and thus are unsuitable for some types of paleoclimatic records, and deep sea core records come from long distances away from the actual fossil and stone tool remains. The Hominin Sites and Paleolakes Drilling Project (HSPDP) was developed to address these issues. The project has focused its efforts on the eastern African Rift Valley, where much of the evidence for early hominins has been recovered. We have collected about 2 km of sediment drill core from six basins in Kenya and Ethiopia, in lake deposits immediately adjacent to important fossil hominin and archaeological sites. Collectively these cores cover in time many of the key transitions and critical intervals in human evolutionary history over the last 4 Ma, such as the earliest stone tools, the origin of our own genus Homo, and the earliest anatomically modern Homo sapiens. Here we document the initial field, physical property, and core description results of the 2012-2014 HSPDP coring campaign.
Venomous snakes often display extensive variation in venom composition both between and within species. However, the mechanisms underlying the distribution of different toxins and venom types among populations and taxa remain insufficiently known. Rattlesnakes (Crotalus, Sistrurus) display extreme inter-and intraspecific variation in venom composition, centered particularly on the presence or absence of presynaptically neurotoxic phospholipases A2 such as Mojave toxin (MTX). Interspecific hybridization has been invoked as a mechanism to explain the distribution of these toxins across rattlesnakes, with the implicit assumption that they are adaptively advantageous. Here, we test the potential of adaptive hybridization as a mechanism for venom evolution by assessing the distribution of genes encoding the acidic and basic subunits of Mojave toxin across a hybrid zone between MTX-positive Crotalus scutulatus and MTX-negative C. viridis in southwestern New Mexico, USA. Analyses of morphology, mitochondrial and single copy-nuclear genes document extensive admixture within a narrow hybrid zone. The genes encoding the two MTX subunits are strictly linked, and found in most hybrids and backcrossed individuals, but not in C. viridis away from the hybrid zone. Presence of the genes is invariably associated with presence of the corresponding toxin in the venom. We conclude that introgression of highly lethal neurotoxins through hybridization is not necessarily favored by natural selection in rattlesnakes, and that even extensive hybridization may not lead to introgression of these genes into another species.
Preface
(2016)
Subsurface microbial communities undertake many terminal electron-accepting processes, often simultaneously. Using a tritium-based assay, we measured the potential hydrogen oxidation catalyzed by hydrogenase enzymes in several subsurface sedimentary environments (Lake Van, Barents Sea, Equatorial Pacific, and Gulf of Mexico) with different predominant electron-acceptors. Hydrogenases constitute a diverse family of enzymes expressed by microorganisms that utilize molecular hydrogen as a metabolic substrate, product, or intermediate. The assay reveals the potential for utilizing molecular hydrogen and allows qualitative detection of microbial activity irrespective of the predominant electron-accepting process. Because the method only requires samples frozen immediately after recovery, the assay can be used for identifying microbial activity in subsurface ecosystems without the need to preserve live material. We measured potential hydrogen oxidation rates in all samples from multiple depths at several sites that collectively span a wide range of environmental conditions and biogeochemical zones. Potential activity normalized to total cell abundance ranges over five orders of magnitude and varies, dependent upon the predominant terminal electron acceptor. Lowest per-cell potential rates characterize the zone of nitrate reduction and highest per-cell potential rates occur in the methanogenic zone. Possible reasons for this relationship to predominant electron acceptor include (i) increasing importance of fermentation in successively deeper biogeochemical zones and (ii) adaptation of H(2)ases to successively higher concentrations of H-2 in successively deeper zones.
In a network with a mixture of different electrophysiological types of neurons linked by excitatory and inhibitory connections, temporal evolution leads through repeated epochs of intensive global activity separated by intervals with low activity level. This behavior mimics "up" and "down" states, experimentally observed in cortical tissues in absence of external stimuli. We interpret global dynamical features in terms of individual dynamics of the neurons. In particular, we observe that the crucial role both in interruption and in resumption of global activity is played by distributions of the membrane recovery variable within the network. We also demonstrate that the behavior of neurons is more influenced by their presynaptic environment in the network than by their formal types, assigned in accordance with their response to constant current.
