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219 results for “Equatorial Guinea”
National Checklists 2017: Equatorial Guinea Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from Equatorial Guinea collected using effechecka and geonames polygons
National Checklists 2019: Equatorial Guinea Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>A list of species from Equatorial Guinea collected using effechecka and geonames polygons
Transport Starter Data Kit: Historical socio-transport data for Equatorial Guinea
<p>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.</p>
Infrastructure Climate Resilience Assessment Data Starter Kit for Equatorial Guinea
<p> This starter data kit collects extracts from global, open datasets relating to climate hazards and infrastructure systems. </p> <p> 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. </p> <p> 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. </p> <p>Hazards:</p> <ul> <li>coastal and river flooding (Ward et al, 2020)</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> <p>Exposure:</p> <ul> <li>population (Schiavina et al, 2023)</li> <li>built-up area (Pesaresi et al, 2023)</li> <li>roads (OpenStreetMap, 2023)</li> <li>railways (OpenStreetMap, 2023)</li> <li>power plants (Global Energy Observatory et al, 2018)</li> <li>power transmission lines (Arderne et al, 2020)</li> </ul> <p> The spatial intersection of hazard and exposure datasets is a first step to analyse vulnerability and risk to infrastructure and people. </p> <p> 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=11539">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. </p> <p> These Python libraries may be a useful place to start analysis of the data in the packages produced by this workflow: </p> <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> <p> 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. </p> <p> 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). </p> <p><strong>References</strong></p> <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> 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> 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 (2023) 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> 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>
National Checklists: Equatorial Guinea Species List
Data from: GBIF.org (23 January 2025) GBIF Occurrence Download <a href="https://doi.org/10.15468/dl.vd2ajk" target="_blank" rel="noopener">https://doi.org/10.15468/dl.vd2ajk</a>
Figs. 1-3 in Description of a new species of Thaumaglossa Redtenbacher, 1867 (Coleoptera¡ Dermestidae) from the Republic of Equatorial Guinea (West Africa).
Figs. 1-3.- Thaumaglossa escalerai, new species. 1.- habitus, dorsal aspect. 2.- antenna. 3.- genitalia.
CCG Starter Data Kit: Equatorial Guinea
<p>A starter data kit for Equatorial Guinea</p>
Using cumulative impact mapping to prioritise marine conservation efforts in Equatorial Guinea
<p>Marine biodiversity is under extreme pressure from anthropogenic activity globally, leading to calls to protect at least 10% of the world's oceans within marine protected areas (MPAs) and other effective area-based conservation measures by 2020. Fulfilling such commitments, however, requires a detailed understanding of the distribution of potentially detrimental human activities, and their predicted impacts. One such approach that is being increasingly used to strengthen our understanding of human impacts is cumulative impact mapping; as it can help identify economic sectors with the greatest potential impact on species and ecosystems in order to prioritise conservation management strategies, providing clear direction for intervention. In this paper, we present the first local cumulative utilisation impact mapping exercise for the Bioko-Corisco-Continental area of Equatorial Guinea's Exclusive Economic Zone – situated in the Gulf of Guinea one of the most important and least studied marine regions in the Eastern Central Atlantic. This study examines the potential impact of ten direct anthropogenic activities on a suite of key marine megafauna species and reveals that the most suitable habitats for these species, located on the continental shelf, are subject to the highest threat scores. However, in some coastal areas, the persistence of highly suitable habitat subject to lower threat scores suggests that there are still several strategic areas that are less impacted by human activity that may be suitable sites for protected area expansion. Highlighting both the areas with potentially the highest impact, and those with lower impact levels, as well as particularly damaging activities can inform the direction of future conservation initiatives in the region.</p>
FIGURE 2 in First record of Tardigrada from São Tomé (Gulf of Guinea, Western Equatorial Africa) and description of Pseudechiniscus santomensis sp. nov. (Heterotardigrada: Echiniscidae)
FIGURE 2. Cuticular plate ornamentation of: A, Pseudechiniscus santomensis sp. nov. (holotype); B, P. bartkei; C, P. gullii; D, P. quadrilobatus; E, P. spinerectus and F, P. novaezeelandiae novaezeelandiae. Arrows indicate delicate striae connecting the dots. Scale bars = 10 µm.
