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690 results for “Geometric morphometrics”
Fig. 1 in Wing geometric morphometrics to distinguish and identify Haematobosca flies (Diptera: Muscidae) from Thailand
Fig. 1. Heads in the lateral view and the pleura of Haematobosca sanguinolenta (A, B) and H. aberrans (C, D). The anterior and posterior katepisternal setae (arrow) were used to distinguish between both species. Photographs were prepared by the authors.
Fig. 5 in Wing geometric morphometrics to distinguish and identify Haematobosca flies (Diptera: Muscidae) from Thailand
Fig. 5. Mean shape of male (A) and female (B) Haematobosca sanguinolenta and H. aberrans after Procrustes superimposition.
Fig. 6 in Wing geometric morphometrics to distinguish and identify Haematobosca flies (Diptera: Muscidae) from Thailand
Fig. 6. Factor map of the first two principal components (PC1, 47% as horizontal axis and PC2, 33% as vertical axis) of wing shape variables (A) and factor map of the first two discriminant factors (DF1, 66.8% as horizontal axis and DF2, 31.8% as vertical axis, the two discriminant factors represent 98.6% of the total discriminant space) of wing shape variables (B). Each point represents the individuals of male and female Haematobosca sanguinolenta and H. aberrans, and each polygon corresponds to a different species and sex. Squares represent the mean values in each group.
FIGURE 5 in Non-linear ontogenetic shape change in Cryptolithus tesselatus (Trilobita) using three-dimensional geometric morphometrics
FIGURE 5. Principal components analysis of 3D fixed and semi landmarks. 1, PC 1 vs PC 2; point size represents relative centroid size of specimen. 2-4, Landmark configuration of shape represented by low PC 1 score, typical of largest specimens, in dorsal, anterior, and right lateral views, respectively. 5-7, Landmark configuration of shape represented by high PC 1 score, typical of smallest specimens, in dorsal, anterior, and right lateral views, respectively.
FIGURE 4 in Non-linear ontogenetic shape change in Cryptolithus tesselatus (Trilobita) using three-dimensional geometric morphometrics
FIGURE 4. Slice through volume rendering of Cryptolithus tesselatus (AMNH FI-101479), shown in dorsal view in inset. Red line in inset shows the orientation of the slice across the specimen. Bright white area is sediment trapped within the bilaminar structure of the cephalon. Blue arrows point to suture between upper and lower lamellae; red arrows point to fringe-pits.
FIGURE 1 in Non-linear ontogenetic shape change in Cryptolithus tesselatus (Trilobita) using three-dimensional geometric morphometrics
FIGURE 1. Cephalon of Cryptolithus tesselatus (AMNH FI-101479) showing morphological terms used in this paper, following Whittington (1968) and Hughes et al. (1975). Concentric arcs are labeled according to their placement relative to the girder (expressed on the ventral side): E = external; I = internal. "Fringe-pits" are circled in yellow; the "F-pits" represent a subset of these interior to the labeled concentric arcs. Specimen is 6.6 mm long.
FIGURE 8 in Non-linear ontogenetic shape change in Cryptolithus tesselatus (Trilobita) using three-dimensional geometric morphometrics
FIGURE 8. Length vs width of Cryptolithus tesselatus cephala, coded for the number of concentric arcs of fringe-pits expressed in each specimen. The first three concentric arcs (E, I1, and I2) are complete when first expressed. Based on clustering, I3 is likely completed over three molts, first by only 1-3 fringe-pits, then 8-10 fringe-pits, then 13-15 fringe-pits with the anteriormost in line with the 10th radial rows of fringe-pits in arcs E-I. The dataset includes the 23 2 specimens, which were CT-scanned as well as 31 additional silicified specimens from the collection; specimens that were CT-scanned are outlined in red. Arrows indicate the specimens shown in Figures 1 and 7. Inset in upper right corner is a magnified view of the specimens in the dashed box. The scaling component describing the relationship between length and width is 1.153 (1 = isometric growth).
FIGURE 7 in Non-linear ontogenetic shape change in Cryptolithus tesselatus (Trilobita) using three-dimensional geometric morphometrics
FIGURE 7. Additions of fringe-pits associated with early meraspid stages of ontogeny in Cryptolithus tesselatus. 1, meraspid stage 2 showing two concentric arcs of fringe-pits, AMNH FI-101498, x35. 2, meraspid stage 2 showing two concentric arcs of fringe-pits, AMNH FI-101499, x35. 3, merapid stage 3 showing three concentric arcs of fringe-pits and first few fringe-pits of I3, FI-101496, x20. 4, later meraspid stage showing complete set of fringe-pits, AMNH FI- 101494, x15. Scale bars are 1 mm.