Individuals within populations often differ substantially in habitat use, the ecological consequences of which can be far reaching. Stable isotope analysis provides a convenient and often cost effective means of indirectly assessing the habitat use of individuals that can yield valuable insights into the spatiotemporal distribution of foraging specialisations within a population. Here we use the stable isotope ratios of southern sea lion (Otaria flavescens) pup vibrissae at the Falkland Islands, in the South Atlantic, as a proxy for adult female habitat use during gestation. A previous study found that adult females from one breeding colony (Big Shag Island) foraged in two discrete habitats, inshore (coastal) or offshore (outer Patagonian Shelf). However, as this species breeds at over 70 sites around the Falkland Islands, it is unclear if this pattern is representative of the Falkland Islands as a whole. In order to characterize habitat use, we therefore assayed carbon (delta C-13) and nitrogen (delta N-15) ratios from 65 southern sea lion pup vibrissae, sampled across 19 breeding colonies at the Falkland Islands. Model-based clustering of pup isotope ratios identified three distinct clusters, representing adult females that foraged inshore, offshore, and a cluster best described as intermediate. A significant difference was found in the use of inshore and offshore habitats between West and East Falkland and between the two colonies with the largest sample sizes, both of which are located in East Falkland. However, habitat use was unrelated to the proximity of breeding colonies to the Patagonian Shelf, a region associated with enhanced biological productivity. Our study thus points towards other factors, such as local oceanography and its influence on resource distribution, playing a prominent role in inshore and offshore habitat use.
Brief communication
(2016)
In March 2015, a new international blueprint for disaster risk reduction (DRR) was adopted in Sendai, Japan, at the end of the Third UN World Conference on Disaster Risk Reduction (WCDRR, 14-18 March 2015). We review and discuss the agreed commitments and targets, as well as the negotiation leading the Sendai Framework for DRR (SF-DRR) and discuss briefly its implication for the later UN-led negotiations on sustainable development goals and climate change.
The extent of gene flow during the range expansion of non-native species influences the amount of genetic diversity retained in expanding populations. Here, we analyse the population genetic structure of the raccoon dog (Nyctereutes procyonoides) in north-eastern and central Europe. This invasive species is of management concern because it is highly susceptible to fox rabies and an important secondary host of the virus. We hypothesized that the large number of introduced animals and the species' dispersal capabilities led to high population connectivity and maintenance of genetic diversity throughout the invaded range. We genotyped 332 tissue samples from seven European countries using 16 microsatellite loci. Different algorithms identified three genetic clusters corresponding to Finland, Denmark and a large 'central' population that reached from introduction areas in western Russia to northern Germany. Cluster assignments provided evidence of long-distance dispersal. The results of an Approximate Bayesian Computation analysis supported a scenario of equal effective population sizes among different pre-defined populations in the large central cluster. Our results are in line with strong gene flow and secondary admixture between neighbouring demes leading to reduced genetic structuring, probably a result of its fairly rapid population expansion after introduction. The results presented here are remarkable in the sense that we identified a homogenous genetic cluster inhabiting an area stretching over more than 1500km. They are also relevant for disease management, as in the event of a significant rabies outbreak, there is a great risk of a rapid virus spread among raccoon dog populations.
Since 1998, elite athletes’ sport injuries have been monitored in single sport event, which leads to the development of first comprehensive injury surveillance system in multi-sport Olympic Games in 2008. However, injury and illness occurred in training phases have not been systematically studied due to its multi-facets, potentially interactive risk related factors. The present thesis aim to address issues of feasibility of establishing a validated measure for injury/illness, training environment and psychosocial risk factors by creating the evaluation tool namely risk of injury questionnaire (Risk-IQ) for elite athletes, which based on IOC consensus statement 2009 recommended content of preparticipation evaluation(PPE) and periodic health exam (PHE).
A total of 335 top level athletes and a total of 88 medical care providers from Germany and Taiwan participated in tow “cross-sectional plus longitudinal” Risk-IQ and MCPQ surveys respectively. Four categories of injury/illness related risk factors questions were asked in Risk-IQ for athletes while injury risk and psychological related questions were asked in MCPQ for MCP cohorts. Answers were quantified scales wise/subscales wise before analyzed with other factors/scales. In addition, adapted variables such as sport format were introduced for difference task of analysis.
Validated with 2-wyas translation and test-retest reliabilities, the Risk-IQ was proved to be in good standard which were further confirmed by analyzed results from official surveys in both Germany and Taiwan. The result of Risk-IQ revealed that elite athletes’ accumulated total injuries, in general, were multi-factor dependent; influencing factors including but not limited to background experiences, medical history, PHE and PPE medical resources as well as stress from life events. Injuries of different body parts were sport format and location specific. Additionally, medical support of PPE and PHE indicated significant difference between German and Taiwan.
The result of the present thesis confirmed that it is feasible to construct a comprehensive evalua-tion instrument for heterogeneous elite athletes cohorts’ risk factor analysis for injury/illness oc-curred during their non-competition periods. In average and with many moderators involved, Ger-man elite athletes have superior medical care support yet suffered more severe injuries than Tai-wanese counterparts. Opinions of injury related psychological issues reflected differently on vari-ous MCP groups irrespective of different nationalities. In general, influencing factors and interac-tions existed among relevant factors in both studies which implied further investigation with multiple regression analysis is needed for better understanding.
Background: Dementia is a psychiatric condition the development of which is associated with numerous aspects of life. Our aim was to estimate dementia risk factors in German primary care patients.
