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111 results for “shell variability”
Fig. 1. A in Fractal analysis of ostracod shell variability: A comparison with geometric and classic morphometrics
Fig. 1. A. Ideal uniform network of 225 points spaced 2 mm apart over an area of 30 × 30 mm2. B. The log of number of pairs C of the stations, with mutual distance smaller than R, as a function of log(R) (mm); the vertical dashed lines represent the lower (4 mm) and upper (16 mm) limits of R, inside which the linear slope provides the best fitting to the investigated co−ordinates.
Fig. 8 in Fractal analysis of ostracod shell variability: A comparison with geometric and classic morphometrics
Fig. 8. This plot is the same as in Fig. 7, except for marks have been appended according to sample of provenance instead of species.
Fig. 3 in Fractal analysis of ostracod shell variability: A comparison with geometric and classic morphometrics
Fig. 3. Krithe compressa (Seguenza, 1880), right valves; transparence drawings from external view; sample 50 (A–G), sample 51 (H–R), sample 58 (S–BB); upper Pliocene. A. KC−01, B.O.C. 2519. B. KC−02, B.O.C. 2520. C. KC−03, B.O.C. 2521. D. KC−04, B.O.C. 2522.E. KC−05, B.O.C. 2523. F. KC−06, B.O.C. 2524. G. KC−07, B.O.C. 2525. H. KC−08, B.O.C. 2526. I. KC−09, B.O.C. 2527. J. KC−10, B.O.C. 2528. K. KC−11, B.O.C. 2529. L. KC−12, B.O.C. 2530. M. KC−13, B.O.C. 2531. N. KC−14, B.O.C. 2532. O. KC−15, B.O.C. 2533. P. KC−16, B.O.C. 2534. Q. KC−17, B.O.C. 2535. R. KC−18, B.O.C. 2536. S. KC−19, B.O.C. 2537. T. KC−20, B.O.C. 2538. U. KC−21, B.O.C. 2539. V. KC−22, B.O.C. 2540. W. KC−23, B.O.C. 2541. X. KC−24, B.O.C. 2542. Y. KC−25, B.O.C. 2543. Z. KC−26, B.O.C. 2544. AA. KC−27, B.O.C. 2545. BB. KC−28, B.O.C. 2546.
Fig. 2. Shell morphometric variables. A in Morphology and taxonomic assessment of eight genetic clades of Mercuria Boeters, 1971 (Caenogastropoda, Hydrobiidae), with the description of five new species
Fig. 2. Shell morphometric variables. A. Image of a specimen of Mercuria similis (Draparnaud, 1805) indicating the landmarks (red) and semilandmarks (blue) used for the geometric morphometric analysis (PCA). B–C. Drawings of shells of Mercuria Boeters, 1971, showing the linear measurements made on the shell and protoconch.
Fig. 4 in The Study Of Age-Related Variability Of Pigmentation Patterns Of The Shells Of Dreissena Polymorpha (Bivalvia, Dreissenidae) From Different Parts Of It'S Range
Fig. 4. Frequences of main pattern types at different age zones on zebra mussel shells.
Fig. 10 in Ecophenotypic plasticity versus evolutionary trends-morphological variability in Upper Jurassic bivalve shells from Portugal
Fig. 10. Box plot of rib numbers in Arcomytilus. Numbers in squared brackets refer to Fig. 2.
Fig. 6 in Fractal analysis of ostracod shell variability: A comparison with geometric and classic morphometrics
Fig. 6. Location of landmarks chose on Krithe valve for shape analysis.
Shelled Pteropod individual-based model output for the publication: The impact of aragonite saturation variability on shelled pteropods: An attribution study in the California current system
Open the record for dataset details and reuse information.
FIGURES 35 in Redescription, shell variability and geographic distribution of Plagiodontes dentatus (Wood, 1828) (Gastropoda: Orthalicidae: Odontostominae) from Uruguay and Argentina
FIGURES 35. Representative shells of the three species of Plagiodontes under comparison. 3, Plagiodontes dentatus (Wood, 1828); 4, P. multiplicatus (Doering, 1874); 5, P. patagonicus (d'Orbigny, 1835).
FIGURES 813 in Redescription, shell variability and geographic distribution of Plagiodontes dentatus (Wood, 1828) (Gastropoda: Orthalicidae: Odontostominae) from Uruguay and Argentina
FIGURES 813. SEM photographs of the protoconch sculpture in Plagiodontes spp. 8, P. dentatus; 9, newly hatched P. patagonicus; 10, P. multiplicatus; 11, closeup of Fig. 9, showing the maximum development of the spiral lines crossing the axial striae; 12, eroded apex of P. multiplicatus; 13, closeup of figure 12, showing the remains of spiral sculpture in the protoconch. Bar "a" scales Figures 8, 9, 10, and 12; bar "b" scales Figures 11 and 13.
FIGURES 67 in Redescription, shell variability and geographic distribution of Plagiodontes dentatus (Wood, 1828) (Gastropoda: Orthalicidae: Odontostominae) from Uruguay and Argentina
FIGURES 67. SEM photographs of the teleoconch sculpture near the aperture lip. 6, Plagiodontes dentatus; 7, P. multiplicatus.
FIGURES 1416 in Redescription, shell variability and geographic distribution of Plagiodontes dentatus (Wood, 1828) (Gastropoda: Orthalicidae: Odontostominae) from Uruguay and Argentina
FIGURES 1416. SEM photographs of the apertural teeth in Plagiodontes spp. 14, P. dentatus; 15, P. multiplicatus (arrow indicates the presence of a denticle on the columellar tooth); 16, P. patagonicus.
