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Soil bacteria play a fundamental role in pedogenesis. However, knowledge about both the impact of climate and slope aspects on microbial communities and the consequences of these items in pedogenesis is lacking. Therefore, soil-bacterial communities from four sites and two different aspects along the climate gradient of the Chilean Coastal Cordillera were investigated. Using a combination of microbiological and physicochemical methods, soils that developed in arid, semi-arid, mediterranean, and humid climates were analyzed. Proteobacteria, Acidobacteria, Chloroflexi, Verrucomicrobia, and Planctomycetes were found to increase in abundance from arid to humid climates, while Actinobacteria and Gemmatimonadetes decreased along the transect. Bacterial-community structure varied with climate and aspect and was influenced by pH, bulk density, plant-available phosphorus, clay, and total organic-matter content. Higher bacterial specialization was found in arid and humid climates and on the south-facing slope and was likely promoted by stable microclimatic conditions. The presence of specialists was associated with ecosystem-functional traits, which shifted from pioneers that accumulated organic matter in arid climates to organic decomposers in humid climates. These findings provide new perspectives on how climate and slope aspects influence the composition and functional capabilities of bacteria, with most of these capabilities being involved in pedogenetic processes.
Distributed environmental models such as land surface models (LSMs) require model parameters in each spatial modeling unit (e.g., grid cell), thereby leading to a high-dimensional parameter space. One approach to decrease the dimensionality of the parameter space in these models is to use regularization techniques. One such highly efficient technique is the multiscale parameter regionalization (MPR) framework that translates high-resolution predictor variables (e.g., soil textural properties) into model parameters (e.g., porosity) via transfer functions (TFs) and upscaling operators that are suitable for every modeled process. This framework yields seamless model parameters at multiple scales and locations in an effective manner. However, integration of MPR into existing modeling workflows has been hindered thus far by hard-coded configurations and non-modular software designs. For these reasons, we redesigned MPR as a model-agnostic, stand-alone tool. It is a useful software for creating graphs of NetCDF variables, wherein each node is a variable and the links consist of TFs and/or upscaling operators. In this study, we present and verify our tool against a previous version, which was implemented in the mesoscale hydrologic model (mHM; https://www.ufz.de/mhm, last access: 16 January 2022). By using this tool for the generation of continental-scale soil hydraulic parameters applicable to different models (Noah-MP and HTESSEL), we showcase its general functionality and flexibility. Further, using model parameters estimated by the MPR tool leads to significant changes in long-term estimates of evapotranspiration, as compared to their default parameterizations. For example, a change of up to 25 % in long-term evapotranspiration flux is observed in Noah-MP and HTESSEL in the Mississippi River basin. We postulate that use of the stand-alone MPR tool will considerably increase the transparency and reproducibility of the parameter estimation process in distributed (environmental) models. It will also allow a rigorous uncertainty estimation related to the errors of the predictors (e.g., soil texture fields), transfer function and its parameters, and remapping (or upscaling) algorithms.
Selection of high-performance lines with respect to traits of interest is a key step in plant breeding. Genomic prediction allows to determine the genomic estimated breeding values of unseen lines for trait of interest using genetic markers, e.g. single-nucleotide polymorphisms (SNPs), and machine learning approaches, which can therefore shorten breeding cycles, referring to genomic selection (GS). Here, we applied GS approaches in two populations of Solanaceous crops, i.e. tomato and pepper, to predict morphometric and colorimetric traits. The traits were measured by using scoring-based conventional descriptors (CDs) as well as by Tomato Analyzer (TA) tool using the longitudinally and latitudinally cut fruit images. The GS performance was assessed in cross-validations of classification-based and regression-based machine learning models for CD and TA traits, respectively. The results showed the usage of TA traits and tag SNPs provide a powerful combination to predict morphology and color-related traits of Solanaceous fruits. The highest predictability of 0.89 was achieved for fruit width in pepper, with an average predictability of 0.69 over all traits. The multi-trait GS models are of slightly better predictability than single-trait models for some colorimetric traits in pepper. While model validation performs poorly on wild tomato accessions, the usage as many as one accession per wild species in the training set can increase the transferability of models to unseen populations for some traits (e.g. fruit shape for which predictability in unseen scenario increased from zero to 0.6). Overall, GS approaches can assist the selection of high-performance Solanaceous fruits in crop breeding.
Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large-scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large-scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana. We demonstrate the accuracy of RDT through a comparative analysis with atom mappings from a large database of biochemical reactions, MetaCyc. We further show the utility of our automated workflow by simulating N-15 isotope enrichment and identifying nitrogen (N)-containing metabolites which show enrichment patterns that are informative for flux estimation in future N-15-MFA studies of A. thaliana. The automated workflow established in this study can be readily expanded to other species for which metabolic models have been established and the resulting atom mappings will facilitate MFA and graph-theoretic structural analyses with large-scale metabolic networks.
Shallow earthquakes frequently disturb the hydrological and mechanical state of the subsurface, with consequences for hazard and water management. Transient post-seismic hydrological behavior has been widely reported, suggesting that the recovery of material properties (relaxation) following ground shaking may impact groundwater fluctuations. However, the monitoring of seismic velocity variations associated with earthquake damage and hydrological variations are often done assuming that both effects are independent. In a field site prone to highly variable hydrological conditions, we disentangle the different forcing of the relative seismic velocity variations delta v retrieved from a small dense seismic array in Nepal in the aftermath of the 2015 M-w 7.8 Gorkha earthquake. We successfully model transient damage effects by introducing a universal relaxation function that contains a unique maximum relaxation timescale for the main shock and the aftershocks, independent of the ground shaking levels. Next, we remove the modeled velocity from the raw data and test whether the corresponding residuals agree with a background hydrological behavior we inferred from a previously calibrated groundwater model. The fitting of the delta v data with this model is improved when we introduce transient hydrological properties in the phase immediately following the main shock. This transient behavior, interpreted as an enhanced permeability in the shallow subsurface, lasts for similar to 6 months and is shorter than the damage relaxation (similar to 1 yr). Thus, we demonstrate the capability of seismic interferometry to deconvolve transient hydrological properties after earthquakes from non-linear mechanical recovery.
Nocardioides alcanivorans sp. nov., a novel hexadecane-degrading species isolated from plastic waste
(2022)
Strain NGK65(T), a novel hexadecane degrading, non-motile, Gram-positive, rod-to-coccus shaped, aerobic bacterium, was isolated from plastic polluted soil sampled at a landfill.
Strain NGK65(T) hydrolysed casein, gelatin, urea and was catalase-positive. It optimally grew at 28 degrees C. in 0-1% NaCl and at pH 7.5-8.0. Glycerol, D-glucose, arbutin, aesculin, salicin, potassium 5-ketogluconate. sucrose, acetate, pyruvate and hexadecane were used as sole carbon sources.
The predominant membrane fatty acids were iso-C-16:0 followed by iso-C(17:)0 and C-18:1 omega 9c. The major polar lipids were phosphatidylglycerol, phosphatidylethanolamine, phosphatidylinositol and hydroxyphosphatidylinositol.
The cell-wall peptidoglycan type was A3 gamma, with LL-diaminopimelic acid and glycine as the diagnostic amino acids. MK 8 (H-4) was the predominant menaquinone. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain NGK65(T) belongs to the genus Nocardioides (phylum Actinobacteria). appearing most closely related to Nocardioides daejeonensis MJ31(T) (98.6%) and Nocardioides dubius KSL-104(T) (98.3%).
The genomic DNA G+C content of strain NGK65(T) was 68.2%.
Strain NGK65(T) and the type strains of species involved in the analysis had average nucleotide identity values of 78.3-71.9% as well as digital DNA-DNA hybridization values between 22.5 and 19.7%, which clearly indicated that the isolate represents a novel species within the genus Nocardioides.
Based on phenotypic and molecular characterization, strain NGK65(T) can clearly be differentiated from its phylogenetic neighbours to establish a novel species, for which the name Nocardioides alcanivorans sp. nov. is proposed.
