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Supporting Data - Taxonomic reassessment of Tetrapygus niger (Arbacioida, Echinoidea): molecular and morphological evidence support its placement in Arbacia

This dataset contains the accession numbers and links of the sequences of the specimens analyzed by this work, other sequences used for the analyses can be found in the original article. The species from which the sequences were extracted are: Tetrapygus niger Molina, 1782; Arbacia dufresnii Blainville, 1825; Arbacia spatuligera Valenciennes, 1846 and Coelopleurus floridanus A. Agassiz, 1872. The accession numbers for the Cytochrome Oxidase subunit I (COI) and 28S of the nuclear genome are presented separately.In addition, the morphological data of Tetrapygus niger (Test diameter, test height and peristome diameter) presented in this study are shown, as well as their collectors, corresponding collection, country and locality.

opencc-by-4.0Jul 2022View details →

Bird counts at Buanyuantula, Makalondi, Niger (1991-1993)

Bird counts along transects carried out by <a href="https://www.wikiwand.com/de/Pierre_Souvairan_(Missionar)">Pierre Souvairan (1921-1998)</a> from June 1991 to September 1993 at Buanyuantula (spelled <a href="https://www.openstreetmap.org/#map=16/12.8087/1.7377">Boignontoula in OpenStreetMap</a>), Makalondi, Niger, near the <a href="https://www.openstreetmap.org/#map=15/12.8029/1.7393">Kulbu pools</a>. Patrick Giraudoux helped Pierre Souvairan to design the protocol during his stays in Dijon, France. Patrick Giraudoux (in December 1991) and Dominique Michelat (in July-August 1995) visited Pierre Souvairan once on the spot at Buanyuantula, then digitized and secured the data. Two transect strips were walked, corresponding to grids of 100 x 100 m mesh. Each transect was walked along a line crossing the grid, observing birds at maximum 50 m on each side of the transect line. - The NS strip corresponds to a 2.5 km x 200 m strip. The grid consists in two contiguous sub-strips (one north, one south of 100 x 100 m mesh each) stretching E - W between Buanyuantula and the Kulbu pools depression. Three 2.5 km transects lines were walked: one "N" in the middle of the northern strip, one "M", median, at the common border of the two strips, one "S" in the middle of the southern strip. - Transects B, for "bas-fond" (wetland), has two discrete segments 01B-10B and 16B-25B, and was walked at the higher water limit of the Kulbu pools area. <table align="center"> <caption> Transect dates </caption> <thead> <tr> <th scope="col">Transect</th> <th scope="col">Beginning</th> <th scope="col">End</th> <th scope="col"> Fortnight number </th> </tr> </thead> <tbody> <tr> <td>N</td> <td>June 1991, fortnight #1</td> <td>May 1992, fortnight #2</td> <td>24</td> </tr> <tr> <td>S</td> <td>June 1991, fortnight #1</td> <td>May 1992, fortnight #2</td> <td>24</td> </tr> <tr> <td>M</td> <td>September 1992, fortnight #1</td> <td>August 1993, fortnight #2</td> <td>24</td> </tr> <tr> <td>01B-10B</td> <td>October 1992, fortnight #1</td> <td>September 1993, fortnight #2</td> <td>24</td> </tr> <tr> <td>16B-25B</td> <td>September 1992, fortnight #1</td> <td>August 1993, fortnight #2</td> <td>24</td> </tr> </tbody> </table> Caveat: the approximate place of those transects has been georeferenced in July 2022 by Patrick Giraudoux and Dominique Michelat based on Google Earth and Bing satellite backgrounds imported in QuantumGIS 3.24.2-Tisler, and on a hand-made document (<a href="https://zenodo.org/record/6905506/files/Itine%CC%81raire%20lettre%2018101992.jpeg?download=1">Itinéraire lettre 18101992.jpeg)</a> Pierre Souvairan prepared and sent in October 1992. On the satellite background, Pierre Souvairan's compound (cabin and field), some tracks (e.g. Makalondi trail), the Buanyuantula village were still clearly visible as well as the general geomorphological features of the area. However, irrevocable differences still remain between georeferenced files and Pierre Souvairan's paper maps. We have prioritized the consistency with undoubtful features such as well identified tracks, acknowledging that after more than 30 years when the hand made maps have been drawn, vegetation features, wetland border, etc. might have sensibly changed. Pierre Souvairan was an excellent ornithologist, but had one bad eye (half blind). Assuming a constant bias due to this, comparability between observations is fine in term of relative abundance. This issue must however be considered, should comparisons with other observers be done. FILE DESCRIPTION: Main files Files <a