Find research datasets worth reusing

opencc-by-4.0Mar 2020View details →

Analogue models testing the interaction between a propagating continental rift and inherited crustal fabrics

This dataset presents the results of an experimental series of analogue models performed to investigate the interaction between a propagating continental rift and inherited crustal fabrics. Our experimental series was designed adopting a parametric approach, which consisted in the systematic variation of the orientation of various kinds of brittle discontinuities (e.g., faults, fractures, foliations, etc.). Structures of models have been analysed quantitatively by means of photogrammetric digital elevation model reconstruction and semi-automatic fault pattern quantification. In this dataset, we show the row data and specific elaborations supporting the interpretation of results.

opencc-by-4.0Feb 2024View details →

Supplementary Material 4 (Spatio-temporal metabolic rifts in urban construction material circularity)

This video map shows the relative changes in environmental impacts at different locations per year for 2017-2050.

opencc-by-4.0Feb 2024View details →

Supplementary Material 1-3 (Spatio-temporal metabolic rifts in urban construction material circularity)

Dataset 1 contains life cycle impact factors used for each stage of the urban metabolism for all spatial levels. Dataset 2 contains the transport distances and modes from supplier locations for all spatial levels. Dataset 3 contains material flow and life cycle impact assessment results for each year (2017-2050) and all spatial levels.

opencc-by-4.0Nov 2024View details →

Role of Volcano-Tectonic Interactions During Early-Phase Magma-Assisted Continental Rifting: Supplementary Model Files

Input and output model files for the manual script titlted "Role of Volcano-Tectonic Interactions During Early-Phase Magma-Assisted Continental Rifting" submitted to Journal of Geophysical Research: Solid Earth.

