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294 results for “Britain”
Figure 1 from: Ainsworth A, Cannon P, Dentinger B (2013) DNA barcoding and morphological studies reveal two new species of waxcap mushrooms (Hygrophoraceae) in Britain. MycoKeys 7: 45-62. https://doi.org/10.3897/mycokeys.7.5860
Figure 1 - Maximum likelihood phylogram using full and partial nuclear ribosomal internal transcribed spacers (ITS) sequences. Numbers above branches are nonparametric bootstrap values. Tree is arbitrarily rooted at the midpoint. Two well-supported terminal clades representing the new species Gliophorus reginae and Gliophorus europerplexus are superimposed over light grey boxes. Species names for specimens from which sequences were derived are followed by fungarium or INSD accession number, and geographic location. Notations (H) and (P) indicate specimens used were holotypes or paratypes, respectively.
Figure 4 from: Ainsworth A, Cannon P, Dentinger B (2013) DNA barcoding and morphological studies reveal two new species of waxcap mushrooms (Hygrophoraceae) in Britain. MycoKeys 7: 45-62. https://doi.org/10.3897/mycokeys.7.5860
Figure 4 - Basidiomata of Gliophorus europerplexus, scale bars represent 10 mm. Photographs A–D by D.J. Harries taken in situ at, or of collectionsfrom, the type locality, and E by B.T.M.D. A, B K(M)181245* C, D K(M)181246* holotype E K(M)181241*.
Figure 6 from: Ainsworth A, Cannon P, Dentinger B (2013) DNA barcoding and morphological studies reveal two new species of waxcap mushrooms (Hygrophoraceae) in Britain. MycoKeys 7: 45-62. https://doi.org/10.3897/mycokeys.7.5860
Figure 6 - Distribution of Gliophorus reginae (●) and Gliophorus europerplexus (▲) in Britain based on sequenced collections and plotted using SimpleMappr (Shorthouse 2010).
Figure 3 from: Ainsworth A, Cannon P, Dentinger B (2013) DNA barcoding and morphological studies reveal two new species of waxcap mushrooms (Hygrophoraceae) in Britain. MycoKeys 7: 45-62. https://doi.org/10.3897/mycokeys.7.5860
Figure 3 - Microscopic characters of Gliophorus reginae collected from the type locality, B–G mounted in Congo Red, scale bars represent 10 µm. A Spores from water mount of spore print K(M)181127* B Subregular lamellar trama from squash mount K(M)181129* C Pileipellis hyphae showing medallion clamp connections K(M)181127* D–F Basidial developmental series K(M)181129* G Basidium K(M)181127*.
Figure 5 from: Ainsworth A, Cannon P, Dentinger B (2013) DNA barcoding and morphological studies reveal two new species of waxcap mushrooms (Hygrophoraceae) in Britain. MycoKeys 7: 45-62. https://doi.org/10.3897/mycokeys.7.5860
Figure 5 - Microscopic characters of Gliophorus europerplexus, A mounted in Melzer's Reagent and B–D(holotype) in Congo Red, scale bars represent 10 µm. A Spores from lamellar squash K(M)181241*B Subregular lamellar trama from squash mount K(M)181246*C–D Basidia K(M)181246*.
Figure 2 from: Ainsworth A, Cannon P, Dentinger B (2013) DNA barcoding and morphological studies reveal two new species of waxcap mushrooms (Hygrophoraceae) in Britain. MycoKeys 7: 45-62. https://doi.org/10.3897/mycokeys.7.5860
Figure 2 - Basidiomata of Gliophorus reginae showing pileal colour range: A–D purple, E–F pink and G–H reddish brown, scale bars represent 20 mm. Photographs C–F taken in situ at the type locality. A, B K(M)181115* photographed by R.D. Foster. C K(M)181117* and D K(M)181123 photographed by R. Winnall. E(left), F K(M)181128* and E (right) K(M)181127* photographed by A.M.A. G, H K(M)181124* photographed by D.J. Harries.
