Analysis of 1,000+ Type-Strain Genomes Substantially Improves Taxonomic Classification of Alphaproteobacteria.

The class Alphaproteobacteria is comprised of a diverse assemblage of Gram-negative bacteria that includes organisms of varying morphologies, physiologies and habitat preferences many of which are of clinical and ecological importance. Alphaproteobacteria classification has proved to be difficult, not least when taxonomic decisions rested heavily on a limited number of phenotypic features and interpretation of poorly resolved 16S rRNA gene trees. Despite progress in recent years regarding the classification of bacteria assigned to the class, there remains a need to further clarify taxonomic relationships. Here, draft genome sequences of a collection of genomes of more than 1000 Alphaproteobacteria and outgroup type strains were used to infer phylogenetic trees from genome-scale data using the principles drawn from phylogenetic systematics. The majority of taxa were found to be monophyletic but several orders, families and genera, including taxa recognized as problematic long ago but also quite recent taxa, as well as a few species were shown to be in need of revision. According proposals are made for the recognition of new orders, families and genera, as well as the transfer of a variety of species to other genera and of a variety of genera to other families. In addition, emended descriptions are given for many species mainly involving information on DNA G+C content and (approximate) genome size, both of which are confirmed as valuable taxonomic markers. Similarly, analysis of the gene content was shown to provide valuable taxonomic insights in the class. Significant incongruities between 16S rRNA gene and whole genome trees were not found in the class. The incongruities that became obvious when comparing the results of the present study with existing classifications appeared to be caused mainly by insufficiently resolved 16S rRNA gene trees or incomplete taxon sampling. Another probable cause of misclassifications in the past is the partially low overall fit of phenotypic characters to the sequence-based tree. Even though a significant degree of phylogenetic conservation was detected in all characters investigated, the overall fit to the tree varied considerably

Potential of Airborne LiDAR Derived Vegetation Structure for the Prediction of Animal Species Richness at Mount Kilimanjaro

The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results

Electronic excitations of α- Fe2 O3 heteroepitaxial films measured by resonant inelastic x-ray scattering at the Fe L edge

Resonant inelastic x-ray scattering (RIXS) spectra of hematite (α-Fe2O3) were measured at the Fe L3 edge for heteroepitaxial thin films which were undoped and doped with 1% Ti, Sn, or Zn, in the energy-loss range in excess of 1 eV to study electronic transitions. The spectra were measured for several momentum transfers q, conducted at both low temperature (T=14 K) and room temperature. While we cannot rule out dispersive features possibly owing to propagating excitations, the coarse envelopes of the general spectra did not appreciably change shape with q, implying that the bulk of the observed L-edge RIXS intensity originates from (mostly) nondispersive ligand field excitations. Summing the RIXS spectra over q and comparing the results at T=14 K to those at T=300 K revealed pronounced temperature effects, including an intensity change and energy shift of the ≈1.4 eV peak, a broadband intensity increase of the 3-4 eV range, and higher energy features. The q-summed spectra and their temperature dependencies are virtually identical for nearly all of the samples with different dopants, save for the temperature dependence of the Ti-doped sample's spectrum, which we attribute to being affected by a large number of free charge carriers. Comparing with magnetization measurements for different temperatures and dopings likewise did not show a clear correlation between the RIXS spectra and the magnetic ordering states. To clarify the excited states, we performed spin multiplet calculations which were in excellent agreement with the RIXS spectra over a wide energy range and provide detailed electronic descriptions of the excited states. The implications of these findings to the photoconversion efficiency of hematite photoanodes is discussed

Predicting solar cell performance from terahertz and microwave spectroscopy

Mobilities and lifetimes of photogenerated charge carriers are core properties of photovoltaic materials and can both be characterized by contactless terahertz or microwave measurements. Here, the expertise from fifteen laboratories is combined to quantitatively model the current-voltage characteristics of a solar cell from such measurements. To this end, the impact of measurement conditions, alternate interpretations, and experimental inter-laboratory variations are discussed using a (Cs,FA,MA)Pb(I,Br)3 halide perovskite thin-film as a case study. At 1 sun equivalent excitation, neither transport nor recombination is significantly affected by exciton formation or trapping. Terahertz, microwave, and photoluminescence transients for the neat material yield consistent effective lifetimes implying a resistance-free JV-curve with a potential power conversion efficiency of 24.6 %. For grainsizes above ≈20 nm, intra-grain charge transport is characterized by terahertz sum mobilities of ≈32 cm2 V−1 s−1. Drift-diffusion simulations indicate that these intra-grain mobilities can slightly reduce the fill factor of perovskite solar cells to 0.82, in accordance with the best-realized devices in the literature. Beyond perovskites, this work can guide a highly predictive characterization of any emerging semiconductor for photovoltaic or photoelectrochemical energy conversion. A best practice for the interpretation of terahertz and microwave measurements on photovoltaic materials is presented

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Analysis of 1,000+ Type-Strain Genomes Substantially Improves Taxonomic Classification of Alphaproteobacteria.