href="https://zenodo.org/record/6905506/files/carres_date.txt?download=1">carres_date.txt </a>, <a href="https://zenodo.org/record/6905506/files/especes.txt?download=1">especes.txt </a>, <a href="https://zenodo.org/record/6905506/files/observations.txt?download=1">observations.txt  </a>are tables of a relational database. They can be linked using the index field 'carre' between <a href="https://zenodo.org/record/6905506/files/carres_date.txt?download=1">carres_date.txt</a> and <a href="https://zenodo.org/record/6905506/files/observations.txt?download=1">observations.txt</a>, and the index field 'espece' between <a href="https://zenodo.org/record/6905506/files/observations.txt?download=1">observations.txt </a>and <a href="https://zenodo.org/api/files/7f6752aa-6261-4287-a7d3-db865b022f89/especes.txt?versionId=46b71a45-2815-4e8e-bhttps://zenodo.org/record/6905506/files/especes.txt?download=1689-44cc2999ae99">especes.txt</a>. <a href="https://zenodo.org/record/6905506/files/carres_date.txt?download=1">carres_date.txt </a> <ul> <li>carre, grid square ID : digits 1-2, the grid square ID; digit 3, transect ID (N, north; S, south; M, Median; B, Bas-fond); digit 4-5, the fortnight number from the first survey fortnight to the last one (1 - 24). Examples: 01N01 is square 01 of transect N, first fortnight; 01N10 is square 01 of transect N, tenth fortnight.</li> <li>annee, year (91-93 for 1991-1993)</li> <li>duree, crossing duration (in hour fraction: e.g. 5 mn = 5/60 = 0.08). The speed at which each grid square was crossed (depending on vegetation density, number of observations, etc.)</li> <li>mois, month (1-12)</li> <li>date, the date of the crossing (computed for convenience from the year, month and fortnight: day 10 was given arbitrarily for the first fortnight, and day 20 for the second  fortnight of the month).</li> </ul> <a href="https://zenodo.org/record/6905506/files/especes.txt?download=1">especes.txt </a> <ul> <li>espece, ID number</li> <li>nom, Latin name</li> <li>code, 4 digits abbreviation</li> </ul> <a href="https://zenodo.org/record/6905506/files/observations.txt?download=1">observations.txt </a> <ul> <li>carre, carre ID (for joining see the field ‘carre’ field in the file<a href="https://zenodo.org/record/6905506/files/carres_date.txt?download=1"> carres_date.txt</a>)</li> <li>espece, species ID number (for joining see the field ‘espece’ in the file <a href="https://zenodo.org/record/6905506/files/especes.txt?download=1">especes.txt</a>)</li> <li>nombre, number of individuals observed</li> </ul> Supplementary files <a href="https://zenodo.org/record/6905506/files/Carte Makalondi.jpeg?download=1">Carte Makalondi.jpeg </a>the scan of a map Pierre Souvairan drew with the location of the places mentioned in his correspondence. <a href="https://zenodo.org/record/6905506/files/Geometries_Grid_NS_B_transectLines.zip?download=1">Geometries_Grid_NS_B_transectLines.zip  </a>the grid and transect geometries (ESRI and kml). <a href="https://zenodo.org/record/6905506/files/Itine%CC%81raire%20lettre%2018101992.jpeg?download=1">Itinéraire lettre 18101992.jpeg </a>the scan of a map Pierre Souvairan drew and sent to Patrick Giraudoux (letter received in October 1992). Georeferenced locations are available in <a href="https://zenodo.org/record/6905506/files/Name_coordinates.kml?download=1">Name_coordinates.kml</a>. <a href="https://zenodo.org/record/6905506/files/Name_coordinates.kml?download=1">Name_coordinates.kml </a>the georeferenced locations of places mentioned in the field map <a href="https://zenodo.org/record/6905506/files/Carte Makalondi.jpeg?download=1">Carte Makalondi.jpeg</a>. <a href="https://zenodo.org/record/6905506/files/PhotosNumbered.pdf?download=1">PhotosNumbered.pdf</a> photos taken on the spot in December 1991 by Patrick Giraudoux. The place where each photo was taken and the direction is in red in the transect map <a href="https://zenodo.org/record/6905506/files/ScanTransectPhotos.jpg?download=1">ScanTransectPhotos.jpg</a>. <a href="https://zenodo.org/record/6905506/files/ScanTransectPhotos.jpg?download=1">ScanTransectPhotos.jpg</a> 20 x 140.4 cm field map of the NS strip with vegetation data, drawn by Pierre Souvairan likely in 1991. <a href="https://zenodo.org/record/6905506/files/Transects_Grids_Map.jpg?download=1">Transects_Grids_Map.jpg</a> Map of the area, with the exact location of pools, Buanyuantula village, Pierre Souvairan's cabin, and the general location of the grids and transects. Note that the latter two have been approximately located based on Pierre Souvairan's field maps (see caveat above). Background Bing satellite accessed 31/07/2022.

