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Fig. 3 in High Fecundity, Rapid Development and Selfing Ability in Three Species of Viviparous Land Snails Phaedusinae (Gastropoda: Stylommatophora: Clausiliidae) from East Asia
Fig. 3. Stereophaedusa jacobiana. (A) adult (F1 generation); (B) neonates; (C) clausilium; (D) dissected adult with eggs; (E-F) egg and embryos from dissected adults. Scale bar = 1 mm.
Fig. 2 in High Fecundity, Rapid Development and Selfing Ability in Three Species of Viviparous Land Snails Phaedusinae (Gastropoda: Stylommatophora: Clausiliidae) from East Asia
Fig. 2. Tauphaedusa tau. (A) adult (F1 generation); (B) neonates; (C) clausilia; (D-E) eggs and embryos from dissected adults. Scale bar = 1 mm. © 2018 Academia Sinica, Taiwan
Fig. 2 in Evidence of positive selection suggests possible role of aquaporins in the water-to-land transition of mudskippers
Fig. 2 Sequence alignment and structural annotation of AQP10a and AQP11b showing positively selected positions in mudskippers (indicated with triangles and olive green or purple bars, respectively). The sequences of the corresponding paralogs of D. rerio are included as reference. Upper bars denote helices and loops. Boxes denote NPA motifs
Fig. 1 in Evidence of positive selection suggests possible role of aquaporins in the water-to-land transition of mudskippers
Fig. 1 Bayesian inference cladogram of vertebrate aquaporins based on 394 aligned amino acid positions. Filled bullets on nodes denote support for both BI and ML methods of phylogenetic inference. Open bullets on nodes denote support for only one of the methods (either BI or ML). Absence of bullet on a node denotes no support for any of the methods. Aquaporin classes are indicated with colour panels and class paralogs
Datasets for "Global Assessment of Atmospheric Forcing Uncertainties in The Common Land Model 2024 Simulations"
<p>This repository provides the datasets for the publication "Global Assessment of Atmospheric Forcing Uncertainties in The Common Land Model 2024 Simulations".</p>
40-year monthly mean AVHRR GAC Land Surface Temperature data for the Pan-Arctic region (Pan-Arctic AVHRR LST)
<p><em>This data collection contains 40 years of monthly mean daytime AVHRR Global Area Coverage (GAC) land surface temperature (LST) data. This dataset covers the 1981-2020 perdiod and covers the whole globe above 50° latitude. The spatial extent of the dataset is the following : (-180°, 50°N) ; (180°, 90°N)</em></p> <p><strong>Dataset description:</strong></p> <p>The LST monthly mean composites are computed from daily daytime LST files, that were generated from the EUMETSAT AVHRR PyGAC FDR (https://navigator.eumetsat.int/product/EO:EUM:DAT:0862) as described in Dupuis et al. (2024). These daily LST files contain only cloud-free pixels and pixels with sufficient quality regarding satellite zenith angle and error margin from the radiative transfer modelling. The probabilistic cloud mask from the CLARA-A3 (https://navigator.eumetsat.int/product/EO:EUM:DAT:0874) dataset has been used. The LST monthly means do not contain any water masks, as potential users might have different requirements regarding water masks. The dataset has been validated against in situ data from the SURFRAD (https://gml.noaa.gov/grad/surfrad/overview.html), ARM (https://arm.gov/capabilities/observatories/nsa) and KIT (https://www.imk-asf.kit.edu/english/skl_stations.php) networks.</p> <p><strong>Data & File Overview:</strong></p> <p>Short description: AVHRR GAC LST daytime monthly mean composites: daily land surface temperature data are averaged to monthly composites for every afternoon and mid-day satellite (10 different satellites).