opencc-by-4.0May 2022View details →

Luangwa Rift Active Fault Database v1.0

First release of the Luangwa Rift Active Fault Database for the submission of a manuscript to EGU Solid Earth. Active fault database for the Luangwa Rift, Zambia compiled by Tess Turner, Luke Wedmore and Juliet Biggs at University of Bristol. The Luangwa Rift Active Fault Database (LRAFD) is a freely available open-source geospatial database of active fault traces within the Luangwa Rift, Zambia. The active fault database has been designed and released in line with the Global Earthquake Model standards. Full details of the criteria used to assess activity will be released in a publication that is currently in preparation. Citation Please cite the latest release of this database on Zenodo in addition to the following manuscript: Turner, T. Wedmore, L.N.J., Biggs, J. Williams, J.N., Sichingabula, H.M., Kabumbu, C., Banda, K. The Luangwa Rift Active Fault Database and fault reactivations along the southwestern branch of the East African Rift. _Submitted to EGU Solid Earth_ Data Format The LRAFD is a geospatial database containing a collection of active fault traces in GIS vector format. Each fault is mapped as a single continuous GIS feature, and has associated metadata that describe the geometry of the fault and various aspects of its exposure and the methodology used to map the fault. The list below describes the attributes within the LRAFD. These attributes are based on the <a href="https://github.com/cossatot/gem-global-active-faults">Global Earthquake Model Global Active Faults Database</a> (<a href="https://github.com/cossatot/gem-global-active-faults">GEM-GAFD</a>; <a href="https://doi.org/10.1177%2F8755293020944182">Styron and Pagani, 2020</a>). Note, we do not currently include all attributes from the <a href="http://github.com/cossatot/gem-global-active-faults">GEM-GAFD</a> as these data have not been collected in the Luangwa Rift. It is the intention that future versions of this database will include more attributes. No assessment is made of the seismogenic properties of the faults in the LRAFD as this is subjective. These data have been compiled in the publication associated with this database. Data Table <table> <caption>Luangwa Rift Active Fault Database Attributes</caption> <thead> <tr> <th scope="col">Attribute</th> <th scope="col">Data Type</th> <th scope="col">Description</th> <th scope="col">Notes</th> </tr> </thead> <tbody> <tr> <td>LRAFD_ID</td> <td>integer</td> <td>Unique Fault IDentification number assigned to each fault trace</td> <td> </td> </tr> <tr> <td>Fault_Name</td> <td>string</td> <td>Name of Fault</td> <td>Assigned using local geographic features or towns</td> </tr> <tr> <td>Dip_Direction</td> <td>string</td> <td>Compass quadrant of fault dip direction</td> <td> </td> </tr> <tr> <td>slip_type</td> <td>string</td> <td>kinematic type of fault</td> <td>e.g. normal, reverse, sinistral-strike slip, dextral-strike slip</td> </tr> <tr> <td>Fault_Length</td> <td>decimal</td> <td>Straight line distance between the tips of the fault</td> <td> </td> </tr> <tr> <td>GeomorphicExpression</td> <td>string</td> <td>Geomorphic feature/features used to identify the fault trace and its extent</td> <td>e.g. escarpment, fault scarp, offset sedimentary feature</td> </tr> <tr> <td>Method</td> <td>string</td> <td>DEM or geologic dataset used to identify and map the fault trace</td> <td>e.g. digital elevation model hillshade, slope map</td> </tr> <tr> <td>Confidence</td> <td>integer</td> <td>Confidence of recent (Quaternary) activity</td> <td>Ranges from 1-4, 1 if high certainty, 4 if low certainty</td> </tr> <tr> <td>ExposureQuality</td> <td>integer</td> <td>Fault exposure quality</td> <td>1 if high, 2 if low</td> </tr> <tr> <td>EpistemicQuality</td> <td>integer</td> <td>Certainty of whether a fault exists there</td> <td>1 if high, 2 if low</td> </tr> <tr> <td>Accuracy</td> <td>integer</td> <td>Coarsest scale at which fault trace can be mapped, expressed as the denominator of the map scale</td> <td>reflects the prominence of the fault's geomorphic expression</td> </tr> <tr> <td>GeologicalMapExpression</td> <td>string</td> <td>extent of correlation between fault traces and legacy geological map</td> <td>whether faults have been previously mapped and/or follow geological contacts</td> </tr> <tr> <td>Notes</td> <td>string</td> <td>Any additional or relevant information regarding the fault</td> <td> </td> </tr> <tr> <td>References</td> <td>string</td> <td>Relevant literature/geological maps where the fault is mentioned/described</td> <td> </td> </tr> </tbody> </table>   File Formats Following the <a href="http://github.com/cossatot/gem-global-active-faults">GEM-GAFD</a>, this database is provided in a variety of GIS vector file formats. <a href="http://geojson.org/">GeoJSON</a> is the version of record, and any changes should be made in this version, before they are converted to other filed formats using the <a href="https://github.com/LukeWedmore/luangwa_rift_active_fault_database/blob/main/convert.sh">convert.sh</a> shell script available in this repository. This script uses the <a href="https://gdal.org/">GDAL</a> tool <a href="https://gdal.org/programs/ogr2ogr.html">ogr2ogr</a> and is adapted from a script posted by Richard Styron (<a href="https://github.com/cossatot/central_am_carib_faults/blob/master/convert.sh">https://github.com/cossatot/central_am_carib_faults/blob/master/convert.sh</a>), who we thank for making this publicly available. The other versions available are <a href="https://support.esri.com/en/white-paper/279">ESRI Shapefile</a>, <a href="https://earth.google.com">KML</a>, <a href="https://www.generic-mapping-tools.org/">GMT</a> and <a href="https://www.geopackage.org/">Geopackage</a>. Note that in the <a href="http://support.esri.com/en/white-paper/279">ESRI Shapefile</a> format, the length of the attribute are restricted in length by the format, so we advise against using this format. Version Control This version of the database is v1.0 and is associated with the release of the data for submission of the associated manuscript. It is intended that this database is updated in future versions by both the authors and other users. As such we encourage edits of the [GeoJSON] file and the submission of pull requests on the <a href="https://github.com/LukeWedmore/luangwa_rift_active_fault_database">associated github site</a>. Please contact Luke Wedmore (<<a href="mailto:luke.wedmore@bristol.ac.uk?subject=Luangwa%20Rift%20Active%20Fault%20Databse%20Zenodo%20Release">luke.wedmore@bristol.ac.uk</a>>) for information or to report errors in the database. References Styron, Richard, and Marco Pagani. “The GEM Global Active Faults Database.” Earthquake Spectra, vol. 36, no. 1_suppl, Oct. 2020, pp. 160–180, doi:10.1177/8755293020944182.