opencc-zeroNov 2018View details →

Herbarium specimen image of Hyoscyamus niger L., part of the collection of Natural History Museum, University of Tartu

Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published. Content of this deposition: - A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values. - A JPEG image file of the scanned herbarium sheet. - A lossless TIFF image from which the JPEG image has been derived.

opencc-zeroNov 2018View details →

Herbarium specimen image of Cotoneaster niger (Wahlb.) Fr., part of the collection of Natural History Museum, University of Tartu

opencc-zeroAug 2024View details →

National Checklists 2017: Niger Species List

Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See https://github.com/diatomsRcool/checklists for detailsA list of species from Niger collected using effechecka and geonames polygons

opencc-zeroAug 2024View details →

National Checklists 2019: Niger Species List

Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See https://github.com/diatomsRcool/checklists for details.A list of species from Niger collected using effechecka and geonames polygons

opencc-by-4.0Sep 2024View details →

Kam-Niger-Congo comparative word list

This is a comparative word list containing data collected with the Leipzig-Jakarta word list, intended to compare basic vocabulary between Kam and other Niger-Congo languages. It contains reconstructions for a variety of proto-languages already available in the literature (e.g. Jukunoid, Mumuyic, Proto-Bantu, Proto-Gbe, Proto-Potou-Akanic, and Proto-Fula-Sereer), as well as the author's own quasi-reconstructions for Niger-Congo, Benue-Congo, and Delta-Cross and cognate judgements.

opencc-by-4.0Feb 2009View details →

Figs 2-4 in Xanthopygoides niger Cameron, 1951 (Xanthopygina) belongs to the genus Philonthus Stephens, 1829 (Philonthina): systematic and nomenclatural changes for the African Staphylinini (Coleoptera, Staphylinidae, Staphylininae, Staphylinini)

Figs 2-4. Philonthus neoniger Solodovnikov, nom. nov. Details of structure: 2, prothorax (in vertral view, only left side illustrated, anterior leg removed); 3, aedeagus in dorsal (parameral) view (internal sac evert-ed); 4, aedeagus in lateral view (internal sac everted). Scale bar 1 mm.