FIGURE 3 in Non-linear ontogenetic shape change in Cryptolithus tesselatus (Trilobita) using three-dimensional geometric morphometrics
FIGURE 3. Placement of points defining patch on glabella. Points in red are redundant to fixed landmarks as described in the text and Appendix 2. After the surface landmarks were extracted using Landmark Editor, the redundant landmarks were removed from the final data file. Specimen shown is AMNH FI-101482; specimen is 7.1 mm long.
FIGURE 10 in Non-linear ontogenetic shape change in Cryptolithus tesselatus (Trilobita) using three-dimensional geometric morphometrics
FIGURE 10. Allometry in the cranidia/cephala of other trilobite species as described by 2D geometric morphometrics. 1, Marrolithus bureaui, data from figure 5 of Delabroye and Crônier (2008), breakpoint shown is at 2.8, which was the best supported threshold model (Table 2). 2, Aulacopleura koninckii, data from figure 3 of Hong et al. (2014), breakpoint set at 2.0. 3, Triarthrus becki, data from figure 6 of Kim et al. (2002); breakpoint at 0.6. 4, Zacanthopsis palmeri, data from figure 13 of Hopkins and Webster (2009), breakpoint set at 0.8. 5, Haniwa quadrata, data from figure 5 of Park and Choi (2011b), breakpoint set at 1.4. 6, Liostracina tangwangzhaiensis, data from figure 3 of Park et al. (2014), breakpoint set at 1.55. 7, Apatokephalus latilimbatus, data from figure 4 of Park and Kihm (2015), breakpoint set at 0.85. 8, Olenellus gilberti, data from figure 23B of Webster (2015), breakpoint set at 1.0. Breakpoints are all in units of natural log of centroid size. Red lines = linear regression models; blue lines = threshold models.
FIGURE 2 in Non-linear ontogenetic shape change in Cryptolithus tesselatus (Trilobita) using three-dimensional geometric morphometrics
FIGURE 2. Different views of 3D surface model rendering of Cryptolithus tesselatus showing placement of fixed landmarks. All landmarks are indicated at least once, with the exception of 11 (paired with 12). Unpaired landmarks = 17– 20; paired landmarks = 1–16, 21–23, 42; semi-landmarks along first internal list shown by dashed line and represented by landmarks 24–41. See Appendix 2 for full description of all landmarks. Surface reconstruction is of AMNH FI-101479.
FIGURE 9 in Non-linear ontogenetic shape change in Cryptolithus tesselatus (Trilobita) using three-dimensional geometric morphometrics
FIGURE 9. Ontogeny of Cryptolithus tesselatus based on 2D geometric morphometrics. 1, Fixed landmarks consistently recognizable in dorsal view. Red dashed line shows curve described by first internal list along which were placed 21 semi-landmarks. Specimen shown is AMNH FI- 101479; specimen is 6.7 mm long. 2, Principal components analysis of 2D fixed- and semi-landmarks. Point size represents relative centroid size of specimen. Insets are deformation plots showing shapes represented by largest and smallest PC 1 values. 3, Allometric curve; amount of shape change represented by the Procrustes distance between each specimen and the smallest specimen. Red solid line = linear regression model; blue solid line = threshold model 1; thin black dashed line = threshold model 2; thick black dashed line = threshold model 3. Threshold model 1 is the best supported model (Table 1).
FIGURE 6 in Non-linear ontogenetic shape change in Cryptolithus tesselatus (Trilobita) using three-dimensional geometric morphometrics
FIGURE 6. Allometric growth in Cryptolithus tesselatus. Size (x-axis) is represented by the natural log of centroid size. Change in shape (y-axis) is represented by the Procrustes distance between each specimen and the smallest specimen in the dataset; the Procrustes distances in this case represent the relative amount of change that specimens underwent during development. Red solid line = linear regression model; blue solid line = threshold model 1; thin black dashed line = threshold model 2; thick black dashed line = threshold model 3. Threshold model 1 is the best supported model.
FIGURE 4 in Talpa fossilis or Talpa europaea? Using geometric morphometrics and allometric trajectories of humeral moles remains from Hungary to answer a taxonomic debate
FIGURE 4. Boxplot of the centroid sizes. Bottom and top of the boxes are the first and third quartiles; horizontal solid black lines represent the median; whiskers represent the minimum and maximum values.