The class Alphaproteobacteria is comprised of a diverse assemblage of Gram-negative bacteria that includes organisms of varying morphologies, physiologies and habitat preferences many of which are of clinical and ecological importance. Alphaproteobacteria classification has proved to be difficult, not least when taxonomic decisions rested heavily on a limited number of phenotypic features and interpretation of poorly resolved 16S rRNA gene trees. Despite progress in recent years regarding the classification of bacteria assigned to the class, there remains a need to further clarify taxonomic relationships. Here, draft genome sequences of a collection of genomes of more than 1000 Alphaproteobacteria and outgroup type strains were used to infer phylogenetic trees from genome-scale data using the principles drawn from phylogenetic systematics. The majority of taxa were found to be monophyletic but several orders, families and genera, including taxa recognized as problematic long ago but also quite recent taxa, as well as a few species were shown to be in need of revision. According proposals are made for the recognition of new orders, families and genera, as well as the transfer of a variety of species to other genera and of a variety of genera to other families. In addition, emended descriptions are given for many species mainly involving information on DNA G+C content and (approximate) genome size, both of which are confirmed as valuable taxonomic markers. Similarly, analysis of the gene content was shown to provide valuable taxonomic insights in the class. Significant incongruities between 16S rRNA gene and whole genome trees were not found in the class. The incongruities that became obvious when comparing the results of the present study with existing classifications appeared to be caused mainly by insufficiently resolved 16S rRNA gene trees or incomplete taxon sampling. Another probable cause of misclassifications in the past is the partially low overall fit of phenotypic characters to the sequence-based tree. Even though a significant degree of phylogenetic conservation was detected in all characters investigated, the overall fit to the tree varied considerably

Carrier localization on the nanometer-scale limits transport in metal oxide photoabsorbers

Metal oxides are considered as stable and low-cost photoelectrode candidates for hydrogen production by photoelectrochemical solar water splitting. However, their power conversion efficiencies usually suffer from poor transport of photogenerated charge carriers, which has been attributed previously to a variety of effects occurring on different time and length scales. In search for common understanding and for a better photo-conducting metal oxide photoabsorber, CuFeO2, α-SnWO4, BaSnO3, FeVO4, CuBi2O4, α-Fe2O3, and BiVO4 are compared. Their kinetics of thermalization, trapping, localization, and recombination are monitored continuously 100 fs–100 µs and mobilities are determined for different probing lengths by combined time-resolved terahertz and microwave spectroscopy. As common issue, we find small mobilities < 3 cm2V-1s-1. Partial carrier localization further slows carrier diffusion beyond localization lengths of 1–6 nm and explains the extraordinarily long conductivity tails, which should not be taken as a sign of long diffusion lengths. For CuFeO2, the localization is attributed to electrostatic barriers that enclose the crystallographic domains. The most promising novel material is BaSnO3, which exhibits the highest mobility after reducing carrier localization by annealing in H2. Such overcoming of carrier localization should be an objective of future efforts to enhance charge transport in metal oxides.Published versionThe authors acknowledge the financial support for this work from the Helmholtz International Research School "Hybrid Integrated Systems for Conversion of Solar Energy" (HI-SCORE), an initiative co-funded by the Initiative and Networking Fund of the Helmholtz Association (HIRS-0008). M.K. acknowledges funding from the German Bundesministerium fuer Bildung and Forschung (BMBF), project "H2Demo" (no. 03SF0619K). We acknowledge Avner Rothschild for providing lab facilities at the Technion. Open access funding enabled and organized by Projekt DEAL

Electronic excitations of α- Fe2 O3 heteroepitaxial films measured by resonant inelastic x-ray scattering at the Fe L edge

Resonant inelastic x-ray scattering (RIXS) spectra of hematite (α-Fe2O3) were measured at the Fe L3 edge for heteroepitaxial thin films which were undoped and doped with 1% Ti, Sn, or Zn, in the energy-loss range in excess of 1 eV to study electronic transitions. The spectra were measured for several momentum transfers q, conducted at both low temperature (T=14 K) and room temperature. While we cannot rule out dispersive features possibly owing to propagating excitations, the coarse envelopes of the general spectra did not appreciably change shape with q, implying that the bulk of the observed L-edge RIXS intensity originates from (mostly) nondispersive ligand field excitations. Summing the RIXS spectra over q and comparing the results at T=14 K to those at T=300 K revealed pronounced temperature effects, including an intensity change and energy shift of the ≈1.4 eV peak, a broadband intensity increase of the 3-4 eV range, and higher energy features. The q-summed spectra and their temperature dependencies are virtually identical for nearly all of the samples with different dopants, save for the temperature dependence of the Ti-doped sample's spectrum, which we attribute to being affected by a large number of free charge carriers. Comparing with magnetization measurements for different temperatures and dopings likewise did not show a clear correlation between the RIXS spectra and the magnetic ordering states. To clarify the excited states, we performed spin multiplet calculations which were in excellent agreement with the RIXS spectra over a wide energy range and provide detailed electronic descriptions of the excited states. The implications of these findings to the photoconversion efficiency of hematite photoanodes is discussed