Methods: The case-control study included primary care patients (70-90 years) with first diagnosis of dementia (all-cause) during the index period (01/2010-12/2014) (Disease Analyzer, Germany), and controls without dementia matched (1:1) to cases on the basis of age, sex, type of health insurance, and physician. Practice visit records were used to verify that there had been 10 years of continuous follow-up prior to the index date. Multivariate logistic regression models were fitted with dementia as a dependent variable and the potential predictors.
Results: The mean age for the 11,956 cases and the 11,956 controls was 80.4 (SD: 5.3) years. 39.0% of them were male and 1.9% had private health insurance. In the multivariate regression model, the following variables were linked to a significant extent with an increased risk of dementia: diabetes (OR: 1.17; 95% CI: 1.10-1.24), lipid metabolism (1.07; 1.00-1.14), stroke incl. TIA (1.68; 1.57-1.80), Parkinson's disease (PD) (1.89; 1.64-2.19), intracranial injury (1.30; 1.00-1.70), coronary heart disease (1.06; 1.00-1.13), mild cognitive impairment (MCI) (2.12; 1.82-2.48), mental and behavioral disorders due to alcohol use (1.96; 1.50-2.57). The use of statins (OR: 0.94; 0.90-0.99), proton-pump inhibitors (PPI) (0.93; 0.90-0.97), and antihypertensive drugs (0.96, 0.94-0.99) were associated with a decreased risk of developing dementia.
Conclusions: Risk factors for dementia found in this study are consistent with the literature. Nevertheless, the associations between statin, PPI and antihypertensive drug use, and decreased risk of dementia need further investigations.
Reaching the Sustainable Development Goals requires a fundamental socio-economic transformation accompanied by substantial investment in low-carbon infrastructure. Such a sustainability transition represents a non-marginal change, driven by behavioral factors and systemic interactions. However, typical economic models used to assess a sustainability transition focus on marginal changes around a local optimum, whichby constructionlead to negative effects. Thus, these models do not allow evaluating a sustainability transition that might have substantial positive effects. This paper examines which mechanisms need to be included in a standard computable general equilibrium model to overcome these limitations and to give a more comprehensive view of the effects of climate change mitigation. Simulation results show that, given an ambitious greenhouse gas emission constraint and a price of carbon, positive economic effects are possible if (1) technical progress results (partly) endogenously from the model and (2) a policy intervention triggering an increase of investment is introduced. Additionally, if (3) the investment behavior of firms is influenced by their sales expectations, the effects are amplified. The results provide suggestions for policy-makers, because the outcome indicates that investment-oriented climate policies can lead to more desirable outcomes in economic, social and environmental terms.
Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother–child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 Â 10 À8 . In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.
Tracking changes in biodiversity through time requires an understanding of the relationship between modern diversity and how this diversity is preserved in the fossil record. Fossil pollen is one way in which past vegetation diversity can be reconstructed. However, there is limited understanding of modern pollen-vegetation diversity relationships from biodiverse tropical ecosystems. Here, pollen (palynological) richness and diversity (Hill N (1)) are compared with vegetation richness and diversity from forest and savannah ecosystems in the New World and Old World tropics (Neotropics and Palaeotropics). Modern pollen data were obtained from artificial pollen traps deployed in 1-ha vegetation study plots from which vegetation inventories had been completed in Bolivia and Ghana. Pollen counts were obtained from 15 to 22 traps per plot, and aggregated pollen sums for each plot were > 2,500. The palynological richness/diversity values from the Neotropics were moist evergreen forest = 86/6.8, semi-deciduous dry forest = 111/21.9, wooded savannah = 138/31.5, and from the Palaeotropics wet evergreen forest = 144/28.3, semi-deciduous moist forest = 104/4.4, forest-savannah transition = 121/14.1; the corresponding vegetation richness/diversity was 100/36.7, 80/38.7 and 71/39.4 (Neotropics), and 101/54.8, 87/45.5 and 71/34.5 (Palaeotropics). No consistent relationship was found between palynological richness/diversity, and plot vegetation richness/diversity, due to the differential influence of other factors such as landscape diversity, pollination strategy, and pollen source area. Palynological richness exceeded vegetation richness, while pollen diversity was lower than vegetation diversity. The relatively high global diversity of tropical vegetation was found to be reflected in the pollen rain.
Landscape and scale-dependent spatial niches of bats foraging above intensively used arable fields
(2017)
Introduction
Bats are threatened by agricultural intensification, and although bat ecology in agricultural landscapes is in the focus of current research, the effects of interacting spatiotemporal factors on species-specific bat activity above farmland remain understudied. Our aim was to identify spatiotemporal factors and their interactions relevant for the activity of bat species above conventionally managed arable fields.