</p> <ul> <li>File List: This dataset contains monthly daytime land surface temperature (LST) data for the AVHRRs onboard NOAA and MetOp satellites. </li> <li>Filename: Pan_Arctic_LST_avhrr_XXXXX_YYYYMM_DAY__***.nc, where XXXXX represents the satellite identifier, YYYYMM the monthly timestamp (YYYY=year, MM=month) and *** the timestamp of the file generation.</li> <li>Relationship between files: Each file covers a one-month period and is recorded by a different satellite.</li> </ul> <p>Satellite identifiers:<br><em>AVN07 : NOAA 7</em><br><em>AVN09 : NOAA 9</em><br><em>AVN11 : NOAA 11</em><br><em>AVN14 : NOAA 14</em><br><em>AVN16 : NOAA 16</em><br><em>AVN18 : NOAA 18</em><br><em>AVN19 : NOAA 19</em><br><em>AVMEA : MetOp-A</em><br><em>AVMEB : MetOp-B</em><br><em>AVMEC : MetOp-C</em></p> <p><strong>Data specific information:</strong></p> <p>The LST files are available as a gridded product in the WGS84 coordinate reference system and are distributed as NetCDF files. The dataset covers the pan-Arctic region (-180°, 90°, 180°, 50°) at a spatial resolution of 0.05°x0.05° pixel size.<br>Each *.nc file contains one variable (LST) with three dimensions (time, lat, lon) and five coordinates (time, lat, lon, band and spatial_ref).</p> <p>- spatial_ref (): stores the spatial information, such as the coordinate reference system (CRS) and WKT string.<br>- time (time): stores the timestamp, here the month and the year of the monthly mean. The timestamp is the same for all pixels belonging to the same composite.<br>- lat (lat): stores the latitude of each pixel<br>- lon (lon): stores the longitude of each pixel<br>- band (): empty inherited layer </p> <p> </p> <p><strong>Credit:</strong></p> <p>To use this data please cite this dataset and the respective journal publication:</p> <p>Dupuis, S., Göttsche, F.-M., & Wunderle, S. (2024). Temporal stability of a new 40-year daily AVHRR land surface temperature dataset for the pan-Arctic region. <em>The Cryosphere, 18</em>(12), 6027-6059. <a href="https://doi.org/10.5194/tc-18-6027-2024" target="_blank" rel="nofollow noopener">https://doi.org/10.5194/tc-18-6027-2024</a></p> <p> </p> <div> <div><span>@Article</span><span>{</span><span>tc-18-6027-2024</span><span>,</span></div> <div><span>AUTHOR</span><span> = </span><span>{</span><span>Dupuis, S. and G\"ottsche, F.-M. and Wunderle, S.</span><span>}</span><span>,</span></div> <div><span>TITLE</span><span> = </span><span>{</span><span>Temporal stability of a new 40-year daily AVHRR land surface temperature dataset for the pan-Arctic region</span><span>}</span><span>,</span></div> <div><span>JOURNAL</span><span> = </span><span>{</span><span>The Cryosphere</span><span>}</span><span>,</span></div> <div><span>VOLUME</span><span> = </span><span>{</span><span>18</span><span>}</span><span>,</span></div> <div><span>YEAR</span><span> = </span><span>{</span><span>2024</span><span>}</span><span>,</span></div> <div><span>NUMBER</span><span> = </span><span>{</span><span>12</span><span>}</span><span>,</span></div> <div><span>PAGES</span><span> = </span><span>{</span><span>6027--6059</span><span>}</span><span>,</span></div> <div><span>URL</span><span> = </span><span>{</span><span>https://tc.copernicus.org/articles/18/6027/2024/</span><span>}</span><span>,</span></div> <div><span>DOI</span><span> = </span><span>{</span><span>10.5194/tc-18-6027-2024</span><span>}</span></div> <div><span>}</span></div> </div> <p> </p> <p><strong>Information about funding sources that supported the collection of the data:</strong><br>Dr. Alfred Bretscher Fund (University of Bern)</p> <p> </p>
Carbon storage response to land use/land cover changes and SSP-RCP scenarios simulation: A case study in Yunnan Province, China
Open the record for dataset details and reuse information.
