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123 results for “species database”
Data from 'Tracability of Forest Reproductive Material with the quality label 'Plant van Hier': A DNA database with genetic profiles of native autochthonous tree and shrub species of Flanders, Belgium'
<h2>Background</h2> <p>Indigenous trees and shrubs play an important role in multifunctional forest management. They form a significant part of the biodiversity in our forests. Forest reproductive material (FRM) of autochthonous Flemish origin is sold under the quality label ‘Plant van Hier’, a certification mark of the Agency for Nature and Forests. To ensure the provenance of the seedlings, we developed a DNA-database of genetic profiles of potential parent trees, using species-specific genetic markers. This database enables the traceability of FRM of the ‘Plant van Hier’ label throughout the entire production chain; from seed harvesting and cultivation to planting by the end user.</p> <p>This database contains the genetic profiles of almost all possible parent trees present within 27 Flemish autochthonous seed orchards of eight ecologically important tree and shrub species: <em>Carpinus betulus</em>, <em>Corylus avellana</em>, <em>Frangula alnus</em>, <em>Populus tremula</em>, <em>Sorbus aucuparia</em>, <em>Tilia cordata</em>, <em>Tilia platyphyllos,</em> and <em>Ulmus laevis</em>. The profiles were established using microsatellite markers (11 to 24 markers per species). New genetic markers were developed for <em>Carpinus betulus</em> and <em>Ulmus laevis</em>. PCR products were run on an ABI 3500 Genetic Analyser (Thermo Fisher Scientific).</p> <h2>Files</h2> <p>The files will be updated when new genotypes are added to the seed orchards. The current data files contain data from genotypes collected in the period 2018-2023. </p> <h3>Species_genotypes</h3> <p>These files contain the genetic fingerprints of the parent trees of autochthonous Flemish seed orchards. Missing data is indicated as ‘MD’. For <em>Carpinus betulus</em>, an octoploid species, the allelic phenotype is given instead of the genotype as the number of times that an allele occurs on a specific locus is not known.</p> <p>The next metadata is additionally given:<br>- Species: the Latin name of the species<br>- Seed_orchard: the name of the seed orchard in which the genotypes are located<br>- Code_seed_orchard: the code of the seed orchard in which the genotypes are located as given in the Register of Flemish Forest Reproductive Material (‘Register bosbouwkundig uitgangsmateriaal’; inbo.be)<br>- Genotype: the fieldname given to the genotype<br>- Origin: the location where the genotype was collected in Flanders, Belgium. Genotypes were collected from natural stands which are assumed to have an autochthonous origin. When the specific location is unknown, the location ‘Flanders’ is given. <br>- Year_sampled: the year in which the genotypes were sampled in the respective seed orchard for genetic analysis.</p> <h3>Species_binsets</h3> <p>These files contain the binsets and allele names that are used to score the alleles of the genotypes in the programme Geneious Prime 2019.3.2 (<a href="https://www.geneious.com">https://www.geneious.com</a>). For <em>Tilia platyphyllos </em>and <em>Tilia cordata</em>, the same binsets were used.</p>
RivFISH - An European database on fish species presence across river basins
<p>The RivFISH database aggregates the available data on freshwater-dependent fish presence in Europe, validated at the river basin level and considering taxonomical synonyms for species names, thus allowing for a maximization of data usage and robustness. This database also promotes interoperability with other datasets, including the IUCN Red List of Threatened Species, FishBase and the Catchment Characterisation and Modelling (CCM2) – River and Catchment Database v2.1. It is, as far as the authors know, the most up-to-date and comprehensive database on the presence of freshwater-dependent fish species for European river basins. The structure of the database is also prepared to deal with future alterations in species taxonomy, as well as new records of species occurrence in river basins.</p>
A bite force database of 654 insect species
<p>The insect bite force database as described in Rühr et al. (<strong>accepted</strong>): A bite force database for 654 insect species. doi: <a href="https://doi.org/10.1038/s41597-023-02731-w">1038/s41597-023-02731-w</a>.</p><p>The code used to convert the raw measurements to the final database and to create all tables and figures of the original publication can be found on its <a href="https://github.com/Peter-T-Ruehr/InsectBiteForceDatabase">GitHub Page</a> (under release <a href="https://github.com/Peter-T-Ruehr/InsectBiteForceDatabase/releases/tag/v1.0.0">v1.0.0</a>).</p>
WCSdb: A database of Wild Coffea Species.