Methods
We repeatedly monitored relative bat activity above open arable fields in Germany using acoustic monitoring. We used site-related biotic and abiotic factors and landscape characteristics across five spatial scales, their combinations, and interactions to identify those factors which best explain variation in bat activity.
Results
Numerous interactions between landscape characteristics and the insect abundance affected bat activity above fields. For instance, Pipistrellus pipistrellus became more active with increasing insect abundance, but only above fields with a low proportion of woody vegetation cover in the surroundings. Additionally, the level of bat activity in summer depended on landscape characteristics. For example, the activity of Pipistrellus nathusii was relatively low in summer above fields that were surrounded by vegetation patches with a high degree of edge complexity (e.g., hedgerow). However, the activity remained at a relatively high level and did not differ between seasons above fields that were surrounded by vegetation patches with a low degree of edge complexity (e.g., roundly shaped forest patch).
Conclusions
Our results revealed that landscape characteristics and their interactions with insect abundance affected bat activity above conventionally managed fields and highlighted the opportunistic foraging behavior of bats. To improve the conditions for bats in agricultural landscapes, we recommend re-establishing landscape heterogeneity to protect aquatic habitats and to increase arthropod availability.
Novel nanogels that possess the capacity to change their physico-chemical properties in response to external stimuli are promising drug-delivery candidates for the treatment of severe skin diseases. As thermoresponsive nanogels (tNGs) are capable of enhancing penetration through biological barriers such as the stratum corneum and are taken up by keratinocytes of human skin, potential adverse consequences of their exposure must be elucidated. In this study, tNGs were synthesized from dendritic polyglycerol (dPG) and two thermoresponsive polymers. tNG_dPG_tPG are the combination of dPG with poly(glycidyl methyl ether-co-ethyl glycidyl ether) (p(GME-co-EGE)) and tNG_dPG_pNIPAM the one with poly(N-isopropylacrylamide) (pNIPAM). Both thermoresponsive nanogels are able to incorporate high amounts of dexamethasone and tacrolimus, drugs used in the treatment of severe skin diseases. Cellular uptake, intracellular localization and the toxicological properties of the tNGs were comprehensively characterized in primary normal human keratinocytes (NHK) and in spontaneously transformed aneuploid immortal keratinocyte cell line from adult human skin (HaCaT). Laser scanning confocal microscopy revealed fluorescently labeled tNGs entered into the cells and localized predominantly within lysosomal compartments. MTT assay, comet assay and carboxy-H2DCFDA assay, demonstrated neither cytotoxic or genotoxic effects, nor any induction of reactive oxygen species of the tNGs in keratinocytes. In addition, both tNGs were devoid of eye irritation potential as shown by bovine corneal opacity and permeability (BCOP) test and red blood cell (RBC) hemolysis assay. Therefore, our study provides evidence that tNGs are locally well tolerated and underlines their potential for cutaneous drug delivery.
The dynamics of fragmentation and vibration of molecular systems with a large number of coupled degrees of freedom are key aspects for understanding chemical reactivity and properties. Here we present a resonant inelastic X-ray scattering (RIXS) study to show how it is possible to break down such a complex multidimensional problem into elementary components. Local multimode nuclear wave packets created by X-ray excitation to different core-excited potential energy surfaces (PESs) will act as spatial gates to selectively probe the particular ground-state vibrational modes and, hence, the PES along these modes. We demonstrate this principle by combining ultra-high resolution RIXS measurements for gas-phase water with state-of-the-art simulations.
In this combined theoretical and experimental study we report a full analysis of the resonant inelastic X-ray scattering (RIXS) spectra of H2O, D2O and HDO. We demonstrate that electronically-elastic RIXS has an inherent capability to map the potential energy surface and to perform vibrational analysis of the electronic ground state in multimode systems. We show that the control and selection of vibrational excitation can be performed by tuning the X-ray frequency across core-excited molecular bands and that this is clearly reflected in the RIXS spectra. Using high level ab initio electronic structure and quantum nuclear wave packet calculations together with high resolution RIXS measurements, we discuss in detail the mode coupling, mode localization and anharmonicity in the studied systems.
The Pathological Narcissism Inventory (PNI) is a multidimensional measure for assessing grandiose and vulnerable features in narcissistic pathology. The aim of the present research was to construct and validate a German translation of the PNI and to provide further information on the PNI's nomological net. Findings from a first study confirm the psychometric soundness of the PNI and replicate its seven-factor first-order structure. A second-order structure was also supported but with several equivalent models. A second study investigating associations with a broad range of measures (DSM Axis I and II constructs, emotions, personality traits, interpersonal and dysfunctional behaviors, and well-being) supported the concurrent validity of the PNI. Discriminant validity with the Narcissistic Personality Inventory was also shown. Finally, in a third study an extension in a clinical inpatient sample provided further evidence that the PNI is a useful tool to assess the more pathological end of narcissism.
Climate or land use?
