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.
2,911
datasets available to search
ShareScore release 0.7.1
Dataset results
2,911 results for “dispersal”
Supplemental appendices: Bursts of rapid diversification, multiple dispersals out of southern Africa, and two origins of dioecy punctuate the evolution of Asparagus
<p>Supplemental datasets for manuscript titled "Bursts of rapid diversification, multiple dispersals out of southern Africa, and two origins of dioecy punctuate the evolution of Asparagus"</p>
Gaussian approximation of dispersion potentials for efficient featurization and machine-learning predictions of metal–organic frameworks
<p>Scripts and data for the publication</p>
Larval dispersal in three coral reef decapod species: influence of larval duration on the metapopulation structure
<p>Database on larval dispersal contains three files in excel format. The name of the files indicates the species and its PLD (pelagic larval duration)</p>
F I G U R E 6 in Dispersal in dendritic networks: Ecological consequences on the spatial distribution of population densities
F I G U R E 6 Euclidean distances moved by Tetrahymena individuals depending on densities in our entire dataset. Across all replicates of all landscapes (patches from different landscapes types highlighted by different symbols; see legend) we find positively densitydependent movement. The solid lines represent fits of the averaged linear mixed model (red: dendritic landscapes; blue: linear landscapes) and the shaded area shows 95% confidence intervals (see Table 4 for model selection results). [Colour figure can be viewed at wileyonlinelibrary.com]
F I G U R E 4 in Dispersal in dendritic networks: Ecological consequences on the spatial distribution of population densities
F I G U R E 4 Comparison of variation in population densities between linear and dendritic networks at day 15 of the experiment. The solid line represents the difference between inter-quartile range (IQR) over median population densities of linear and dendritic landscapes. The distribution (grey) represents the distribution of the differences between IQR over median population densities of 200,000 random re-samplings for our data. As we theoretically expect the dendritic landscapes to be more variable we can perform a one-sided test which gives a probability of p =.047 of our observed difference between IQR to median ratios to be larger than zero. [Colour figure can be viewed at wileyonlinelibrary.com]
F I G U R E 3 in Dispersal in dendritic networks: Ecological consequences on the spatial distribution of population densities
F I G U R E 3 Fit of theoretical expectations to the distribution of Tetrahymena population densities depending on network type (linear versus dendritic networks), network position (central versus inner versus outer nodes) for day 15. Violin plots show the overall distribution of the data, the white point gives the median, and the solid black line the 25% and 75% percentiles, respectively. Given the network structure (Figure 1) and the three replicates per landscape, distributions include N = 18 (9, 3) measurements for outer (inner, central) nodes of dendritic networks and N = 6 (6, 18) measurements for outer (inner, central) nodes of linear landscapes. Horizontal red and blue lines visualise fits of the theoretically expected distribution of population densities to data from the dendritic and linear networks assuming network specific dispersal rates (d) and carrying capacities (K). White squares show fits of the theoretically expected distribution of population densities assuming the same d and K values for both network types. Shaded areas, respectively, error bars, show 95% confidence intervals of the fits. [Colour figure can be viewed at wileyonlinelibrary.com]
F I G U R E 2 in Dispersal in dendritic networks: Ecological consequences on the spatial distribution of population densities
F I G U R E 2 Distribution of Tetrahymena population densities depending on network type (linear versus dendritic networks), network position (central versus inner versus outer nodes) and time (days 0, 8 and 15). Violin plots show the overall distribution of the data, the white point gives the median, and the solid black line the 25% and 75% percentiles, respectively. Given the network structure (Figure 1) and the three replicates per landscape, distributions include N = 18 (9, 3) measurements for outer (inner, central) nodes of dendritic networks and N = 6 (6, 18) measurements for outer (inner, central) nodes of linear landscapes. Horizontal lines visualise back-transformed parameter estimates of the averaged linear mixed effects model and shaded areas show 95% confidence intervals (see Table 2 for model selection results). [Colour figure can be viewed at wileyonlinelibrary.com]
F I G U R E 1 in Dispersal in dendritic networks: Ecological consequences on the spatial distribution of population densities
F I G U R E 1 Median population densities (in thousands of individuals) of Tetrahymena in corresponding dendritic (a) and linear (b) landscapes at the end of the experiment (day 15) and across the three replicate landscapes. In these landscapes, outer nodes are labelled "O," inner and central nodes are labelled "I" and "C", respectively. [Colour figure can be viewed at wileyonlinelibrary.com]
F I G U R E 5 in Dispersal in dendritic networks: Ecological consequences on the spatial distribution of population densities