<p>This the data table of the WCSdb: A database of Wild <em>Coffea</em> Species web site. The photo Gallery associated to this web site are available at <a href="https://dataverse.ird.fr/dataset.xhtml?persistentId=doi:10.23708/JZA8I2">https://doi.org/10.23708/JZA8I2</a> and the sequencing data at <a href="https://doi.org/10.23708/KWRIJJ%22%20%5Ct%20%22_blank">https://doi.org/10.23708/KWRIJJ</a></p> <p>Coffee is a beverage enjoyed by millions of people worldwide and an important commodity for millions of people. Beside the two cultivated species (<em>Coffea arabica</em> and <em>Coffea canephora</em>), the 139 wild coffee species belong to the <em>Coffea</em> genus are largely unknown to coffee scientists and breeders although these species may be crucial for future coffee crop development to face climate changes. Here we present the Wild Coffee Species database (WCSdb) hosted by Pl@ntNet platform (<a href="http://publish.plantnet-project.org/project/wildcofdb_en">http://publish.plantnet-project.org/project/wildcofdb_en</a>), providing information for 140 coffee species, for which 84 contain a photo gallery and 82 contain sequencing data (GBS, chloroplast or whole genome sequences). The objective of this database is to better understand and characterize the species (identification, morphology, biochemical compounds, genetic diversity, sequence data) in order to better protect and promote them. </p>
Ecostack - Database on ESP invertebrate species
<p>This document is composed of two parts: a report and the associated Microsoft Access database with information collected for selected Ecosystem Service Provider (ESP) species.</p> <p>The objective of this database was to provide compiled, and ready to use, information on the biology and ecology of key Ecosystem Service Providers (ESP) within the studied EU agricultural landscapes to be modelled in ALMaSS (agent-based or subpopulation-based models that will run on ALMaSS landscapes and will be used to test Ecostack scenarios). This information was necessary to build the “formal model” for each species, a step of paramount important in model building.</p> <p>The DB contains information from species being currently modelled but is prepared to be updated with new information on the same or other ESP species. To better understand the DB, it is advisable to consult the associated report.</p>
Alien Species First Records Database
<p>The Alien Species First Records data set contains years (first records) when an established alien species was first recorded in a region (mostly countries, but also sub-national units).</p><p>The first records were gathered in a collaborative effort involving >50 researchers worldwide from various sources consisting of online databases, scientific publications, reports and personal collections. A full list of data sources is provided in the data set and the data are described in more detail in the (compilation of data, list of data sources, delineation of continents, analyses etc.) in the following publication, which can be downloaded with free access:</p><p>Seebens, H., Blackburn, T. M., Dyer, E. E., Genovesi, P., Hulme, P. E., Jeschke, J. M., … Essl, F. (2017). No saturation in the accumulation of alien species worldwide. Nature Communications, 8(1), 14435. https://doi.org/10.1038/ncomms14435</p><p>The data set was revised and further extended in version 1.2, which was introduced by:</p><p>Seebens, H., Blackburn, T. M., Dyer, E. E., Genovesi, P., Hulme, P. E., Jeschke, J. M., … Essl, F. (2018). Global rise in emerging alien species results from increased accessibility of new source pools. Proceedings of the National Academy of Sciences, 115(10), E2264–E2273. https://doi.org/10.1073/pnas.1719429115</p><p>One of the above references needs to be cited in case of using the data set.</p><p>Note that single years of first records were generated from original records in cases latest years (e.g., '<1920', 'pre-1920') or ranges (e.g., '1920s', 1920-1930') were provided in the original document following these rules:</p><ul><li>If latest years were provided (e.g., '<1920'), this year was taken (e.g., '1920')</li><li>If ranges of years larger 20 years were provided in the original source, these records were removed.</li><li>If ranges of years equal or less than 20 years were provided in the original document, a random year was selected from this time period. This was done to avoid artificial peaks at e.g. the mean value or the first year of that period.</li></ul><p>Consequently, some records represent years randomly drawn from the original time period, which makes the column 'FirstRecord' different from the original data source. The original first record as provided in the source is provided in the column 'FirstRecord_orig' of the data set.</p>