(2017)
This study intends to contribute to the ongoing discussion on whether land use and land cover changes (LULC) or climate trends have the major influence on the observed increase of flood magnitudes in the Sahel. A simulation-based approach is used for attributing the observed trends to the postulated drivers. For this purpose, the ecohydrological model SWIM (Soil and Water Integrated Model) with a new, dynamic LULC module was set up for the Sahelian part of the Niger River until Niamey, including the main tributaries Sirba and Goroul. The model was driven with observed, reanalyzed climate and LULC data for the years 1950–2009. In order to quantify the shares of influence, one simulation was carried out with constant land cover as of 1950, and one including LULC. As quantitative measure, the gradients of the simulated trends were compared to the observed trend. The modeling studies showed that for the Sirba River only the simulation which included LULC was able to reproduce the observed trend. The simulation without LULC showed a positive trend for flood magnitudes, but underestimated the trend significantly. For the Goroul River and the local flood of the Niger River at Niamey, the simulations were only partly able to reproduce the observed trend. In conclusion, the new LULC module enabled some first quantitative insights into the relative influence of LULC and climatic changes. For the Sirba catchment, the results imply that LULC and climatic changes contribute in roughly equal shares to the observed increase in flooding. For the other parts of the subcatchment, the results are less clear but show, that climatic changes and LULC are drivers for the flood increase; however their shares cannot be quantified. Based on these modeling results, we argue for a two-pillar adaptation strategy to reduce current and future flood risk: Flood mitigation for reducing LULC-induced flood increase, and flood adaptation for a general reduction of flood vulnerability.
The "Lomonosov" space project is lead by Lomonosov Moscow State University in collaboration with the following key partners: Joint Institute for Nuclear Research, Russia, University of California, Los Angeles (USA), University of Pueblo (Mexico), Sungkyunkwan University (Republic of Korea) and with Russian space industry organi-zations to study some of extreme phenomena in space related to astrophysics, astroparticle physics, space physics, and space biology. The primary goals of this experiment are to study:
-Ultra-high energy cosmic rays (UHECR) in the energy range of the Greizen-ZatsepinKuzmin (GZK) cutoff;
-Ultraviolet (UV) transient luminous events in the upper atmosphere;
-Multi-wavelength study of gamma-ray bursts in visible, UV, gamma, and X-rays;
-Energetic trapped and precipitated radiation (electrons and protons) at low-Earth orbit (LEO) in connection with global geomagnetic disturbances;
-Multicomponent radiation doses along the orbit of spacecraft under different geomagnetic conditions and testing of space segments of optical observations of space-debris and other space objects;
-Instrumental vestibular-sensor conflict of zero-gravity phenomena during space flight.
This paper is directed towards the general description of both scientific goals of the project and scientific equipment on board the satellite. The following papers of this issue are devoted to detailed descriptions of scientific instruments.
Rehabilitation after autologous chondrocyte implantation for isolated cartilage defects of the knee
(2017)
Autologous chondrocyte implantation for treatment of isolated cartilage defects of the knee has become well established. Although various publications report technical modifications, clinical results, and cell-related issues, little is known about appropriate and optimal rehabilitation after autologous chondrocyte implantation. This article reviews the literature on rehabilitation after autologous chondrocyte implantation and presents a rehabilitation protocol that has been developed considering the best available evidence and has been successfully used for several years in a large number of patients who underwent autologous chondrocyte implantation for cartilage defects of the knee.
Salt marshes filter pollutants, protect coastlines against storm surges, and sequester carbon, yet are under threat from sea level rise and anthropogenic modification. The sustained existence of the salt marsh ecosystem depends on the topographic evolution of marsh platforms. Quantifying marsh platform topography is vital for improving the management of these valuable landscapes. The determination of platform boundaries currently relies on supervised classification methods requiring near-infrared data to detect vegetation, or demands labour-intensive field surveys and digitisation. We propose a novel, unsupervised method to reproducibly isolate salt marsh scarps and platforms from a digital elevation model (DEM), referred to as Topographic Identification of Platforms (TIP). Field observations and numerical models show that salt marshes mature into subhorizontal platforms delineated by subvertical scarps. Based on this premise, we identify scarps as lines of local maxima on a slope raster, then fill landmasses from the scarps upward, thus isolating mature marsh platforms. We test the TIP method using lidar-derived DEMs from six salt marshes in England with varying tidal ranges and geometries, for which topographic platforms were manually isolated from tidal flats. Agreement between manual and unsupervised classification exceeds 94% for DEM resolutions of 1 m, with all but one site maintaining an accuracy superior to 90% for resolutions up to 3 m. For resolutions of 1 m, platforms detected with the TIP method are comparable in surface area to digitised platforms and have similar elevation distributions. We also find that our method allows for the accurate detection of local block failures as small as 3 times the DEM resolution. Detailed inspection reveals that although tidal creeks were digitised as part of the marsh platform, unsupervised classification categorises them as part of the tidal flat, causing an increase in false negatives and overall platform perimeter. This suggests our method may benefit from combination with existing creek detection algorithms. Fallen blocks and high tidal flat portions, associated with potential pioneer zones, can also lead to differences between our method and supervised mapping. Although pioneer zones prove difficult to classify using a topographic method, we suggest that these transition areas should be considered when analysing erosion and accretion processes, particularly in the case of incipient marsh platforms. Ultimately, we have shown that unsupervised classification of marsh platforms from high-resolution topography is possible and sufficient to monitor and analyse topographic evolution.
