The spiders (Araneae) of pure pine and birch stands on restored open dump sites in Saxony and Brandenburg (Germany)

The spiders (Araneae) of pure pine and birch stands on restored open dump sites in Saxony and Brandenburg (Germany). The spider communities of four restored, afforested pure stands of first generation pine, birch and birch-robinia in the postmining landscape and one natural pine forest of the Lower Lusatia (Germany: Saxony and Brandenburg) were investigated. From 1997-98 a total of 6368 spiders were caught using stemeclectors and pitfall traps. More than 50% of the specimens collected were juveniles. The remaining individuals were identified and represent 123 species from 23 families. Among them several taxa are listed in the Red Data Lists of Germany (n = 16), Brandenburg (n = 13) and Saxony (n = 14). One species, Clubiona leucaspis is rare in Germany and new to Saxony. When comparing afforested stands of pine on postmining areas with natural ones the species Coelotes terrestris (Amaurobiidae) was observed exclusively in the latter. The absence of this species on restored sites seems to indicate a disturbance of the soil up to almost 60 years after the end of restoration. According to pitfall trapping in three pine forests the increasing biomass of spiders indicates a high predation rate at the oldest site, whereas the highest species diversity was found on younger, rehabilitated sites.Die Spinnengemeinschaft der Stamm- und stammnahen Bodenregion von vier Forststandorten auf rekultivierten Kippenböden des Niederlausitzer Braunkohlenreviers wurde untersucht. Von 1997-1998 wurde die Stammzönose mittels Stammeklektoren und zusätzlich 1998 die epigäische Spinnenfauna der stammnahen Bereiche durch Bodenfallen erfasst. Als Referenz zu den untersuchten Kippenstandorten diente ein alter Kiefernreinbestand auf natürlich geschichtetem Boden. Von den erfassten Spinnen (6368 Individuen) waren 50,2% juvenil. Die adulten Tiere konnten 123 Arten aus 23 Familien zugeordnet werden. Eine Art, Clubiona leucaspis, war neu für Sachsen, 23 Arten werden in der Roten Liste Deutschlands (n = 16), Brandenburgs (n = 13) und Sachsens (n = 15) aufgeführt. Die unterschiedliche Vorgeschichte (rekultiviert oder natürlich) und der Baumbesatz (Kiefer oder Birke) der Untersuchungsflächen bedingte zum Teil deutliche Unterschiede hinsichtlich verschiedener populationsökologischer Parameter (Familien-, Artenzahl, Diversität, Aktivitätsbiomasse). Die Ergebnisse werden hinsichtlich der daraus resultierenden Folgen für den Natur- und Artenschutz, die Dominanzstruktur der Spinnenzönosen, die natürliche Schädlingsregulation diskutiert. Die Abwesenheit einzelner Taxa (hier: Coelotes terrestris und Hahnia helveola) wird als Indikator für eine Unterbrechung der Faunentradition interpretiert

Seismotectonic study of the Fergana region (Southern Kyrgyzstan): distribution and kinematics of local seismicity

We present new seismicity and focal-mechanism data for the Fergana basin and surrounding mountain belts in western Kyrgyzstan from a temporary local seismic network. A total of 210 crustal earthquakes with hypocentral depths shallower than 25 km were observed during a 12-month period in 2009/2010. The hypocenter distribution indicates a complex net of seismically active structures. The seismicity derived in this study is mainly concentrated at the edges of the Fergana basin, whereas the observed rate of seismicity within the basin is low. The seismicity at the dominant tectonic feature of the region, the Talas-Fergana fault, is likewise low, so the fault seems to be inactive or locked. To estimate the uncertainties of earthquake locations derived in this study, a strong explosion with known origin time and location is used as a ground truth calibration event which suggests a horizontal and vertical accuracy of about 1 km for our relocations. We derived 35 focal mechanisms using first motion polarities and retrieved a set of nine moment tensor solutions for earthquakes with moment magnitude (Mw) ranging from 3.3 to 4.9 by waveform inversion. The solutions reveal both thrust and strike-slip mechanisms compatible with a NW-SE direction of compression for the Fergana region. Two previously unknown tectonic structures in the Fergana region could be identified, both featuring strike-slip kinematics. The combined analysis of the results derived in this study allowed a detailed insight into the currently active tectonic structures and their kinematics where little information had previously been available

A decade-long silent ground subsidence hazard culminating in a metropolitan disaster in Maceió, Brazil

