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In Germany, active bat rabies surveillance was conducted between 1993 and 2012. A total of 4546 oropharyngeal swab samples from 18 bat species were screened for the presence of EBLV-1- , EBLV-2- and BBLV-specific RNA. Overall, 0 center dot 15% of oropharyngeal swab samples tested EBLV-1 positive, with the majority originating from Eptesicus serotinus. Interestingly, out of seven RT-PCR-positive oropharyngeal swabs subjected to virus isolation, viable virus was isolated from a single serotine bat (E. serotinus). Additionally, about 1226 blood samples were tested serologically, and varying virus neutralizing antibody titres were found in at least eight different bat species. The detection of viral RNA and seroconversion in repeatedly sampled serotine bats indicates long-term circulation of the virus in a particular bat colony. The limitations of random-based active bat rabies surveillance over passive bat rabies surveillance and its possible application of targeted approaches for future research activities on bat lyssavirus dynamics and maintenance are discussed.
Passive and active polarization elements were created by surface and bulk photo-alignment of LCs, reactive LCs, photo-sensitive LCP and photo-curable monomer/LC composites. The use of different photo-sensitive liquid crystalline materials for the development of highly anisotropic elements with high spatial resolution and stability or, alternatively, fast switch ability will be discussed. Photo-active and voltage tunable polarization and diffraction elements are presented. For active micro-optic application a photo-addressed patterned retarder was created. Electrically switchable diffraction gratings were generated by interference exposure of photo-curable LC composites at room temperature characterized by droplet free morphology. These polarization sensitive diffraction elements are characterized be excellent optical properties and low switching times.
The new generation of solar instruments provides better spectral, spatial, and temporal resolution for a better understanding of the physical processes that take place on the Sun. Multiple-component profiles are more commonly observed with these instruments. Particularly, the He i 10830 triplet presents such peculiar spectral profiles, which give information on the velocity and magnetic fine structure of the upper chromosphere. The purpose of this investigation is to describe a technique to efficiently fit the two blended components of the He i 10830 triplet, which are commonly observed when two atmospheric components are located within the same resolution element. The observations used in this study were taken on 2015 April 17 with the very fast spectroscopic mode of the GREGOR Infrared Spectrograph (GRIS) attached to the 1.5-m GREGOR solar telescope, located at the Observatorio del Teide, Tenerife, Spain. We apply a double-Lorentzian fitting technique using Levenberg-Marquardt least-squares minimization. This technique is very simple and much faster than inversion codes. Line-of-sight Doppler velocities can be inferred for a whole map of pixels within just a few minutes. Our results show sub-and supersonic downflow velocities of up to 32 km s(-1) for the fast component in the vicinity of footpoints of filamentary structures. The slow component presents velocities close to rest. (C) 2016 WILEY-VCH Verlag GmbH& Co. KGaA, Weinheim
Improved measurements of the photospheric and chromospheric three-dimensional magnetic and flow fields are crucial for a precise determination of the origin and evolution of active regions. We present an illustrative sample of multi-instrument data acquired during a two-week coordinated observing campaign in August 2015 involving, among others, the GREGOR solar telescope (imaging and near-infrared spectroscopy) and the space missions Solar Dynamics Observatory (SDO) and Interface Region Imaging Spectrograph (IRIS). The observations focused on the trailing part of active region NOAA 12396 with complex polarity inversion lines and strong intrusions of opposite polarity flux. The GREGOR Infrared Spectrograph (GRIS) provided Stokes IQUV spectral profiles in the photospheric Si i.1082.7 nm line, the chromospheric He I lambda 1083.0 nm triplet, and the photospheric Ca I lambda 1083.9 nm line. Carefully calibrated GRIS scans of the active region provided maps of Doppler velocity and magnetic field at different atmospheric heights. We compare quick-look maps with those obtained with the " Stokes Inversions based on Response functions" (SIR) code, which furnishes deeper insight into the magnetic properties of the region. We find supporting evidence that newly emerging flux and intruding opposite polarity flux are hampering the formation of penumbrae, i.e., a penumbra fully surrounding a sunspot is only expected after cessation of flux emergence in proximity to the sunspots. (C) 2016 WILEY-VCH Verlag GmbH& Co.KGaA, Weinheim
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.
