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26,475 results for “Genera”
Fig. 603 in Nearctic Anthomyzidae: a monograph of Anthomyza and allied genera (Diptera)
Fig. 603. Phylogeny and its biogeographic implication for species of the genus Fungomyza.
Figs. 158–159 in Review of the Palaearctic genera of Saprininae (Coleoptera: Histeridae)
Figs. 158–159. Saprininae, mesotibia, schematic: 158 – dorsal view; 159 – ventral view.
Fig. 146 in Review of the Palaearctic genera of Saprininae (Coleoptera: Histeridae)
Fig. 146. Saprininae, pronotum and elytra, oblique lateral view.
Figs. 156–157 in Review of the Palaearctic genera of Saprininae (Coleoptera: Histeridae)
Figs. 156–157. Saprininae, protibia, schematic: 156 – dorsal view; 157 – ventral view.
Fig. 4 in Review of the Palaearctic genera of Saprininae (Coleoptera: Histeridae)
Fig. 4. Saprininae, antenna, dorsal view, schematic.
Figs. 148–149 in Review of the Palaearctic genera of Saprininae (Coleoptera: Histeridae)
Figs. 148–149. Saprininae, prosternum: 148 – Hypocacculus sp.; 149 – Gnathoncus sp.
Figs. 160–161. Myrmetes paykulli Kanaar, 1979 in Review of the Palaearctic genera of Saprininae (Coleoptera: Histeridae)
Figs. 160–161. Myrmetes paykulli Kanaar, 1979, mesotibia: 160 – dorsal view; 161 – ventral view.
Fig. 3 in Review of the Palaearctic genera of Saprininae (Coleoptera: Histeridae)
Fig. 3. Saprininae, head, dorsal view, schematic.
Fig. 6 in Two new species of planthoppers from India (Hemiptera: Auchenorrhyncha: Delphacidae) in the genera Parasogata and Eoeurysa
Fig. 6. Distribution map of the new species.
Phylogenetic diversity and environment form assembly rules for Arctic diatom genera – a study on recent and ancient sedimentary DNA
<p><span><b>Aim</b></span></p> <p><span>This study investigates taxonomic and phylogenetic diversity in diatom genera to evaluate assembly rules for eukaryotic microbes across the Siberian treeline. We first analysed how phylogenetic distance relates to taxonomic richness and turnover. Second, we used relatedness indices to evaluate if environmental filtering or competition influences the assemblies in space and through time. Third, we used distance-based ordination to test which environmental variables shape diatom turnover.</span></p> <p><span><b>Location</b></span></p> <p><span>Yakutia and Taymyria, Russia: we sampled 78 surface sediments and a sediment core, extending to 7000 years before present, to capture the forest–tundra transition in space and time, respectively. </span></p> <p><span><b>Taxon</b></span></p> <p><span>Arctic freshwater diatoms.</span></p> <p><span><b>Methods</b></span></p> <p><span>We applied metabarcoding to retrieve diatom diversity from surface and core sedimentary DNA. The taxonomic assignment binned sequence types (lineages) into genera and created taxonomic (abundance of lineages within different genera) and phylogenetic datasets (phylogenetic distances of lineages within different genera).</span></p> <p><span><b>Results</b></span></p> <p><span>Contrary to our expectations, we find a unimodal relationship between phylogenetic distance and richness in diatom genera. We discern a positive relationship between phylogenetic distance and taxonomic turnover in spatially and temporally distributed diatom genera. Further, we reveal positive relatedness indices in diatom genera across the spatial environmental gradient and predominantly in time-slices at a single location, with very few exceptions assuming effects of competition. Distance-based ordination of taxonomic and phylogenetic turnover indicates that lake environment variables, like HCO<sub>3</sub><sup>–</sup> and water depth, largely explain diatom turnover. </span></p> <p><span><b>Main conclusion</b></span></p> <p>Phylogenetic and abiotic assembly rules are important in understanding the regional assembly of diatom genera across lakes in the Siberian treeline ecotone. Using a space–time approach we are able to exclude the influence of geography and elucidate that lake environmental variables primarily shape the assemblies. We conclude that some diatom genera have greater capabilities to adapt to environmental changes, whereas others will be putatively replaced or lost due to the displacement of the Arctic tundra biome under recent global warming.</p>
Gilbert Islands, Kiribati: Size Frequency of Coral Genera (2012 - 2018)
<p>This dataset contains the size-frequency of coral genera in Abaiang and Tarawa Atolls, Gilbert Islands, Republic of Kiribati. We collected data every two years from 2012 through 2018.<br> <br> The methods are described in http://doi.org/10.1371/journal.pone.0255304.</p>
Figures 15-19 in Two new genera of Desmiphorini (Coleoptera, Cerambycidae, Lamiinae) with description of a species with non-retractile parameres
Figures 15-19. Obscenoides compta (Martins & Galileo, 2005) comb. nov., male abdomen: (15) Dorsal; (16) Ventral with detailed tergite VIII; (17) Lateral with detailed tubercle at ventrite V; (18) Posterior; (19) Lateral, schema highlighting the internal position of the genitalia: ml (in green) = median lobe, viii (in red) = tergite VIII, tg (in yellow) = tegmen. Scale bars: 1 mm.
