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606 results for “Guyana”
National Checklists 2017: Guyana 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 Guyana collected using effechecka and geonames polygons
National Checklists 2019: Guyana 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 Guyana collected using effechecka and geonames polygons
Figure 9. Ischnopter galibi Hebard, 1926 in New and enigmatic cockroaches (Dictyoptera: Blattodea) of Guyana
Figure 9. Ischnopter galibi Hebard, 1926. Adult male. (a) Ventral subgenital plate. Voucher number: DEKBO0869. (b) Ventral supra-anal plate. Voucher number: DEKBO0348. (c) Terminal terga showing supra-anal plate and tergal gland. Voucher number: DEKBO0344. (d) Right phallomere (R2). (e) Left phallomere (L3). (f). Medial phallomere (Lvm). Voucher number: DEKBO0869. (g) Wing. Voucher number: DEKBO0634.
Figure 6 in New and enigmatic cockroaches (Dictyoptera: Blattodea) of Guyana
Figure 6. Dasyblatta warei sp. nov. (a–c) Adult male holotype. Voucher number: DECBA0907. (a) Dorsal body; (b) dorsal abdomen; (c). ventral abdomen. (d, e) Adult female allotype. Voucher number: DECBA1803. (d) Dorsal body; (e) ventral body.
FIGURES 1 - 4. 1, 2. Calliaspis surinamensis Borowiec, 2000 in A new species of Calliaspis Dejean, 1837 (Coleoptera: Chrysomelidae: Cassidinae) from French Guyana
FIGURES 1 - 4. 1, 2. Calliaspis surinamensis Borowiec, 2000: 1. Dorsal; 2. Lateral; 3, 4. Calliaspis cerdai sp. nov.: 3. Dorsal; 4. Lateral.
Infrastructure Climate Resilience Assessment Data Starter Kit for Guyana
<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>
Figure 14 in Mastiglanis durantoni from French Guyana, a second species in the genus (Siluriformes: Heptapteridae), with a CT scan survey of phylogenetically-relevant characters
Figure 14. – Schematic illustrations of the occipital process and part of posterior cranial fontanel in species of Mastiglanis. A: Mastiglanis durantoni, MZUSP 118119, paratype; B-G: M. asopos, B: MZUSP 93307 (Rio Negro basin), C: MZUSP 81411 (Rio Negro basin), D: MZUSP 86958 (Rio Preto da Eva basin), E-G: MZUSP 97150 (Rio Xingu basin). Scale bars = 1 mm.
Figure 13 in Mastiglanis durantoni from French Guyana, a second species in the genus (Siluriformes: Heptapteridae), with a CT scan survey of phylogenetically-relevant characters
Figure 13. – CT scan image of posterior portion of skull and anterior part of vertebral column of Mastiglanis durantoni, MZUSP 118118, paratype, ventral view. Anterior to top. Abbreviations: bo, basioccipital; ex, exoccipital; fr, frontal; pa, parasphenoid; par, parapophysis; plr, pleural rib; pro, prootic; pt, pterotic; ptr, pterosphenoid; pts, posttemporo-supracleithrum; sph, sphenotic; tp4a, anterior ramus of transverse process of vertebra 4; tp4p, posterior ramus of transverse process of vertebra 4; tp5, transverse process of vertebra 5; tr, tripus; trs, transscapular process; vc5-7, vertebral centra 5 to 7.
Figure 12 in Mastiglanis durantoni from French Guyana, a second species in the genus (Siluriformes: Heptapteridae), with a CT scan survey of phylogenetically-relevant characters
Figure 12. – CT scan image of suspensorium of Mastiglanis durantoni, MZUSP 118118, paratype, lateral view. Anterior to left. Abbreviations: ent, entopterygoid; hy, hyomandibula; io, interopercle; mt, metapterygoid; op, opercle; po, preopercle; qu, quadrate; sbpo, subpreopercle; spo, suprapreopercle.
Figure 9 in Mastiglanis durantoni from French Guyana, a second species in the genus (Siluriformes: Heptapteridae), with a CT scan survey of phylogenetically-relevant characters
Figure 9. – Live specimen of Mastiglanis durantoni n. sp, lateral view, French Guiana (photo by P.Y. Le Bail). Specimen not preserved.
Figure 6 in Mastiglanis durantoni from French Guyana, a second species in the genus (Siluriformes: Heptapteridae), with a CT scan survey of phylogenetically-relevant characters
Figure 6. – CT scan image of premaxilla of Mastiglanis durantoni, MZUSP 118118, paratype. A: Dorsal view; B: Ventral view. Anterior to top.
