Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,104
datasets available to search
ShareScore release 0.9.0
Dataset results
1,104 results for “morphological variation”
FIGURE 2 in Morphological variation in Acrossocheilus hemispinus (Teleostei: Cyprinidae: Barbinae), with comments on its taxonomic status
FIGURE 2. Lateral views of body in A. h. hemispinus (A–E) and A. h. cinctus (F–J). (A) IHB 20070500086, juvenile, unsexed, 56.12 mm SL, Huotong, Fujian Province; (B) IHB 20070600187, subadult, female, 70.36 mm SL, Jian'ou, Fujian Province; (C) IHB 20070600188, subadult, male, 76.83 mm SL, Jian'ou, Fujian Province; (D) IHB 20070500083, adult, female, 124.61 mm SL, Huotong, Fujian Province; (E) IHB 20070500168, adult, male, 107.96 mm SL, Yongtai, Fujian Province; (F) IHB 75V2912, juvenile, unsexed, 40.56 mm SL, Jinxiu, Guangxi Province; (G) IHB 0605415, subadult, female, 81.36 mm SL, Yiyang, Jiangxi Province; (H) IHB 0605427, subadult, male, 99.23 mm SL, Yiyang, Jiangxi Province; (I) IHB 20080500002, adult, female, 128.3 mm SL, Rongshui, Guangxi Province; (J) IHB 20080500001, adult, male, 124.1 mm SL, Rongshui, Guangxi Province. Scale bar =10 mm.
FIGURE 1 in Morphological variation in Acrossocheilus hemispinus (Teleostei: Cyprinidae: Barbinae), with comments on its taxonomic status
FIGURE 1. Map showing the distribution of A. h. hemispinus (̝) and A. h. cinctus (․). 1. Xi Jiang (river); 2. Chang Jiang; 3. Le'an Jiang; 4. Xin Jiang; 5. Qiupu He; 6. Ling Jiang; 7. Min Jiang; 8. Muyang Xi.
FIGURE 3 in Morphological variation in Acrossocheilus hemispinus (Teleostei: Cyprinidae: Barbinae), with comments on its taxonomic status
FIGURE 3. Scatter plots representing variation in shape between groups using Burnaby size-adjusted multivariate shape information, bounded by minimum convex polygons. (A) males of A. h. hemispinus (n=26, cross) and A. h. cinctus (n=37, open square); (B) females of A. h. hemispinus (n=32, cross) and A. h. cinctus (n=25, open square).
Figure 6 in Morphology of the Podarcis wall lizards (Squamata: Lacertidae) from the Iberian Peninsula and North Africa: patterns of variation in a putative cryptic species complex
Figure 6. Observed frequencies for the different character states of the categorical pholidotic characters presenting sufficient variation across the sample examined, and multidimensional scaling (MDS) scatter plot of Manly's overlap index between lineages. White always represents character state 0 and black represents character state 1, except for SL_SUBOC, in which white represents state 4 and black represents state 5. See Table 1 for group codes, Material and methods for variable abbreviations, and Figure 1 for the visual symbols used to represent each lineage.
Figure 5 in Morphology of the Podarcis wall lizards (Squamata: Lacertidae) from the Iberian Peninsula and North Africa: patterns of variation in a putative cryptic species complex
Figure 5. Scatter plots of individuals scores (small symbols) and group means (big symbols) of the first three principal components of variation in continuous pholidotic traits for the mitochondrial lineages examined, considering males (top) and females (bottom) separately. The most highly (+, positively; -, negatively) contributing variables (Table 4) are indicated next to each axis. See Table 1 for group codes and Material and methods for variable abbreviations.
Figure 4 in Morphology of the Podarcis wall lizards (Squamata: Lacertidae) from the Iberian Peninsula and North Africa: patterns of variation in a putative cryptic species complex
Figure 4. Least-squares means for continuous pholidotic traits in the different mitochondrial lineages examined. Vertical bars denote the observed range. Females of each group are always presented first, denoted with a grey vertical bar, and males are in black. See Table 1 for group codes, Material and methods for variable abbreviations, and Figure 1 for the symbols used to represent each lineage. Notice that no data are available for SCGN and SDLN in the PHJS lineage (Table 3).
Figure 3 in Morphology of the Podarcis wall lizards (Squamata: Lacertidae) from the Iberian Peninsula and North Africa: patterns of variation in a putative cryptic species complex
Figure 3. Scatter plots of individual scores (small symbols) and group means (big symbols) of the first three principal components of body shape variation for the mitochondrial lineages examined, considering males (top) and females (bottom) separately. The most highly (+, positively; -, negatively) contributing variables (Table 4) are indicated next to each axis. See Table 1 for group codes and Material and methods for variable abbreviations.
Figure 2 in Morphology of the Podarcis wall lizards (Squamata: Lacertidae) from the Iberian Peninsula and North Africa: patterns of variation in a putative cryptic species complex
Figure 2. Least-squares means for multivariate body size and size-corrected biometric variables in the different mitochondrial lineages examined. Only the characters most relevant for global biometric variation and group discrimination (after principle components analysis and canonical variates analysis, respectively; see Results) are presented. Error bars denote ± standard deviation. Females of each group are always presented first, denoted with a grey vertical bar, and males are in black. See Table 1 for group codes, Material and methods for variable abbreviations, and Figure 1 for symbols used to represent each lineage.