Figures 20-25 in Two new genera of Desmiphorini (Coleoptera, Cerambycidae, Lamiinae) with description of a species with non-retractile parameres
Figures 20-25. Tegmen and median lobe. Obscenoides compta (Martins & Galileo, 2005) comb. nov. (20) Ventral; (23) Lateral. Desmiphora (Desmiphora) fasciculata (Olivier, 1792): (21) Ventral; (24) Lateral. Desmiphora (Desmiphora) elegantula White, 1855: (22) Ventral; (25) Lateral. Scale bars: 1 mm.
Figures 6-14 in Two new genera of Desmiphorini (Coleoptera, Cerambycidae, Lamiinae) with description of a species with non-retractile parameres
Figures 6-14. Obscenoides compta (Martins & Galileo, 2005) comb. nov., male. (6) Dorsal habitus; (9) Abdomen, lateral; (12) Ventral habitus; (13) Lateral habitus; (14) Head, frontal. Desmiphora (Desmiphora) elegantula White, 1855, male: (7) Dorsal habitus; (10) Abdomen, lateral. Desmiphora (Desmiphora) fasciculata (Olivier, 1792), male: (8) Dorsal habitus; (11) Abdomen, lateral. Scale bars: 6-8, 12-13 = 5 mm, 9-11, 14 = 1 mm.
Figures 1-5 in Two new genera of Desmiphorini (Coleoptera, Cerambycidae, Lamiinae) with description of a species with non-retractile parameres
Figures 1-5. Cleidaria cleidae gen. nov. et sp. nov., holotype male. (1) Dorsal habitus; (2) Ventral habitus; (3) Lateral habitus; (4) Tarsal claws; (5) Head, frontal.
Figures 26-31 in Two new genera of Desmiphorini (Coleoptera, Cerambycidae, Lamiinae) with description of a species with non-retractile parameres
Figures 26-31. Schemes of aedeagus. Obscenoides compta (Martins & Galileo, 2005) comb. nov.: (26) Tegmen: A = Ventral, B = Lateral, C = Dorsal; (29) Median lobe: A = Ventral; B = Lateral.The acronyms correspond to: ba = basal apophyses; bs = basal support flap; dl = dorsal lobe; ml = median lobe; mo = median orifice; pa = parameres; ri = ring part; ro = roof; sn = hook-like projection; st = setae; tg = tegmen; ts = tegmen struts; vl = ventral lobe. Desmiphora (Desmiphora) fasciculata (Olivier, 1792). (27) Tegmen: A = Ventral; B = Lateral; (30) Median lobe, lateral. Desmiphora (Desmiphora) elegantula White, 1855. (28) Tegmen: A = Ventral; B = Lateral; (31) Median lobe, lateral.
