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670 results for “Molluscs”
FIG. 16 in Opisthobranch molluscs from the Chagos Archipelago, Central Indian Ocean
FIG. 16. (a). Fryeria marindica Chag96/27: 24 mm. (b) Phyllidia coelestis Chag96/43b: 28 mm. (c) Phyllidia multituberculata Chag96 /29: 27 mm. (d) Phyllidiella meandrina Chag96 /35: 18 mm. (e) Phyllidiella rosans Chag96/48: 15 mm. (f) Phyllidiella striata Chag96/2: 35 mm.
FIG. 19 in Opisthobranch molluscs from the Chagos Archipelago, Central Indian Ocean
FIG. 19. (a) Phyllidiella zeylanica Chag96/19: 24 mm. (b) Phyllidiopsi s cardinalis Chag96 /75: 38 mm. (c) Phyllidiopsis xishaensis Chag96 /26: 18 mm. (d) Phyllidiopsis sp. Chag96/65: 37 mm.
FIG. 18 in Opisthobranch molluscs from the Chagos Archipelago, Central Indian Ocean
FIG. 18. (a) Phyllidiella striata: tracing of Bergh (1889) taf. 84, ®gure 23. (b) Scyllaea pelagica Chag96/55: radular teeth drawn with camera lucida, row 1. (c) Dermatobranchus sp. Chag96/85: dorsal view: composite drawing from life and camera lucida (based on preserved length of 6 mm).
FIG. 20 in Opisthobranch molluscs from the Chagos Archipelago, Central Indian Ocean
FIG. 20. SEM of radular teeth. (A) Dermatobranchus albus Chag96 /45, scale 510 mm. (B) Dermatobranchus sp. Chag96 /85, scale 510 mm.
FIG. 2 in Opisthobranch molluscs from the Chagos Archipelago, Central Indian Ocean
FIG. 2. (a) Chelidonur a punctata Chag96 /1: 50 mm. (b) Chelidonur a sandrana Chag96 /54: 13 mm. (c) Thuridilla bayeri Chag96/93: 15 mm. (d) Aplysia cf. parvula Chag96 /18: 10 mm. (e) Nembrotha lineolata Chag96/62: 65 mm. (f) Notodoris minor Chag96/84a: 21 mm.
Fig. 2 in A Review Of Species Diversity, Distribution And Ecology Of Freshwater Gastropod Molluscs Inhabiting The Ukrainian Transcarpathian
Fig. 2. Selected types of ecotopes in the region of materials sampling, Transcarpathia: 1— Chorna Voda (Mertse) River, near the Gat village (locality 15); 2 — artificial pool in the floodplain of Latorytsia River, near Chop town (locality 8); 3 — stream near the Bukove village (locality 20); 4 — creek in the territory of Carpathian Biosphere Reserve Headquarters (locality 5).
Fig. 3 in A Review Of Species Diversity, Distribution And Ecology Of Freshwater Gastropod Molluscs Inhabiting The Ukrainian Transcarpathian
Fig. 3. Shells of Transcarpathian gastropod molluscs: 1 — Viviparus viviparus (locality 12); 2 — Contectiana contecta (locality 15); 3 — Viviparus sphaeridius (locality 12); 4 — Bithynia tentaculata (locality 15); 5 — Valvata (Cincinna) ambigua (locality 15); 6 — Bithynia troschelii (locality 13); 7 — Valvata (Cincinna) piscinalis (locality 22); 8 — Lithoglyphus naticoides (locality 9); 9–11 — Planorbis planorbis (locality 15); 12, 13 — Planorbarius corneus (locality 15). Scale bars are given for 1–3, 4–8, and 9–13 correspondingly.
Fig. 4 in A Review Of Species Diversity, Distribution And Ecology Of Freshwater Gastropod Molluscs Inhabiting The Ukrainian Transcarpathian
Fig. 4. Shells of Transcarpathian gastropod molluscs: 1 — Radix peregra (locality 55); 2 — R. lagotis (locality 48); 3–5 — Physa acuta (3, 4—from locality 6; 5 — locality 15); 6–8 — Anisus septemgyratus (locality 58); 9–11 — Anisus spirorbis (locality 16); 12–14 — Gyraulus albus (locality 16); 15–17 — Segmentina nitida (locality 14); 18–20 — S. montgazoniana (locality 7); 21–23 — Ancylus fluviatilis (locality 58).