Figure 3 from: Van Dam MH, Laufa R, Riedel A (2016) Four new species of Trigonopterus Fauvel from the island of New Britain (Coleoptera, Curculionidae). ZooKeys 582: 129-141. https://doi.org/10.3897/zookeys.582.7709
Figure 3 - Trigonopterus puncticollis Van Dam & Riedel, sp. n., holotype; a Dorsal habitus b Lateral habitus c Penis.
Figure 2 from: Van Dam MH, Laufa R, Riedel A (2016) Four new species of Trigonopterus Fauvel from the island of New Britain (Coleoptera, Curculionidae). ZooKeys 582: 129-141. https://doi.org/10.3897/zookeys.582.7709
Figure 2 - Trigonopterus obsidianus Van Dam & Riedel, sp. n., holotype; a Dorsal habitus b Lateral habitus c Penis.
Figure 5 from: Van Dam MH, Laufa R, Riedel A (2016) Four new species of Trigonopterus Fauvel from the island of New Britain (Coleoptera, Curculionidae). ZooKeys 582: 129-141. https://doi.org/10.3897/zookeys.582.7709
Figure 5 - Trigonopterus pembertoni (Zimmerman), holotype. Dorsal habitus. Photo courtesy B.P. Bishop Museum.
Figure 4 from: Van Dam MH, Laufa R, Riedel A (2016) Four new species of Trigonopterus Fauvel from the island of New Britain (Coleoptera, Curculionidae). ZooKeys 582: 129-141. https://doi.org/10.3897/zookeys.582.7709
Figure 4 - Trigonopterus silaliensis Van Dam & Riedel, sp. n., holotype; a Dorsal habitus b Lateral habitus c female genitalia.
Figure 1 from: Van Dam MH, Laufa R, Riedel A (2016) Four new species of Trigonopterus Fauvel from the island of New Britain (Coleoptera, Curculionidae). ZooKeys 582: 129-141. https://doi.org/10.3897/zookeys.582.7709
Figure 1 - Trigonopterus chewbacca Van Dam & Riedel, sp. n., holotype; a Dorsal habitus b Lateral habitus c Penis.
Fig. 3 in Hydnum reginae newly described from Britain
Fig. 3. Close-up of the spines of H. reginae. Photograph © Geoffrey Kibby.
Fig. 4 in Hydnum reginae newly described from Britain
Fig. 4. Spores of H. reginae, the scale bar = 10 µm. Photograph © Geoffrey Kibby.
Data from: "Willing to pay?" Tax compliance in Britain and Italy: an experimental analysis
As shown by the recent crisis, tax evasion poses a significant problem for countries such as Greece, Spain and Italy. While these societies certainly possess weaker fiscal institutions as compared to other EU members, might broader cultural differences between northern and southern Europe also help to explain citizens' (un)willingness to pay their taxes? To address this question, we conduct laboratory experiments in the UK and Italy, two countries which straddle this North-South divide. Our design allows us to examine citizens' willingness to contribute to public goods via taxes while holding institutions constant. We report a surprising result: when faced with identical tax institutions, redistribution rules and audit probabilities, Italian participants are significantly more likely to comply than Britons. Overall, our findings cast doubt upon "culturalist" arguments that would attribute cross-country differences in tax compliance to the lack of morality amongst southern European taxpayers.