F I G U R E 5 Euclidean distances moved by Tetrahymena individuals depending on network type (linear versus dendritic networks), network position (central versus inner versus outer nodes) and time (days 0, 8 and 15). Violin plots show the overall distribution of the data, the white point gives the median, and the solid black line the 25% and 75% percentiles, respectively. Given the network structure (Figure 1) and the three replicates per landscape distributions include N = 18 (9, 3) measurements for outer (inner, central) nodes of dendritic networks and N = 6 (6, 18) measurements for outer (inner, central) nodes of linear landscapes. Horizontal lines visualise back-transformed parameter estimates of the averaged linear mixed effects model and shaded areas show 95% confidence intervals (see Table 3 for model selection results). [Colour figure can be viewed at wileyonlinelibrary.com]
Fig. 3 in How far do tadpoles travel in the rainforest? Parent-assisted dispersal in poison frogs
Fig. 3 Boxplot illustrating the difference in distance between the observed tadpole transport distances and the nearest known pool available for each tracked frog and species. Asterisks denote statistically significant differences based on Mann-Whitney-Wilcoxon and Wilcoxon Signed-Rank Tests (p <0.05). (Color figure online)
Fig. 1 in How far do tadpoles travel in the rainforest? Parent-assisted dispersal in poison frogs
Fig. 1 Photographs of the two study species: a Ameerega trivittata and b Dendrobates tinctorius transporting tadpoles while wearing a radio-transmitter. Ameerega trivittata typically transports 15–30 tadpoles while D. tinctorius only transport one or two tadpoles. The numbers and arrows indicate: (1) tadpoles, (2) radio-transmitter, and (3) a silicone waistband for attachment. (Color figure online)
Fig. 2 in How far do tadpoles travel in the rainforest? Parent-assisted dispersal in poison frogs
Fig. 2 Map of the study area showing the movements during the tadpole transport of a seven A. trivittata males and b 11 D. tinctorius males. Blue circles represent confirmed tadpole deposition sites; house symbols represent approximated start location of the tadpole transport; each line corresponds to a transport event and each color represents a different individual. a Blue solid and dashed lines mark creek beds, which provided most deposition sites; dotted area corresponds to the forest edge. The shown trajectories do not represent complete movement patterns because some frogs were first detected already outside their home areas and near the deposition sites. Note the difference in map scales between the two species. (Color figure online)
Replication data for: Evidence for Dispersing 1D Majorana Channels in an Iron-based Superconductor
<p>Replication Data for: Evidence for Dispersing 1D Majorana Channels in an Iron-based Superconductor</p>
Seismic dispersion and attenaution in fluid-saturated carbonate rocks: effect of microstructure and pressure
<p>Dataset for the article "Seismic dispersion and attenaution in fluid-saturated carbonate rocks: effect of microstructure and pressure"<br> by Borgomano J.V.M., Pimienta L.X., Fortin J., Gueguen Y.</p> <p>submitted to Journal of Geophysical Research: Solid Earth.</p> <p>Please refer to the ReadMe file or to borgomano@geologie.ens.fr for more details.</p>
Fig. 5 in Resurrection of the Comoran fish scale gecko Geckolepis humbloti Vaillant, 1887 reveals a disjunct distribution caused by natural overseas dispersal
Fig. 5 Photos of Geckolepis humbloti. a ZSM 80/2010 from the type locality Grand Comoro. Lateral scales were shed in a defensive reaction during capturing. b ZSM 84/2010 at 632 m near Pomoni, Anjouan, the highest recorded locality of any Geckolepis. c ZSM 1699/2008 at Choungui, Mayotte, in a natural hiding place under the bark of a tree. d Habitat of G. humbloti at the dry forest of Saziley, Mayotte
Fig. 4 in Resurrection of the Comoran fish scale gecko Geckolepis humbloti Vaillant, 1887 reveals a disjunct distribution caused by natural overseas dispersal
Fig. 4 The skulls of Geckolepis humbloti (ZSM 81/2006 and ZSM 80/ 2010) in a dorsal, b ventral, and c lateral view. Length of bar = 1 mm. See Supplementary A3 for PDF-embedded interactive 3D models of these skulls
Fig. 1 in Resurrection of the Comoran fish scale gecko Geckolepis humbloti Vaillant, 1887 reveals a disjunct distribution caused by natural overseas dispersal
Fig. 1 Results of the molecular genetic analysis of Geckolepis. The maximum likelihood tree is based on 12S and ND4 sequences. Only closely related outgroups are shown. Support values of 1000 bootstrap repeats are given below nodes. TB Tsingy de Bemaraha, AN Anjouan, GC Grand Comoro, MA Mayotte, Mo Mohéli. All representatives of the taxonomically unresolved Geckolepis maculata complex are named Geckolepis maculata in the tree
Fig. 3 in A dragonfly in the desert: genetic pathways of the widespread Trithemis arteriosa (Odonata: Libellulidae) suggest male-biased dispersal
Fig. 3 Bayesian analysis of the nuclear genetic structure of T. arteriosa populations based on eight microsatellite loci. Each vertical bar represents an individual and is partitioned into one to three coloured segments indicating the individual membership in the three genetic
Fig. 3 in Systematics of Cuscuta chinensis species complex (subgenus Grammica, Convolvulaceae): evidence for long-distance dispersal and one new species
Fig. 3 Phylogenetic relationships among species of the Cuscuta chinensis (C. c.) complex obtained from maximum likelihood (ML) analyses of individual trnL-F (a) and ITS (b) as well as combined datasets (c), all under the HKY + G model of DNA evolution. Asterisks indicate nodes that collapsed in a strict consensus of equally
Fig. 1 a–i in Systematics of Cuscuta chinensis species complex (subgenus Grammica, Convolvulaceae): evidence for long-distance dispersal and one new species
Fig. 1 a–i Morphology of dissected calyx in species of Cuscuta chinensis complex. a,d Cuscuta chinensis var. chinensis. b,e C. chinensis var. applanata. c,f C. alata. g C. potosina. h C. azteca. i C. yucatana. Bars 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.