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.
2,556
datasets available to search
ShareScore release 0.9.0
Dataset results
2,556 results for “assemblages”
Figure 2 in A comparison of the structure of 2 waterbird assemblages during postbreeding movements in the arid zone of Uzbekistan
Figure 2. Relationship between species numbers and numbers of individuals on defined sections of the Amu-Darya (open triangle and dotted regression line; N = 10) and Syr-Darya (filled circle and solid regression line; N = 8) rivers.
Fig. 6 in Foraminiferal Assemblages And Facies Associations In The Upper Jurassic Carbonates From Ardeu Unit (Metaliferi Mountains, Romania)
Fig. 6 Main facies associations of the carbonates from the Ardeu Unit. a Bio-oncoidal grainstone (F1) (Sample 48). Notice the thin rims of isopachus fibrous early cement bordering most of the bioclasts. b Bio-intraclastic grainsote/rudstone with Parurgonina caelinensis (P), Everticyclammina praekelleri (E) and Bacinella-type oncoids (B) (F1) (Sample 64). c Oncoidal wackestone/floatstone with numerous Bacinella-type oncoids, Thaumatoporella parvovesiculifera bridges and scarce foraminifera (F2) (Sample 5). d Bio-oncoidal floatstone with Rivularia-type cyanobacteria oncoids and Parurgonina caelinensis (F2) (Sample 23). Most of the oncoids are encrusted by Lithocodium aggregatum. e Coral-microbial-microencruster boundstone (F3) (Sample 183). f Brecciated bio-intraclastic grainstone with reef fragments (F4) (Sample 194). g Intraclastic rudstone (F5) (Sample 161). The intraclasts characterize different facies zones. h Intra-extra-bioclastic packstone/rudstone with different grain sorting and various intraclasts (F5) (Sample 160).
Fig. 2 Upper Jurassic foraminifers from the Ardeu Unit. a-h in Foraminiferal Assemblages And Facies Associations In The Upper Jurassic Carbonates From Ardeu Unit (Metaliferi Mountains, Romania)
Fig. 2 Upper Jurassic foraminifers from the Ardeu Unit. a-h Labyrinthina mirabilis Weynschenk (a - Sample 153, b - Sample 27, c - Sample 64, d - Sample 165, e - Sample 33, f - Sample 21, g - Sample 159, h - Sample 55). i-p Parurgonina caelinensis Cuvillier, Foury & Pignatti Morano (i - Sample 65, j - Sample 36, k - Sample 129, l - Sample 30, m - Sample 23, n - Sample 65, o - Sample 38, p - Sample 64).
Fig. 1 in Foraminiferal Assemblages And Facies Associations In The Upper Jurassic Carbonates From Ardeu Unit (Metaliferi Mountains, Romania)
Fig. 1 Geological map of the BalȘa-Ardeu-Băcâia region (modified after Mantea & Tomescu, 1986) 1 Mesozoic ophiolites (CăpâlnaȘ-Techereu Nappe); 2 Oxfordian limestones (Ardeu Unit); 3 Kimmeridgian-Tithonian carbonates (Ardeu Unit); 4 Barremian-Aptian limestones (Ardeu Unit); 5 Aptian conglomerates and sandstones (CăpâlnaȘ-Techereu Nappe); 6 Albian breccia and sandstones (CăpâlnaȘ-Techereu Nappe); 7 Coniacian-Santonian siltites and sandstones; 8 Santonian- Campanian marls; 9 Santonian-Maastrichtian flysch deposits; 10?Maastrichtian-Paleogene continental deposits; 11 Badenian limestones; 12 Quaternary deposits; 13 Faults; 14 Nappe; 15 Location of the studied sections.
Fig. 3 in A community analysis approach to parasite transmission in multi-host systems: Assemblages of small mammal prey and Echinococcus multilocularis in an urban area in North America
Fig. 3. Plot of the Canonical Correlation Analysis on the principal coordinates (CAP) of small mammal assemblages in five parks and natural areas in urban Calgary, AB, Canada, 2012–2013, using the cluster as a grouping factor. The cluster 1 is on the lower right corner, cluster 2 is on the lower left corner, and cluster 3 is on the center to the top of the plot. The 45% similarity contour line is drawn based on the dendrogram in Fig. 2a. a) Vectors were overlaid showing the correlation with the abundances of each species to each cluster. The red vector shows the correlation with the abundance of all the susceptible species combined. b) Vectors were overlaid showing the correlation with the proportion of each species to each cluster. The red vector shows the correlation with the proportion of all the susceptible species. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Text-fig. 1. Taphonomic and pathological phenomena of cave bear bones from Late Pleistocene deposits from Vařekova chodba in Za Hájovnou Cave (Moravia, the Czech Republic); a – fragment of vertebra with bite marks; b – fragment of right humerus, proximal part with bite marks; c – thoracic vertebra with pathological rib facet; d–e – fused left astragalus with left calcaneus (d: medial view, e: dorsal view). in Basic Population And Taphonomic Analysis Of Bear Assemblages From Za Hájovnou Cave (Moravia, The Czech Republic): A Fossil Record From 1987-2007
Text-fig. 1. Taphonomic and pathological phenomena of cave bear bones from Late Pleistocene deposits from Vařekova chodba in Za Hájovnou Cave (Moravia, the Czech Republic); a – fragment of vertebra with bite marks; b – fragment of right humerus, proximal part with bite marks; c – thoracic vertebra with pathological rib facet; d–e – fused left astragalus with left calcaneus (d: medial view, e: dorsal view).