opencc-by-4.0May 2022View details →

Luangwa Rift Fault Scarp Measurements

First Release associated with submission of article to EGU Solid Earth. Scarp height measurements for faults in the Luangwa Rift performed by Tess Turner for her University of Bristol MSci Earth Sciences final year project. If you use these measurements please cite the following paper in addition to this dataset: Turner, T., Wedmore, L.N.J., Biggs, J., Williams, J. Sichingabula, H.M., Kabumbu, C. Banda, K. The Luangwa Rift Active Fault Database and fault reactivation along the southwestern branch of the East African Rift. In preparation for Solid Earth These measurements were performed on SRTM data using the method outlined in <a href="https://doi.org/10.1029/2019TC005834">Wedmore et al., 2020</a>. Topographic profiles were sampled event 30 m and stacked at 120 m intervals along strike. Four faults in the Luangwa Rift have been measured using this technique: The Chipola, Chitembo, Kabungo and Molaza faults. The traces of these faults, and all other known active faults in the Luangwa Rift have been separately archived as part of the <a href="https://github.com/LukeWedmore/luangwa_rift_active_fault_database">Luangwa Rift Active Fault Database</a>. Data Format Files are provided in comma separated value (<a href="https://datatracker.ietf.org/doc/html/rfc4180">csv</a>) format. Each file contains one header line with descriptions of the data contained within each column. The column headings and extra information are summarised in the table below. Where data columns #5-10 are blank, this is because no measurements were possible in the profile corresponding to that particular row number. If columns 11-16 are blank, this is because there are no scarp height measurements within the sampling window of the moving average. Attribute Table <table align="left"> <caption>Attribute Table for the measurements of scarp height in the Luangwa Rift</caption> <thead> <tr> <th scope="col">Column #</th> <th scope="col">Attribute</th> <th scope="col">Units</th> <th scope="col">Data Type</th> <th scope="col">Notes</th> </tr> </thead> <tbody> <tr> <td>1</td> <td>Longitude</td> <td>decimal degrees</td> <td>Float</td> <td> </td> </tr> <tr> <td>2</td> <td>Latitude</td> <td>decimal degrees</td> <td>Float</td> <td> </td> </tr> <tr> <td>3</td> <td>Distance Along Fault</td> <td>kilometers</td> <td>Float</td> <td> </td> </tr> <tr> <td>4</td> <td>Distance Along Fault</td> <td>meters</td> <td>Integer</td> <td> </td> </tr> <tr> <td>5</td> <td>Scarp Height</td> <td>meters</td> <td>Float</td> <td>Mean scarp height measurement of 10,000 iterations of scarp height with varying subset of points in the hanging wall, scarp and footwall slopes.</td> </tr> <tr> <td>6</td> <td>Scarp Height Standard Deviation</td> <td>meters</td> <td>Float</td> <td>Standard deviation of 10,000 iterations of meausuring the scarp height with varying subset of points in the hanging wall, scarp and footwall slopes.</td> </tr> <tr> <td>7</td> <td>Upper Slope Angle  </td> <td>degrees</td> <td>Float</td> <td>Mean upper slope dip angle of 10,000 iterations of subset of points selected from the footwall slope (above the top of the fault scarp).</td> </tr> <tr> <td>8</td> <td>upper Slope Angle Standard Deviation</td> <td>degrees</td> <td>Float</td> <td>Standard devation of upper slope angle of 10,000 random subsets of the points selected on the upper slope of the fault.</td> </tr> <tr> <td>9</td> <td>Lower Slope Angle</td> <td>degrees</td> <td>Float</td> <td>Mean lower slope dip angle of 10,000 iterations of subset of points selected from the hanging wall slope.</td> </tr> <tr> <td>10</td> <td>lower Slope Angle Standard Deviation</td> <td>degrees</td> <td>Float</td> <td>Standard devation of lower slope angle of 10,000 random subsets of the points selected on the lower slope of the fault.</td> </tr> <tr> <td>11</td> <td>Filtered median offset (1 km)</td> <td>meters</td> <td>Float</td> <td>median scarp height over 1 km  of the distance along strike (0.5 km either side of the point).</td> </tr> <tr> <td>12</td> <td>filtered standard deviation (1km)</td> <td>meters</td> <td>Float</td> <td>standard deviation scarp height over 1 km  of the distance along strike (0.5 km either side of the point).</td> </tr> <tr> <td>13</td> <td>Filtered median offset (3 km) </td> <td>meters</td> <td>Float</td> <td>median scarp height over 3 km  of the distance along strike (1.5 km either side of the point).</td> </tr> <tr> <td>14</td> <td>filtered standard deviation (3km)</td> <td>meters</td> <td>Float</td> <td>standard deviation scarp height over 3 km  of the distance along strike (1.5 km either side of the point).</td> </tr> <tr> <td>15</td> <td>Filtered median offset (5 km)</td> <td>meters</td> <td>Float</td> <td>median scarp height over 5 km  of the distance along strike (2.5 km either side of the point).</td> </tr> <tr> <td>16</td> <td>filtered standard deviation (5km)</td> <td>meters</td> <td>Float</td> <td>standard deviation scarp height over 5 km  of the distance along strike (2.5 km either side of the point).</td> </tr> </tbody> </table>                                                 Version Control This release is archived as part of the publication Turner et al. (submitted to EGU Solid Earth). It is intended that this database will be updated in the future as high resolution topography products become available and/or methods for measuring fault scarps improve. Please contact Luke Wedmore <<a href="mailto:luke.wedmore@bristol.ac.uk?subject=Luangwa%20Rift%20Fault%20Scarp%20Measurements%20Zenodo%20Upload">luke.wedmore@bristol.ac.uk</a>> for more information or if you spot any errors. References Wedmore, L.N.J., Biggs, J., Williams, J.N., Fagereng, Å., Dulanya, Z., Mphepo, F., Mdala, H. (2020) Active Fault Scarps in Southern Malawi and Their Implications for the Distribution of Strain in Incipient Continental Rifts. _Tectonics_, 39(3), e2019TC005834, <a href="https://doi.org/10.1029/2019TC005834">doi.org/10.1029/2019TC005834</a>

