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.
309
datasets available to search
ShareScore release 0.7.1
Dataset results
309 results for “phenotypic variation”
Habitat range and phenotypic variation in twelve salt marsh plants on Sapelo Island, Georgia, USA.
We measured traits of twelve salt marsh plant species at sites around Sapelo Island GA in August of 1999. Plant species represent six families - Asteraceae: Aster tenuifolius L., Borrichia frutescens L., Iva frutescens L.; Bataceae: Batis maritima L.; Chenopodiaceae: Salicornia bigelovii Torrey, Salicornia virginica L.; Juncaceae: Juncus roemerianus Scheele; Plumbaginaceae: Limonium carolinianum (Walter) Britton; Poaceae: Distichlis spicata (L.) Greene, Spartina alterniflora Loisel., Spartina patens (Aiton) Muhl., Sporobolus virginicus (L.) Kunth; all nomenclature follows Radford et al. (1968). Soil cores were taken adjacent to each plant to measure soil water content, porewater salinity, and organic content.
Phenotypic variation and quantitative trait loci for resistance to southern anthracnose and clover rot in red clover
<p>Red clover (<em>Trifolium pratense</em> L.) is an important forage legume of temperate regions, particularly valued for its high yield potential and its high forage quality. Despite substantial breeding progress during the last decades, continuous improvement of cultivars is crucial to ensure yield stability in view of newly emerging diseases or changing climatic conditions. The high amount of genetic diversity present in red clover ecotypes, landraces and cultivars provides an invaluable, but often unexploited resource for the improvement of key traits such as yield, quality, and resistance to biotic and abiotic stresses.</p> <p>A collection of 397 red clover accessions was genotyped using a pooled genotyping-by-sequencing approach with 200 plants per accession. Resistance to the two most pertinent diseases in red clover production, southern anthracnose caused by <em>Colletotrichum trifolii</em>, and clover rot caused by <em>Sclerotinia trifoliorum, </em>was assessed using spray inoculation. The mean survival rate for southern anthracnose was 22.9% and the mean resistance index for clover rot was 34.0%. Genome-wide association analysis revealed several loci significantly associated with resistance to southern anthracnose and clover rot. Most of these loci are in coding regions. One quantitative trait locus (QTL) on chromosome 1 explained 16.8% of the variation in resistance to southern anthracnose. For clover rot resistance we found eight QTL, explaining together 80.2% of the total phenotypic variation. The SNPs associated with these QTL provide, once validated, a promising resource for marker-assisted selection in existing breeding programs, facilitating the development of novel cultivars with increased resistance against two devastating fungal diseases of red clover.</p>
Phenotypic diversity of root architecture and genotypic variation in durum wheat under salt stress
<p>Supplementary data consists of Principal Components values for traits detected under salt and control conditions (S1); Markers' locations onto the durum wheat reference genome associated with QTL (S2); Markers associated with genes from NCBI database (S4); PCR results and alleles distribrution</p>
Phenotypic trait variation of Herminium monorchis in the Qinghai-Tibetan Plateau with grazing intensity and climatic conditions
This data set contains raw data supporting the research entitled “Livestock grazing outweighs climate in driving trait variation of a widespread alpine plant” (currently under peer review), which documents how phenotypic traits of a widespread herbaceous plant in the Qinghai-Tibetan Plateau, Herminium monorchis, vary with grazing intensity and environmental conditions.
Phenotypic plasticity in response to fine-grained environmental variation in predation.
1. In nature, organisms experience environmental variability at coarse-grained (inter-generational) and fine-grained (intra-generational) scales and a common response to environmental variation is phenotypic plasticity. The emphasis of most empirical work on plasticity has been on examining coarse-grained variation with the goal of understanding the costs and benefits of plastic responses in response to a particular environment. 2. In this study, we investigated the effects of fine-grained variation in predation on the inducible defences of larval wood frogs (Rana sylvatica) by widely altering the density and feeding schedule of caged predators (Dytiscusspp.) while holding average predation constant. 3. We found that predator cues induced change in tadpole behaviour, morphology, and mass. Surprisingly, however, temporal variation in predation did not cause the tadpoles to alter their activity (compared to a constant predation treatment) or mass. Temporal variation in predation did alter tadpole tail depth, but only when experiencing our most extreme variation treatment in which the predators were fed once every 8 days. Under these conditions, the predator-induced tadpole tail was less extreme compared to environments containing constant predation. 4. While a number of previous studies have examined behavioural responses of prey to temporal variation in predation risk without holding average predation constant, this appears to be the first test of temporal variation per se. As in previous studies of organism responses to temporal variation in resources, our results suggest that fine-grained environmental variability can affect the expression of phenotypically plastic traits, but our tadpoles appear to be generally unresponsive to this finegrained variation for many of their traits.
