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.
1,549
datasets available to search
ShareScore release 0.7.1
Dataset results
1,549 results for “invertebrate”
Figure 1 from: Knight L, Brancelj A, Hänfling B, Cheney C (2015) The groundwater invertebrate fauna of the Channel Islands. Subterranean Biology 15: 69-94. https://doi.org/10.3897/subtbiol.15.4792
Figure 1 - The location of the Channel Islands in the English Channel (map from Robins et al. 2012).
Figure 5 from: Simões MH, Souza-Silva M, Ferreira RL (2015) Cave physical attributes influencing the structure of terrestrial invertebrate communities in Neotropics. Subterranean Biology 16: 103-121. https://doi.org/10.3897/subtbiol.16.5470
Figure 5 - Non-metric multidimensional scaling (Jaccard index) using presence and absence of species sampled in 55 limestone caves of the Brazilian Savannah. The figure shows that the cave, despite dry most of the year, is subject to seasonal flooding (Deus Me Livre cave), and then was more similar to caves with streams.
Figure 4 from: Simões MH, Souza-Silva M, Ferreira RL (2015) Cave physical attributes influencing the structure of terrestrial invertebrate communities in Neotropics. Subterranean Biology 16: 103-121. https://doi.org/10.3897/subtbiol.16.5470
Figure 4 - Correlation between the richness of troglomorphic species and linear development and water body presence/absence. The barr represents the average and the trace the standard deviation. Different letters indicate significant differences in average richness.
Figure 3 from: Simões MH, Souza-Silva M, Ferreira RL (2015) Cave physical attributes influencing the structure of terrestrial invertebrate communities in Neotropics. Subterranean Biology 16: 103-121. https://doi.org/10.3897/subtbiol.16.5470
Figure 3 - Correlation between total richness and width of entrances, linear development and water body presence/absence. The barr represents the average and the trace the standard deviation. Different letters indicate significant differences in average richness.
Figure 1 from: Simões MH, Souza-Silva M, Ferreira RL (2015) Cave physical attributes influencing the structure of terrestrial invertebrate communities in Neotropics. Subterranean Biology 16: 103-121. https://doi.org/10.3897/subtbiol.16.5470
Figure 1 - Cave distribution at Minas Gerais state, Brazil (black triangle), where terrestrial invertebrates were sampled.
Figure 1 from: Souza-Silva M, Ferreira RL (2015) Cave invertebrates in Espírito Santo state, Brazil: a primary analysis of endemism, threats and conservation priorities. Subterranean Biology 16: 79-102. https://doi.org/10.3897/subtbiol.16.5227
Figure 1 - Distribution of 15 caves in the Atlantic Forest in the state of Espírito Santo, with invertebrate fauna inventoried in this study. Source: SOS Mata Atlântica (2011).
Figure 8 from: Souza-Silva M, Ferreira RL (2015) Cave invertebrates in Espírito Santo state, Brazil: a primary analysis of endemism, threats and conservation priorities. Subterranean Biology 16: 79-102. https://doi.org/10.3897/subtbiol.16.5227
Figure 8 - Human alterations in caves of Espírito Santo, Brazil. A religious use in granite cave in Venda Nova dos Imigrantes B transformation of granitic cave into a church in Itaimbé-Itaguassu C deforestation surrounding cave in Ecoporanga, D drainage exploitation in granite cave near Pedro Canário E use of cave as goat corral F road construction destroying cave chambers in Vargem Alta G and I Limoeiro cave entrance with religious and tourist use in Conceição de Castelo H using limestone cave as a timber-yard in Vargem Alta.
Figure 7 from: Souza-Silva M, Ferreira RL (2015) Cave invertebrates in Espírito Santo state, Brazil: a primary analysis of endemism, threats and conservation priorities. Subterranean Biology 16: 79-102. https://doi.org/10.3897/subtbiol.16.5227
Figure 7 - Almost significant differences between the diversity and total and relative richness of invertebrates in caves that develop in carbonate rocks and magma in the state of Espírito Santo. Average, ± SE, ± SD.
Figure 3 from: Souza-Silva M, Ferreira RL (2015) Cave invertebrates in Espírito Santo state, Brazil: a primary analysis of endemism, threats and conservation priorities. Subterranean Biology 16: 79-102. https://doi.org/10.3897/subtbiol.16.5227
Figure 3 - Some of the troglomorphic invertebrates sampled in 15 caves in Atlantic forest at Espírito Santo state, Brazil. A Escadabiidae, B Trachelipodidae, C Pseudonannolene sp., D Cryptodesmidae, E Trichopolidesmydae, F Zygentoma, G Trichorhina sp.
Figure 2 from: Souza-Silva M, Ferreira RL (2015) Cave invertebrates in Espírito Santo state, Brazil: a primary analysis of endemism, threats and conservation priorities. Subterranean Biology 16: 79-102. https://doi.org/10.3897/subtbiol.16.5227
Figure 2 - Composition and richness of invertebrate taxa collected in 15 caves in the state of Espírito Santo, Brazil.
