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123 results for “species database”
Fig. 2 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 2. Web interface of taxon in Database of Korean National Species List. (A) Provides hierarchical structure of taxon with the tree interface. (B) shows basic information of taxon including KTSN, species properties, representative common names, and status of KTSN. (C) displays ranks, names, common names, identifiers, origins and etc. (D) displays information higher taxa based on hierarchical systems. (E) shows the list of synonyms. (F) is the list of references related to this taxon. (G) is the list of all common names except representative name.
Fig. 12 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 12. System structure of Database of Korean National Species List. Grey rectangles represent systems related to the Database of National Species List of Korea and blue rectangles indicates systems using species information via Database of National Species List of Korea outside of NIBR. Black arrows indicate utilization of taxonomic information from the Database of National Species List of Korea and Grey arrows present communication with institutes outside of NIBR. Dotted grey arrow means commination channel will be established soon.
Fig. 1 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 1. Database structure of Database of Korean National Species List. (A) Presents relationship of major entities of the Database of Korean National Species List. Black thick lines are n:m relationship and blue arrows show detailed content types of each entity. (B) displays example of hierarchical relations of higher taxa originated from two different systems, KNSL and APG IV.
Fig. 6 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 6. Download page of Korean National Species List. This web page provides the download link of National Species List of Korea in the main page of the platform for biodiversity in Korea (http://www.kbr.go.kr/).
Fig. 3 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 3. Tree interface of taxon. (A) Shows interface to search by management groups, rank, and name. Yellow arrow indicates fold- er icon which open all higher nodes of the taxon up and grey arrow shows check icon which provides detailed information of the taxon. (B) displays tree interface for hierarchical structure of taxa. Plus icon indicated by blue arrow means open the lower taxa in the specific taxon, and each node (orange arrow) represents each taxon.
Fig. 11 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 11. Web interface of reporting tools in Database of Korean National Species List. (A) Presents the basket of report. Dotted box presents option of generating reports. (B) shows the list of tasks registered for generating report. (C) displays three different formats of report generated by the Database of National Species List of Korea.
Linked collectors and determiners for: DATABASE OF FINDS OF RARE LICHEN SPECIES Lobaria pulmonaria IN RUSSIA.
Natural history specimen data linked to collectors and determiners held within, "DATABASE OF FINDS OF RARE LICHEN SPECIES Lobaria pulmonaria IN RUSSIA". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/4bb083e8-53b9-418e-b83d-105e75a1798d">https://bionomia.net/dataset/4bb083e8-53b9-418e-b83d-105e75a1798d</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/4bb083e8-53b9-418e-b83d-105e75a1798d">https://gbif.org/dataset/4bb083e8-53b9-418e-b83d-105e75a1798d</a>. Formatted as a Frictionless Data package.
Filtered GBIF dataset of occurrences for food species in the brown bear (Ursus arctos) trophic database
<p>We reviewed 47 studies of brown bear diet in Europe by searching in SCI Journals, master’s and PhD theses, and grey literature. We obtained a list of 276 species in the brown bear diet in Europe and Turkey. We used the R package rgbif to download occurrences of each food species from the Global Biodiversity Information Facility (GBIF). We selected occurrences of food species, with an uncertainty of <1 km2, in Europe, North Africa and the Middle East for the period 1989–2018.</p>
Data from: A global database of butterfly species native distributions
Open the record for dataset details and reuse information.
Data from: Integrated SDM database: Enhancing the relevance and utility of species distribution models in conservation management
Open the record for dataset details and reuse information.
Master Plant Species Information Database for the Sevilleta National Wildlife Refuge, New Mexico (1989-1996)
This data base contains taxonomic and ecological information for the plant species on the Sevilleta National Wildlife Refuge.
Data from: PalmTraits 1.0, a species-level functional trait database for palms worldwide
Plant traits are critical to plant form and function —including growth, survival and reproduction— and therefore shape fundamental aspects of population and ecosystem dynamics as well as ecosystem services. Here, we present a global species-level compilation of key functional traits for palms (Arecaceae), a plant family with keystone importance in tropical and subtropical ecosystems. We derived measurements of essential functional traits for all (>2500) palm species from key sources such as monographs, books, other scientific publications, as well as herbarium collections. This includes traits related to growth form, stems, armature, leaves and fruits. Although many species are still lacking trait information, the standardized and global coverage of the data set will be important for supporting future studies in tropical ecology, rainforest evolution, paleoecology, biogeography, macroecology, macroevolution, global change biology and conservation. Potential uses are comparative eco-evolutionary studies, ecological research on community dynamics, plant-animal interactions and ecosystem functioning, studies on plant-based ecosystem services, as well as conservation science concerned with the loss and restoration of functional diversity in a changing world.
