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  • GFZ Data Services  (5)
  • American Chemical Society
  • 2020-2023  (6)
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  • 1
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    Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts (2022)
    GFZ Data Services
    Details
    Publication Date: 2022-06-16
    Description: Abstract
    Description: As the negative impacts of hydrological extremes increase in large parts of the world, a better understanding of the drivers of change in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. To fill this gap, we present an IAHS Panta Rhei benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area (Kreibich et al. 2017, 2019). The contained 45 paired events occurred in 42 different study areas (in three study areas we have data on two paired events), which cover different socioeconomic and hydroclimatic contexts across all continents. The dataset is unique in covering floods and droughts, in the number of cases assessed and in the amount of qualitative and quantitative socio-hydrological data contained. References to the data sources are provided in 2022-002_Kreibich-et-al_Key_data_table.xlsx where possible. Based on templates, we collected detailed, review-style reports describing the event characteristics and processes in the case study areas, as well as various semi-quantitative data, categorised into management, hazard, exposure, vulnerability and impacts. Sources of the data were classified as follows: scientific study (peer-reviewed paper and PhD thesis), report (by governments, administrations, NGOs, research organisations, projects), own analysis by authors, based on a database (e.g. official statistics, monitoring data such as weather, discharge data, etc.), newspaper article, and expert judgement. The campaign to collect the information and data on paired events started at the EGU General Assembly in April 2019 in Vienna and was continued with talks promoting the paired event data collection at various conferences. Communication with the Panta Rhei community and other flood and drought experts identified through snowballing techniques was important. Thus, data on paired events were provided by professionals with excellent local knowledge of the events and risk management practices.
    Keywords: hydrological extremes ; risk dynamics ; human-flood system ; human-drought system ; socio-hydrology ; risk management ; flood ; drought ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 ENVIRONMENTAL GOVERNANCE/MANAGEMENT 〉 WATER MANAGEMENT ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 DROUGHTS ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 FLOODS ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; environmental assessment 〉 environmental risk assessment
    Type: Dataset , Dataset
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  • 2
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    Lithospheric-scale 3D model of the Southern Central Andes (2020)
    GFZ Data Services
    Details
    Publication Date: 2022-01-05
    Description: Abstract
    Description: The Central Andean orogeny is caused by the subduction of the Nazca oceanic plate beneath the South-American continental plate. In Particular, the Southern Central Andes (SCA, 27°-40°S) are characterized by a strong N-S and E-W variation in the crustal deformation style and intensity. Despite being the surface geology relatively well known, the information on the deep structure of the upper plate in terms of its thickness and density configurations is still scarcely constrained. Previous seismic studies have focused on the crustal structure of the northern part of the SCA (~27°-33°S) based upon 2D cross-sections, while 3D crustal models centred on the South-American or the Nazca Plate have been published with lower resolution. To gain insight into the present-day state of the lithosphere in the area, we derived a 3D model that is consistent with both the available geological and seismic data and with the observed gravity field. The model consists on a continental plate with sediments, a two-layer crust and the lithospheric mantle being subducted by an oceanic plate. The model extension covers an area of 700 km x 1100 km, including the orogen, the forearc and the forelands.