In order to predict which ecosystem functions are most at risk from biodiversity loss, meta-analyses have generalised results from biodiversity experiments over different sites and ecosystem types. In contrast, comparing the strength of biodiversity effects across a large number of ecosystem processes measured in a single experiment permits more direct comparisons. Here, we present an analysis of 418 separate measures of 38 ecosystem processes. Overall, 45 % of processes were significantly affected by plant species richness, suggesting that, while diversity affects a large number of processes not all respond to biodiversity. We therefore compared the strength of plant diversity effects between different categories of ecosystem processes, grouping processes according to the year of measurement, their biogeochemical cycle, trophic level and compartment (above- or belowground) and according to whether they were measures of biodiversity or other ecosystem processes, biotic or abiotic and static or dynamic. Overall, and for several individual processes, we found that biodiversity effects became stronger over time. Measures of the carbon cycle were also affected more strongly by plant species richness than were the measures associated with the nitrogen cycle. Further, we found greater plant species richness effects on measures of biodiversity than on other processes. The differential effects of plant diversity on the various types of ecosystem processes indicate that future research and political effort should shift from a general debate about whether biodiversity loss impairs ecosystem functions to focussing on the specific functions of interest and ways to preserve them individually or in combination.
Land-use intensification is a key driver of biodiversity change. However, little is known about how it alters relationships between the diversities of different taxonomic groups, which are often correlated due to shared environmental drivers and trophic interactions. Using data from 150 grassland sites, we examined how land-use intensification (increased fertilization, higher livestock densities, and increased mowing frequency) altered correlations between the species richness of 15 plant, invertebrate, and vertebrate taxa. We found that 54% of pairwise correlations between taxonomic groups were significant and positive among all grasslands, while only one was negative. Higher land-use intensity substantially weakened these correlations(35% decrease in rand 43% fewer significant pairwise correlations at high intensity), a pattern which may emerge as a result of biodiversity declines and the breakdown of specialized relationships in these conditions. Nevertheless, some groups (Coleoptera, Heteroptera, Hymenoptera and Orthoptera) were consistently correlated with multidiversity, an aggregate measure of total biodiversity comprised of the standardized diversities of multiple taxa, at both high and lowland-use intensity. The form of intensification was also important; increased fertilization and mowing frequency typically weakened plant-plant and plant-primary consumer correlations, whereas grazing intensification did not. This may reflect decreased habitat heterogeneity under mowing and fertilization and increased habitat heterogeneity under grazing. While these results urge caution in using certain taxonomic groups to monitor impacts of agricultural management on biodiversity, they also suggest that the diversities of some groups are reasonably robust indicators of total biodiversity across a range of conditions.
Intermolecular charge-transfer states at the interface between electron donating (D) and accepting (A) materials are crucial for the operation of organic solar cells but can also be exploited for organic light-emitting diodes(1,2). Non-radiative charge-transfer state decay is dominant in state-of-the-art D-A-based organic solar cells and is responsible for large voltage losses and relatively low power-conversion efficiencies as well as electroluminescence external quantum yields in the 0.01-0.0001% range(3,4). In contrast, the electroluminescence external quantum yield reaches up to 16% in D-A-based organic light-emitting diodes(5-7). Here, we show that proper control of charge-transfer state properties allows simultaneous occurrence of a high photovoltaic and emission quantum yield within a single, visible-light-emitting D-A system. This leads to ultralow-emission turn-on voltages as well as significantly reduced voltage losses upon solar illumination. These results unify the description of the electro-optical properties of charge-transfer states in organic optoelectronic devices and foster the use of organic D-A blends in energy conversion applications involving visible and ultraviolet photons(8-11).