Data from: Symbioses with nitrogen-fixing bacteria: nodulation and phylogenetic data across legume genera
How species interactions shape global biodiversity and influence diversification is a central – but also data-hungry – question in evolutionary ecology. Microbially-based mutualisms are widespread and could cause diversification by ameliorating stress and thus allowing organisms to colonize and adapt to otherwise unsuitable habitats. Yet the role of these interactions in generating species diversity has received limited attention, especially across large taxonomic groups. In the massive angiosperm family Leguminosae, plants often associate with root-nodulating bacteria that ameliorate nutrient stress by fixing atmospheric nitrogen. These symbioses are ecologically-important interactions, influencing community assembly, diversity, and succession, contributing ~100-290 million tons of N annually to natural ecosystems, and enhancing growth of agronomically-important forage and crop plants worldwide. In recent work attempting to determine whether mutualism with N-fixing bacteria led to increased diversification across legumes, we were unable to definitively resolve the relationship between diversification and nodulation. We did, however, succeed in compiling a very large searchable, analysis-ready database of nodulation data for 749 legume genera (98% of Leguminosae genera; LPWG 2017), which, along with associated phylogenetic information, will provide a valuable resource for future work addressing this question and others. For each legume genus, we provide information about the species richness, frequency of nodulation, subfamily association, and topological correspondence with an additional data set of 100 phylogenetic trees curated for database compatibility. We found 386 legume genera were confirmed nodulators (i.e., all species examined for nodulation nodulated), 116 were non-nodulating, 4 were variable (i.e., containing both confirmed nodulators and confirmed non-nodulators), and 243 had not been examined for nodulation in published studies. Interestingly, data exploration revealed that nodulating legume genera are ~3× more species-rich than non-nodulating genera, but we did not find evidence that this difference in diversity was due to differences in net diversification rate. Our metadata file describes in more detail the structure of these data that provide a foundational resource for future work as more nodulation data become available, and as greater phylogenetic resolution of this ca. 19,500-species family comes into focus.
Data from: Feasibility of nuclear ribosomal region ITS1 over ITS2 in barcoding taxonomically challenging genera of subtribe Cassiinae (Fabaceae)
Premise of the Study The internal transcribed spacer (ITS) region is situated between 18S and 26S in a polycistronic rRNA precursor transcript. It had been proved to be the most commonly sequenced region across plant species to resolve phylogenetic relationships ranging from shallow to deep taxonomic levels. Despite several taxonomical revisions in Cassiinae, a stable phylogeny remains elusive at the molecular level, particularly concerning the delineation of species in the genera Cassia, Senna and Chamaecrista. This study addresses the comparative potential of ITS datasets (ITS1, ITS2 and concatenated) in resolving the underlying morphological disparity in the highly complex genera, to assess their discriminatory power as potential barcode candidates in Cassiinae. Methodology A combination of experimental data and an in-silico approach based on threshold genetic distances, sequence similarity based and hierarchical tree-based methods was performed to decipher the discriminating power of ITS datasets on 18 different species of Cassiinae complex. Lab-generated sequences were compared against those available in the GenBank using BLAST and were aligned through MUSCLE 3.8.31 and analysed in PAUP 4.0 and BEAST1.8 using parsimony ratchet, maximum likelihood and Bayesian inference (BI) methods of gene and species tree reconciliation with bootstrapping. DNA barcoding gap was realized based on the Kimura two-parameter distance model (K2P) in TaxonDNA and MEGA. Principal Findings Based on the K2P distance, significant divergences between the inter- and intra-specific genetic distances were observed, while the presence of a DNA barcoding gap was obvious. The ITS1 region efficiently identified 81.63% and 90% of species using TaxonDNA and BI methods, respectively. The PWG-distance method based on simple pairwise matching indicated the significance of ITS1 whereby highest number of variable (210) and informative sites (206) were obtained. The BI tree-based methods outperformed the similarity-based methods producing well-resolved phylogenetic trees with many nodes well supported by bootstrap analyses. Conclusion The reticulated phylogenetic hypothesis using the ITS1 region mainly supported the relationship between the species of Cassiinae established by traditional morphological methods. The ITS1 region showed a higher discrimination power and desirable characteristics as compared to ITS2 and ITS1 + 2, thereby concluding to be the locus of choice. Considering the complexity of the group and the underlying biological ambiguities, the results presented here are encouraging for developing DNA barcoding as a useful tool for resolving taxonomical challenges in corroboration with morphological framework.
FIGURES 1 – 2. Brachypterodina morae. 1 in New flightless Eumolpinae of the genera Apterodina Bechyné and Brachypterodina n. gen. (Coleoptera: Chrysomelidae) from the Neotropics
FIGURES 1 – 2. Brachypterodina morae. 1. male, dorsal view; 2. female, dorsal view.
FIGURE 23 in Review of unreported shorefly genera of the tribe Scatellini from the New Zealand subregion (Diptera: Ephydridae) with description of three new species
FIGURE 23. Karekare, the type locality of Haloscatella karekare.
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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.