    Description: Methods
    Description: Different data sets were integrated to derive the lithospheric features: - We used the global relief model of ETOPO1 (Amante and Eakins 2009) for the topography and bathymetry. - The sub-surface structures were defined by integrating seismically constrained models, including the South-American crustal thickness of Assumpção et al. (2013; model A; 0.5 degree resolution), the sediment thickness of CRUST1 (Laske et al. 2013) and the slab geometry of SLAB2 (Hayes et al. 2018). - Additionally, we included seismic reflection and refraction profiles performed on the Chile margin (Araneda et al. 2003; Contreras-Reyes et al. 2008, 2014, 2015; Flueh et al. 1998; Krawzyk et al. 2006; Moscoso et al. 2011; Sick et al. 2006; Von Huene et al. 1997). - Besides, we used sediment thickness maps from the intracontinental basin database ICONS (6 arc minute resolution, Heine 2007) and two oceanic sediment compilations: one along the southern trench axis (Völker et al. 2013) and another of global-scale (GlobSed; Straume et al. 2019). To build the interfaces between the main lithospheric features, we compiled and interpolated these datasets on a regular grid with a surface resolution of 25 km. For that purpose, the convergent algorithm of the software Petrel was used. We assigned constant densities within each layer, except for the lithospheric mantle. In this case, we implemented a heterogeneous distribution by converting s-wave velocities from the SL2013sv seismic tomography (Schaeffer and Lebedev 2013) to densities. The python tool VelocityConversion was used for the conversion (Meeßen 2017). To further constrain the crustal structure of the upper plate, a gravity forward modelling was carried out using IGMAS+ (Schmidt et al. 2010). The gravity anomaly from the model (calculated gravity) was compared to the free-air anomaly from the global gravity model EIGEN-6C4 (observed gravity; Förste et al 2014; Ince et al. 2019). Subsequently, the crystalline crust of the upper plate was split vertically into two layers of different densities. We inverted the residual between calculated and observed gravity to compute the depth to the interface between the two crustal layers. For the inverse modelling of the gravity residual, the Python package Fatiando a Terra was used (Uieda et al. 2013) For each layer, the depth to the top surface, thickness and density can be found as separate files. All files contain identical columns: - Northing as "X Coord (UTM zone 19S)"; - Easting as "Y Coord (UTM zone 19S)"; - depth to the top surface as "Top (m.a.s.l)" and - thickness of each layer as "Thickness (m)". The header ‘Density’ indicates the bulk density of each unit in kg/m3. For the oceanic and continental mantle units, a separate file is provided with a regular grid of the density distribution with a lateral resolution of 8 km x 9 km and a vertical resolution of 5 km. The containing columns are: Northing as "X Coord (UTM zone 19S)"; Easting as "Y Coord (UTM zone 19S)"; depth as "Depth (m.a.s.l)" and density as "Density (kg/m3)"
    Keywords: Lithosphere ; Gravity Modelling ; Andes ; EARTH SCIENCE ; EARTH SCIENCE 〉 LAND SURFACE 〉 TOPOGRAPHY 〉 TOPOGRAPHICAL RELIEF ; EARTH SCIENCE 〉 OCEANS 〉 BATHYMETRY/SEAFLOOR TOPOGRAPHY 〉 BATHYMETRY ; EARTH SCIENCE 〉 SOLID EARTH ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOMORPHIC LANDFORMS/PROCESSES 〉 TECTONIC LANDFORMS 〉 MOUNTAINS ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOMORPHIC LANDFORMS/PROCESSES 〉 TECTONIC PROCESSES 〉 SUBDUCTION ; EARTH SCIENCE 〉 SOLID EARTH 〉 GRAVITY/GRAVITATIONAL FIELD ; EARTH SCIENCE 〉 SOLID EARTH 〉 GRAVITY/GRAVITATIONAL FIELD 〉 GRAVITY ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 SEDIMENTS ; EARTH SCIENCE SERVICES 〉 MODELS 〉 GEOLOGIC/TECTONIC/PALEOCLIMATE MODELS
    Type: Dataset , Dataset
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  • 3
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    3D thermal model of the southern Central Andes (2021)
    GFZ Data Services
    Details
    Publication Date: 2022-01-05
    Description: Abstract
    Description: The Central Andean orogen formed as a result of the subduction of the oceanic Nazca plate beneath the continental South-American plate. In the southern segment of the Central Andes (SCA, 29°S-39°S), the oceanic plate subducts beneath the continental plate with distinct dip angles from north to south. Subduction geometry, tectonic deformation, and seismicity at this plate boundary are closely related to lithospheric temperature distribution in the upper plate. Previous studies provided insights into the present-day thermal field with focus on the surface heat flow distribution in the orogen or through modelling of the seismic velocity distribution in restricted regions of the SCA as indirect proxy of the deep thermal field. Despite these recent advances, the information on the temperature distribution at depth of the SCA lithosphere remains scarcely constrained. To gain insight into the present-day thermal state of the lithosphere in the region, we derived the 3D lithospheric temperature distribution from inversion of S-wave velocity to temperature and calculations of the steady state thermal field. The configuration of the region – concerning both, the heterogeneity of the lithosphere and the slab dip – was accounted for by incorporating a 3D data-constrained structural and density model of the SCA into the workflow (Rodriguez Piceda et al. 2020a-b). The model consists on a continental plate with sediments, a two-layer crust and the lithospheric mantle being subducted by an oceanic plate. The model extension covers an area of 700 km x 1100 km, including the orogen (i.e. magmatic arc, main orogenic wedge), the forearc and the foreland, and it extents down to 200 km depth.
