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42 results for “invertebrate biodiversity”
Data from: Species turnover and invasion of dominant freshwater invertebrates alter biodiversity-ecosystem function relationship
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Blue consequences of the green bioeconomy: clear-cutting intensifies the harmful impacts of land drainage on stream invertebrate biodiversity
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Data from: Invertebrate biodiversity in cold groundwater fissures in Iceland
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Data and code for a high-resolution summary of Cambrian to Early Triassic marine invertebrate biodiversity
<p>Data compilation and standardization were conducted through the Geobiodiversity Database from 2013 to 2017. The raw dataset contained 266,110 local Cambrian to Triassic records of 45,318 taxonomic units from 3,766 published stratigraphic sections. These were collected from all major Chinese tectonic plates. The authors spent three years verifying the taxonomic assignments into a consistent paleontological taxonomic classification system. Identifications to genus or higher taxonomic ranks were omitted. All non-marine fossil groups (e.g., plants, vertebrates, pollen, spores) were also removed. Species recovered from only a single locality were removed after a few test calculations in order to partially standardize the sampling and research efforts and avoid the "monograph effect". The final dataset retained after all standardization procedures included 116,060 local records of the stratigraphic ranges of 11,268 species in 3,112 published stratigraphic sections. </p> <p>The CONOP.SAGA program was designed for high-performance computing of geological time scale and biodiversity analysis in 2017. We designed a special hybrid algorithm that combined simulated annealing and a genetic algorithm to overcome the limitations of classic CONOP program designed by Pete Sadler.</p>
Supplementary material 1 from: Bigatti G, Signorelli J (2018) Marine invertebrate biodiversity from the Argentine Sea, South Western Atlantic. ZooKeys 791: 47-70. https://doi.org/10.3897/zookeys.791.22587
List of Valid species reported as living in the Argentine Sea :
Figure 3 from: Bigatti G, Signorelli J (2018) Marine invertebrate biodiversity from the Argentine Sea, South Western Atlantic. ZooKeys 791: 47-70. https://doi.org/10.3897/zookeys.791.22587
Figure 3 Distribution of main taxonomic marine invertebrate groups. The parenthesys after the province indicates the percentage of species mentioned as living in each province. The parenthesys after the phyllum initials indicates the number of species mentioned in the literature.
Figure 1 from: Bigatti G, Signorelli J (2018) Marine invertebrate biodiversity from the Argentine Sea, South Western Atlantic. ZooKeys 791: 47-70. https://doi.org/10.3897/zookeys.791.22587
Figure 1 Cumulative curve for valid marine invertebrate species reported as living in the Argentine Sea (South Western Atlantic). Each dot in the figure represents the year when the taxa was described (and subsequently reported in the literature as living in the Argentine Sea).
Figure 2 from: Bigatti G, Signorelli J (2018) Marine invertebrate biodiversity from the Argentine Sea, South Western Atlantic. ZooKeys 791: 47-70. https://doi.org/10.3897/zookeys.791.22587
Figure 2 Number of valid marine invertebrate species described per decade that were subsequently mentioned in the literature as living in the Argentine Sea.
Linked collectors and determiners for: Centre for Biodiversity Genomics (BIOUG) - Marine Invertebrates.
Natural history specimen data linked to collectors and determiners held within, "Centre for Biodiversity Genomics (BIOUG) - Marine Invertebrates". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/5ca5f0b6-d221-4f69-b7ac-8579180942b5">https://bionomia.net/dataset/5ca5f0b6-d221-4f69-b7ac-8579180942b5</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/5ca5f0b6-d221-4f69-b7ac-8579180942b5">https://gbif.org/dataset/5ca5f0b6-d221-4f69-b7ac-8579180942b5</a>. Formatted as a Frictionless Data package.
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).
Figure 3 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 3 - Distribution of stygofauna sampling effort by lithology in Queensland, Australia; In Figure 3 the total number of samples is indicated by numerical figures located above the columns and the percentage of samples is indicated by numerical figures along the x-axis.
Figure 2 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 2 - Outline map of Queensland, Australia highlighting the location of stygofauna sampling sites and other localities; In Figure 2 an outline map shows the location of all 582 stygofauna sampling sites and other key localities mentioned in the text (e.g. Bowen Basin, Murray–Darling Basin, Proserpine–Sarina Lowlands IBRA region).
Data and code for a high-resolution summary of Cambrian to Early Triassic marine invertebrate biodiversity
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Figure 1 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 1 - Diagram map of the structure of the 'Queensland Subterranean Aquatic Fauna Database'.
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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.