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609 results for “morphometric analysis”
Figure 4 from: Li M, Sylvester SP, Wang Z-P, Pei Y-D, Gao X-F, Zhao Y, Jiang W-Q (2020) Re-instatement of Sorbus harrowiana (Rosaceae), based on morphometric analysis. PhytoKeys 166: 29-39. https://doi.org/10.3897/phytokeys.166.57672
Figure 4 Sorbus harrowianaA growing near the road in mixed forest B growing on a steep forested slope above road C growing on Lithorcarpus like an epiphytic shrub D fruiting branch E pinnately compound-leaves.
Figure 2 from: Li M, Sylvester SP, Wang Z-P, Pei Y-D, Gao X-F, Zhao Y, Jiang W-Q (2020) Re-instatement of Sorbus harrowiana (Rosaceae), based on morphometric analysis. PhytoKeys 166: 29-39. https://doi.org/10.3897/phytokeys.166.57672
Figure 2 Type pictures of Sorbus insignis (Hook. f.) Hedl. (A barcode K000758177) and S. harrowiana (Balf. f. & W. W. Smith) Rehd. (B barcode E00072735).
Figure 1 from: Li M, Sylvester SP, Wang Z-P, Pei Y-D, Gao X-F, Zhao Y, Jiang W-Q (2020) Re-instatement of Sorbus harrowiana (Rosaceae), based on morphometric analysis. PhytoKeys 166: 29-39. https://doi.org/10.3897/phytokeys.166.57672
Figure 1 Box plot of comparisons between S. harrowiana and S. insignis in middle leaflet length, width and l/w ratio. Significant differences found upon analysis using non-parametric Wilcoxon rank sum test on untransformed data (Wilcoxon) and parametric Welch Two Sample T-test on log10 transformed data (T-test) are noted within the figures (*** = p < 0.001).
Data from: Crowdsourced geometric morphometrics enable rapid large-scale collection and analysis of phenotypic data
1. Advances in genomics and informatics have enabled the production of large phylogenetic trees. However, the ability to collect large phenotypic datasets has not kept pace. 2. Here, we present a method to quickly and accurately gather morphometric data using crowdsourced image-based landmarking. 3. We find that crowdsourced workers perform similarly to experienced morphologists on the same digitization tasks. We also demonstrate the speed and accuracy of our method on seven families of ray-finned fishes (Actinopterygii). 4. Crowdsourcing will enable the collection of morphological data across vast radiations of organisms, and can facilitate richer inference on the macroevolutionary processes that shape phenotypic diversity across the tree of life.
Data from: Genomic analysis of morphometric traits in bighorn sheep using the Ovine Infinium® HD SNP BeadChip
Elucidating the genetic basis of fitness-related traits is a major goal of molecular ecology. Traits subject to sexual selection are particularly interesting, as non-random mate choice should deplete genetic variation and thereby their evolutionary benefits. We examined the genetic basis of three sexually selected morphometric traits in bighorn sheep (Ovis canadensis): horn length, horn base circumference, and body mass. These traits are of specific concern in bighorn sheep as artificial selection through trophy hunting opposes sexual selection. Specifically, horn size determines trophy status and, in most North American jurisdictions, if an individual can be legally harvested. Using between 7,994–9,552 phenotypic measures from the long-term individual-based study at Ram Mountain (Alberta, Canada), we first showed that all three traits are heritable (h2 = 0.15–0.23). We then conducted a genome-wide association study (GWAS) utilizing a set of 3,777 SNPs typed in 76 individuals using the Ovine Infinium® HD SNP BeadChip. We found suggestive association for body mass at a single locus (OAR9_91647990). The absence of strong associations with SNPs suggests that the traits are likely polygenic. These results represent a step forward for characterizing the genetic architecture of fitness related traits in sexually dimorphic ungulates.
Fig. 2 in Morphometric analysis and taxonomic revision of Anisopteromalus Ruschka (Hymenoptera: Chalcidoidea: Pteromalidae) - an integrative approach
Fig. 2. Size and shape analysis of females of OTUs Anisopteromalus calandrae and A. quinarius using all variables except gaster breadth. (A, B) Shape PCA, scatterplot of first against second shape PC (A), scatterplot of isosize against first shape PC (B). Symbols: blue dots, A. calandrae; red squares, A. quinarius; in parentheses the variance explained by each shape PC. (C, D) Ratio spectra, PCA ratio spectrum (C), allometry ratio spectrum (D); horizontal bars in the ratio spectra represent 68% bootstrap confidence intervals based on 1000 replicates.