opencc-by-4.0Jan 2021View details →

qdgc Niger

QDGC tables delivered in geopackage file - - - - - - - - - - - - - - - - - - - - - - QDGC represents a way of making (almost) equal area squares covering a specific area to represent specific qualities of the area covered. The squares themselves are based on the degree squares covering earth. Around the equator we have 360 longitudinal lines , and from the north to the south pole we have 180 latitudinal lines. Together this gives us 64800 segments or tiles covering earth. Within each geopackage file you will find a number of tables with these names: -tbl_qdgc_01 -tbl_qdgc_02 -tbl_qdgc_03 -tbl_qdgc_04 -tbl_qdgc_05 -etc The attributes for each table are: qdgc Unique Quarter Degree Grid Cell reference string area_reference Country level_qdgc QDGC level cellsize degrees decimal degree for the longitudal and latitudal length of the cell lon_center Longitude center of the cell lat_center Latitudal center of the cell area_km2 Calculated area for the cell geom Geometry Metadata -------- Geodata GCS_WGS_1984 Datum: D_WGS_1984 Prime Meridian: 0 Areas are calculated with different versions of Albers Equal Area Conic using the PostGIS function st_area. For the African continent I have used Africa Albers Equal Area Conic which will look like this: - st_area(st_transform(geom, 102022))/1000000) Licensing --------- Creative Commons Attribution 4.0 International Conditions ---------- Delivered to the user as-is. No guarantees. If you find errors, please tell me and I will try to fix it. Suggestions for improvements can be addressed to the github repository: https://github.com/ragnvald/qdgc Thankyou -------- The work has over the years been supported and received advice and moral support from many organisations and stakeholders. Here are some of them: - Tanzania Wildlife Research Institute - Dept of Biology, NTNU, Norway - Norwegian Environment Agency - Eivin Røskaft, Steven Prager, Howard Frederick, Julian Blanc, Honori Maliti, Paul Ramsey References ---------- * http://en.wikipedia.org/wiki/QDGC * http://www.mindland.com/wp/projects/quarter-degree-grid-cells/about-qdgc/ * http://en.wikipedia.org/wiki/Lambert_azimuthal_equal-area_projection * http://www.safe.com Ragnvald Larsen Trondheim 23rd of January, 2021 ragnvald@mindland.com www.mindland.com

opencc-by-4.0Apr 2020View details →

Figure 7 Arrenurus niger n in New records of the water mite genus Arrenurus Dugès, 1834 from South America (Acari: Hydrachnidia: Arrenuridae), with the description of five new species and one new subspecies

Figure 7 Arrenurus niger n. sp. A-E holotype male, F paratype female. A – dorsum; B – venter; C – right palp; D – left palp (segments rotated); E – IV-leg-6; F = venter. Scale bars: A-B, F = 100 µm, C-E = 50 µm.

opencc-zeroJan 2016View details →

Daily Activity and Nest Occupation Patterns of Fox Squirrels (Sciurus niger) Throughout the Year

The daily distribution of activity has been studied in detail in ground squirrels in the field as well as in the laboratory, but studies of tree squirrels have been few and generally limited to the sampling of behavior of groups of animals. In this study, the authors investigated the general activity and nest occupation patterns of fox squirrels in a natural setting using temperature-sensitive data loggers that measure activity as changes in the microenvironment of the animal. Data were obtained from 25 distinct preparations, upon 13 unique squirrels, totaling 1385 recording days. Fox squirrels exhibited robust daily rhythmicity of locomotor activity, comparable to that of laboratory rats and gerbils. The animals were clearly diurnal, with a predominantly unimodal activity pattern, although individual squirrels occasionally exhibited bimodal patterns, particularly in the spring and summer. Even during the short days of winter (9 hours), the squirrels typically left the nest after dawn and returned before dusk, spending only about 7 hours out of the nest each day. Although the duration of the daily active phase did not change with the seasons, the squirrels exited the nest earlier in the day when the days became longer in the summer and exited the nest later in the day when the days became shorter in the winter, thus tracking dawn along the seasons. During the few hours each day spent outside the nest, fox squirrels seemed to spend most of the time sitting or lying. These findings suggest that fox squirrels may have adopted a slow life history strategy.