    Description: Methods
    Description: To predict the temperature distribution in the SCA, the model volume was subdivided into two domains: (1) a shallow domain, including the crust and uppermost mantle to a depth of ~50 km below mean sea level (bmsl), where the steady-state conductive thermal field was calculated using as input the 3D structural and density model of the area (Rodriguez Piceda et al., 2020a-b); (2) a deep domain between a depth of ~50 and 200 km bmsl, where temperatures were converted from S wave seismic velocities (Assumpção et al., 2013) using the approach by Goes et al. (2000) as implemented in the python tool VelocityConversion (Meeßen 2017). The 3D model of Rodriguez Piceda et al. (2020) consists of the following layers: (1) water; (2) oceanic sediments; (3) continental sediments; (4) upper continental crystalline crust; (5) lower continental crystalline crust; (6) continental lithospheric mantle (7) shallow oceanic crust; (8) deep oceanic crust; (9) oceanic lithospheric mantle; and (10) oceanic sub-lithospheric mantle. For the computation of temperatures in the shallow domain, three main modifications were made to the 3D model of Rodriguez Piceda et al. (2020a-b). First, we removed the water layer thus considering the topography/bathymetry as the top of the model. Second, the horizontal resolution was increased to 5 km and, third, the layers were vertically refined by a factor of 3 to 32. We assigned constant thermal properties (bulk conductivity λ and radiogenic heat production S) to each layer of the model according to each lithology (Alvarado et al. 2007, 2009; Ammirati et al. 2013, 2015, 2018; Araneda et al., 2003; Brocher, 2005; Čermák and Rybach, 1982; Contreras-Reyes et al., 2008; Christensen & Mooney, 1995; Gilbert et al., 2006; Hasterok & Chapman, 2011; He et al., 2008; Marot et al., 2014, Pesicek et al., 2012; Rodriguez Piceda et al., 2020; Scarfi & Barbieri, 2019; Vilà et al.,2010; Wagner et al., 2005; Xu et al., 2004). The steady-state conductive thermal field in the shallow domain was calculated applying the Finite Element Method as implemented in the software GOLEM (Cacace & Jacquey, 2017; Jacquey & Cacace, 2017). For the computation, we assigned fixed temperatures along the top and base of the model as thermal boundary conditions. The upper boundary condition was set at the topography/bathymetry and it is the temperature distribution from the ERA-5 land data base (Muñoz Sabater, 2019). The lower boundary condition was set at a constant depth of 50 km bmsl for areas where the Moho is shallower than 50 km bmsl and at the Moho depth proper where this interface is deeper than the abovementioned threshold. The temperature distribution at this boundary condition was calculated from the conversion of S-wave velocities to temperatures (Assumpção et al., 2013).
