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 8 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 8. Dependence of the coefficient of variation of the spawning start time from the average time of the spawning onset and the coefficient of variation of the end of the spawning from the average time of the end of the spawning. The abscissa axis – days of the year; the ordinate axis – coefficient of variation (blue dot – spawning start time, red dot – spawning end time); lines – second order approximation polynomials.
Figure 7. Fine-scale components RDA 1-3 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 7. Fine-scale components RDA 1-3 of the annual temperature variation. Black line – the original data, colored lines – smoothed data. The abscissa axis – the number of days from 1 July of the previous year to June 31 of the next year.
Figure 3 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 3. Annual course of the temperature (A) and residuals of the trend line (B). The abscissa axis – the number of days from 1 July of the previous year to June 31 of the next year, the ordinate axis – the average temperature for the period 1998–2018 (A). Line indicates the graph of the polynomial of the fourth degree.
Figure 2 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 2. The dynamics of air temperature from 1998 to 2018. The line indicates an approximation of the average annual temperature trend Temp = 8.81 + 0.059 t, where Temp – average annual temperature, t – the order of year: 1 – 1998, 2 – 1999, etc.
Figure 6. Medium-scale components RDA 1-3 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 6. Medium-scale components RDA 1-3 of the annual temperature variation. Black line – the original data, colored lines – smoothed data. The abscissa axis – the number of days from 1 July of the previous year to June 31 of the next year.
Figure 1 in Effects of temperature patterns on the spawining phenology and niche overlap of fish assemblages in the water bodies of the Dnipro River basin
Figure 1. Map of the "Dnipro-Orilskiy»Nature Reserve and spawning locations. I – Nikolayev system of water bodies; II – river Protoch system and Obukhov floodplain; III – the channel of the river Dnipro; IV – water bodies of the Taromske ledge.
Figure 6 in Spatio-temporal variability in the Cladocera assemblage of a subtropical hypersaline lagoon
Figure 6. Cluster analysis (Bray Curtis Similarity) of the stations sampled (stations 11 and 12 in front of the date, followed by the month number and then supporting the year) during the monitoring of the Araruama lagoon aquatic biota, in function of the zooplankton assemblage richness and abundance.
Figure 15 in Albian to Turonian agglutinated foraminiferal assemblages of the Lower Saxony Cretaceous sub-basins - implications for sequence stratigraphy and paleoenvironmental interpretation
Figure 15. Albian, Cenomanian, and Turonian micro-bioevents, their subtypes defined by agglutinated foraminifers, and interpreted bottomwater nutrient regimes in the Lower Saxony Cretaceous as well as in the Subhercynian subbasins. Micro-bioevent subtypes correlate with one or more acmes of specific agglutinated foraminiferal species. Depositional sequences and their stratigraphical relations are from Janetschke et al. (2015: Fig. 6).
Figure 2 from: Ávila MP, Carvalho RN, Casatti L, Simião-Ferreira J, de Morais LF, Teresa FB (2018) Metrics derived from fish assemblages as indicators of environmental degradation in Cerrado streams. Zoologia 35: 1-8. https://doi.org/10.3897/zoologia.35.e12895
Figure 2 Stream sites grouped by their environmental characteristics by using UPGMA (Unweighted Pair Group Method with Arithmetic Mean). Height at y-axis refers to Euclidean distance.
Figure 3 from: Ávila MP, Carvalho RN, Casatti L, Simião-Ferreira J, de Morais LF, Teresa FB (2018) Metrics derived from fish assemblages as indicators of environmental degradation in Cerrado streams. Zoologia 35: 1-8. https://doi.org/10.3897/zoologia.35.e12895
Figure 3 Box-and-Whisker plots of the three sensitive metrics. Rectangles represent the 1st and 3rd quartiles, small squares are medians, bars are maximum and minimum values. Different letters indicate statistically significant differences.
Figure 1 from: Ávila MP, Carvalho RN, Casatti L, Simião-Ferreira J, de Morais LF, Teresa FB (2018) Metrics derived from fish assemblages as indicators of environmental degradation in Cerrado streams. Zoologia 35: 1-8. https://doi.org/10.3897/zoologia.35.e12895
Figure 1 Map of South America highlighting the Goiás State (Brazil) and the sampling sites located in the Santa Tereza sub-basin, Upper Tocantins River basin.
Figure 1 from: Souza CD, Batista VS, Fabré NN (2018) What are the main local drivers determining richness and fishery yields in tropical coastal fish assemblages? Zoologia 35: 1-12. https://doi.org/10.3897/zoologia.35.e12898
Figure 1 Location of the sampled area within the Alagoas coast. Jaraguá fishing harbor and the fishery sites were indicated.