opencc-by-4.0May 2022View details →

Data file for: Three-Dimensional Electrical Imaging Across the Cona Woka Rift and Yalaxiangbo Dome in Southern Tibetan Plateau

The magnetotellurics data were used to study  the lithospheric electrical  structure across the Cona Woka rift and Yalaxiangbo dome in the southern Tibetan plateau, conducted by Institute of Geophysical and Geochemical Exploration, Chinese Academy of Geological Sciences.  The data file of CN6.dat was generated by the Matlab code EM3DVP. You are recommended to refer to the Kelbert et al., 2014 paper: https://doi.org/10.1016/j.cageo.2014.01.010 for a brief understanding of the data file formats.

opencc-by-4.0May 2019View details →

A Global Plate Model Including Lithospheric Deformation Along Major Rifts and Orogens Since the Triassic

Global deep‐time plate motion models have traditionally followed a classical rigid plate approach, even though plate deformation is known to be significant. Here we present a global Mesozoic–Cenozoic deforming plate motion model that captures the progressive extension of all continental margins since the initiation of rifting within Pangea at ~240 Ma. The model also includes major failed continental rifts and compressional deformation along collision zones. The outlines and timing of regional deformation episodes are reconstructed from a wealth of published regional tectonic models and associated geological and geophysical data. We reconstruct absolute plate motions in a mantle reference frame with a joint global inversion using hot spot tracks for the last 80 million years and minimizing global trench migration velocities and net lithospheric rotation. In our optimized model, net rotation is consistently below 0.2°/Myr, and trench migration scatter is substantially reduced. Distributed plate deformation reaches a Mesozoic peak of 30 × 106 km2 in the Late Jurassic (~160–155 Ma), driven by a vast network of rift systems. After a mid‐Cretaceous drop in deformation, it reaches a high of 48 x 106 km2 in the Late Eocene (~35 Ma), driven by the progressive growth of plate collisions and the formation of new rift systems. About a third of the continental crustal area has been deformed since 240 Ma, partitioned roughly into 65% extension and 35% compression. This community plate model provides a framework for building detailed regional deforming plate networks and form a constraint for models of basin evolution and the plate‐mantle system.   The agegrids associated with this model can be accessed at: <a href="https://repo.gplates.org/webdav/PlateModel_Age_SR_Grids/Muller_etal_2019_Tectonics/" target="_blank" rel="noopener">https://repo.gplates.org/webdav/PlateModel_Age_SR_Grids/Muller_etal_2019_Tectonics/</a>

opencc-by-4.0Jul 2024View details →

Continuous phylogeography analysis of Rift Valley fever virus (RVFV) in Africa and the Arabian Peninsula