Database for "Ecological perspectives on female and male reproductive success with competition in two Serapias species" Annals of Botany 2024
<p>Public data from the paper: Ecological perspectives on female and male reproductive success with competition in two Serapias species by J. Borràs, J. Cursach, C. Herrera, S. Perelló-Suau and M. Capó published in Annals of Botany 2024. <a href="https://doi.org/10.1093/aob/mcae074">DOI: 10.1093/aob/mcae074</a></p>
OctocoralTraits: a global database of trait information for octocoral species
<p>The OctocoralTraits_v2_2 ZIP file contains structured data and code to create all figures from the manuscript: “The Octocoral Trait Database: a global database of trait information for octocoral species”. The folder also contains the code used to validate the data descriptor.</p> <p>Specifically, the folder contains the following files:</p> <p>· Code.R – This is the annotated code used to create all figures in R. (v R studio; 2023.06.0+421)</p> <p>· OctocoralTraits_v2_2.csv – This is the first data realase of the octocoral trait database, used to create all figures of the manuscript.</p> <p>· sp_id.csv – This is a file containing the list of accepted octocoral species contained in the database</p> <p>· iqtree.tre – This is a tree object used to create a family-resolved tree of octocorals. It has been downloaded from McFadden et al. 2022. Revisionary systematics of Octocorallia (Cnidaria: Anthozoa) guided by phylogenomics</p> <p>· MEOW folder – A folder containing regional information from Spalding et al. 2007. Marine Ecoregions of the World: A Bioregionalization of Coastal and Shelf Areas</p> <p>· Provinces_coord.csv: A file containing the coordinates of marine provinces, also derived from Spalding et al. 2007</p> <p>· Table_ids folder - A folder containing tables with information of the corresponding ids that appear in the file database.</p> <p>· Validation folder: A folder containing a Technical_validation.R file that was used to flag outliers and extreme outliers, duplicated rows and potential structural errors in the data (e.g., a given observation_id linked to more than one resource, species or location). </p>
Database of initial survival of three pine species after antitranspirant application
<p>Raw data from the Revista Mexicana de Ciencias Forestales paper: "Initial survival of three pine species after antitranspirant application" Revista Mexicana de Ciencias Forestales <strong>2022</strong> 13(69): 176-199. doi:<a href="http://dx.doi.org/10.3390/f9020071">10.29298/rmcf.v13i69.1145.</a></p> <p>The database corresponds to seedlings of three Mexican pines: <em>P. cooperi, P. durangensis</em> and <em>P. engelmannii</em>, that were treated with three antitranspirant products (Vapor Gard, Fitoglass, and Ecofilm) and two application methods (spraying and immersion). Survival data and root neck diameter were measured.</p>
Table of hsp65 OTUs (cutoff 99%), their inferred taxonomic allocations according to the hsp65 database and, for selected OTUs, closest species obtained from GenBank (BLAST) with percent identity.