Update and expansion of the database of bio-ecological information on non-target arthropod species
<p>The current database updates and extends the database on arthropods inhabiting European arable crops established in 2012 (Meissle <em>et al.</em> 2012). The data was collected to support environmental risk assessment of genetically modified (GM) crops in the European Union and provides a detailed overview of the arthropod fauna in arable crops across Europe.The data was obtained from systematic literature searches conducted to identify publications on small grain cereals and to identify additional publications on the crops covered by the previous database (maize, beet, potato, oilseed rape, rice, cotton, soy). The final database contains information on more than 4000 arthropod species, > 27700 records, and > 2000 references.</p> <p>The database consists of three tables containing information on species (taxonomy, ecological function, feeding guild, habitat), abundances (crop, collection method, location, sampling duration, collected species), and references (authors, year, title, source). Taxonomy was verified with European and global taxonomic catalogues and taxonomic experts. Ecological information, in particular feeding guilds of adults and juveniles, was double checked with appropriate literature, and provided in detail. References for taxonomic and ecological information were included for each species record</p> <p>For maize, beet, potato, oilseed rape, rice, and soybean, 258 additional studies were found and entered into the database, resulting in 2774 additional records. For those crops, the updated database contains 16610 records of 3264 species. Most of the records are available for maize (6648), followed by beet, potato, and oilseed rape (ca. 3000 records each). Relatively few records are available for rice (601), soy (231), and cotton (184). Overall, small grain cereals in Europe were reported to harbour more than 2000 arthropod species. Most information is available for wheat (7626 records and 1664 species), followed by barley (2308 records and 893 species). Rye, oats, and triticale are represented by 453, 369, and 273 records and 269, 187, and 171 species, respectively. Only few records are available for buckwheat and sorghum, and no records for millet and canary seed. Overall, small grain cereals in Europe are reported to harbour more than 2000 arthropod species. For the other crops, the updated database contains more than 3200 species. Most of the species recorded in small grain cereals are predators (63% of the abundance records), followed by herbivores (21%), decomposers (8%), parasitoids (7%), and pollinators (1%). </p> <p>The database contains reports from 37 countries in Europe and was extracted from references with a publication date ranging from 1925-2014.</p>
Cyprus Database of Alien Species – CyDAS
<p>This repository includes data and datasets derived and adapted from the Cyprus Database of Alien Species (CyDAS) (https://ris-ky.info/cydas), an openly accessible, online, dynamic platform providing informational resources on alien species on the island of Cyprus. The platform includes information on 1,293 terrestrial, freshwater and marine introduced taxa, with species profiles being constantly updated to keep track of new arrivals. The CyDAS aims to catalogue and supplement our knowledge on the alien species of Cyprus; to develop and enhance early warning and rapid response systems; to raise public awareness of the risks posed by the IAS subset; to strengthen and enhance engagement and public participation in surveys in the field of biological invasions; and to inform IAS policy. CyDAS is a free, online database and we would like to other encourage researchers and decision-makers to provide information on IAS.</p> <p>For further information on the data refer to the READ ME file. Please cite these data according to the assigned DOI as well as according to the citation of the data paper on Scientific Data.</p>
Data from: Integrated SDM database: Enhancing the relevance and utility of species distribution models in conservation management