    Keywords: Lithosphere ; Andes ; Subduction ; Thermal Model ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOMORPHIC LANDFORMS/PROCESSES 〉 TECTONIC LANDFORMS 〉 MOUNTAINS ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOMORPHIC LANDFORMS/PROCESSES 〉 TECTONIC PROCESSES 〉 SUBDUCTION ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOTHERMAL DYNAMICS 〉 GEOTHERMAL TEMPERATURE ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOTHERMAL DYNAMICS 〉 GEOTHERMAL TEMPERATURE 〉 TEMPERATURE PROFILES ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 SEDIMENTS ; EARTH SCIENCE SERVICES 〉 MODELS 〉 GEOLOGIC/TECTONIC/PALEOCLIMATE MODELS
    Type: Dataset , Dataset
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  • 4
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    Synthase-Selective Exploration of a Tunicate Microbiome by Activity-Guided Single-Cell Genomics (2021)
    American Chemical Society
    In:  ACS Chemical Biology .
    Details
    Publication Date: 2022-01-07
    Description: While thousands of environmental metagenomes have been mined for the presence of novel biosynthetic gene clusters, such computational predictions do not provide evidence of their in vivo biosynthetic functionality. Using fluorescent in situ enzyme assay targeting carrier proteins common to polyketide (PKS) and nonribosomal peptide synthetases (NRPS), we applied fluorescence-activated cell sorting to tunicate microbiome to enrich for microbes with active secondary metabolic capabilities. Single-cell genomics uncovered the genetic basis for a wide biosynthetic diversity in the enzyme-active cells and revealed a member of marine Oceanospirillales harboring a novel NRPS gene cluster with high similarity to phylogenetically distant marine and terrestrial bacteria. Interestingly, this synthase belongs to a larger class of siderophore biosynthetic gene clusters commonly associated with pestilence and disease. This demonstrates activity-guided single-cell genomics as a tool to guide novel biosynthetic discovery.
    Type: Article , PeerReviewed
    Format: text
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  • 5
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    Mechanical data of simulated basalt-built faults from rotary shear and direct shear experiments (2021)
    GFZ Data Services
    Details
    Publication Date: 2022-02-11
    Description: Abstract
    Description: Here we report the raw data of the friction experiments carried out on basalt-built simulated faults defined by rock-on-rock contacts and powdered gouge. The experiments were specifically designed to investigate the role of fault microstructure on the frictional properties of basalts and the fault slip stability, and were conducted with the rotary-shear apparatus (SHIVA) and the biaxial deformation apparatus (BRAVA), hosted at the National Institute of Geophysics and Volcanology (INGV) in Rome. Simulated faults were sheared at constant normal stress from 4 to 30 MPa. In SHIVA experiments, we deformed samples at constant slip velocity of 10 μm/s up to 56 mm net slip. In BRAVA tests we performed a sequence of velocity steps (0.1 to 300 μm/s), followed by slide-hold-slide tests (30-3000 s holds; V=10 μm/s slides). Our main results highlight the frictionally strong nature of basalt faults and show opposite friction velocity dependence upon the velocity upsteps: while fault gouges exhibit velocity weakening behavior with increasing normal stress and sliding velocity, bare rock surfaces transition to velocity strengthening behavior as we approach higher slip velocities. The experiments setup and data are further described in the manuscript “Frictional properties of basalt experimental faults and implications for volcano-tectonic settings and geo-energy sites” to which these data are supplementary material.
    Keywords: Fault mechanics ; Friction of basalts ; Rate and State Friction ; Bare rock surfaces ; Simulated fault gouge ; EPOS ; multi-scale laboratories ; rock and melt physical properties ; alkali-olivine_basalt ; Biaxial ; Friction ; Rotary Shear ; Strain gauge
    Type: Dataset , Dataset
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  • 6
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    AK1006 Archäobotanische Funde der eisenzeitlichen latènezeitlichen befestigten Höhensiedlung "Dünsberg" bei Biebertal-Fellingshausen (Gießen, Hessen) (2022)
    GFZ Data Services
    Details
    Publication Date: 2022-08-02
    Description: Abstract
    Description: Archäobotanische Untersuchung (Samen, Früchte) zur Eisenzeit (Latène, Kelten). Fundstellentyp: befestigte Höhensiedlung. Ort: Biebertal-Fellingshausen, Dünsberg (DÜN), Gießen, Hessen, Germany. Gefördert durch die Deutsche Forschungsgemeinschaft (DFG), Aktenzeichen KR 1569/1 (SPP 190 "Romanisierung").