Convergent evolution of barnacles and molluscs sheds lights in origin and diversification of calcareous shell and sessile lifestyle
<p><span>The calcareous shell and sessile lifestyle are the representative phenotypes of many molluscs, which happen to be present in barnacles, a group of unique crustaceans. The origin of these phenotypes is unclear, but it may be embodied in the convergent genetics of such distant groups (interphylum). </span><span>Herein, we perform comprehensive comparative genomics analysis in barnacles and molluscs, and reveal a genome-wide strong convergent molecular evolution between them, including coexpansion of biomineralisation and organic matrix genes for shell formation, and origination of lineage-specific orphan genes for settlement. Notably, the expanded biomineralisation gene encoding alkaline phosphatase evolves a novel, highly conserved motif that may trigger the origin of barnacle shell formation. Unlike molluscs, barnacles adopt novel organic matrices and cement proteins for shell formation and settlement, respectively, and their calcareous shells have potentially originated from the cuticle system of crustaceans. Therefore, our study corroborates the idea that selection pressures driving convergent evolution may strongly act in organisms inhabiting similar environments regardless of phylogenetic distance. The convergence signatures shed light on the origin of the shell and sessile lifestyle of barnacles and molluscs. In addition, notable nonconvergence signatures are also present and may contribute to morphological and functional specificities.</span></p>
Raw data and alignments for: Application of palaeogenetic techniques to historic mollusc shells reveals phylogeographic structure in a New Zealand abalone
<p>Natural history collections worldwide contain a plethora of mollusc shells. Recent studies have detailed the sequencing of DNA extracted from shells up to thousands of years old and from various taphonomic and preservational contexts. However, previous approaches have largely addressed methodological rather than evolutionary research questions. Here we report the generation of DNA sequence data from mollusc shells using such techniques, applied to <em>Haliotis virginea</em> Gmelin, 1791, a New Zealand abalone, in which morphological variation has led to the recognition of several forms and subspecies. We successfully recovered near-complete mitogenomes from 22 specimens including 12 dry-preserved shells up to 60 years old. We used a combination of palaeogenetic techniques that have not previously been applied to shell, including DNA extraction optimized for ultra-short fragments and hybridization-capture of single-stranded DNA libraries. Phylogenetic analyses revealed three major, well-supported clades comprising samples from: 1) the Three Kings Islands; 2) the Auckland, Chatham and Antipodes Islands; and 3) mainland New Zealand and Campbell Island. This phylogeographic structure does not correspond to the currently recognized forms. Critically, our non-reliance on freshly collected or ethanol-preserved samples enabled inclusion of topotypes of all recognized subspecies as well as additional difficult-to-sample populations. Broader application of these comparatively cost-effective and reliable methods to modern, historical, archaeological and palaeontological shell samples has the potential to revolutionize invertebrate genetic research.</p>
PATTERNS OF RICHNESS OF FRESHWATER MOLLUSCS FROM CHILE: PREDICTIONS OF ITS DISTRIBUTION BASED ON NULL MODELS
<p>Script and data for GLM analysis and co-occurrence analysis. </p>
Registry of introduced terrestrial molluscs in Belgium
<p><strong>Introduction</strong></p> <p>The Registry of introduced terrestrial molluscs in Belgium is a species checklist dataset maintained by Thierry Backeljau at the Royal Belgian Institute for Natural Sciences (RBINS). It contains information on all (29) non-native terrestrial molluscs occurring in the wild in Belgium since 1800. The list was originally compiled for EASIN (<a href="https://easin.jrc.ec.europa.eu/easin">https://easin.jrc.ec.europa.eu/easin</a>) and is based on a literature survey and information from RBINS. The dataset can be used for researching and managing terrestrial alien molluscs or compiling regional and national registries of alien species.</p> <p>The registry is maintained as a Google Spreadsheet and exported and uploaded here as an Excel file and csv files for each sheet. The dataset is also published for the TrIAS project (Tracking Invasive Alien Species <a href="http://trias-project.be">http://trias-project.be</a>, Vanderhoeven et al. 2017) as a standardized Darwin Core Archive, openly available on GBIF (<a href="https://doi.org/10.15468/t13kwo">https://doi.org/10.15468/t13kwo</a>).</p> <p>Issues with the dataset can be reported at <a href="https://github.com/trias-project/alien-mollusca-checklist">https://github.com/trias-project/alien-mollusca-checklist</a></p> <p><strong>Files</strong></p> <ul> <li> <p><strong>alien_mollusca_checklist.xlsx</strong>: Excel export of the Google Spreadsheet in which the data are maintained.</p> </li> <li> <p><strong>metadata.csv</strong>: definitions for the fields in <code>taxa.csv</code>, <code>references.csv</code>, <code>synonyms.csv</code> and <code>vernacular_names.csv</code>, with information about the content, the number of values allowed, the necessity of a controlled vocabulary and whether or not the information is obligatory.</p> </li> <li> <p><strong>taxa.csv</strong>: scientific names and higher classification, as well as the species’ presence or absence in Belgium, its first and last observation date, native range, introduction pathway and degree of establishment.</p> </li> <li> <p><strong>references.csv</strong>: all references used to compile the dataset.</p> </li> <li> <p><strong>synonyms.csv</strong>: synonyms for the scientific names in <code>taxa.csv</code>.</p> </li> <li> <p><strong>vernacular_names.csv</strong>: Dutch, French, English and German vernacular names for the scientific names in <code>taxa.csv</code>.</p> </li> </ul>
Malay Peninsular Terrestrial Molluscs: Resource (163) DwCA
Open the record for dataset details and reuse information.