Fig. 1 in Morphometric analysis and taxonomic revision of Anisopteromalus Ruschka (Hymenoptera: Chalcidoidea: Pteromalidae) - an integrative approach
Fig. 1. Scatterplot of first against second shape PC of females of all six OTUs of Anisopteromalus. (A, B) Shape PCA, including all 20 variables (A) and with variable gaster breadth omitted (B). Closed symbols: blue dots, A. calandrae; red squares, A. quinarius. Open symbols: violet diamonds, A. apiovorus; green upside down triangles, A. caryedophagus; black circle, A. ceylonensis; orange triangles, A. cornis. In (B), name-bearing types are marked with bold plus signs, the light blue plus sign indicates the position of the neotype of A. calandrae. The variance explained by each shape PC is given in parentheses.
Fig. 3. Shape PCA for exploring female variation within Anisopteromalus calandrae and A in Morphometric analysis and taxonomic revision of Anisopteromalus Ruschka (Hymenoptera: Chalcidoidea: Pteromalidae) - an integrative approach
Fig. 3. Shape PCA for exploring female variation within Anisopteromalus calandrae and A. quinarius using all variables except gaster breadth. The analyses included three cultured laboratory strains for each OTU. (A) Scatterplot of first against second shape PC of A. calandrae: cross, strain Bamberg USA; plus signs, strain Savannah USA; open circles, strain Slough (ICSP) UK. (B) Scatterplot of first against second shape PC of A. quinarius: cross, strain Moscow (MSU) Russia; plus signs, strain Michurinsk Russia; open squares, strain Fresno USA. The variance explained by each shape PC is given in parentheses.
Fig. 3 in Morphometric Analysis Of Сapillaria Anatis (Nematoda, Capillariidae) From Anas Platyrhynchos Domesticus
Fig. 3. Tail end of Ơ Сapillaria anatis: а — general view; b — laterally; с — dorsally; d — proximal end of spicule; Pb — pseudobursa, Ll — lateral lobes, Sh — spicule sheath with small spikes, S — spicule, Ds — distal end of spicule.
Data from: Principal component analysis as an alternative treatment for morphometric characters: phylogeny of caseids as a case study
In a recent study, the phylogeny of Caseidae (a herbivorous family of Palaeozoic synapsids belonging to the paraphyletic grade known as pelycosaurs) was analysed with a dataset employing more than three hundred continuous morphological characters in an effort to follow the principles of total evidence. Continuous characters are a source of great debate, with disagreements surrounding their suitability for and treatment in phylogenetic analysis. A number of shortcomings were identified in the handling of continuous characters in this study of caseids, including the use of gap weighting to discretize the characters and potential issues with redundancy and character non-independence. Therefore, an alternative treatment for these characters is suggested here. First, rather than using gap weighting, the continuous characters were analysed in the program TNT, in which the raw values can be treated as continuous rather than discrete. Second, prior to the phylogenetic analysis, the continuous characters were subjected to a log-ratio principal component analysis, and then the principal components were included in the character matrix rather than the raw ratios. Analysing the original data in TNT produced little difference in the results, but using the principal components as continuous characters resulted in alternative positions for Caseopsis agilis, Ennatosaurus tecton and Caseoides sanangeloensis. The differences are judged to be due to the reduced redundancy of the characters, the smaller number of principal components not overwhelming the discrete characters and the use of a scaling method which allows principal components with a higher variance to have a greater influence on the analysis. The positions of highly fragmentary fossils depended heavily on the method used to treat the missing characters in the principal component analysis, and so the method proposed here is not recommended for analysing very incomplete taxa.
Supplementary material 3 from: Ren J, Bai M, Yang X-K, Zhang R-Z, Ge S-Q (2017) Geometric morphometrics analysis of the hind wing of leaf beetles: proximal and distal parts are separate modules. ZooKeys 685: 131-149. https://doi.org/10.3897/zookeys.685.13084
Coordinates data of landmarks. :
Figure 4 from: Ren J, Bai M, Yang X-K, Zhang R-Z, Ge S-Q (2017) Geometric morphometrics analysis of the hind wing of leaf beetles: proximal and distal parts are separate modules. ZooKeys 685: 131-149. https://doi.org/10.3897/zookeys.685.13084
Figure 4 - Modularity test results. A The hypothesized partition: proximal part landmarks 1-6, 23, 24, and 26–36 and distal part landmarks 7–22, 25; different colour presents different modules B The partition with minimal covariance in all evaluated 104 partitions by RV coefficient C The partition with minimal covariance in all evaluated 106 partitions by RV coefficient.
Figure 2 from: Ren J, Bai M, Yang X-K, Zhang R-Z, Ge S-Q (2017) Geometric morphometrics analysis of the hind wing of leaf beetles: proximal and distal parts are separate modules. ZooKeys 685: 131-149. https://doi.org/10.3897/zookeys.685.13084
Figure 2 - PCA and CVA results. A Centroid size graph of hind wing landmarks (Procrustes fit) B PCA results, the shape changes associated with the first three PCs: the relative size of the apical area which could be considered the main feature (variance contribution ratio was 45.01%) to influence of the overall variance of the hind wing, the changes of cross vein cv in the middle area (variance contribution ratio was 12.39%), and relative size of the anal area size (variance contribution ratio was 10.56%) C CVA results, the axis of CV1 and CV2 presented the first two large shape variance of all variance; points with different colours indicated different subtribes' specimens; the ellipse is presented as an equal-frequency ellipse with a given probability level of 90%, which contains approximately 90% of the data points.