Fig. 2 in Ground beetle assemblages (Coleoptera, Carabidae) in the third year of regeneration after a hurricane in the Puszcza Piska pine forests
Fig. 2. Log-fitted abundance curves for carabid beetle species abundance in stands destroyed by the hurricane (P) and control stands (M) in age classes: I and V.
Fig. 3 in Assemblages of beetles (Coleoptera) in a peatbog and surrounding pine forest
Fig. 3. PCA biplot for the sites and for the species of beetles. Eigenvalues of the first two axes were 118.153 and 19.158, respectively, explaining 86.1% and 13.9% of the variation in the species dataset. Abbreviations of species of beetles are listed in Table 2.
Figure 5 in Spider assemblages and dynamics on a seasonal island in the Pripyat River, Belarus
Figure 5. Activity density dynamics of dominants Oedothorax retusus and Pardosa prativaga in the period of 30 April to 30 May, 2006 and 2007 data combined with number of samples of the 2 study years averaged. The mean number of specimens (□) with arms of standard deviation values.
Figure 1 in Structure of the macrozoobenthos assemblages in the central part of the northwestern Black Sea shelf (Zernov's Phyllophora field) at the beginning of the 21 century
Figure 1. Map (after Revkov et al. 2018 with additions) of the benthic surveys performed in 2010– 2013 aboard R/V "Professor Vodyanitsky" in the Zernov's Phyllophora Field water area
Figure 2 in Life in the extreme environment: Structure and species richness of bird assemblages on Yuzhny Island of Novaya Zemlya, Russia
Figure 2. Structure of bird assemblages on Yuzhny Island of Novaya Zemlya. (A) Cluster analysis of bird assemblages. Ward's classification approach was applied to a Euclidean distance matrix, which was calculated based on bird species abundances (categorical estimations by using a five-point logarithmic scale). (B)-(C) Histograms of the distribution of bird ecological groups (number of species in each group) over the range of habitats (B) and over relative occurrence of each species through habitats (C).
Figure 5 in Postmucilage status of teleost fish assemblages in the Sea of Marmara
Figure 5. Spatial variation of target (green bar), bycatch (blue bar) and total biomass (numbers above the bars) of teleost fish assemblages in the Sea of Marmara, Türkiye.
Figure 1 in Postmucilage status of teleost fish assemblages in the Sea of Marmara
Figure 1. Map of the study area with stations and sampling points (red marks) in the Sea of Marmara, Türkiye. Dashed black lines represent the limit of the stations (S1: Erdek Gulf, S2: Marmara Islands, S3: Bandırma Gulf, S4: Gemlik Gulf, S5: İzmit Gulf, S6: Prens Islands, S7: Avcılar, S8: Silivri, S9: Tekirdağ, S10: Şarköy).
Figure 6 in Phytoplankton assemblages under hydrochemical conditions of the Volga River Delta
Figure 6. Distribution of groups identified as a result of cluster analysis of abiotic factors (temperature, silica, nitrates, mineral phosphorus). Blue – Ch1, Green – Ch2, Cian – Ch3, Red – Ch4.
Figure 4 in Phytoplankton assemblages under hydrochemical conditions of the Volga River Delta
Figure 4. Similarity dendrogram demonstrating environmental conditions identified based on a comparison of abiotic factors of the aquatic environment (temperature, °C; silica, μM, mineral phosphorus, μM; nitrate nitrogen, μM).
Fig. 1. a in Spatial and seasonal patterns in fish assemblage in Córrego Rico, upper Paraná River basin
Fig. 1. a) Map of SouthAmerica with Brazil location. b) Córrego Rico basin in São Paulo State. c) Córrego Rico basin (Modified from a figure by L. A. Amaral - unpublished) with the samples stretches.
Fig. 2 in Spatial and seasonal patterns in fish assemblage in Córrego Rico, upper Paraná River basin
Fig. 2. Non-metric multidimensional scaling (NMDS) ordination of environmental variables data from Córrego Rico stretches. a) All samples (stretches - S1 to S7; month and year of sample - mmyy): b) Samples divided in rainy (R) and dry (D) seasons (stretches - S1 to S7).