Fig. 6 in Cranial phenotypic variation in Meriones crassus and M. libycus (Rodentia, Gerbillinae), and a morphological divergence in M. crassus from the Iranian Plateau and Mesopotamia (Western Zagros Mountains)
Fig. 6. Scatter plot of PCA results on shape variables of the (A) ventral, (B) dorsal and (C) lateral sides of Meriones crassus Sundevall, 1842 specimens. Legends: ○ = Iranian Plateau, ● = Western Zagros, * = Kuwait, Δ = Arabian, ▲ = Jeddah, □ = Jordan/NW Arabia, ■ = African. Deformation grids (two times magnified) along the first principal components, representing shape differences between configurations corresponding to minimal and maximal scores, are shown to the right of each plot. For the numbering of landmarks, see Fig. 2.
Fig. 4 in Cranial phenotypic variation in Meriones crassus and M. libycus (Rodentia, Gerbillinae), and a morphological divergence in M. crassus from the Iranian Plateau and Mesopotamia (Western Zagros Mountains)
Fig. 4. Scatter plot of the CVA results of the (A) ventral and (B) dorsal shape data of Meriones crassus Sundevall, 1842 (two groups) and M. libycus Lichtenstein, 1823. Legends: ○ = M. crassus (other than Western Zagros), ● = M. crassus of Western Zagros, □ = M. libycus. The grids below show deformation along the arrows, when moving from the M. crassus group mean shape to the Western Zagros group mean shape (A1 and B1), and from the M. libycus mean shape to the mean shape of the Western Zagros (A2 and B2) (shape differences magnified three times for better visualization). For the numbering of landmarks, see Fig. 2.
Fig. 3 in Cranial phenotypic variation in Meriones crassus and M. libycus (Rodentia, Gerbillinae), and a morphological divergence in M. crassus from the Iranian Plateau and Mesopotamia (Western Zagros Mountains)
Fig. 3. Scatter plot of RW1 versus RW2 of the (A) ventral and (B) dorsal cranium of Meriones crassus Sundevall, 1842 and M. libycus Lichtenstein, 1823. Legends: ○ = M. crassus (other than Western Zagros), ● = M. crassus of Western Zagros, □ = M. libycus. Below: thin-plate spline deformation grids visualize shape variation as expressed by the first two RWs axes (grids represent shape difference between configurations corresponding to lowest and highest RW-values). For the numbering of landmarks, see Fig. 2.
Fig. 7 in Cranial phenotypic variation in Meriones crassus and M. libycus (Rodentia, Gerbillinae), and a morphological divergence in M. crassus from the Iranian Plateau and Mesopotamia (Western Zagros Mountains)
Fig. 7. CVA scatter plot (axes 1 and 2) on shape variables of the (A) ventral, (B) dorsal and (C) lateral side of the Meriones crassus groups (Jeddah group not included). Legends: ○ = Iranian plateau, ● = Western Zagros, Δ = Arabian and ■ = African. Grids show deformation (3 x magnified) when following the trajectory within the morphospace along the arrows and between the groups' consensus (from African to Western Zagros – A1, B1 and C1; and from Iranian plateau to Western Zagros – A2, B2 and C2). For the numbering of landmarks, see Fig. 2.
Fig. 1 in Cranial phenotypic variation in Meriones crassus and M. libycus (Rodentia, Gerbillinae), and a morphological divergence in M. crassus from the Iranian Plateau and Mesopotamia (Western Zagros Mountains)
Fig. 1. Map showing the sampling localities of Meriones crassus Sundevall, 1842 (circles) and M. libycus Lichtenstein, 1823 (squares) and groups of sampling localities indicated by ellipses (see more detail about the grouping in Material and Methods). The dark closed symbols are the sampling localities of the type specimens (synonyms of Meriones crassus and M. libycus, see Table 1). The ellipses (from left to right) show the following groups: African, Jeddah, Arabian, Western Zagros and Iranian Plateau.
FIGURE 4 in Fungia fungites (Linnaeus, 1758) (Scleractinia, Fungiidae) is a species complex that conceals large phenotypic variation and a previously unrecognized genus
FIGURE 4 Maximum likelihood (ML) tree based on ITS sequences. Numbers on main branches show percentages of bootstrap values (>50%) in neighbor-joining (NJ) and ML.