With the growing size and use of night light time series from the Visible Infrared Imaging Radiometer Suite Day/Night Band (DNB), it is important to understand the stability of the dataset. All satellites observe differences in pixel values during repeat observations. In the case of night light data, these changes can be due to both environmental effects and changes in light emission. Here we examine the stability of individual locations of particular large scale light sources (e.g., airports and prisons) in the monthly composites of DNB data from April 2012 to September 2017. The radiances for individual pixels of most large light emitters are approximately normally distributed, with a standard deviation of typically 15-20% of the mean. Greenhouses and flares, however, are not stable sources. We observe geospatial autocorrelation in the monthly variations for nearby sites, while the correlation for sites separated by large distances is small. This suggests that local factors contribute most to the variation in the pixel radiances and furthermore that averaging radiances over large areas will reduce the total variation. A better understanding of the causes of temporal variation would improve the sensitivity of DNB to lighting changes.
X-ray free-electron lasers (XFELs) and table-top sources of x-rays based upon high harmonic generation (HHG) have revolutionized the field of ultrafast x-ray atomic and molecular physics, largely due to an explosive growth in capabilities in the past decade. XFELs now provide unprecedented intensity (1020 W cm−2) of x-rays at wavelengths down to ~1 Ångstrom, and HHG provides unprecedented time resolution (~50 attoseconds) and a correspondingly large coherent bandwidth at longer wavelengths. For context, timescales can be referenced to the Bohr orbital period in hydrogen atom of 150 attoseconds and the hydrogen-molecule vibrational period of 8 femtoseconds; wavelength scales can be referenced to the chemically significant carbon K-edge at a photon energy of ~280 eV (44 Ångstroms) and the bond length in methane of ~1 Ångstrom. With these modern x-ray sources one now has the ability to focus on individual atoms, even when embedded in a complex molecule, and view electronic and nuclear motion on their intrinsic scales (attoseconds and Ångstroms). These sources have enabled coherent diffractive imaging, where one can image non-crystalline objects in three dimensions on ultrafast timescales, potentially with atomic resolution. The unprecedented intensity available with XFELs has opened new fields of multiphoton and nonlinear x-ray physics where behavior of matter under extreme conditions can be explored. The unprecedented time resolution and pulse synchronization provided by HHG sources has kindled fundamental investigations of time delays in photoionization, charge migration in molecules, and dynamics near conical intersections that are foundational to AMO physics and chemistry. This roadmap coincides with the year when three new XFEL facilities, operating at Ångstrom wavelengths, opened for users (European XFEL, Swiss-FEL and PAL-FEL in Korea) almost doubling the present worldwide number of XFELs, and documents the remarkable progress in HHG capabilities since its discovery roughly 30 years ago, showcasing experiments in AMO physics and other applications. Here we capture the perspectives of 17 leading groups and organize the contributions into four categories: ultrafast molecular dynamics, multidimensional x-ray spectroscopies; high-intensity x-ray phenomena; attosecond x-ray science.
Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies.
E-Learning Symposium 2018
(2018)
In den vergangenen Jahren sind viele E-Learning-Innovationen entstanden. Einige davon wurden auf den vergangenen E-Learning Symposien der Universität Potsdam präsentiert: Das erste E-Learning Symposium im Jahr 2012 konzentrierte sich auf unterschiedliche Möglichkeiten der Studierendenaktivierung und Lehrgestaltung. Das Symposium 2014 rückte vor allem die Studierenden ins Zentrum der Aufmerksamkeit. Im Jahr 2016 kam es durch das Zusammengehen des Symposiums mit der DeLFI-Tagung zu einer Fokussierung auf technische Innovationen. Doch was ist aus den Leuchttürmen von gestern geworden, und brauchen wir überhaupt noch neue Leuchttürme? Das Symposium setzt sich in diesem Jahr unter dem Motto „Innovation und Nachhaltigkeit – (k)ein Gegensatz?“ mit mediengestützten Lehr- und Lernprozessen im universitären Kontext auseinander und reflektiert aktuelle technische sowie didaktische Entwicklungen mit Blick auf deren mittel- bis langfristigen Einsatz in der Praxis.