FIGURE 2. Claws II in Determinants and taxonomic consequences of extreme egg shell variability in Ramazzottius subanomalus (Biserov, 1985) (Tardigrada)
FIGURE 2. Claws II of similar size females exhibiting haplotype 1 (A) or haplotype 2 (B) as seen in PCM. Minor differences were found between the two haplotypes in morphometry of the internal claws, with haplotype 1 females having slightly smaller claws in relation to the buccal tube length (see Tables 1–2 statistics and Figure 4A for a graphic illustration of the differences in claw dimensions). Scale bar in micrometres.
FIGURE 3 in Determinants and taxonomic consequences of extreme egg shell variability in Ramazzottius subanomalus (Biserov, 1985) (Tardigrada)
FIGURE 3. Chorions of eggs laid by females exhibiting haplotype 1 (A-F) or haplotype 2 (G-L) as seen in PCM and SEM. Highly significant differences were found between the two haplotypes in all measured morphometric eggs traits (see Table 3 for statistics and Figure 4B for a graphic illustration). In general, haplotype 1 eggs were larger and exhibited longer, thinner and more numerous processes than haplotype 2 eggs. Note, however, also the considerable variation within the haplotypes (see Table 3 and Figure 4B for statistics). Scale bars in micrometres, scale for all PCM photomicrographs same as on the photomicrograph A.
FIGURE 1 in Determinants and taxonomic consequences of extreme egg shell variability in Ramazzottius subanomalus (Biserov, 1985) (Tardigrada)
FIGURE 1. Graphic illustration of the experimental design: A—protocol that allows a permanent preservation of eggs but not of adult females; B—protocol that allows a permanent preservation of adult females and empty chorions but not of entire eggs (if only a single egg is laid).
Figure 3 in A dark shell hiding great variability: a molecular insight into the evolution and conservation of melanic Daphnia populations in the Alps
Figure 3. Map of the Alps showing European Daphnia pulicaria populations (1–12) and haplotypes (A1–A10) considered in this study. Different colours and patterns identify haplotypes found in more than one population or together with other haplotypes. See Table 1 for details of populations.
Figure 1 in A dark shell hiding great variability: a molecular insight into the evolution and conservation of melanic Daphnia populations in the Alps
Figure 1. Map showing the distribution of European Daphnia pulicaria, including melanic populations specifically sampled in alpine lakes in the Western Italian Alps for this study. Within the enlarged box, the dashed grey line delimits river catchments where melanic populations were found (Orco and Dora di Savaranche). On the right, one melanic specimen from lake Nivolet. Abbreviations: GPNP, Gran Paradiso National Park. Abbreviations: SJM, Svalbard; RUS, Russia; ISL, Island; NOR, Norway; SWE, Sweden; GBR, Great Britain; DEU, Germany; POL, Poland; CZE, Czech Republic; CHE, Switzerland; ESP, Spain; HUN, Hungary; MNE, Montenegro; ALB, Albania; MKD, Macedonia; TRI, Trebecchi Inferiore; TRS, Trebecchi Superiore; NIV, Nivolet; LIL, Lillet.
Fig. 13 in Intra- and interspecific shell variability of the genus Urocythereis Ruggieri, 1950 (Ostracoda: Hemicytheridae) in the La Strea Bay (Ionian Sea, Italy)
Fig. 13. Non-metric multidimensional scaling (n-MDS) analysis. A. Results for "non-normalized area" mode. B. Results for "normalized area" mode.
Fig. 9 in Intra- and interspecific shell variability of the genus Urocythereis Ruggieri, 1950 (Ostracoda: Hemicytheridae) in the La Strea Bay (Ionian Sea, Italy)
Fig. 9. Comparison of valve outlines obtained by Morphomatica analysis. Results for "normalized area" mode. A. U. ilariae sp. nov. B. U. margaritifera (G.W. Müller, 1894). C. U. distinguenda (Neviani, 1928).
Quantifying shell outline variability in extant and fossil Laqueus (Brachiopoda: Terebratulida): are outlines good proxies for long-looped brachidial morphology and can they help us characterize species?
<p>Extant and extinct terebratulide brachiopod species have been defined primarily on the basis of morphology. What is the fidelity of morphological species to biological species? And how can we test this fidelity with fossils? Taxonomically and phylogenetically, the most informative internal feature in the brachiopod suborder Terebratellidina is the geometrically complex long-looped brachidium, which, given their fragile nature, are not commonly preserved in the fossil record. In their absence, it is essential to test other sources of morphological data when trying to recognize and identify species. We analyzed valve outlines and brachidia in the genus <i>Laqueus</i> to explore the utility of shell shape in discriminating extant and fossil species. Using geometric morphometric methods, we quantified valve outline variability using elliptical Fourier methods and tested whether long-looped brachidial morphology correlates with shell outline shape. We then built classification models based on machine learning algorithms using outlines as shape variables to predict fossil species' identities. Our results demonstrate that valve outline shape is significantly correlated with long-looped brachidial shape and that even relatively simple outlines are sufficiently morphologically distinct to enable extant <i>Laqueus</i> species to be identified, validating current taxonomic assignments. These are encouraging results for the study and delimitation of fossil terebratulide species, and their recognition as biological species. In addition, machine learning algorithms can be successfully applied to help solve species recognition and delimitation problems in paleontology, especially when morphology can be characterized quantitatively and analyzed statistically.</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.