Figure 7 in Mastiglanis durantoni from French Guyana, a second species in the genus (Siluriformes: Heptapteridae), with a CT scan survey of phylogenetically-relevant characters
Figure 7. – CT scan image of lower jaw of Mastiglanis durantoni, MZUSP 118118, paratype, lateral view, left side, anterior to left. Abbreviations: aa, anguloarticular; den, dentary; lsp, opening for latero-sensory pore; tr, trabeculae.
Figure 5 in Mastiglanis durantoni from French Guyana, a second species in the genus (Siluriformes: Heptapteridae), with a CT scan survey of phylogenetically-relevant characters
Figure 5. – CT scan image of anterior portion of neurocranium of Mastiglanis durantoni, MZUSP 118118, paratype, dorsal view. Abbreviations: fr, frontal; le, lateral ethmoid; me, mesethmoid.
Figure 3 in Mastiglanis durantoni from French Guyana, a second species in the genus (Siluriformes: Heptapteridae), with a CT scan survey of phylogenetically-relevant characters
Figure 3. – Heads in ventral view, showing difference in upper-jaw lengths. A: Mastiglanis durantoni, n. sp., paratype, MZUSP 118118, 46.9 mm SL; B: Mastiglanis asopos, paratype, MZUSP 7446, 43.9 mm SL.
Figure 2 in Mastiglanis durantoni from French Guyana, a second species in the genus (Siluriformes: Heptapteridae), with a CT scan survey of phylogenetically-relevant characters
Figure 2. – Mastiglanis durantoni, n. sp., holotype, MNHN 2015- 244, 63.7 mm SL. (A) Dorsal and (B) ventral views of head.
Figure 1 in Mastiglanis durantoni from French Guyana, a second species in the genus (Siluriformes: Heptapteridae), with a CT scan survey of phylogenetically-relevant characters
Figure 1. – Mastiglanis durantoni, n. sp., holotype, MNHN 2015- 244, male, 63.7 mm SL, Tampok River, tributary to Maroni stream, French Guiana. Lateral view.
National Checklists: Guyana 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>
Figure 2 in THE ENTOLOMATACEAE OF THE PAKARAIMA MOUNTAINS OF GUYANA VII: ENTOLOMA DICYMBOPHILUM SP. NOV. AND A KEY TO GUYANESE SPECIES OF ENTOLOMA S. STR.
Figure 2. Microscopic features of Entoloma dicymbophilum Largent & T.W.Henkel, sp. nov. A, basidiospores; B, basidia and basidioles; C, pileipellis and subtending trama; D, pileus trama. All photographs of the holotype, Henkel 9740, taken by D. L. Largent. Scale bars: A and B, 10 μm; C and D, 50 μm.
Figure 1. Entoloma dicymbophilum Largent & T.W in THE ENTOLOMATACEAE OF THE PAKARAIMA MOUNTAINS OF GUYANA VII: ENTOLOMA DICYMBOPHILUM SP. NOV. AND A KEY TO GUYANESE SPECIES OF ENTOLOMA S. STR.
Figure 1. Entoloma dicymbophilum Largent & T.W.Henkel, sp. nov. A, Field habit, off-white to cream basidiomata with exposed lamellae, Upper Potaro Basin, Guyana; B, immature basidioma (lateral view). Each scale bar, 20 mm. Photographs of the holotype, Henkel 9740, taken by Todd Elliott (A) and Terry Henkel (B).
Fig. 5 in Trophic ecology of Arapaima in Guyana: giant omnivores in Neotropical floodplains
Fig. 5. Structures associated with feeding in Arapaima, including: a) bony plates on the roof of the buccal cavity (vo = vomer, pas = parasphenoid, enp = entopterygoid, and dpt+ecp = fused dermopalatine+ectopterygoid), b) bony tongue (abbtp = anterior basibranchial toothplate) and gill rakers (gr), and c) jaw teeth (jaw bones are d = dentary, mx = maxilla, and pmx = premaxilla). Panels a and b are for a specimen from Mamirauá Reserve, Brazil (now a dried skeleton at Instituto Nacional de Pesquisas da Amazônia, Manaus, Brazil (INPA 26583, 121 cm TL, collected by C. Arantes, Nov. 2006); panel c is of a dried skull specimen from the Essequibo River that was on display at Iwokrama Centre, Guyana (estimated 239 cm TL, based on morphometric data for Essequibo basin Arapaima, Stewart & Watson, pers. comm.).
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.