Dieser Tagungsband zum E-Learning Symposium 2018 an der Universität Potsdam beinhaltet eine Mischung von Forschungs- und Praxisbeiträgen aus verschiedenen Fachdisziplinen und eröffnet vielschichtige Perspektiven auf das Thema E-Learning. Dabei werden die Vielfalt der didaktischen Einsatzszenarien als auch die Potentiale von Werk-zeugen und Methoden der Informatik in ihrem Zusammenspiel beleuchtet.
In seiner Keynote widmet sich Reinhard Keil dem Motto des Symposiums und geht der Nachhaltigkeit bei E-Learning-Projekten auf den Grund. Dabei analysiert und beleuchtet er anhand seiner über 15-jährigen Forschungspraxis die wichtigsten Wirkfaktoren und formuliert Empfehlungen zur Konzeption von E-Learning-Projekten. Im Gegensatz zu rein auf Kostenersparnis ausgerichteten (hochschul-)politischen Forderungen proklamiert er den Ansatz der hypothesengeleiteten Technikgestaltung, in der Nachhaltigkeit als Leitfrage oder Forschungsstrategie verstanden werden kann. In eine ähnliche Richtung geht der Beitrag von Iris Braun et al., die über Erfolgsfaktoren beim Einsatz von Audience Response Systemen in der universitären Lehre berichten.
Ein weiteres aktuelles Thema, sowohl für die Bildungstechnologie als auch in den Bildungswissenschaften allgemein, ist die Kompetenzorientierung und –modellierung. Hier geht es darum (Problemlöse-)Fähigkeiten gezielt zu beschreiben und in den Mittelpunkt der Lehre zu stellen. Johannes Konert stellt in einem eingeladenen Vortrag zwei Projekte vor, die den Prozess beginnend bei der Definition von Kompetenzen, deren Modellierung in einem semantischen maschinenlesbaren Format bis hin zur Erarbeitung von Methoden zur Kompetenzmessung und der elektronischen Zertifizierung aufzeigen. Dabei geht er auf technische Möglichkeiten, aber auch Grenzen ein. Auf einer spezifischeren Ebene beschäftigt sich Sarah Stumpf mit digitalen bzw. mediendidaktischen Kompetenzen im Lehramtsstudium und stellt ein Framework für die Förderung ebensolcher Kompetenzen bei angehenden Lehrkräften vor.
Der Einsatz von E-Learning birgt noch einige Herausforderungen. Dabei geht es oft um die Verbindung von Didaktik und Technik, den Erhalt von Aufmerksamkeit oder den Aufwand für das Erstellen von interaktiven Lehr- und Lerninhalten. Drei Beiträge in diesem Tagungsband beschäftigen sich mit dieser Thematik in unterschiedlichen Kontexten und zeigen Best-Practices und Lösungsansätze auf: Der Beitrag von Martina Wahl und Michael Hölscher behandelt den besonderen Kontext von Blended Learning-Szenarien in berufsbegleitenden Studiengängen. Um die Veröffentlichung eines global frei verfügbaren Onlinekurses abseits der großen MOOC Plattformen und den didaktischen Herausforderungen auch hinsichtlich der Motivation geht es im Beitrag von Ennio Marani und Isabel Jaisli. Schließlich schlagen Gregor Damnik et al. die automatische Erzeugung von Aufgaben zur Erhöhung von Interaktivität und Adaptivität in digitalen Lernressourcen vor, um den teilweise erheblichen Erstellungsaufwand zu reduzieren.
Zum Thema E-Learning zählen auch immer mobile Apps bzw. Spiele. Gleich zwei Beiträge beschäftigen sich mit dem Einsatz von E-Learning-Tools im Gesundheitskontext: Anna Tscherejkina und Anna Morgiel stellen in ihrem Beitrag Minispiele zum Training von sozio-emotionalen Kompetenzen für Menschen mit Autismus vor, und Stephanie Herbstreit et al. berichten vom Einsatz einer mobilen Lern-App zur Verbesserung von klinisch-praktischem Unterricht.
Retrieval of water constituents from hyperspectral in-situ measurements under variable cloud cover
(2018)
Remote sensing and field spectroscopy of natural waters is typically performed under clear skies, low wind speeds and low solar zenith angles. Such measurements can also be made, in principle, under clouds and mixed skies using airborne or in-situ measurements; however, variable illumination conditions pose a challenge to data analysis. In the present case study, we evaluated the inversion of hyperspectral in-situ measurements for water constituent retrieval acquired under variable cloud cover. First, we studied the retrieval of Chlorophyll-a (Chl-a) concentration and colored dissolved organic matter (CDOM) absorption from in-water irradiance measurements. Then, we evaluated the errors in the retrievals of the concentration of total suspended matter (TSM), Chl-a and the absorption coefficient of CDOM from above-water reflectance measurements due to highly variable reflections at the water surface. In order to approximate cloud reflections, we extended a recent three-component surface reflectance model for cloudless atmospheres by a constant offset and compared different surface reflectance correction procedures. Our findings suggest that in-water irradiance measurements may be used for the analysis of absorbing compounds even under highly variable weather conditions. The extended surface reflectance model proved to contribute to the analysis of above-water reflectance measurements with respect to Chl-a and TSM. Results indicate the potential of this approach for all-weather monitoring.
