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24 results for “quantitative characters”
Supplementary material 1 from: Biniari K, Daskalakis I, Bouza D, Stavrakaki M (2019) Comparative study of qualitative and quantitative characters of grape cultivar 'Mavrodafni' (Vitis vinifera L.) and 'Renio' grown in different regions of the Protected Designation of Origin Mavrodafni Patras. Viticulture Data Journal 1: e37852. https://doi.org/10.3897/vdj.1.e37852
<p>This is the raw dataset of the measurements performed on the samples collected from the two varieties from the different locations. There are three repetitions per measurement and no statistical analysis has been performed.</p>
FIGURE 6. Correlation between characters 4–5 and 1–6 in Quantitative analysis of interspecific and ontogenetic variation in Osteoglossum species (Teleostei: Osteoglossiformes: Osteoglossidae)
FIGURE 6. Correlation between characters 4–5 and 1–6, including all size classes of Osteoglossum species. Numbers represent species and classes, where, 1= postembryos and juveniles of O. ferreirai; 2= adults of O. ferreirai; 3= postembryos and juveniles of O. bicirrhosum; 4= adults of O. bicirrhosum.
FIGURE 4. Correlation between characters 13–14 and 1–2 in Quantitative analysis of interspecific and ontogenetic variation in Osteoglossum species (Teleostei: Osteoglossiformes: Osteoglossidae)
FIGURE 4. Correlation between characters 13–14 and 1–2, including all size classes of Osteoglossum species. Numbers represent species and classes, where, 1= postembryos and juveniles of O. ferreirai; 2= adults of O. ferreirai; 3= postembryos and juveniles of O. bicirrhosum; 4= adults of O. bicirrhosum.
FIGURE 9 in A new species of the genus Mesosmittia Brundin, 1956 (Diptera: Chironomidae) from the Neotropics with a cladistic analysis of the genus using quantitative characters
FIGURE 9. Cladogram obtained from the analysis of standardized ranges data set under equal weights (Length= 167.082; CI= 55.9; RI= 51.51; Fit= 22.3). Below nodes the characters and its optimized character states are shown, synapomorphies in bold. Continuous characters were transformed from the standardization to raw data for a better understanding. Above nodes from left to right: Absolute frequency, GC, Absolute Bremer support, Relative Bremer support.
FIGURE 7 in A new species of the genus Mesosmittia Brundin, 1956 (Diptera: Chironomidae) from the Neotropics with a cladistic analysis of the genus using quantitative characters
FIGURE 7. Strict consensus trees calculated for each set of trees obtained from each of the four data sets.
FIGURES 5–6 in A new species of the genus Mesosmittia Brundin, 1956 (Diptera: Chironomidae) from the Neotropics with a cladistic analysis of the genus using quantitative characters
FIGURES 5–6. Mesosmittia museophila sp. n. Male adult. Hypopygium general view. (5) dorsal view. (6) ventral view.
FIGURES 1–4 in A new species of the genus Mesosmittia Brundin, 1956 (Diptera: Chironomidae) from the Neotropics with a cladistic analysis of the genus using quantitative characters
FIGURES 1–4. Mesosmittia museophila sp. n. Male adult. (1) Tentorium, stipes and cibarial pump. (2) Wing. (3) Hypopygium dorsal view. (4) Hypopygium with tergite IX removed, right ventral view, left dorsal view.
FIGURE 8 in A new species of the genus Mesosmittia Brundin, 1956 (Diptera: Chironomidae) from the Neotropics with a cladistic analysis of the genus using quantitative characters
FIGURE 8. Agreement subtrees calculated for each set of trees obtained from each of the four data sets.
Supplementary material 1 from: Griebenow ZH, Jones SC, Eaton TD (2017) Seeking quantitative morphological characters for species identification in soldiers of Puerto Rican Heterotermes (Dictyoptera, Blattaria, Termitoidae, Rhinotermitidae). ZooKeys 725: 17-29. https://doi.org/10.3897/zookeys.725.20010
Definitions of soldier morphometric parameters : Explanation note: Definitions of all morphometric parameters utilized in this study, sensu Roonwal (1969).
FIGURE 7. Variability range for the chosen quantitative characters. Points indicate a median value, boxes represent 5 and 95 in A revision of taxonomic relation between Oenothera royfraseri and O. turoviensis (sect. Oenothera, subsect. Oenothera; Onagraceae) based on multivariate analyses of morphological characters
FIGURE 7. Variability range for the chosen quantitative characters. Points indicate a median value, boxes represent 5 and 95 percentile, whiskers around the boxes refer to 1 and 99 percentile; B – O. biennis, P – O. perangusta, R – O. royfraseri (including the specimens labelled as O. turoviensis, except the original material of the latter), T – O. turoviensis (the original material only).
Data from: Comparing measures of breeding inequality and opportunity for selection with sexual selection on a quantitative character in bighorn rams
The reliability and consistency of the many measures proposed to quantify sexual selection have been questioned for decades. Realized selection on quantitative characters measured by the selection differential i was approximated by metrics based on variance in breeding success, using either the opportunity for sexual selection Is or indices of inequality. There is no consensus about which metric best approximates realized selection on sexual characters. Recently, the opportunity for selection on character mean OSM was proposed to quantify the maximum potential selection on characters. Using 21 years of data on bighorn sheep (Ovis canadensis), we investigated the correlations between seven indices of inequality, Is, OSM and i on horn length of males. Bighorn sheep are ideal for this comparison because they are highly polygynous, sexually dimorphic, ram horn length is under strong sexual selection, and we have detailed knowledge of individual breeding success. Different metrics provided conflicting information, potentially leading to spurious conclusions about selection patterns. Iδ, an index of breeding inequality, and to a lesser extent Is, showed the highest correlation with i on horn length, suggesting that these indices document breeding inequality in a selection context. OSM on horn length was strongly correlated with i, Is, and indices of inequality. By integrating information on both realized sexual selection and breeding inequality, OSM appeared to be the best proxy of sexual selection and may be best suited to explore its ecological bases.