Public transport travel time matrices for Great Britain (TTM 2023)
<h2><strong>Overview</strong></h2> <p>This dataset provides ready-to-use door-to-door public transport travel time estimates for each of the 2011 Census at the lower super output area (LSOA) and data zone (DZ) units (42,000 LSOA/DZ units in total) in Great Britain (GB) to every other reachable within 150 minutes during the morning peak for the year 2023 using. This information comprises an all-to-all travel time matrix (TTM) at the national level. The TTM are estimated for public transport, bicycle, and walking. Public transport estimates are estimated for two times of departure, specifically during the morning peak and at night. Altogether, these TTMs present a range of opportunities for researchers and practitioners, such as the development of accessibility measures, spatial connectivity, and the evaluation of public transport service changes throughout the day.</p> <p>A full data descriptor is available in 'technical_note.html' file as part of the records of this repository.</p> <h2>Data records</h2> <p>The TTM structure follows a row matrix format, where each row represents a unique origin-destination pair. The TTMs are offered in a set of sequentially named <code>.parquet</code> files (more information about Parquet format at: <a href="https://parquet.apache.org/">https://parquet.apache.org/</a>). The structure contains one directory for each mode, where ‘bike’, ‘pt’, and ‘walk’, correspond to bicycle, public transport, and walking, respectively.</p> <h3>Walking</h3> <p>The walking TTM contains 13.3 million rows and three columns. The table below offers a description of the columns.</p> <div> <span>Table 1: </span>Walking travel time matrix codebook. <table><tbody><tr> <th>Variable</th> <th>Type</th> <th>Description</th> </tr> </tbody><tbody> <tr> <td>from_id</td> <td>nominal</td> <td>2011 LSOA/DZ geo-code of origin</td> </tr> <tr> <td>to_id</td> <td>nominal</td> <td>2011 LSOA/DZ geo-code of destination</td> </tr> <tr> <td>travel_time_p050</td> <td>numeric</td> <td>Travel time walking in minutes</td> </tr> </tbody> </table> </div> <h3>Bicycle</h3> <p>The bicycle TTM includes 40 million rows and four columns which are described in the table below.</p> <div> <span>Table 2: </span>Bicycle travel time matrix codebook. <table><tbody><tr> <th>Variable</th> <th>Type</th> <th>Description</th> </tr> </tbody><tbody> <tr> <td>from_id</td> <td>nominal</td> <td>2011 LSOA/DZ geo-code of origin</td> </tr> <tr> <td>to_id</td> <td>nominal</td> <td>2011 LSOA/DZ geo-code of destination</td> </tr> <tr> <td>travel_time_p050</td> <td>numeric</td> <td>Travel time by bicycle in minutes</td> </tr> <tr> <td>travel_time_adj</td> <td>numeric</td> <td>Adjusted travel time by bicycle in minutes. This adds 5 minutes for locking to the unadjusted estimate.</td> </tr> </tbody> </table> </div> <h3>Public transport</h3> <p>The LSOA/DZ TTM consists of six columns and 265 million rows. The internal structure of the records is displayed in the table below:</p> <div> <span>Table 3: </span>Public transport LSOA/DZ travel time matrix codebook. <table><tbody><tr> <th>Variable</th> <th>Type</th> <th>Description</th> </tr> </tbody><tbody> <tr> <td>from_id</td> <td>nominal</td> <td>2011 LSOA/DZ geo-code of origin</td> </tr> <tr> <td>to_id</td> <td>nominal</td> <td>2011 LSOA/DZ geo-code of destination</td> </tr> <tr> <td>travel_time_p025</td> <td>numeric</td> <td>25 travel time percentile by public transport in minutes</td> </tr> <tr> <td>travel_time_p050</td> <td>numeric</td> <td>50 travel time percentile by public transport in minutes</td> </tr> <tr> <td>travel_time_p075</td> <td>numeric</td> <td>75 travel time percentile by public transport in minutes</td> </tr> <tr> <td>time_of_day</td> <td>nominal</td> <td>A discrete value indicating the time of departure used. Levels: ‘am’ = 7 a.m.; ‘pm’ = 9 p.m.</td> </tr> </tbody> </table> </div> <p> </p> <p> </p>
Britain's Oldest Door
Located near the Chapter House in Westminster Abbey, London this is Britain's oldest door. "Most likely constructed in the 1050s for St Edward the Confessor." Date: 1050s. https://www.westminster-abbey.org/about-the-abbey/history/britains-oldest-door 139 photos taken in June 2021 with a Sony a6000 and processed in Reality Capture. Source: Objaverse 1.0 / Sketchfab
Figure 1. – Sicyopus beremeensis. A in A new species of Sicyopus (Teleostei: Gobiidae) from New Britain (Papua New Guinea)
Figure 1. – Sicyopus beremeensis. A: Male (49 mm); B: Female (45 mm) (photograph by P. Amick).