Table 3. Principal component loading values for seven habitat variables across 13 in Impacts of Wastewater Effluent on Temperate Stream Fish Assemblage Structure
<p>Table 3. Principal component loading values for seven habitat variables across 13 sites.</p><table><tbody><tr><th>Variable</th><th>PC1</th><th>PC2</th><th>PC3</th><th>PC4</th><th>PC5</th><th>PC6</th><th>PC7</th></tr></tbody><tbody><tr><th>Mean depth</th><td>0.48071</td><td>0.28063</td><td>0.17675</td><td>0.44277</td><td>0.31253</td><td>0.60423</td><td>0.01098</td></tr><tr><th>Max depth</th><td>0.52734</td><td>0.2317</td><td>0.01965</td><td>0.21237</td><td>0.15811</td><td><i>–</i> 0.7713</td><td>0.05367</td></tr><tr><th>Discharge</th><td>0.1488</td><td>0.53788</td><td><i>–</i> 0.4311</td><td>0.37747</td><td><i>–</i> 0.599</td><td>0.02831</td><td><i>–</i> 0.0247</td></tr><tr><th>% gravel</th><td>0.52703</td><td><i>–</i> 0.0162</td><td><i>–</i> 0.1975</td><td><i>–</i> 0.5051</td><td><i>–</i> 0.3351</td><td>0.17973</td><td>0.53227</td></tr><tr><th>% pebble</th><td><i>–</i> 0.0551</td><td><i>–</i> 0.5723</td><td><i>–</i> 0.4095</td><td>0.52749</td><td>0.10692</td><td><i>–</i> 0.0208</td><td>0.46008</td></tr><tr><th>% cobble</th><td><i>–</i> 0.292</td><td>0.16769</td><td>0.66603</td><td>0.16685</td><td><i>–</i> 0.1803</td><td><i>–</i> 0.0806</td><td>0.61335</td></tr><tr><th>% boulder</th><td><i>–</i> 0.3204</td><td>0.47152</td><td><i>–</i> 0.3636</td><td><i>–</i> 0.2349</td><td>0.60197</td><td><i>–</i> 0.0034</td><td>0.35384</td></tr></tbody></table>
Table 1 in Impacts of Wastewater Effluent on Temperate Stream Fish Assemblage Structure
<p>Table 1. PERMANOVA table of results indicating a significant difference in fish assemblage structure between East and West Fork sites (<i>Pseudo-F</i> ¼ 10.481, df ¼ 1, <i>P</i> ¼ 0.0001) after accounting for the effect of the site distance covariate, which does influence fish assemblage structure (Pseudo- <i>F</i> ¼ 7.813, df ¼ 1, <i>P</i> ¼ 0.00015). Stream distance data (between sites) were square root transformed prior to analysis to ensure that distance variation of East and West Fork sites were more comparable.</p><table><tbody><tr><th><b>Source</b></th><th><b>df</b></th><th><b>SS</b></th><th><b>MS</b></th><th><b>Pseudo- <i>F</i></b></th><th><b><i>P</i> (perm)</b></th><th><b>Unique perms</b></th></tr></tbody><tbody><tr><th>Distance (covariate)</th><td>1</td><td>6650.8</td><td>6650.8</td><td>7.813</td><td>0.0001</td><td>9959</td></tr><tr><th>Site (East vs. West)</th><td>1</td><td>8921.9</td><td>8921.9</td><td>10.481</td><td>0.0001</td><td>9955</td></tr><tr><th>Res</th><td>23</td><td>19579</td><td>851.26</td><td></td><td></td><td></td></tr><tr><th>Total</th><td>25</td><td>35152</td><td></td><td></td><td></td><td></td></tr></tbody></table>
Table 4. Principal component loading values for the four substrate categories measured across all 26 in Impacts of Wastewater Effluent on Temperate Stream Fish Assemblage Structure
<p>Table 4. Principal component loading values for the four substrate categories measured across all 26 sites.</p><table><tbody><tr><th>Variables</th><th>PC1</th><th>PC2</th><th>PC3</th><th>PC4</th></tr></tbody><tbody><tr><th>% gravel</th><td>0.63444</td><td>0.50857</td><td>0.10028</td><td>0.5734</td></tr><tr><th>% pebble</th><td>0.20598</td><td><i>–</i> 0.8296</td><td><i>–</i> 0.0496</td><td>0.51658</td></tr><tr><th>% cobble</th><td><i>–</i> 0.6728</td><td>0.13769</td><td>0.49052</td><td>0.53647</td></tr><tr><th>% boulder</th><td><i>–</i> 0.3201</td><td>0.18476</td><td><i>–</i> 0.8642</td><td>0.3414</td></tr></tbody></table>
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.