Figure 6 from: Souza-Silva M, Ferreira RL (2015) Cave invertebrates in Espírito Santo state, Brazil: a primary analysis of endemism, threats and conservation priorities. Subterranean Biology 16: 79-102. https://doi.org/10.3897/subtbiol.16.5227
Figure 6 - A Significant relationship of the increased richness of collected invertebrates with the increase in size of caves in limestone and granitic rocks and B no significant relationship without limestone caves in the state of Espírito Santo.
Figure 9 from: Souza-Silva M, Ferreira RL (2015) Cave invertebrates in Espírito Santo state, Brazil: a primary analysis of endemism, threats and conservation priorities. Subterranean Biology 16: 79-102. https://doi.org/10.3897/subtbiol.16.5227
Figure 9 - A Distribution of cave biological relevance B cave impacts category and C cave fauna vulnerability in the state of Espírito Santo. Gray shading on maps represents remnants of the Atlantic Forest.
Figure 5 from: Souza-Silva M, Ferreira RL (2015) Cave invertebrates in Espírito Santo state, Brazil: a primary analysis of endemism, threats and conservation priorities. Subterranean Biology 16: 79-102. https://doi.org/10.3897/subtbiol.16.5227
Figure 5 - A Distribution of caves, B relative richness and C total richness of the 15 caves of the state of Espírito Santo, Brazil.
Figure 10 from: Glanville K, Schulz C, Tomlinson M, Butler D (2016) Biodiversity and biogeography of groundwater invertebrates in Queensland, Australia. Subterranean Biology 17: 55-76. https://doi.org/10.3897/subtbiol.17.7542
Figure 10 - Scatterplots showing the relationship between stygofauna taxon richness per sample and different physico-chemical variables; In Figure 10 the scatterplots presented are based on available data in the Queensland Subterranean Aquatic Fauna database where: depth to groundwater is available for 113 samples in meters below ground level (mbgl); electrical conductivity is available for 137 samples in microSiemens per centimetre (μS/cm); pH is available for 130 samples; and temperature is available for 77 samples in degrees Celsius (°C).
Figure 5 from: Glanville K, Schulz C, Tomlinson M, Butler D (2016) Biodiversity and biogeography of groundwater invertebrates in Queensland, Australia. Subterranean Biology 17: 55-76. https://doi.org/10.3897/subtbiol.17.7542
Figure 5 - Biogeography of described families in Queensland, Australia; In Figure 5 the total number of subregions a described family has been recorded inhabiting is indicated by numerical figures located to the right of the bars and the total number of samples is indicated by numerical figures located along the y-axis.
Figure 4 from: Glanville K, Schulz C, Tomlinson M, Butler D (2016) Biodiversity and biogeography of groundwater invertebrates in Queensland, Australia. Subterranean Biology 17: 55-76. https://doi.org/10.3897/subtbiol.17.7542
Figure 4 - Stygofauna discovery rates by lithology in Queensland, Australia; In Figure 4 the discovery rate of stygofauna is indicated by numerical figures located above the columns, the total number of samples is indicated by numerical figures located along the x-axis, and the average stygofauna discovery rate (28%) is plotted as a grey, dashed line.
Figure 8 from: Glanville K, Schulz C, Tomlinson M, Butler D (2016) Biodiversity and biogeography of groundwater invertebrates in Queensland, Australia. Subterranean Biology 17: 55-76. https://doi.org/10.3897/subtbiol.17.7542
Figure 8 - Distribution of described families across different lithologies in Queensland, Australia; In Figure 8 the total number of lithologies is indicated by numerical figures located to the right of the bars and the total number of samples is indicated by numerical figures located along the y-axis.
Figure 7 from: Glanville K, Schulz C, Tomlinson M, Butler D (2016) Biodiversity and biogeography of groundwater invertebrates in Queensland, Australia. Subterranean Biology 17: 55-76. https://doi.org/10.3897/subtbiol.17.7542
Figure 7 - Diversity of described families across different lithologies in Queensland, Australia; In Figure 7 the total number of described families is indicated by numerical figures located above the columns and the total number of samples is indicated by numerical figures located along the x-axis.
Figure 6 from: Glanville K, Schulz C, Tomlinson M, Butler D (2016) Biodiversity and biogeography of groundwater invertebrates in Queensland, Australia. Subterranean Biology 17: 55-76. https://doi.org/10.3897/subtbiol.17.7542
Figure 6 - Diversity of described families in different IBRA subregions in Queensland, Australia; In Figure 6 the total number of described families is indicated by numerical figures located to the right of the bars and the total number of samples is indicated by numerical figures located along the y-axis.
Figure 9 from: Glanville K, Schulz C, Tomlinson M, Butler D (2016) Biodiversity and biogeography of groundwater invertebrates in Queensland, Australia. Subterranean Biology 17: 55-76. https://doi.org/10.3897/subtbiol.17.7542
Figure 9 - Comparison of systemic composition of described families from Australia and the World Average; In Figure 9 the systemic composition of described stygofauna families is compared between the Pilbara region (Western Australia, Australia) derived from Eberhard et al. (2005), Queensland (Australia), and the World Average derived from Eberhard et al. (2005).
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.