<p><span>1. Species' ranges are changing at accelerating rates. Species distribution models (SDMs) are powerful tools that help rangers and decision-makers prepare for reintroductions, range shifts, reductions, and/or expansions by predicting habitat suitability across landscapes. Yet, range-expanding or -shifting species in particular face other challenges that traditional SDM procedures cannot quantify, due to large differences between a species' currently-occupied range and potential future range. The realism of SDMs is thus lost and not as useful for conservation management in practice. Here, we address these challenges with an extended assessment of habitat suitability through an <i>integrated SDM database (iSDMdb)</i>.</span></p> <p><span>2. The<i> iSDMdb</i> is a spatial database of predicted sites in a species' prediction range, derived from SDM results, and is a single spatial feature that contains additional, user-friendly data fields that synthesise and summarise SDM predictions and uncertainty, human impacts, restoration features, novel preferences in novel spaces, and management priorities. To illustrate its utility<i>,</i> we used the endangered New Zealand sea lion (<i>Phocarctos hookeri</i>). We consulted with wildlife rangers, decision-makers, and sea lion experts to supplement SDM predictions with additional, more realistic, and applicable information for management. </span></p> <p><span>3. Almost half the data fields included in this database resulted from engaging with these end-users during our study. The SDM found 395 predicted sites. However, the <i>iSDMdb</i>'s additional assessments showed that the actual suitability of most sites (90%) was questionable due to human impacts. >50% of sites contained unnatural barriers (fences, grazing grasslands), and 75% of sites had roads located within the species' range of inland movement. Just 5% of the predicted sites were mostly (>80%) protected.</span></p> <p><span>4. Integrating SDM results with supplemental assessments provides a way to address SDM limitations, especially for range-expanding or -shifting species. SDM products for conservation applications have been critiqued for lacking transparency and interpretation support, and ineffectively communicating uncertainty. The <i>iSDMdb</i> addresses these issues and enhances the practical relevance and utility of SDMs for stakeholders, rangers, and decision-makers. We exemplify how to build an <i>iSDMdb</i> using open-source tools, and how to make diverse, complex assessments more accessible for end-users.</span></p>
Development of thrips barcode database and multiplex real-time PCR assay for quarantine and agriculture pest species
<p>Thrips (Order Thysanoptera) species are agriculturally important as plant sap sucking pests and vectors of several plant diseases. They are very small insects and commonly associated with imported commodities at New Zealand border in all life stages. Morphological identification of thrips is mainly performed on adults, but the available identification keys for immature stages do not include many species and are inadequate, thus DNA barcode was regularly used for thrips identification, here, we have generated DNA barcode data for over 29 thrips species from over 100 individuals. At New Zealand border,<em> Frankliniella occidentalis </em>is the dominant species intercepted, followed by <em>F. panamensis</em>, <em>Thrips palmi</em> and <em>T. tabaci </em>and several other thrips species. Hence, we have also developed a multiplex real time PCR assay, targeting the four thrips species to facilitate the identification of quarantine interceptions with more accurate and faster diagnostic method for any developmental stages. The DNA barcode database further assists in thrip identification. The assay showed high specificity for all the four target species and could detect 10 copies/ µL of the target DNA. Linear responses and high correlation coefficients between the amount of DNA and <em>C</em><sub>q</sub> values for each species were also achieved. The method was tested on single egg, larva and adult and proved to be applicable for all life stages of the four species. This study has demonstrated the assay is a useful biosecurity tool for rapid and reliable identification of the target thrips species. </p>
Shapefiles representing regions in alien species databases for 9 taxa