Data supporting the publication of "Interactive effects of climate change and land-use change on mammal range retraction in Great Britain"
<p><strong>Table S1 (Species records) provided as a separate .xlsx file in Supporting Information. </strong>List of species included in the sample with corresponding attributes, number of records and rates of change over time.</p> <p>Column A (Scientific name): species’ accepted scientific name (n = 43 species).</p> <p>Column B (Common name): species’ common name in Great Britain (n = 43 names).</p> <p>Column C (Order): species’ taxonomical Order (n = 6 Orders).</p> <p>Column D (Family): species’ taxonomical Family (n = 14 Families).</p> <p>Column E (Guild): species’ sampling guild (n = 3 Guilds, either Bats, Midlarge, or Small</p> <p>Column F (Distribution): species’ distribution status in Great Britain (n = 3 Statuses, either Native, Naturalised, or Non-Native).</p> <p>Column G (Habitat): species’ habitat preference (n = 2 Habitats, either Terrestrial or Freshwater).</p> <p>Column H (Records): total number of records per species from 1960 to 2016 (average = 10,931).</p> <p>Column I (1960s): total number of records per species from 1960 to 1969 (average = 420).</p> <p>Column J (1970s): total number of records per species from 1970 to 1979 (average = 457).</p> <p>Column K (1980s): total number of records per species from 1980 to 1989 (average = 423).</p> <p>Column L (1990s): total number of records per species from 1990 to 1999 (average = 641).</p> <p>Column M (2000s): total number of records per species from 2000 to 2010 (average = 943).</p> <p>Column N (2010s): total number of records per species from 2011 to 2016 (average = 870).</p> <p>Column O (Hectads TP1): number of hectads where the species has been recorded in Time Period 1, from 1960 to 1992 (average = 892).</p> <p>Column P (Hectads TP2): number of hectads where the species has been recorded in Time Period 2, from 2000 to 2016 (average = 1,117).</p> <p>Column Q (Hectads Total): number of hectads where the species has been recorder from 1960 to 2016 (average = 1,315).</p> <p>Column R (Extirpation rate): species’ extirpation rate, calculated as the ratio of extirpations over the sum of extirpations and persistences (average = 0.24). The sum of extirpation and persistence rates is always equal to 1.</p> <p>Column S (Persistence rate): species’ persistence rate, calculated as the ratio of persistences over the sum of extirpations and persistences (average = 0.76). The sum of persistence and extirpation rates is always equal to 1.</p> <p>Column T (Occupancy TP1): species’ occupancy estimate in Time Period 1, from 1960 to 1992, as calculated in Frescalo (average = 0.395).</p> <p>Column U (Occupancy TP2): species’ occupancy estimate in Time Period 2, from 2000 to 2016, as calculated in Frescalo (average = 0.403).</p> <p>Column V (Occupancy change): change in the species’ occupancy estimates between Time Periods 1 and 2, as calculated in Frescalo (average = 0.076).</p> <p>Column W (Occupancy change slope): average yearly change in the species’ occupancy estimates from 1960 to 2016, as calculated in Frescalo (average = -0.001).</p> <p>Column X (Frequency TP1): adjusted frequency of occurrence in Time Period 1, from 1960 to 1992, as calculated in Frescalo (average = 0.527).</p> <p>Column Y (Frequency TP2): adjusted frequency of occurrence in Time Period 2, from 2000 to 2016, as calculated in Frescalo (average = 0.461).</p> <p>Column Z (Frequency change): change in the adjusted frequency of occurrence between Time Periods 1 and 2, as calculated in Frescalo (average = -0.066).</p>
Figures 6, 7 in The species of four genera of Metopiinae (Hymenoptera: Ichneumonidae) in Britain, with new host records and descriptions of four new species
Figures 6, 7. Ischyrocnemis goesi ♀. (2) Head, anterior view. (3) Whole insect, lateral view.
The relationship between Mute Swan Cygnus olor population trends in Great Britain and environmental change
<p>Data used in the publication: Ki <em>et al.</em> 2023. The relationship between Mute Swan Cygnus olor population trends in Great Britain and environmental change, Bird Study. doi: 10.1080/00063657.2023.2239554</p>
ScienceDex guides
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.