Recovering genomics clusters of secondary metabolites from lakes using genome-resolved metagenomics
(2018)
Metagenomic approaches became increasingly popular in the past decades due to decreasing costs of DNA sequencing and bioinformatics development. So far, however, the recovery of long genes coding for secondary metabolites still represents a big challenge. Often, the quality of metagenome assemblies is poor, especially in environments with a high microbial diversity where sequence coverage is low and complexity of natural communities high. Recently, new and improved algorithms for binning environmental reads and contigs have been developed to overcome such limitations. Some of these algorithms use a similarity detection approach to classify the obtained reads into taxonomical units and to assemble draft genomes. This approach, however, is quite limited since it can classify exclusively sequences similar to those available (and well classified) in the databases. In this work, we used draft genomes from Lake Stechlin, north-eastern Germany, recovered by MetaBat, an efficient binning tool that integrates empirical probabilistic distances of genome abundance, and tetranucleotide frequency for accurate metagenome binning. These genomes were screened for secondary metabolism genes, such as polyketide synthases (PKS) and non-ribosomal peptide synthases (NRPS), using the Anti-SMASH and NAPDOS workflows. With this approach we were able to identify 243 secondary metabolite clusters from 121 genomes recovered from our lake samples. A total of 18 NRPS, 19 PKS, and 3 hybrid PKS/NRPS clusters were found. In addition, it was possible to predict the partial structure of several secondary metabolite clusters allowing for taxonomical classifications and phylogenetic inferences. Our approach revealed a high potential to recover and study secondary metabolites genes from any aquatic ecosystem.
Cells and organelles are not homogeneous but include microcompartments that alter the spatiotemporal characteristics of cellular processes. The effects of microcompartmentation on metabolic pathways are however difficult to study experimentally. The pyrenoid is a microcompartment that is essential for a carbon concentrating mechanism (CCM) that improves the photosynthetic performance of eukaryotic algae. Using Chlamydomonas reinhardtii, we obtained experimental data on photosynthesis, metabolites, and proteins in CCM-induced and CCM-suppressed cells. We then employed a computational strategy to estimate how fluxes through the Calvin-Benson cycle are compartmented between the pyrenoid and the stroma. Our model predicts that ribulose-1,5-bisphosphate (RuBP), the substrate of Rubisco, and 3-phosphoglycerate (3PGA), its product, diffuse in and out of the pyrenoid, respectively, with higher fluxes in CCM-induced cells. It also indicates that there is no major diffusional barrier to metabolic flux between the pyrenoid and stroma. Our computational approach represents a stepping stone to understanding microcompartmentalized CCM in other organisms.
Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.
Understanding of wave environments is critical for the understanding of how particles are accelerated and lost in space. This study shows that in the vicinity of Europa and Ganymede, that respectively have induced and internal magnetic fields, chorus wave power is significantly increased. The observed enhancements are persistent and exceed median values of wave activity by up to 6 orders of magnitude for Ganymede. Produced waves may have a pronounced effect on the acceleration and loss of particles in the Jovian magnetosphere and other astrophysical objects. The generated waves are capable of significantly modifying the energetic particle environment, accelerating particles to very high energies, or producing depletions in phase space density. Observations of Jupiter's magnetosphere provide a unique opportunity to observe how objects with an internal magnetic field can interact with particles trapped in magnetic fields of larger scale objects.
Extreme weather resilience has been defined as being based on three pillars: resistance (the ability to lower impacts), recovery (the ability to bounce back), and adaptive capacity (the ability to learn and improve). These resilience pillars are important both before and after the occurrence of extreme weather events. Extreme weather insurance can influence these pillars of resilience depending on how particular insurance mechanisms are structured. We explore how the lessons learnt from the current best insurance practices can improve resilience to extreme weather events. We employ an extensive inventory of private property and agricultural crop insurance mechanisms to conduct a multi-criteria analysis of insurance market outcomes. We draw conclusions regarding the patterns in the best practice from six European countries to increase resilience. We suggest that requirements to buy a bundle extreme weather event insurance with general insurance packages are strengthened and supported with structures to financing losses through public-private partnerships. Moreover, support for low income households through income vouchers could be provided. Similarly, for the agricultural sector we propose moving towards comprehensive crop yield insurance linked to general agricultural subsidies. In both cases a nationally representative body can coordinate the various stakeholders into acting in concert.