Spatiotemporal-explicit Bayesian phylogenetic trees and MCMC log files for Rift Valley fever virus large, medium and non-structural genetic sequences generated by BEAST v1.10 <ol> <li>Log files (logs.zip)</li> <li>Tree files (trees.zip)</li> </ol>

opencc-by-4.0Aug 2024View details →

Dataset for "Deflected Mantle Flow and Shearing-aligned Lithospheric Melt under the Strike-slip Dead Sea Rift"

Dataset 1: All of the individual shear-wave splitting measurements in the Dead Sea rift, including 1855 A and B measurements and 1088 Null measurements Dataset 2: Three component seismic waveforms used for shear-wave splitting measurement, for PKS, SKKS, and SKS, respectively Dataset 3: Earthquake catalogue with magnitude Mb 2.6 or above in the Dead Sea rift. Downloaded from the International Seismological Centre (https://www.isc.ac.uk/)                   Reference: International Seismological Centre (2024), On-line Bulletin, [Dataset] doi:10.31905/D808B830 Dataset 4: Holocene Volcano List. Downloaded from Global Volcanism Program (https://volcano.si.edu/volcanolist_holocene.cfm)                   Reference: Global Volcanism Program, 2024. Volcanoes of the World (v. 5.2.2; 22 Aug 2024). Distributed by Smithsonian Institution, compiled by Venzke, E. [Database] doi:10.5479/si.GVP.VOTW5-2024.5.2

opencc-by-4.0Jun 2021View details →

Historical forest cover in the Kivu Rift (1958)

If you use this dataset, please refer to our work: Depicker, A., Jacobs, L., Mboga, N. et al. Historical dynamics of landslide risk from population and forest-cover changes in the Kivu Rift. Nat Sustain (2021). https://doi.org/10.1038/s41893-021-00757-9 This .tif file represents the forest cover in the Kivu Rift in 1958, covering parts of the eastern DRC, western Rwanda, and western Burundi. The forest data was derived from 1 m resolution panchromatic historical aerial photographs (conserved at the Royal Museum for Central Africa) and resampled to a 30 m resolution. The data range from 0 to 1, representing the % of forest cover. Data smaller than 0 can be considered NoData values. This work was funded by the Belgian Science Policy Office (BELSPO) through the PAStECA project (BR/165/A3/PASTECA) entitled `Historical Aerial Photographs and Archives to Assess Environmental Changes in Central Africa' (http://pasteca.africamuseum.be/).

opencc-by-4.0Jun 2021View details →

Supplementary Files for "Geodetic constraints on cratonic microplates and broad strain during rifting of thick Southern African lithosphere"

This repository contains the supplementary files and tables for the manuscript: Geodetic constraints on cratonic microplates and broad strain during rifting of thick Southern African lithosphere L. N. J. Wedmore1, Biggs, J.1, Floyd, M.2, Fagereng, Å.3, Mdala, H.4, Chindandali, P.5, Williams, J.3, Mphepo, F.4 1School of Earth Sciences, University of Bristol, Bristol, UK 2Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA 3School of Earth and Environmental Sciences, Cardiff University, Cardiff, UK 4Geological Survey Department, Mzuzu Regional Office, Mzuzu, Malawi 5Geological Survey Department, Zomba, Malawi This manuscriptis published in Geophysical Research Letters: <a href="https://doi.org/10.1029/2021GL093785">https://doi.org/10.1029/2021GL093785</a> Please contact the author (luke.wedmore@bristol.ac.uk) for more information.   File Information File S1 – Table of GNSS station velocities for the combined southern Malawi/GeoPRISMS/Saria et al. (2014) solution in the ITRF14 reference frame. File S2 – Table of GNSS station and the references for the data used in this paper. File S3 – Details of the sites used for the two-plate test and the results of this inversion. File S4 – Details of the sites used for the three-plate test and the results of this inversion. File S5 – A sig_neu command file with details of the random noise added to outlier sites within GLOBK.

opencc-by-4.0Sep 2021View details →

Landslide Susceptibility in the North Tanganyika-Kivu Rift Region

The map is derived from the ensemble landslide susceptibility model as presented in the paper entitled "The added value of a regional landslide susceptibility assessment: The western branch of the East African Rift". This work was published in Geomorphology (https://doi.org/10.1016/j.geomorph.2019.106886). Refer to this paper when using this map. The map covers parts of the eastern DRC, Rwanda, and Burundi. The map is provided in .tif format and displays values between 0 (low susceptibility) and 1000 (high susceptibility). The coordinate reference system is EPSG:4326 - WGS84.