opencc-by-sa-4.0Dec 2023View details →

Infrastructure Climate Resilience Assessment Data Starter Kit for Niger

This starter data kit collects extracts from global, open datasets relating to climate hazards and infrastructure systems. These extracts are derived from global datasets which have been clipped to the national scale (or subnational, in cases where national boundaries have been split, generally to separate outlying islands or non-contiguous regions), using Natural Earth (2023) boundaries, and is not meant to express an opinion about borders, territory or sovereignty. Human-induced climate change is increasing the frequency and severity of climate and weather extremes. This is causing widespread, adverse impacts to societies, economies and infrastructures. Climate risk analysis is essential to inform policy decisions aimed at reducing risk. Yet, access to data is often a barrier, particularly in low and middle-income countries. Data are often scattered, hard to find, in formats that are difficult to use or requiring considerable technical expertise. Nevertheless, there are global, open datasets which provide some information about climate hazards, society, infrastructure and the economy. This "data starter kit" aims to kickstart the process and act as a starting point for further model development and scenario analysis. Hazards: <ul> <li>coastal and river flooding (Ward et al, 2020; Baugh et al, 2024)</li> <li>extreme heat and drought (Russell et al 2023, derived from Lange et al, 2020)</li> <li>tropical cyclone wind speeds (Russell 2022, derived from Bloemendaal et al 2020 and Bloemendaal et al 2022)</li> </ul> Exposure: <ul> <li>population (Schiavina et al, 2023)</li> <li>built-up area (Pesaresi et al, 2023)</li> <li>roads (OpenStreetMap, 2025)</li> <li>railways (OpenStreetMap, 2025)</li> <li>power plants (Global Energy Observatory et al, 2018)</li> <li>power transmission lines (Arderne et al, 2020)</li> </ul> Contextual information: <ul> <li>elevation (European Union and ESA, 2021)</li> <li>land-use and land cover (Copernicus Climate Change Service and Climate Data Store, 2019)</li> <li>administrative boundaries from geoBoundaries (Runfola et al., 2020)</li> </ul> The spatial intersection of hazard and exposure datasets is a first step to analyse vulnerability and risk to infrastructure and people. To learn more about related concepts, there is a free short course available through the Open University on <a href="https://www.open.edu/openlearncreate/course/view.php?id=12278">Infrastructure and Climate Resilience</a>. This <a href="https://opsis.eci.ox.ac.uk/courses/2-infra-for-resil/">overview of the course</a> has more details. These Python libraries may be a useful place to start analysis of the data in the packages produced by this workflow: <ul> <li> <a href="https://github.com/tomalrussell/snkit"><code>snkit</code></a> helps clean network data </li> <li> <a href="https://github.com/nismod/snail"><code>nismod-snail</code></a> is designed to help implement infrastructure exposure, damage and risk calculations </li> </ul> The <a href="https://github.com/nismod/open-gira"><code>open-gira</code></a> repository contains a larger workflow for global-scale open-data infrastructure risk and resilience analysis. For a more developed example, some of these datasets were key inputs to a regional climate risk assessment of current and future flooding risks to transport networks in East Africa, which has a related online visualisation tool at <a href="https://east-africa.infrastructureresilience.org/">https://east-africa.infrastructureresilience.org/</a> and is described in detail in Hickford et al (2023). References <ul> <li> Arderne, Christopher, Nicolas, Claire, Zorn, Conrad, & Koks, Elco E. (2020). Data from: Predictive mapping of the global power system using open data [Dataset]. In Nature Scientific Data (1.1.1, Vol. 7, Number Article 19). Zenodo. DOI: <a href="https://doi.org/10.5281/zenodo.3628142">10.5281/zenodo.3628142</a> </li> <li> Baugh, Calum; Colonese, Juan; D'Angelo, Claudia; Dottori, Francesco; Neal, Jeffrey; Prudhomme, Christel; Salamon, Peter (2024): Global river flood hazard maps. European Commission, Joint Research Centre (JRC) [Dataset] PID: <a href="http://data.europa.eu/89h/jrc-floods-floodmapgl_rp50y-tif">data.europa.eu/89h/jrc-floods-floodmapgl_rp50y-tif</a> </li> <li> Bloemendaal, Nadia; de Moel, H. (Hans); Muis, S; Haigh, I.D. (Ivan); Aerts, J.C.J.H. (Jeroen) (2020): STORM tropical cyclone wind speed return periods. 