FIGURE 5 in Measuring relative flower size in Anthurium (Araceae) as a continuous quantitative character
FIGURE 5. Comparison of relative flower size (RFS) between spadix zones within three populations of Anthurium erskinei and A. talmonii. Boxplots show untransformed RFS values. Populations: ersk_Lencois: A. erskinei, Lençóis; talm_Lencois: A. talmonii, Lençóis; talm_Mucuge: A. talmonii, Mucugê. Computed in R (R Core Team. 2013).
FIGURE 2. Anthurium talmonii. A in Measuring relative flower size in Anthurium (Araceae) as a continuous quantitative character
FIGURE 2. Anthurium talmonii. A. Natural population in habitat on rock outcrops. B. Spadix in close-up showing the flowers. C. Inflorescence rotated to a horizontal position, showing the spadix and the three spadix zones sampled for flower and spadix diameter measurements. Ba: Base zone. d: spadix diameter. M: Middle zone. U: Upper zone. w: flower transverse width. Scale bars: 1.0 cm (B and C); 10.0 cm (A).
FIGURE 1. Anthurium erskinei. A in Measuring relative flower size in Anthurium (Araceae) as a continuous quantitative character
FIGURE 1. Anthurium erskinei. A. Natural population in habitat on rock outcrops. B. Spadix in close-up showing the flowers. C. Inflorescence rotated to a horizontal position, showing the spadix, spathe and the three spadix zones sampled for flower and spadix diameter measurements. Ba: Base zone. d: spadix diameter. M: Middle zone. U: Upper zone. w: flower transverse width. Scale bars: 1.0 cm (B and C); 10.0 cm (A).
FIGURE 4 in Measuring relative flower size in Anthurium (Araceae) as a continuous quantitative character
FIGURE 4. Comparison of relative flower size (RFS) in three populations (one of Anthurium erskinei and two of A. talmonii). Boxplots show RFS values plotted as natural logarithms to achieve homogeneity of variances. Populations: ersk_Lencois: A. erskinei, Lençóis; talm_Lencois: A. talmonii, Lençóis; talm_Mucuge: A. talmonii, Mucugê. Computed in R (R Core Team 2013).
FIGURE 6 in Measuring relative flower size in Anthurium (Araceae) as a continuous quantitative character
FIGURE 6. Comparison of relative flower size (RFS) in three populations of Anthurum erskinei and A. talmonii. Left Column: original RFS values. Right Column: bootstrapped mean RFS values (means of 10,000 samples of 25 RFS values, with replacement). Populations:- ersk_Lencois: A. erskinei, Lençóis; talm_Lencois: A. talmonii, Lençóis; talm_Mucuge: A. talmonii, Mucugê. Computed in R (R Core Team 2013).
FIGURE 3 in Measuring relative flower size in Anthurium (Araceae) as a continuous quantitative character
FIGURE 3. Phenological phases in Anthurium talmonii (A–F) and A. erskinei (G–L) respectively, with the enlarged detail. Pre-anthesis (A, G); Female anthesis (B, H); Male anthesis (C, I); Post-anthesis (D, J); Pre-fruiting (E, K), Fruiting (F, L). Scale bars: 1.0 cm. Photos by T.A. Pontes©, except F (macro): L. Pataro©.
Data from: Comparing measures of breeding inequality and opportunity for selection with sexual selection on a quantitative character in bighorn rams
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Data from: Bayesian estimation of species divergence times using correlated quantitative characters
Discrete morphological data have been widely used to study species evolution, but the use of quantitative (or continuous) morphological characters is less common. Here, we implement a Bayesian method to estimate species divergence times using quantitative characters. Quantitative character evolution is modelled using Brownian diffusion with character correlation and character variation within populations. Through simulations, we demonstrate that ignoring the population variation (or population "noise") and the correlation among characters leads to biased estimates of divergence times and rate, especially if the correlation and population noise are high. We apply our new method to the analysis of quantitative characters (cranium landmarks) and molecular data from carnivoran mammals. Our results show that time estimates are affected by whether the correlations and population noise are accounted for or ignored in the analysis. The estimates are also affected by the type of data analysed, with analyses of morphological characters only, molecular data only, or a combination of both; showing noticeable differences among the time estimates. Rate variation of morphological characters among the carnivoran species appears to be very high, with Bayesian model selection indicating that the independent-rates model fits the morphological data better than the autocorrelated-rates model. We suggest that using morphological continuous characters, together with molecular data, can bring a new perspective to the study of species evolution. Our new model is implemented in the MCMCtree computer program for Bayesian inference of divergence times.
Figure 2 from: Griebenow ZH, Jones SC, Eaton TD (2017) Seeking quantitative morphological characters for species identification in soldiers of Puerto Rican Heterotermes (Dictyoptera, Blattaria, Termitoidae, Rhinotermitidae). ZooKeys 725: 17-29. https://doi.org/10.3897/zookeys.725.20010
Figure 2 Pronotal metrics: AA'= maximum length of pronotum; BB' = maximum width of pronotum; CC' = depth of anterior pronotal notch; DD' = depth of posterior pronotal notch. Parallels are marked in black.
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Allen Brain Atlas
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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
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