FIGURE 1 in Fungia fungites (Linnaeus, 1758) (Scleractinia, Fungiidae) is a species complex that conceals large phenotypic variation and a previously unrecognized genus
FIGURE 1 Map of the sampling sites. Downloaded from Brill.com 12/12/2023 03:06:27PM via Open Access. This is an open access article distributed under the terms of the CC-BY 4.0 License. https://creativecommons.org/licenses/by/4.0/
FIGURE 7 in Fungia fungites (Linnaeus, 1758) (Scleractinia, Fungiidae) is a species complex that conceals large phenotypic variation and a previously unrecognized genus
FIGURE 7 Specimens in Clade A (Fungia fungites). Scale bars: 1 cm for white bar, 1 mm for black bar. A. Living specimen of immature type (MUFS C307). B. Septal dentation (MUFS C307). C. Costal spine (MUFS C307). D. Living specimen of attached morph (MUFS C309). E. Septal dentation (MUFS C309). F. Costal spine (MUFS C309). G. Living specimen of unattached morph (MUFS C324). H. Septal dentation (MUFS C324). I. Costal spine (MUFS C324).
FIGURE 10 in Fungia fungites (Linnaeus, 1758) (Scleractinia, Fungiidae) is a species complex that conceals large phenotypic variation and a previously unrecognized genus
FIGURE 10 Neotype of Fungia fungites (RMNH16235). Scale bars: 1cm. A. Upper side. B. Basal side. C. Enlarged view Downloaded from Brill.com 12/12/2023 03:06:27PM of septa. D. Enlarged view of viacostal Openspines Access.. This is an open access article distributed under the terms of the CC-BY 4.0 License. https://creativecommons.org/licenses/by/4.0/
FIGURE 5 in Fungia fungites (Linnaeus, 1758) (Scleractinia, Fungiidae) is a species complex that conceals large phenotypic variation and a previously unrecognized genus
FIGURE 5 Box plot of density of septal dentation and costal spine between clades A (Fungia fungites) and B (Fungiidae sp.). The lower and upper limits of the rectangular boxes indicate the 25 to 75% range, and the horizontal line within the boxes is the median (50%).
FIGURE 6 in Fungia fungites (Linnaeus, 1758) (Scleractinia, Fungiidae) is a species complex that conceals large phenotypic variation and a previously unrecognized genus
FIGURE 6 Scatter plot of numbers of septa versus corallum diameter between clades A (Fungia fungites) and B (Fungiidae sp.). Plots for F. fungites are shown by circle whereas Fungiidae sp. are shown by triangle. Blank plots mean attached specimens and plots for solid mean unattached specimens.
FIGURE 8 in Fungia fungites (Linnaeus, 1758) (Scleractinia, Fungiidae) is a species complex that conceals large phenotypic variation and a previously unrecognized genus
FIGURE 8 Specimens in Clade B (Fungiidae sp.). Scale bars: 1 cm for white bar, 1 mm for black bar. A. Living specimen of immature type (MUFS C335). B. Septal dentation (MUFS C335). C. Costal spine (MUFS C335). D. Corallites of attached morph (MUFS C188). E. Septal dentation (MUFS C188). F. Costal spine (MUFS C188). G. Living specimen of unattached morph (MUFS C338). H. Septal dentation (MUFS C338) I. Costal spine (MUFS C338).
FIGURE 2 in Fungia fungites (Linnaeus, 1758) (Scleractinia, Fungiidae) is a species complex that conceals large phenotypic variation and a previously unrecognized genus
FIGURE 2 Schematic illustration of Fungia fungites. A. Cross section in F. fungites. B. Side view of septum. Abbreviations and symbols: CD, Corallum diameter; CoC, Center of corallum; CS, Costal spine; M, Mouth; ST, Septal tooth; TSE, Top of septal edge; a, density of septal dentation; b, density of costal spine.
FIGURE 9 in Fungia fungites (Linnaeus, 1758) (Scleractinia, Fungiidae) is a species complex that conceals large phenotypic variation and a previously unrecognized genus
FIGURE 9 Micromorphology of septal side using scanning electron microscopy. Scale bars: 0.5 cm. A. Immature type in Clade A (MUFS C307). B. Attached morph in Clade A (MUFS C309). C. Unattached morph in Clade A (MUFS C325). D. Immature type in Clade B (MUFS C166). E. Attached morph in Clade B (MUFS C188). C. Unattached morph in Clade B (MUFS C338).
FIGURE 3 in Fungia fungites (Linnaeus, 1758) (Scleractinia, Fungiidae) is a species complex that conceals large phenotypic variation and a previously unrecognized genus
FIGURE 3 Maximum likelihood (ML) tree based on COI sequences. Numbers on main branches show percentages of bootstrap values (>50%) in neighbor-joining (NJ) and ML.
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.