FIGURE 3. 1 in Talpa fossilis or Talpa europaea? Using geometric morphometrics and allometric trajectories of humeral moles remains from Hungary to answer a taxonomic debate
FIGURE 3. 1, Scatterplot of the first two axes of the PCA. Deformation grids refer to axes extremes (positive and negative values). 2, Scatterplot of the first and third axes of PCA. Deformation grids refer to axes extremes (positive and negative values).
FIGURE 5. 1 in Talpa fossilis or Talpa europaea? Using geometric morphometrics and allometric trajectories of humeral moles remains from Hungary to answer a taxonomic debate
FIGURE 5. 1, CCA scatterplot of the shape and size variables. 2, Plot of the Euclidean distances between the predicted shape values of Talpa fossilis and T. europaea against 10 discrete CS intervals.
FIGURE 2. 1 in Talpa fossilis or Talpa europaea? Using geometric morphometrics and allometric trajectories of humeral moles remains from Hungary to answer a taxonomic debate
FIGURE 2. 1, Landmarks (large grey circles) and semilandmarks (small white circles) digitized on the humerus in caudal norm: 1) lateral end of greater tuberosity; 2) articular facet for clavicula; 3) proximal edge of the articular facet for clavicula; 4) bicipital notch; 5) proximal end of lesser tuberosity; 6) medial edge of the minor tuberosity; 7) lateral edge of the lesser tuberosity; 8) bicipital ridge; 9) middle point of the bicipital tunnel; 10) lateral end of the scalopine ridge; 11) proximal end of the teres tubercle; 12-14) surface of the teres tubercle; 15) distal end of the teres tubercle; 16-18) minor sulcus; 19) posterior margin of the lateral epicondyle; 21-22) lateral epicondyle; 22-24) trochlear area; 25-27) medial epicondyle; 28) posterior margin of the medial epicondyle; 29-32) greater sulcus; 33-36) humeral head. Scalebar equals 1 mm. 2, Insertion areas of the main muscles involved in the digging movement. 1. Pectoral ridge where muscle Pectoralis pars sternalis inserts. 2. Teres tubercle where muscles Teres major and Latissimus dorsi inserts.
Fig. 7 in Fractal analysis of ostracod shell variability: A comparison with geometric and classic morphometrics
Fig. 7. RW1/RW2 plot showing the neat separation of Krithe compressa from Krithe iniqua specimens. Deformation grids along RW1 (set at values of –0.2 and 0.2) are reported. A. Plot of RW1 against RW2 scores. B, C. Shell deformation at extreme values along RW1.
Fig. 4 in Fractal analysis of ostracod shell variability: A comparison with geometric and classic morphometrics
Fig. 4. Main morphological features of studied ostracods species. A. Krithe iniqua Abate, Barra, Aiello, and Bonaduce, 1993, right valve, transparence drawing from external view, sample 59, B.O.C. 2518, upper Pliocene, KI−29, sample 59. B. Krithe compressa (Seguenza, 1880), right valve, transparence drawing from external view, KC−29, sample 58, B.O.C. 2547, upper Pliocene.
Fig. 2 in Fractal analysis of ostracod shell variability: A comparison with geometric and classic morphometrics
Fig. 2. Krithe iniqua Abate, Barra, Aiello, and Bonaduce, 1993, right valves; transparence drawings from external view; sample 59; upper Pliocene. A. KI−01, B.O.C. 2490. B. KI−02, B.O.C. 2491. C. KI−03, B.O.C. 2492. D. KI−04, B.O.C. 2493. E. KI−05, B.O.C. 2494. F. KI−06, B.O.C. 2495. G. KI−07, B.O.C. 2496. H. KI−08, B.O.C. 2497. I. KI−09, B.O.C. 2498. J. KI−10, B.O.C. 2499. K. KI−11, B.O.C. 2500. I. KI−12, B.O.C. 2501. L. KI−13, B.O.C. 2502. M. KI−14, B.O.C. 2503. N. KI−15, B.O.C. 2504. O. KI−16, B.O.C. 2505. P. KI−17, B.O.C. 2506. Q. KI−18, B.O.C. 2507. R. KI−19, B.O.C. 2508. S. KI−20, B.O.C. 2509. T. KI−21, B.O.C. 2510. U. KI−22, B.O.C. 2511. V. KI−23, B.O.C. 2512. W. KI−24, B.O.C. 2513. Y. KI−25, B.O.C. 2514. Z. KI−26, B.O.C. 2515. AA. KI−27, B.O.C. 2516. BB. KI−28, B.O.C. 2517.
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Allen Brain Atlas
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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
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