Figure 2 from: Souza CD, Batista VS, Fabré NN (2018) What are the main local drivers determining richness and fishery yields in tropical coastal fish assemblages? Zoologia 35: 1-12. https://doi.org/10.3897/zoologia.35.e12898
Figure 2 Rarefaction curves for the samples caught during dry and rain seasons using the bootstrap richness estimator.
Figures 6-9 from: Souza CD, Batista VS, Fabré NN (2018) What are the main local drivers determining richness and fishery yields in tropical coastal fish assemblages? Zoologia 35: 1-12. https://doi.org/10.3897/zoologia.35.e12898
Figures 6-9 Mean ± sd of the number of fishes, fish total length, species richness, and CPUE by climatic seasons (6); CPUE (mean ± sd) by month (7); precipitation by month (8) and wind strength by month (9).
Figures 3-4 from: Souza CD, Batista VS, Fabré NN (2018) What are the main local drivers determining richness and fishery yields in tropical coastal fish assemblages? Zoologia 35: 1-12. https://doi.org/10.3897/zoologia.35.e12898
Figures 3-4 Whittaker plot of fishes from Alagoas coast sampled during the rainy season (3) and the dry season (4).
Figure 5 from: Souza CD, Batista VS, Fabré NN (2018) What are the main local drivers determining richness and fishery yields in tropical coastal fish assemblages? Zoologia 35: 1-12. https://doi.org/10.3897/zoologia.35.e12898
Figure 5 Diversity profile of the dry and rain seasons on the coast of Alagoas. Alpha = 1 Emphasizes the separation of richness and diversity profile.
Figure 9 from: Nefediev PS, Farzalieva GS, Tuf IH, Nedoev KK, Niyazov ST (2018) Millipede and centipede assemblages on the northern and southern slopes of the lowland Altais, southwestern Siberia, Russia (Diplopoda, Chilopoda). In: Stoev P, Edgecombe GD (Eds) Proceedings of the 17th International Congress of Myriapodology, Krabi, Thailand. ZooKeys 741: 219-254. https://doi.org/10.3897/zookeys.741.21936
Figure 9 RDA ordination biplot of the distribution patterns of millipedes in soil samples on the study slopes. Environmental variables significantly contributing to the prediction are in bold. The whole model is statistically significant (F = 4.73, p = 0.002) and explains 20.3 % of variability of species data, the X-axis explains 16.5 %.
Figure 11 from: Nefediev PS, Farzalieva GS, Tuf IH, Nedoev KK, Niyazov ST (2018) Millipede and centipede assemblages on the northern and southern slopes of the lowland Altais, southwestern Siberia, Russia (Diplopoda, Chilopoda). In: Stoev P, Edgecombe GD (Eds) Proceedings of the 17th International Congress of Myriapodology, Krabi, Thailand. ZooKeys 741: 219-254. https://doi.org/10.3897/zookeys.741.21936
Figure 11 RDA ordination biplot of the distribution patterns of centipedes in soil samples on the study slopes. Environmental variables significantly contributing to the prediction are in bold. The whole model is statistically significant (F = 4.12, p = 0.002) and explains 15.2 % of variability of species data, the X-axis explains 10.3 %.
Figures 2-5 from: Nefediev PS, Farzalieva GS, Tuf IH, Nedoev KK, Niyazov ST (2018) Millipede and centipede assemblages on the northern and southern slopes of the lowland Altais, southwestern Siberia, Russia (Diplopoda, Chilopoda). In: Stoev P, Edgecombe GD (Eds) Proceedings of the 17th International Congress of Myriapodology, Krabi, Thailand. ZooKeys 741: 219-254. https://doi.org/10.3897/zookeys.741.21936
Figures 2-5 Two types of study habitats. 2–3 rocky xeromorphic steppe with bushes on the southern slope 4–5 rocky forested sites on the northern slope (2–3 taken in mid-July 2017, 5 taken at the end of May 2016; all by P.N.).
Figure 6-7 from: Nefediev PS, Farzalieva GS, Tuf IH, Nedoev KK, Niyazov ST (2018) Millipede and centipede assemblages on the northern and southern slopes of the lowland Altais, southwestern Siberia, Russia (Diplopoda, Chilopoda). In: Stoev P, Edgecombe GD (Eds) Proceedings of the 17th International Congress of Myriapodology, Krabi, Thailand. ZooKeys 741: 219-254. https://doi.org/10.3897/zookeys.741.21936
Figure 6-7 Range limits of some millipede species in the study area. 6 Distribution of Leptoiulus tigirek (diamond) 7 Distribution of Sibiriulus latisupremus (triangle). The new localities are shown in red.
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.