<p>Shapefiles representing regions in alien species databases.</p> <p>1- Regions_shapefile_amphibians_reptiles - created based on the regional information available in "Capinha, C. <em>et al.</em> Diversity, biogeography and the global flows of alien amphibians and reptiles. <em>Divers Distrib</em> <strong>23</strong>, 1313–1322 (2017)."</p> <p>2- Regions_shapefile_ants_mammals - provided by "Guénard, B., Weiser, M. D., Gómez, K., Narula, N. & Economo, E. P. The Global Ant Biodiversity Informatics (GABI) database: synthesizing data on the geographic distribution of ant species (Hymenoptera: Formicidae). <em>Myrmecological News</em> <strong>24</strong>, 83–89 (2017)."</p> <p>3- Regions_shapefile_birds - created based on the regional information available in "Dyer, E. E., Redding, D. W. & Blackburn, T. M. The global avian invasions atlas, a database of alien bird distributions worldwide. <em>Sci Data</em> <strong>4</strong>, 170041 (2017)."</p> <p>4- Regions_shapefile_freshwater - provided by "Tedesco, P. A. <em>et al.</em> A global database on freshwater fish species occurrence in drainage basins. <em>Sci Data</em> <strong>4</strong>, 170141 (2017)."</p> <p>5- Regions_shapefile_macrofungi - created based on the regional information available in "Monteiro, M. <em>et al.</em> A database of the global distribution of alien macrofungi. <em>Biodiversity Data Journal </em><strong>8</strong>, e51459 (2020)."</p> <p>6- Regions_shapefile_plants - provided by "Kleunen, M. <em>et al.</em> The Global Naturalised Alien Flora (GloNAF) database. <em>Ecology</em> <strong>100</strong>, (2019)."</p> <p>7- Regions_shapefile_spiders - created based on the regional information shared by co-author Wolfgang Nentwig</p> <p> </p>
Figure A2 in A student-based expansion of the strategies of reproduction in fish (STOREFISH) database to 288 North American freshwater and anadromous species for 14 egg and larval traits
Figure A2. – Summary of the 162 answers for survey questions 5-9 (see Tab. A1 for details). Letter refer to the difficulties associated with (A) finding information (B) reading articles in English, (C) accessing documents, and (D) other reasons.
Figure 2 in A student-based expansion of the strategies of reproduction in fish (STOREFISH) database to 288 North American freshwater and anadromous species for 14 egg and larval traits
Figure 2. – The number of species (A) and records (B) in the original (black bars) and new (white bars) data sets for egg (left of the vertical bar) and larval (right of the bar) traits. Numbers in the x-axis correspond to trait numbers in Table I. The maximum possible number of species in (A) was 80 and 288 for the original and new data, respectively. See Table I for trait units and description.
Figure A3 in A student-based expansion of the strategies of reproduction in fish (STOREFISH) database to 288 North American freshwater and anadromous species for 14 egg and larval traits
Figure A3. – Boxplot summaries of the number of references (Q11) and traits (Q12) that the students found. See Table A1 for details.
Fig. 9 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 9. Web page of management of common names in Database of Korean National Species List. This web page displays the list of common names registered in the database.
Fig. 8 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 8. Web pages of management function of special list of species defined by law. (A) Presents the web interface of searching taxon with five functions. (B) shows the list of registered species defined by law with Korean name.
Fig. 10 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 10. Web pages of management of references in Database of Korean National Species List. (A) Shows the list of references with function to assign references to taxa. (B) Web interface of function assigning reference to taxa.
Fig. 7 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 7. Web page of list of special list of species defined by law. This web page provides management function of special list of species defined by law.
Fig. 5 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 5. Introduction page of Korean National Species List. Introduction page of National Species List of Korea in the platform for biodiversity in Korea (http://www.kbr.go.kr/content/view.do?menuKey = 446&contentKey = 14).
Fig. 4 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 4. Web interface of list of taxa with search options. (A) Displays complex interface for searching taxon. (B) is the list view of taxa searched. (C) shows the example of brief information of taxon which will be appeared by clicking KTSN number in the list view.
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
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.