    Description: Abstract
    Description: Archaeobotanical finds (seeds, fruits) of the Iron Age (Latène, Celts). Site type: fortified hilltop settlement. Place: Biebertal-Fellingshausen, Dünsberg (DÜN), Gießen, Hessen, Germany. Funded by the German Research Foundation (DFG), grant number KR 1569/1 (SPP 190 "Romanisierung").
    Description: Other
    Description: Die hier vorliegende Datenpublikation stellt die mit Mitteln der Deutschen Forschungsgemeinschaft (DFG) und der hessenARCHÄOLOGIE (hA, Landesamt für Denkmalpflege Hessen, Wiesbaden/DE) erarbeiteten Daten der archäobotanischen Arbeitsgruppe Wiesbaden über das Datenzentrum des Deutschen GeoForschungsZentrums GFZ Data Services unter Leitung von Dr. Kirsten Elger Open Access bereit. Die dieser Datenpublikation zugrunde liegenden Daten wurden mit dem seit 1997 entwickelten, Microsoft Access basierten Datenbankprogramm ArboDat 2016 erfasst. ArboDat ist ein Medium, selbst oder von anderen erarbeitete archäobotanische Großrest-Daten archäologischer Ausgrabungen zu archivieren und gleichzeitig ein offenes Forschungsinstrument für vielfältige Auswertungen (für die weitere Beschreibung siehe das zugehörige README_de). ArboDat 2016 ist inzwischen in mehr als 40 archäobotanischen Laboren in Ägypten, Belgien, Bulgarien, Deutschland, Frankreich, Griechenland, Großbritannien, Österreich, Polen und der Schweiz in Nutzung. Das Programm mit dem zugehörigen Handbuch wird archäobotanischen Arbeitsstellen für ihre wissenschaftliche Arbeit unentgeltlich zur Verfügung gestellt. Das detaillierte Handbuch ermöglicht einen einfachen Einstieg in die Datenerfassung und Auswertungen ohne Access-Kenntnisse (https://doi.org/10.48440/hA-ArboDat_manual_de).
    Description: Other
    Description: The existing data publication comprises research data from the archaeobotanical work group in Wiesbaden funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) and the hessenARCHÄOLOGIE (hA, Archaeobotanical Department, Landesamt für Denkmalpflege Hessen, Wiesbaden/DE). The data are made open access through the ArboDat 2016 Datacentre hosted at the GFZ which was made available under the direction of Dr. Kirsten Elger, GFZ Data Services. The data provided have been recorded with the database programme ArboDat 2016, developed since 1997 and based on Microsoft Access. ArboDat 2016 is a medium for archiving one's own archaeobotanical macro-remains data from archaeological excavations or those compiled by other authors and a research tool for manifold data evaluations (for further description please refer to the associated README_en). ArboDat 2016 is now distributed among more than 40 archaeobotanical working groups in Austria, Belgium, Bulgaria, Egypt, France, Germany, the United Kingdom, Greece and Switzerland. The programme and the manual are given free of charge to archaeobotanical researchers. The detailed manual (https://doi.org/10.48440/hA-ArboDat_manual_en) is aimed to help new users to get started with ArboDat 2016 even without knowledge of Microsoft Access.
    Keywords: archäologische Fundstelle ; Archäobotanik ; botanische Großreste ; Archäologie ; archaeological site ; archaeobotany ; botanical macroremains ; archaeology ; Samen ; Früchte ; seeds ; fruits ; Vorrömische Eisenzeit ; Mittel- bis Spätlatène ; Kelten ; Iron Age ; Middle until Late Latène ; Celts ; befestigte Höhensiedlung ; fortified hilltop settlement ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 HUMAN SETTLEMENTS 〉 ARCHAEOLOGICAL AREAS
    Type: Dataset , Dataset
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