Figure 1 from: Ren J, Bai M, Yang X-K, Zhang R-Z, Ge S-Q (2017) Geometric morphometrics analysis of the hind wing of leaf beetles: proximal and distal parts are separate modules. ZooKeys 685: 131-149. https://doi.org/10.3897/zookeys.685.13084
Figure 1 - Leaf beetle hind wing (Chrysomela populi Linnaeus), with landmark locations (the dot with number), vein nomenclature and regional division. The nomenclature of the wing venation follows that of Kukalová-Peck & Lawrence (1993, 2004). Radial area: green, central area: blue, medial area: purple, anal area: yellow, apical (folding) area: red. Proximal part landmarks 1–6, 23, 24, and 26–36 mainly include radial, medial, and anal areas; distal part landmarks 7–22 and 25 include the central area, radial cell, and apical area. Abbreviations: Costa (C), Subcosta (Sc), Subcosta Anterior (ScA), Subcosta Posterior (ScP), Radius Anterior (RA), Radius Posterior (RP), Radial cross veins (r3, r4), Media Posterior (MP), Radio-medial cross veins (rp-mp1, rp-mp2), medial cross vein (cv), Cubitus Anterior (CuA), Medio-cubital Cross-vein or Arculus (mp-cua), Anal Anterior (AA), Anal posterior (AP). "+" indicates fused veins. The sub-number of veins reflects vein branches.
Figure 3 from: Ren J, Bai M, Yang X-K, Zhang R-Z, Ge S-Q (2017) Geometric morphometrics analysis of the hind wing of leaf beetles: proximal and distal parts are separate modules. ZooKeys 685: 131-149. https://doi.org/10.3897/zookeys.685.13084
Figure 3 - PLS analysis results. A Scatter plot of the PLS1 of two blocks B Shape changes associated with the first PLS axes of two blocks: each diagram shows the block change along the PLS1 in the positive or negative direction, corresponding to Figure 3A.
Figure 8 from: Cano E, Musarella CM, Cano-Ortiz A, Piñar Fuentes JC, Spampinato G, Pinto Gomes CJ (2017) Morphometric analysis and bioclimatic distribution of Glebionis coronaria s.l. (Asteraceae) in the Mediterranean area. PhytoKeys 81: 103-126. https://doi.org/10.3897/phytokeys.81.11995
Figure 8 - Thermoclimatic distribution of Glebionis coronaria (thermo-Mediterranean) and G. discolor (thermo and meso-Mediterranean) selected samples studied.
Figure 6 from: Cano E, Musarella CM, Cano-Ortiz A, Piñar Fuentes JC, Spampinato G, Pinto Gomes CJ (2017) Morphometric analysis and bioclimatic distribution of Glebionis coronaria s.l. (Asteraceae) in the Mediterranean area. PhytoKeys 81: 103-126. https://doi.org/10.3897/phytokeys.81.11995
Figure 6 - Statistical analysis by box plot of disc cypselas width of Glebionis coronaria and G. discolor.
Figure 4 from: Cano E, Musarella CM, Cano-Ortiz A, Piñar Fuentes JC, Spampinato G, Pinto Gomes CJ (2017) Morphometric analysis and bioclimatic distribution of Glebionis coronaria s.l. (Asteraceae) in the Mediterranean area. PhytoKeys 81: 103-126. https://doi.org/10.3897/phytokeys.81.11995
Figure 4 - Statistical analysis by box plot of cypselas wing width of Glebionis coronaria and G. discolor.
Figure 3 from: Cano E, Musarella CM, Cano-Ortiz A, Piñar Fuentes JC, Spampinato G, Pinto Gomes CJ (2017) Morphometric analysis and bioclimatic distribution of Glebionis coronaria s.l. (Asteraceae) in the Mediterranean area. PhytoKeys 81: 103-126. https://doi.org/10.3897/phytokeys.81.11995
Figure 3 - Box plot of alignment of glands distributed along the cypselas of Glebionis coronaria and G. discolor (Lc = Linearity coefficient).
Figure 7 from: Cano E, Musarella CM, Cano-Ortiz A, Piñar Fuentes JC, Spampinato G, Pinto Gomes CJ (2017) Morphometric analysis and bioclimatic distribution of Glebionis coronaria s.l. (Asteraceae) in the Mediterranean area. PhytoKeys 81: 103-126. https://doi.org/10.3897/phytokeys.81.11995
Figure 7 - Statistical analysis by box plot of disc cypselas length of Glebionis coronaria and G. discolor.
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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)
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DANDI Archive for NWB datasets
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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
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.