Incorporation of trace metals into land snail shells on the Chinese Loess Plateau as proxies for paleo-precipitation
<p><span>This dataset provides the results of trace metal compositions of modern snail shells (<em>Cathaica sp.</em>) collected from </span><span>sixteen sites </span><span>on the Chinese Loess Plateau.</span></p>
Land surface phenology derived from 3 sets of vegetation indices
Open the record for dataset details and reuse information.
Fig. 11 in Les abeilles sauvages de la lande de Streupas (Hymenoptera: Apoidea)
Fig. 11. Colletes succinctus, femelle butinant sur bruyère (© "Paul en Marianne" sur observations.be)
FIGURE 13a–e in Spiders of arid lands: The Ghardaïa region (Northern Sahara) with seven new records for Algeria
FIGURE 13a–e. Plexippus devorans, (a) Male palp, ventral view, (b) Idem, prolateral view, (c) Idem, retrolateral view, (d) Epigyne, (e) Vulva.
FIGURE 10a–e in Spiders of arid lands: The Ghardaïa region (Northern Sahara) with seven new records for Algeria
FIGURE 10a–e. Evarcha nepos, (a) Dorsal view, (b) Male palp, ventral view, (c) Idem, retrolateral view, (d) Idem, prolateral view, (e) Idem, dorsal view.
FIGURE 12a–c in Spiders of arid lands: The Ghardaïa region (Northern Sahara) with seven new records for Algeria
FIGURE 12a–c. Plexippus devorans, (a) Dorsal view of the male, (b) Dorsal view of the female, (c) Ventral view of the female.
FIGURE 11a–e in Spiders of arid lands: The Ghardaïa region (Northern Sahara) with seven new records for Algeria
FIGURE 11a–e. Mogrus logunovi, (a) Female, dorsal view, (b) Idem, ventral view, (c) Epigyne, (d) Vulva, ventral view (e) Idem, dorsal view.
FIGURE 14a–c in Spiders of arid lands: The Ghardaïa region (Northern Sahara) with seven new records for Algeria
FIGURE 14a–c. Steatoda erigoniformis, (a) Dorsal view of the male, (b) Male palp, prolateral view, (c) Idem, ventral view.
FIGURE 9a–h in Spiders of arid lands: The Ghardaïa region (Northern Sahara) with seven new records for Algeria
FIGURE 9a–h. Oecobius paulomaculatus, (a) Male palp, retrolateral view, (b) Idem, ventral view, (c) Idem, prolateral view, (d) Epigyne, (e) Vulva, ventral view (f) Idem, dorsal view.
FIGURE 8a–c in Spiders of arid lands: The Ghardaïa region (Northern Sahara) with seven new records for Algeria
FIGURE 8a–c. Oecobius paulomaculatus, (a) Dorsal view of the male, (b) Dorsal view of the female, (c) Ventral view of the female.
FIGURE 6a–f in Spiders of arid lands: The Ghardaïa region (Northern Sahara) with seven new records for Algeria
FIGURE 6a–f. Male of Zelotes tragicus, (a) Dorsal view, (b) Palp, ventral view, (c) Idem, retrolateral view, (d) Idem, tibial apophysis, (e) Idem, prolateral view, (f) Idem, dorsal view.
FIGURE 2a–c in Spiders of arid lands: The Ghardaïa region (Northern Sahara) with seven new records for Algeria
FIGURE 2a–c. Some sampled biotopes across Ghardaïa, (a) Palm grove of Balouh, (b) Palm grove of Mansoura, (c) River of Kef Doukhane.
FIGURE 4a–h in Spiders of arid lands: The Ghardaïa region (Northern Sahara) with seven new records for Algeria
FIGURE 4a–h. Leptopilos pupa, (a) Male palp, retrolateral view, (b) Idem, tibial apophysis, (c) Idem, ventral view, (e) Idem, ventral-prolateral view, (f) Idem, prolateral view, (g) Idem, dorsal view, Epigyne (g) and vulva (h).
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.