Ground subsidence caused by natural or anthropogenic processes affects major urban areas worldwide. Sinkhole formation and infrastructure fractures have intensified in the federal capital of Maceió (Alagoas, Brazil) since early 2018, forcing authorities to relocate affected residents and place buildings under demolition. In this study, we present a 16-year history (2004–2020) of surface displacement, which shows precursory deformations in 2004–2005, reaching a maximum cumulative subsidence of approximately 200 cm near the Mundaú Lagoon coast in November 2020. By integrating the displacement observations with numerical source modelling, we suggest that extensive subsidence can be primarily associated with the removal of localized, deep-seated material at the location and depth where salt is mined. We discuss the accelerating subsidence rates, influence of severe precipitation events on the aforementioned geological instability, and related hazards. This study suggests that feedback destabilization mechanisms may arise in evaporite systems due to anthropogenic activities, fostering enhanced and complex superficial ground deformation

Evaluation of Remote-Sensing-Based Landslide Inventories for Hazard Assessment in Southern Kyrgyzstan

Large areas in southern Kyrgyzstan are subjected to high and ongoing landslide activity; however, an objective and systematic assessment of landslide susceptibility at a regional level has not yet been conducted. In this paper, we investigate the contribution that remote sensing can provide to facilitate a quantitative landslide hazard assessment at a regional scale under the condition of data scarcity. We performed a landslide susceptibility and hazard assessment based on a multi-temporal landslide inventory that was derived from a 30-year time series of satellite remote sensing data using an automated identification approach. To evaluate the effect of the resulting inventory on the landslide susceptibility assessment, we calculated an alternative susceptibility model using a historical inventory that was derived by an expert through combining visual interpretation of remote sensing data with already existing knowledge on landslide activity in this region. For both susceptibility models, the same predisposing factors were used: geology, stream power index, absolute height, aspect and slope. A comparison of the two models revealed that using the multi-temporal landslide inventory covering the 30-year period results in model coefficients and susceptibility values that more strongly reflect the properties of the most recent landslide activity. Overall, both susceptibility maps present the highest susceptibility values for similar regions and are characterized by acceptable to high predictive performances. We conclude that the results of the automated landslide detection provide a suitable landslide inventory for a reliable large-area landslide susceptibility assessment. We also used the temporal information of the automatically detected multi-temporal landslide inventory to assess the temporal component of landslide hazard in the form of exceedance probability. The results show the great potential of satellite remote sensing for deriving detailed and systematic spatio-temporal information on landslide occurrences, which can significantly improve landslide susceptibility and hazard assessment at a regional scale, particularly in data-scarce regions such as Kyrgyzstan.BMBF, 03G0809, Verbundprojekt WTZ Zentralasien: TIPTIMON - Tien Shan - Pamir Monitoring Programm - Spätkänozoische Geodynamik, Klimainteraktionen und resultierende Risiken in Zentralasie

Enabling energy systems research on HPC

Energy systems research strongly relies on large modeling frameworks. Many of them use linear optimization approaches to calculate blueprints for ideal future energy systems, which become increasingly complex and so do the models. The state-of-the-art to compute them is the application of shared-memory computers combined with approaches to reduce their size. We overcome this and implement a full automatized workflow on HPC using a newly developed solver for distributed memory architectures. Moreover, we address the challenge of uncertainty in scenario analysis by performing sophisticated parameter variations for large-scale power system models, which cannot be solved in the conventional way. Preliminary results show that we are able to identify clusters of future energy system designs, which perform well from different perspectives of energy system research and also consider disruptive events. However, we also see that our approach provides most insights when being applied to rather complex than simple models

FAME-Core: An open Framework for distributed Agent-based Modelling of Energy systems

In this paper we introduce FAME-Core, a Java library supporting development and execution of agent-based simulation models (ABM). It is a main component of the open Framework for distributed Agent-based Models of Energy systems. FAME-Core offers rapid development and fast simulation execution capabilities while reducing required programming skills and efforts for creating and running complex ABM

A multi-perspective approach for exploring the scenario space of future power systems