FIGURE 1 in First record of Tardigrada from São Tomé (Gulf of Guinea, Western Equatorial Africa) and description of Pseudechiniscus santomensis sp. nov. (Heterotardigrada: Echiniscidae)
FIGURE 1. Pseudechinscus santomensis sp. nov., A, Anterior portion of the body of the holotype; the W-shaped fold of the head plate (arrow a), the transverse fold dividing the scapular plate into an anterior and a posterior portion (arrow b), the transverse fold dividing the median plate 1 into an anterior and a posterior portion (arrow c), the buccal cirri, the cephalic papilla (arrow d), the cirrus A and the adjacent clava (arrow e) are visible. B, posterior portion of the body of the holotype; the transverse fold dividing the median plate 2 into an anterior and a posterior portion (arrow a), the intersegmental platelets lateral to the median plates 1 and 2 (arrows b, c), the triangular marginal projections of the undivided pseudosegmental plate (arrows d, e), the papilla on the hind legs (arrow f) are visible. C, posterior portion of the body of a paratype; the undivided median plate 3 (arrow a) and the pseudosegmental plate with reduced marginal projections (arrows b, c) are visible. D, cuticular ornamentation of the ventral body surface of a paratype. The arrows indicate spurs of the internal claws. Scale bars = 10 µm.
FIGURE 3. Fernandea conradti. A in Revision of the Afrotropical genus Fernandea Melichar, 1912 (Hemiptera: Fulgoromorpha: Dictyopharidae), with description of a new species from Equatorial Guinea
FIGURE 3. Fernandea conradti. A. Head, pronotum and mesonotum, dorsal view; B. Head and pronotum, lateral view; C. Head and pronotum, ventral view; D. Segment X and pygofer, dorsal view; E. Pygofer, gonostyles, and segment X, lateral view; F. Pygofer and gonostyles, ventral view; G. Aedeagus, dorsal view; H. Aedeagus, lateral view; I. Aedeagus, ventral view.
FIGURE 2. Fernandea spp., fore femora. A. F in Revision of the Afrotropical genus Fernandea Melichar, 1912 (Hemiptera: Fulgoromorpha: Dictyopharidae), with description of a new species from Equatorial Guinea
FIGURE 2. Fernandea spp., fore femora. A. F. conradti; B. F. latifemorata sp. nov.; C. Forewing and hindwing of F. conradti.
FIGURE 5 in Revision of the Afrotropical genus Fernandea Melichar, 1912 (Hemiptera: Fulgoromorpha: Dictyopharidae), with description of a new species from Equatorial Guinea
FIGURE 5. Fernandea latifemorata sp. nov. A. Head, pronotum and mesonotum, dorsal view; B. Head and pronotum, lateral view; C. Head and pronotum, ventral view (white arrow showing fore coxa); D. Segment X and pygofer, dorsal view; E. Pygofer, gonostyles, and segment X, lateral view; F. Pygofer and gonostyles, ventral view; G. Gonostyle, caudal view (white arrow showing dorsoventrally compressed upper process); H. Aedeagus, dorsal view; I. Aedeagus, lateral view; J. Aedeagus, ventral view.
FIGURE 1 in Revision of the Afrotropical genus Fernandea Melichar, 1912 (Hemiptera: Fulgoromorpha: Dictyopharidae), with description of a new species from Equatorial Guinea
FIGURE 1. Habitus of Fernandea species. A. F. conradti, lectotype, female, dorsal view; B. F. conradti, lectotype, female, lateral view; C. F. latifemorata sp. nov., holotype, male, dorsal view.
FIGURE 4. Fernandea conradti. A in Revision of the Afrotropical genus Fernandea Melichar, 1912 (Hemiptera: Fulgoromorpha: Dictyopharidae), with description of a new species from Equatorial Guinea
FIGURE 4. Fernandea conradti. A. Female terminalia and ectodermal genital ducts, lateral view; B. Female genitalia, ventral view; C. Gonapophysis VIII, dorsolateral view; D. Gonapophysis IX, ventral view; E. Gonoplacs, lateral view; F. Female segment X, dorsal view.
FIGURE 1 in Checklist of the Vascular Plants of Annobón (Equatorial Guinea)
FIGURE 1. Map of Annobón Island. Numbers on the map correspond to the main collection localities, which are indicated in Appendix 1.
FIGURE 4 in Checklist of the Vascular Plants of Annobón (Equatorial Guinea)
FIGURE 4. Asplenium annobonensis Mildbr. ex Viane (based on Velayoset al. 11604, MA). Endemic to Annobón.
FIGURE 5 in Checklist of the Vascular Plants of Annobón (Equatorial Guinea)
FIGURE 5. Discoclaoxylon pubescens (Pax & K. Hoffm.) Exell (based on Velayos et al. 11648, MA). Endemic to Annobón.
Distribution. Benin and Nigeria to Cameroon, Central African Republic, Equatorial Guinea, PR Congo, and probably Gabon. in Herpestidae
Distribution. Benin and Nigeria to Cameroon, Central African Republic, Equatorial Guinea, PR Congo, and probably Gabon.
Distribution. SE Nigeria, Cameroon, Central African Republic, DR Congo, Equatorial Guinea, Gabon, and PR Congo. Also reported from Angola, but this is rejected by some authors. in Herpestidae
Distribution. SE Nigeria, Cameroon, Central African Republic, DR Congo, Equatorial Guinea, Gabon, and PR Congo. Also reported from Angola, but this is rejected by some authors.
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