<p>This table is part of the paper intitled "Comparison of Actinobacteria communities from human-impacted and pristine karst caves"</p>
EWINA_RICH : a database of EarthWorm native and alien species richness accross North America
<p><strong>EWINA_RICH</strong> gathers data on observed and predicted native and alien species richness of earthworms species across geographical units of North America (Mexico, US and Canada), based on data from 1850 to 2021.</p><p>Please refer to the published paper for the details about the process to produce the predictions and the general interpretation of the results.</p><p>Data are given at two distinct spatial resolutions</p><blockquote><p><strong>- Data at the resolution of counties or equivalent</strong></p><ul><li><a href="https://zenodo.org/api/files/61402820-f567-48fb-b030-2353b156a676/EWINA_counties.geojson">EWINA_counties.geojson: </a>Spatial layer of all counties or alike geographical units, with environmental covariates. Used to map geographical units and to predict RASR.</li><li><a href="https://zenodo.org/api/files/61402820-f567-48fb-b030-2353b156a676/EWINA_2000_counties_obs.csv">EWINA_2000_counties_obs.csv</a>: Observed earthworm species richness and RASR (Relative Alien Species Richness) in the geographical units with earthworm data, since year 2000, together with the environmtal covariates.(Coverage based estimates, used in the paper, will be released soon, feel free to reach out if you need them).</li><li><a href="https://zenodo.org/api/files/61402820-f567-48fb-b030-2353b156a676/EWINA_2000_counties_pred.csv">EWINA_2000_counties_pred.csv</a>: Predicted earthworm RASR (Relative Alien Species Richness) and its uncertainty, in all counties or equivalent, based on a model fitted on data after the year 2000.</li></ul><p><strong>- Data at the resolution of TDWG4 geographical units (≈ states)</strong></p><p>see <a href="https://www.tdwg.org/">the Biodiversity Information Facility Website</a> for more info about the definition of TDWG4 geographical units</p><ul><li><a href="https://zenodo.org/api/files/61402820-f567-48fb-b030-2353b156a676/EWINA_TDWG4_aboveground.geojson">EWINA_TDWG4_aboveground.geojson</a><a href="https://zenodo.org/api/files/61402820-f567-48fb-b030-2353b156a676/EWINA_counties.geojson">: </a>Spatial layer of TDWG4 geographical units, with above ground alien taxa richness from Dawson 2017 <a href="https://doi.org/10.1038/s41559-017-0186">https://doi.org/10.1038/s41559-017-0186</a>.</li><li><a href="https://zenodo.org/api/files/61402820-f567-48fb-b030-2353b156a676/EWINA_TDWG4_earthworms.csv">EWINA_TDWG4_earthworms_YYYY.csv:</a> Observed earthworm native and exotic species richness in the TDWG4 units, data cumulated from 1850 to YYYY.</li><li><a href="https://zenodo.org/api/files/dea6f9e3-c6b3-488a-85ea-a9c6d63799c4/EWINA_TDWG4_fun.csv">EWINA_TDWG4_fun.csv</a>: Observed native and alien earthworm species functionnal role in the TDWG4 units, data cumulated from 1850 to 2021.</li></ul></blockquote><p>All data files are provided with a readme file that explains the meaning of the variables.</p><p>Scripts to use the data are stored on GitHub: <a href="https://github.com/JeromeMathieuEcology/GlobalWorming">https://github.com/JeromeMathieuEcology/GlobalWorming</a></p>
Database of freshwater fish species of the Amazonia Region in Colombia: records from ichthyological collections.
<p>The database corresponds to an exhaustive review of freshwater from the Amazonia Region records from the catalogs of scientific reference collections from different institutions. </p>
Species numbers by country.pdf: a listing of total fish species numbers for locations compiled from http://www.fishbase.us online database.
<p>Species numbers by country.pdf: a listing of total fish species numbers for locations compiled from http://www.fishbase.us online database.</p> <p>data from Starck, W.A., Estapé C.J. & Morgan Estapé, A. (2017) The fishes of Alligator Reef and environs in the<br> Florida Keys: a half-century update. Journal of the Ocean Science Foundation, 27, 74–117.</p>
GTDB and RefSeq-RDP databases parsed for species assignment
<p>GTDB and RefSeq-RDP databases parsed for the <em>addSpecies()</em> dada2 function. Both databases were parsed with `<a href="https://github.com/antonioggsousa/GTDB-RefSeq-RDP-assign-spp-dada2/blob/master/script/parsing_DB_dada2_spp_assign.py">parsing_DB_dada2_spp_assign.py</a>` python script using as input both databases downloaded at: <a href="https://zenodo.org/record/2541239#.XM2UgCOZPOQ">https://zenodo.org/record/2541239#.XM2UgCOZPOQ</a>. The python script and a detailed description explaining the code and databases versions can be found at: <a href="https://github.com/antonioggsousa/GTDB-RefSeq-RDP-assign-spp-dada2">https://github.com/antonioggsousa/GTDB-RefSeq-RDP-assign-spp-dada2</a></p> <p> </p>
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.