There are many possible future energy systems – many of them unforeseen. We explore the range of parameter uncertainty and quantify parameter interrelations to generate multiple scenarios. Only sensible parameter combinations remain as in-puts to an energy system optimization and coupled models. In the past, computa-tional limitations have been a major obstacle to calculate such an enormous space of scenarios. Opposed to that, we use high-performance computing. To utilize the HPC-system efficiently the parallel solver for linear programs PIPS-IPM++ is applied. We integrate it into a tool chain of different components including sce-nario generation, energy system optimization and results evaluation and tackle the challenge of coupling a large diversity of software packages in a fully automated HPC workflow. This enables the calculation of all scenarios in a matter of days. Furthermore, we use a set of 37 indicators to provide a comprehensive assess-ment of the simulated energy systems. In this way, we cover multiple perspec-tives, such as system adequacy, security of supply or behavior of market actors. Whereas scenarios with low spatial resolution do not lead to clear results, higher resolutions do. Yet, we identified three clusters of scenarios, among which a group with high natural gas dependency is found. This allows to study disruptive events like price shocks in a vast parameter space and to identify countermeasures for the long-term

Szenarien mit Energieinfrastrukturausfällen unter Einbezug multipler Parameterunsicherheiten

Der Einsatz von Modellen zur Erstellung und Untersuchung von Szenarien ist ein wesentliches Instrument der Energiesystemanalyse. Für die Politikberatung ist die Frage nach der Verlässlichkeit von solchen Szenarien von großer Wichtigkeit, da diese mit großen Unsicherheiten behaftet sein können. Diesem Problem wird in im Forschungsprojekt UNSEEN begegnet: durch das Abfahren eines sehr großen Parameterraums konnten bereits mehr als 1000 Energieszenarien automatisch generiert, berechnet und ausgewertet werden, darunter auch 100 räumlich hoch-aufgelöste Stromsystemmodelle Deutschlands. Letztere Modelle eignen sich auch zur Untersuchung der Auswirkungen von Ausfällen der darin explizit modellierten Energieinfrastrukturen, also von Kraftwerksstandorten, Übertragungsnetzleitungen und Umspannwerken. Der wesentlichen Herausforderung, dafür eine Vielzahl aufwendiger Modellrechnungen performant durchzuführen, begegnen wir mittles eines auf High-Performance-Computing angepassten Modellierungs-Workflows, welcher den entstehenden Szenarioraum auf Basis multi-kriterieller Indikatoren (u. a. zu Angemessenheit, Betriebssicherheit und Wirtschaftlichkeit) bewertbar macht. Die ersten Analysen dieses Szenarioraums zeigen, dass >Best-Perfoming< Szenarien verhältnismäßige geringe Zubauraten für Windkraft aufweisen, bei einer Reduktion der CO2-Emissionen im Stromsektor um 85%-89% gegenüber 1990

HiTSEE KNIME: a visualization tool for hit selection and analysis in high-throughput screening experiments for the KNIME platform

We present HiTSEE (High-Throughput Screening Exploration Environment), a visualization tool for the analysis of large chemical screens used to examine biochemical processes. The tool supports the investigation of structure-activity relationships (SAR analysis) and, through a flexible interaction mechanism, the navigation of large chemical spaces. Our approach is based on the projection of one or a few molecules of interest and the expansion around their neighborhood and allows for the exploration of large chemical libraries without the need to create an all encompassing overview of the whole library. We describe the requirements we collected during our collaboration with biologists and chemists, the design rationale behind the tool, and two case studies on different datasets. The described integration (HiTSEE KNIME) into the KNIME platform allows additional flexibility in adopting our approach to a wide range of different biochemical problems and enables other research groups to use HiTSEE

Reduction of Radiometric Miscalibration—Applications to Pushbroom Sensors

The analysis of hyperspectral images is an important task in Remote Sensing. Foregoing radiometric calibration results in the assignment of incident electromagnetic radiation to digital numbers and reduces the striping caused by slightly different responses of the pixel detectors. However, due to uncertainties in the calibration some striping remains. This publication presents a new reduction framework that efficiently reduces linear and nonlinear miscalibrations by an image-driven, radiometric recalibration and rescaling. The proposed framework—Reduction Of Miscalibration Effects (ROME)—considering spectral and spatial probability distributions, is constrained by specific minimisation and maximisation principles and incorporates image processing techniques such as Minkowski metrics and convolution. To objectively evaluate the performance of the new approach, the technique was applied to a variety of commonly used image examples and to one simulated and miscalibrated EnMAP (Environmental Mapping and Analysis Program) scene. Other examples consist of miscalibrated AISA/Eagle VNIR (Visible and Near Infrared) and Hawk SWIR (Short Wave Infrared) scenes of rural areas of the region Fichtwald in Germany and Hyperion scenes of the Jalal-Abad district in Southern Kyrgyzstan. Recovery rates of approximately 97% for linear and approximately 94% for nonlinear miscalibrated data were achieved, clearly demonstrating the benefits of the new approach and its potential for broad applicability to miscalibrated pushbroom sensor data