4TU.ResearchData. [Dataset]. DOI: <a href="https://doi.org/10.4121/12705164.v3">10.4121/12705164.v3</a> </li> <li> Bloemendaal, Nadia; de Moel, Hans; Dullaart, Job; Haarsma, R.J. (Reindert); Haigh, I.D. (Ivan); Martinez, Andrew B.; et al. (2022): STORM climate change tropical cyclone wind speed return periods. 4TU.ResearchData. [Dataset]. DOI: <a href="https://doi.org/10.4121/14510817.v3">10.4121/14510817.v3</a> </li> <li> Copernicus Climate Change Service, Climate Data Store, (2019): Land cover classification gridded maps from 1992 to present derived from satellite observation. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: <a href="https://doi.org/10.24381/cds.006f2c9a">10.24381/cds.006f2c9a</a> (Accessed on 09-AUG-2024) </li> <li> Copernicus DEM - Global Digital Elevation Model (2021) DOI: <a href="https://doi.org/10.5270/ESA-c5d3d65">10.5270/ESA-c5d3d65</a> (produced using Copernicus WorldDEM™-90 © DLR e.V. 2010-2014 and © Airbus Defence and Space GmbH 2014-2018 provided under COPERNICUS by the European Union and ESA; all rights reserved) </li> <li> Global Energy Observatory, Google, KTH Royal Institute of Technology in Stockholm, Enipedia, World Resources Institute. (2018) Global Power Plant Database. Published on Resource Watch and Google Earth Engine; <a href="http://resourcewatch.org/">resourcewatch.org/</a> </li> <li> Hickford et al (2023) Decision support systems for resilient strategic transport networks in low-income countries – Final Report. Available online: <a href="https://transport-links.com/hvt-publications/final-report-decision-support-systems-for-resilient-strategic-transport-networks-in-low-income-countries">https://transport-links.com/hvt-publications/final-report-decision-support-systems-for-resilient-strategic-transport-networks-in-low-income-countries</a> </li> <li> Lange, S., Volkholz, J., Geiger, T., Zhao, F., Vega, I., Veldkamp, T., et al. (2020). Projecting exposure to extreme climate impact events across six event categories and three spatial scales. Earth's Future, 8, e2020EF001616. DOI: <a href="https://doi.org/10.1029/2020EF001616">10.1029/2020EF001616</a> </li> <li> Natural Earth (2023) Admin 0 Map Units, v5.1.1. [Dataset] Available online: <a href="https://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-details/">www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-details</a> </li> <li> OpenStreetMap contributors, Russell T., Thomas F., nismod/datapkg contributors (2025) Road and Rail networks derived from OpenStreetMap. [Dataset] Available at <a href="https://global.infrastructureresilience.org">global.infrastructureresilience.org</a> </li> <li> Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030) European Commission, Joint Research Centre (JRC) PID: <a href="http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea">data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea</a>, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA </li> <li> Runfola D, Anderson A, Baier H, Crittenden M, Dowker E, Fuhrig S, et al. (2020) geoBoundaries: A global database of political administrative boundaries. PLoS ONE 15(4): e0231866. DOI: <a href="https://doi.org/10.1371/journal.pone.0231866">10.1371/journal.pone.0231866</a>. </li> <li> Russell, T., Nicholas, C., & Bernhofen, M. (2023). Annual probability of extreme heat and drought events, derived from Lange et al 2020 (Version 2) [Dataset]. Zenodo. DOI: <a href="https://doi.org/10.5281/zenodo.8147088">10.5281/zenodo.8147088</a> </li> <li> Schiavina M., Freire S., Carioli A., MacManus K. (2023): GHS-POP R2023A - GHS population grid multitemporal (1975-2030). European Commission, Joint Research Centre (JRC) PID: <a href="http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe">data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe</a>, doi:10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE </li> <li> Ward, P.J., H.C. Winsemius, S. Kuzma, M.F.P. Bierkens, A. Bouwman, H. de Moel, A. Díaz Loaiza, et al. (2020) Aqueduct Floods Methodology. Technical Note. Washington, D.C.: World Resources Institute. Available online at: <a href="https://www.wri.org/publication/aqueduct-floods-methodology">www.wri.org/publication/aqueduct-floods-methodology</a>. </li> </ul>