Figure 1 in Morphology of the Podarcis wall lizards (Squamata: Lacertidae) from the Iberian Peninsula and North Africa: patterns of variation in a putative cryptic species complex
Figure 1. Mitochondrial DNA lineages sampled, maximum likelihood tree of phylogenetic relationships between them (A, modified from Kaliontzopoulou et al., 2011), and map of the localities from which the samples analysed morphologically were obtained (B).
Figure 4 in Patterns of morphological variation amongst semifossorial shrews in the highlands of Guatemala, with the description of a new species (Mammalia, Soricomorpha, Soricidae)
Figure 4. Plot of scores on first two axes from principal components analysis of humeri of five species of broad-clawed Cryptotis (see Table 8).
Figure 3 in Patterns of morphological variation amongst semifossorial shrews in the highlands of Guatemala, with the description of a new species (Mammalia, Soricomorpha, Soricidae)
Figure 3. Plot of scores on first two axes from principal components analysis of skulls of the three largest species of broad-clawed Cryptotis (see Table 7).
Figure 1 in Patterns of morphological variation amongst semifossorial shrews in the highlands of Guatemala, with the description of a new species (Mammalia, Soricomorpha, Soricidae)
Figure 1. Anterior aspect of the humerus illustrating variables measured: BS1, breadth of shaft of humerus from superior base of medial epicondyle to superior base of lateral epicondyle; CD, distance from deltoid process to capitulum; DW, width of distal end of humerus; GT, distance from greater tuberosity to teres tubercle; L1, length of humerus from head to capitulum and trochlea; MT, internal distance from medial epicondyle to teres tubercle; PW, width of proximal end of humerus.
Figure 2 in Patterns of morphological variation amongst semifossorial shrews in the highlands of Guatemala, with the description of a new species (Mammalia, Soricomorpha, Soricidae)
Figure 2. Plot of scores on first two axes from principal components analysis of skulls of six species of broad-clawed Cryptotis (see Table 6).
Figure 7 in Patterns of morphological variation amongst semifossorial shrews in the highlands of Guatemala, with the description of a new species (Mammalia, Soricomorpha, Soricidae)
Figure 7. Distance trees resulting from cluster analyses of morphological data sets derived from six species of broad-clawed Cryptotis: A, 21 craniomandibular variables; B, seven humerus variables; C, eight variables from ray I; D, ten variables from ray III; E, ten variables from ray V; F, combined analyses of 28 forefoot variables; G, combined analysis of 59 variables.
Figure 10. X in Patterns of morphological variation amongst semifossorial shrews in the highlands of Guatemala, with the description of a new species (Mammalia, Soricomorpha, Soricidae)
Figure 10. X-ray images of left mani of: A, Cryptotis parvus parvus (USNM 568977); B, Cryptotis mexicanus (USNM 68298); C, Cryptotis griseoventris (USNM 758905); D, Cryptotis mam (USNM 77057); E, Cryptotis oreoryctes (USNM 569854); F, Cryptotis lacertosus (USNM 569442); G, Cryptotis goodwini (USNM 77078).
Figure 9 in Patterns of morphological variation amongst semifossorial shrews in the highlands of Guatemala, with the description of a new species (Mammalia, Soricomorpha, Soricidae)
Figure 9. Anterior aspect of left humeri of A, Cryptotis parvus parvus (USNM 582437); B, Cryptotis mexicanus (USNM 29541); C, Cryptotis mam (USNM 570340); D, Cryptotis goodwini (USNM 275681); E, Cryptotis goodwini (UMMZ 103416); F, Cryptotis oreoryctes (USNM 569877); G, Cryptotis lacertosus (USNM 569503).
Figure 5 in Patterns of morphological variation amongst semifossorial shrews in the highlands of Guatemala, with the description of a new species (Mammalia, Soricomorpha, Soricidae)
Figure 5. Plots of scores on first two axes from principal components analyses of individual rays from five species of broad-clawed Cryptotis: A, six variables from ray I; B, eight variables from ray III; C, six variables from ray V (see Table 9).
Figure 6 in Patterns of morphological variation amongst semifossorial shrews in the highlands of Guatemala, with the description of a new species (Mammalia, Soricomorpha, Soricidae)
Figure 6. Box-and-whisker plot of width of metacarpal of ray III for five species of broad-clawed Cryptotis. Cross within each box represents the mean, shaded box indicates SD, and vertical line shows the range of values for each species.
FIGURE 17. Protomiltogramma laticeps Malloch, morphological variation. A–B. Morphotype with reduced frontal vitta. C–D in Integrative taxonomy reveals remarkable diversity in Australian Protomiltogramma (Diptera: Sarcophagidae)
FIGURE 17. Protomiltogramma laticeps Malloch, morphological variation. A–B. Morphotype with reduced frontal vitta. C–D. "True laticeps" morphotype. Scale bars = 1 mm.
FIGURE 6 in Morphological variation and affinities of the poorly known snake Atractus caxiuana (Serpentes: Dipsadidae)
FIGURE 6. Lateral view of posterior region of the body above the cloacae (A) of Atractus caxiuana from Taraira, department of Vaupés, Colombia (ICN 10114) and detail of the supra-anal tubercle (B) of Atractus caxiuana from Vila Cachoeira do Samuel, municipality of Porto Velho, state of Rondônia, Brazil (MNRJ 3026). The arrow indicates one of the supra-anal tubercles and the scale bar represents 1 mm.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.