Fig. 4 in The biogeography of non-marine molluscs in the Tuscan Archipelago reveals combined effects of current eco-geographical drivers and paleogeography
Fig. 4 Non-metric multidimensional scaling (NMDS) in RGB (red, green, and blue) color space for Sørensen (βsor) (a), Simpson (βsim) (b), and nestedness indices (βnest) (c) showing land snail presence/ absence in the Tuscan Archipelago using the database of all species except aliens. CAP, Capraia; ELB, Elba; GIA, Giannutri; GIG, Giglio; GOR, Gorgona; MCO, Montecristo; PIA, Pianosa; CER, Cerboli; PAL, Palmaiola; FDG, Formiche di Grosseto; ARG, Monte Argentario
Fig. 5 in The biogeography of non-marine molluscs in the Tuscan Archipelago reveals combined effects of current eco-geographical drivers and paleogeography
Fig. 5 Biogeographical categories of land snail species on islands of the Tuscan Archipelago: (a) including and (b) excluding widespread species
Fig. 1 in The biogeography of non-marine molluscs in the Tuscan Archipelago reveals combined effects of current eco-geographical drivers and paleogeography
Fig. 1 Location of the Tuscan Archipelago in the northern Tyrrhenian Sea, between the Tuscan coast and Corsica
Fig. 6 in The biogeography of non-marine molluscs in the Tuscan Archipelago reveals combined effects of current eco-geographical drivers and paleogeography
Fig. 6 Cluster analysis (a) and non-metric multidimensional scaling (NMDS) in RGB (red, green, and blue) color space (b) for Simpson index (βsimp) showing relationships between Tuscan Archipelago islands and their source pool (Tuscany/Sardo-Corsican complex) considering species of biogeographical interest (SC, Sardo-Corsican species; T, Tuscan species). In cluster analysis, multiscale bootstrap procedure resulted in two different values for each node: on the left,
Fig. 2 in The biogeography of non-marine molluscs in the Tuscan Archipelago reveals combined effects of current eco-geographical drivers and paleogeography
Fig. 2 Cluster analysis for the Sørensen index (βsor) (a all species; b without alien species), Simpson index (βsim) (c all species; d without alien species) and nestedness index (βnest) (e all species; f without alien species). Multiscale bootstrap analysis resulted in two different values for each node: on the left, node support involving the exact number of species in the original dataset; on the right, node support when more resampled species were used. Highly and weakly supported nodes are indicated in black and red, respectively. CAP, Capraia; ELB, Elba; GIA, Giannutri; GIG, Giglio; GOR, Gorgona; MCO, Montecristo; PIA, Pianosa; CER, Cerboli; PAL, Palmaiola; FDG, Formiche di Grosseto; ARG, Monte Argentario
Fig. 3 in The biogeography of non-marine molluscs in the Tuscan Archipelago reveals combined effects of current eco-geographical drivers and paleogeography
Fig. 3 Non-metric multidimensional scaling (NMDS) in RGB (red, green, and blue) color space for Sørensen (βsor) (a), Simpson (βsim) (b), and nestedness indices (βnest) (c) showing land snail presence/ absence in the Tuscan Archipelago using the database of all species. CAP, Capraia; ELB, Elba; GIA, Giannutri; GIG, Giglio; GOR, Gorgona; MCO, Montecristo; PIA, Pianosa; CER, Cerboli; PAL, Palmaiola; FDG, Formiche di Grosseto; ARG, Monte Argentario
R-scripts for the calculation of HW and Bioclimatic models in: "Small vertebrate and mollusc community response to the Holocene environment and climate changes in the Kraków-Częstochowa Upland (Poland)"
<p>HW_Holocene: Tables and R script used for calculation of HW percentage values.</p> <p>PalBER_Bioclimaticmodel_modified: Tables and R script used for the calculation of the climate values through Bioclimatic model. Modified after Royer et al., 2020.</p>
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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)
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.