opencc-by-4.0Dec 2023View details →

Transport Starter Data Kit: Historical socio-transport data for Niger

This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.

F I G U R E 3 in Biological information on a rare pelagic fish, black ruff Centrolophus niger, caught in Icelandic waters: Distribution, feeding, and otoliths

F I G U R E 3 Images of the proximal and distal sides of the right and left otoliths from black ruff Centrolophus niger (Gmelin, 1789). Scale bar and the plane at which the length and width of the otolith were measured are shown.

F I G U R E 1 in Biological information on a rare pelagic fish, black ruff Centrolophus niger, caught in Icelandic waters: Distribution, feeding, and otoliths

F I G U R E 1 Three specimens of black fish (Centrolophus niger) caught during the International Ecosystem Summer Survey of the Nordic Seas in 2021. Specimens were photographed prior to freezing. Photograph by James Kennedy.

F I G U R E 8 Total length v in Biological information on a rare pelagic fish, black ruff Centrolophus niger, caught in Icelandic waters: Distribution, feeding, and otoliths

F I G U R E 8 Total length v. (a) total weight, (b) fork length, and (c) standard length for black ruff Centrolophus niger (Gmelin, 1789) from the current and previous studies. The origin of the previous data is indicated in the legend. (a) Nonlinear and (b, c) linear regression models are shown. Note that total weight corresponds to frozen weight for measurements in the current study, whereas for previous studies, corresponds to the weight given in the respective study.

F I G U R E 2 in Biological information on a rare pelagic fish, black ruff Centrolophus niger, caught in Icelandic waters: Distribution, feeding, and otoliths

F I G U R E 2 Location of sampling stations of the Icelandic component of the International Ecosystem Summer Survey of the Nordic Seas 2009–2021. Stations where black ruff Centrolophus niger (Gmelin, 1789) were caught are shown in Black. The main surface currents in the Northeast Atlantic are shown in the final panel; the cold East Greenland current (green) and the warm Atlantic current (red) (Blindheim & Østerhus, 2005).

F I G U R E 7 Total length v in Biological information on a rare pelagic fish, black ruff Centrolophus niger, caught in Icelandic waters: Distribution, feeding, and otoliths

F I G U R E 7 Total length v. (a) frozen weight, (b) fork length, (c) and standard length and frozen weight v. (d) thawed weight for black ruff Centrolophus niger (Gmelin, 1789). (a) Nonlinear and (b–d) linear regression models are shown (a–d) as well as x = y line (d).

F I G U R E 4 in Biological information on a rare pelagic fish, black ruff Centrolophus niger, caught in Icelandic waters: Distribution, feeding, and otoliths

F I G U R E 4 Temperature profiles from the CTD probe at each station of the Icelandic part of the International Ecosystem Summer Survey of the Nordic Seas (IESSNS) where black ruff Centrolophus niger (Gmelin, 1789) were caught.