opencc-by-4.0Apr 2023View details →

Monogenetic vents in northern Main Ethiopian Rift

This data set contains three files, they are tab-delimited text files. The files have three columns, from the left:: x: UTM-WGS84 coordinate of the center of the vent in meters, y: UTM-WGS84 coordinate of the center of the vent in meters, s: the nearest neighbor distance for each vent, in meters. They were acquired by analyzing shaded relief 30 m images from the Shuttle Radar Topography Mission (SRTM) DEM (http://www2.jpl.nasa.gov/srtm/) with a vertical exaggeration (3x) and by analyzing panchromatic SPOT satellite images (http://www. spotimage.com) with a pixel resolution from 2.5 to 20 m and using Google Earth software (http://earth .google.com/).

opencc-by-4.0Apr 2023View details →

Tryps-IN: A streamlined palaeoproteomics workflow enables ZooMS analysis of 10,000-year-old petrous bones from Jordan rift-valley

Poor preservation of collagen in dry and/or arid environments has hindered the application of Zooarchaeology by mass spectrometry (ZooMS) analysis in many regions of the world, and as a result many zooarchaeological investigations have relied exclusively on the morphological assessment of fragmentary remains, due to the inadequate preservation of biomolecules. The climatic conditions of Southwest Asia include extreme temperature fluctuations unconducive to preservation of proteins and DNA. We performed zooarchaeological analysis of remains from the 10,000-year-old site of Shkārat Msaied in Jordan and sub-sampled twenty-eight petrous bones, the hardest bone in the mammalian skeleton, for species identification by ZooMS. Using an unconventional and simplified extraction protocol we call Tryps-IN, in which digestion was performed without removal of the demineralising EDTA, we taxonomically identified several fragments, outperforming the established ZooMS work-flow. A subset of identifications was subsequently confirmed using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) protein sequencing. The new methodology presented here opens the possibility of further bioarchaeological investigation of other fragmentary faunal assemblages within this region of archaeological significance.

Figures 17-26. Epigynes, ventral view 17 in An of Zelotibia (Araneae, Gnaphosidae), a spider genus with a species swarm in the Albertine Rift

Figures 17-26. Epigynes, ventral view 17 Zelotibia angelica sp. n.; 18 Z. curvifemur sp. n.; 19 Z. fosseyae sp. n., female; 20 Z. johntony sp. n.; 21 Z. kanama sp. n.; 22 Z. kibira sp. n. 23 Z. lejeunei sp. n. 24 Z. major; 25 Z. paucipapillata; 26 Z. subsessa sp. n., (scale bar 0.2 mm).

Figures 12-16 in An of Zelotibia (Araneae, Gnaphosidae), a spider genus with a species swarm in the Albertine Rift

Figures 12-16. Zelotibia curvifemur sp. n. 12 Male palp, retrolateral view; 13 Male palp, ventral view; 13b. Male palp, expanded; Zelotibia lejeunei 14 Male palp, retrolateral view; 15 Male palp, dorsal view; 16 male palp, ventral view. CY: cymbium; E: embolus; MA: median apophysis; SD: sperm duct; ST: subtegulum; T: tegulum. (scale bar 0.5 mm).

Figures 1-11 in An of Zelotibia (Araneae, Gnaphosidae), a spider genus with a species swarm in the Albertine Rift

Figures 1-11. Habitus of Zelotibia 1 Zelotibia angelica sp. n. female; 2 Z. curvifemur sp. n., female; 3 male; 4 Z. fosseyae sp. n., female; 5 Z. johntony sp. n., female; 6 Z. kanama sp. n., female; 7 Z. kibira sp. n., female; 8 Z. lejeunei sp. n., female; 9 Z. major, female; 10 Z. paucipapillata, female; 11 Z. subsessa sp. n., female.

Tip of epigynal scape forming an obtuse angle, spermathecae located imme- diately posterior to tip of scape (e3) in An of Zelotibia (Araneae, Gnaphosidae), a spider genus with a species swarm in the Albertine Rift

Tip of epigynal scape forming an obtuse angle, spermathecae located imme- diately posterior to tip of scape (e3)