The type strain is NGK65(T) (=DSM 113112(T)=NCCB 100846(T)).
Species community structures of Afrotropical butterflies differ depending on the monitoring method
(2022)
Standardised biodiversity assessment is crucial to understand community structures and population dynamics of animals.
There exist various methods to monitor biodiversity. Approaches differ depending on the target species group and the aim of study, and show advantages and disadvantages.
The obtained data and results are influenced by local environmental conditions and seasonal variability.
In a comparative approach, we studied butterfly diversity and community structure in the dryland savannah biome of south-eastern Kenya with two different methods, transect counts and bait trapping.
We repeatedly collected data throughout the dry and rainy seasons, in both near natural and anthropogenically influenced landscapes. Significantly more species and individuals were recorded by transect counts than by bait trapping, though the larger and more mobile Nymphalid species (and in particular representatives of the genus Charaxes) were comparatively overrepresented in traps.
The transect data revealed much more pronounced effects of land-use and seasonality than the trap data. These results show that the choice of data collection methods must depend on the general research question, habitat conditions and season. To study the relative variation of species diversity and abundance, the collection of a fraction of the total species diversity might be sufficient.
However, if the focus is on a largely complete recording of species diversity, the use of various collection methods is essential. More specifically, our data clearly demonstrate that transect counts represent a reasonable method for assessing butterfly diversity for the African dryland savannah region, but fails to fully capture occurrences of all species. Bait trapping can be used only as a supplementary method for assessing some few highly mobile low-density species.
Rainfall-intense summer monsoon seasons on the Indian subcontinent that are exceeding long-term averages cause widespread floods and landslides.
Here we show that the latest generation of coupled climate models robustly project an intensification of very rainfall-intense seasons (June-September).
Under the shared socioeconomic pathway SSP5-8.5, very wet monsoon seasons as observed in only 5 years in the period 1965-2015 are projected to occur 8 times more often in 2050-2100 in the multi-model average.
Under SSP2-4.5, these seasons become only a factor of 6 times more frequent, showing that even modest efforts to mitigate climate change can have a strong impact on the frequency of very strong rainfall seasons.
Besides, we find that the increasing risk of extreme seasonal rainfall is accompanied by a shift from days with light rainfall to days with moderate or heavy rainfall. Additionally, the number of wet days is projected to increase.
Turnschuhdiplomatie
(2022)
Auch wenn der Sport der DDR mit seinen Rekorden und Medaillen als eines ihrer weltweiten Aushängeschilder galt, fehlte bisher eine detaillierte Unter- suchung ihrer internationalen Sportbeziehungen. Der vorliegende Band holt dies in Form einer erstmaligen außen- und sportpolitischen Kontinentalstudie am Beispiel Afrikas nach und erörtert, welche Rolle die vielfältigen Facetten des Sports in der Afrikapolitik der DDR spielten und mit welchen Interessen diese u.a. in den Bereichen der Diplomatie, der kulturellen Auslandsarbeit, des Leistungssports oder des Außenhandels verknüpft waren. Die 610 Seiten starke Schrift beleuchtet die Zeit von 1955 bis 1990 und stützt sich dabei u.a. auf über 2200 (teils erstmals recherchierte) Quellen- und Literaturnachweise. Schwerpunkte bilden hierbei u.a. ausführliche Länder- und Regional- studien für Nordafrika (Ägypten, Algerien), Westafrika (Ghana, Mali, Guinea) sowie zu Äthiopien und Mosambik.
Data Act
(2022)
Der Data Act ist das Herzstück und der vorläufige Abschluss der Vorschläge zur EU-Datenregulierung. Der lang erwartete Entwurf ist ein Paukenschlag: Das Verhältnis zwischen Datenproduzenten, Dateninhabern und Dateninteressenten wird von Grund auf neu austariert. Die EU-Kommission will Datenzugangsrechte, weitreichende Regelungen zu Datenverträgen und Cloud-Services sowie spezifische Interoperabilitätsregelungen normieren. Der Beitrag gibt einen Überblick über die geplanten Regelungen und ordnet diese ein.