GBIF Data Backbone File -- Smithsonian Gap Analysis Tool; Data download of the GBIF database (https://www.gbif.org/) formatted for use in the Smithsonian Gap Analysis tool

Original provider: ARCHELON, the Sea Turtle Protection Society of Greece

Dataset credits: Data provider ARCHELON (2002-2007) Originating data center Satellite Tracking and Analysis Tool (STAT) Project partner ETANAM - Local management agency of the Amvrakikos Bay region Project sponsor or sponsor description LIFE-Nature. A European Union funding programme to develope management plans and protection for NATURA 2000 sites.

Abstract: Little is known of the foraging turtles in Amvrakikos Bay. We have tag returns from turtles that have nested at the three nearby Ionian nesting areas, Kefalonia, Zakynthos and Kyparissia Bay, but when they come and go and where they move around in the bay was unknown. This project has helped to answere some of these important conservation issues.

Supplemental information: Visit STAT's project page for additional information.

This dataset is a summarized representation of the telemetry locations aggregated per species per 1-degree cell.

Zomerganzen - Summering geese management and population counts in Flanders, Belgium is a sampling event dataset published by the Research Institute for Nature and Forest (INBO). The dataset contains over 3,700 sampling events, carried out since 2009, mostly in the months June and July. The data are compiled from different summering geese related projects, but most data were collected through fieldwork within the framework of the EU co-funded Interreg projects INVEXO (http://www.invexo.eu) and RINSE (www.rinse-europe.eu). Since 2015, data collection is funded by INBO. The dataset includes close to 5,000 presence occurrences, as well as over 15,000 absence occurrences. The sampling protocol for the majority of the occurrences are simultaneous counts. Here, the number of individuals of different geese species in a fixed set of areas is determined. Counts are performed within the same weekend to avoid double counting. Simultaneous counts were organised yearly since 2008 and take place the first weekend after July 15, the best period for monitoring the summering population of geese. These counts are performed by professional INBO employees as well as experienced birdwatchers from Natuurpunt using a standardized field protocol. Data are recorded in a citizen science portal (http://waarnemingen.be/waarnemingen_projecten.php?project=231). However, The dataset also comprises opportunistic field observations from the same portal outside this period. Furthermore, data are derived from management actions, such as fertility reduction (egg shaking and pricking), the use of Larsen traps (for Egyptian goose), and the execution of moult captures. Here, the individuals in the dataset were actually removed from the environment. The aim of the data collection is management follow-up and evaluation. Consequently, caution is advised when using these data for trend analysis, distribution range calculation, niche modeling or other. Issues with the dataset can be reported at https://github.com/LifeWatchINBO/data-publication/tree/master/datasets/zomerganzen-events

We strongly believe an open attitude is essential for tackling the IAS problem (Groom et al. 2015). To allow anyone to use this dataset, we have released the data to the public domain under a Creative Commons Zero waiver (http://creativecommons.org/publicdomain/zero/1.0/). We would appreciate it however if you read and follow these norms for data use (http://www.inbo.be/en/norms-for-data-use) and provide a link to the original dataset (https://doi.org/10.15468/a5ubtp) whenever possible. If you use these data for a scientific paper, please cite the dataset following the applicable citation norms and/or consider us for co-authorship. We are always interested to know how you have used or visualized the data, or to provide more information, so please contact us via the contact information provided in the metadata, opendata@inbo.be or https://twitter.com/LifeWatchINBO.

Description

Species occurrence data from Naturrestaurering AS smaller projects.

Temporal scope

• 2011-current Formation period

Geographic scope

Occurrence data collected from projects where Naturrestaurering has been involved within Norway.

Taxonomic scope

Animals, plants, mosses, lichens, and fungi.

Kingdom

• Animalia
• Fungi
• Plantae

Methodology

Study extent

Various species data collected by NaturRestaurering AS from a range of sites spanning the country of Norway in the period 2011 to the present.

Sampling

There is no common protocol for these data. Most of these data are species occurrences or species lists recorded as a smaller part of inspections of areas to form a basis for sustainability analysis, impact assessments, or general evaluation of the biodiversity or natural values of an area.

Quality control

All species data are cross-checked against the "Species Nomenclature Database" from Artsdatabanken Norway to check the vernacularName and the scientificName, as well as check if these correlates. Then the scientificName is checked against the GBIF backbone taxonomy. All species occurrences where the scientificName and the vernacluarName do not match in the "Species Nomenclature Database", or there are other reasons to doubt the validity of the observation is removed from the dataset.

Method steps

Data is recorded in the field, either as an occurrence of a specific species or as a species list. - If necessary the data is converted into DarwinCore format. - The validity of all species occurrences is cross-checked against the "Species Nomenclature Database" (http://www2.artsdatabanken.no/artsnavn/Contentpages/Hjem.aspx) and the "GBIF backbone taxonomy" (https://www.gbif.org/dataset/d7dddbf4-2cf0-4f39-9b2a-bb099caae36c/constituents) using R. - The data is uploaded to the IPT of GBIF-Norway (https://ipt.gbif.no/) and published after quality control by GBIF-Norway.

The purpose of this dataset is to evaluate the impact of fires on reptile and amphibian biodiversity in California's southwest desert. Species data was downloaded from the Global Diversity Information Facility (GBIF). GBIF.org (28 July 2021) GBIF Occurrence Download https://doi.org/10.15468/dl.6kvrr7

A vigorous debate among ecologists concerns two contrasting theories of species distribution and diversity, the niche theory and the neutral theory. The 'continuum hypothesis', supported by modelling results, maintains that rather than being mutually exclusive, these theories represent two ends of a continuum. Here we develop the first empirical test capable of distinguishing between these three theories using continental-scale occurrence data from GBIF and a novel simulation framework of corresponding virtual species; application of this test to a set of 84 Australian mammals supported the continuum hypothesis over the two competing theories.

Repository contains:

- Manuscript supplementary information (Sp.Dis_F1000-Supplementary.pdf)
- All analysis data and code (analysis_data_and_code.zip)
- GBIF raw data in a DwC-A format (0054618-160910150852091.zip). Data is also publicly available via GBIF, with the following DOI: https://doi.org/10.15468/dl.3poqxs

The Barcode of Life Data Systems (BOLD) is designed to support the generation and application of DNA barcode data, but it also provides a unique source of data with potential for many research uses. This paper explores the streamlining of BOLD specimen data to record species distributions – and its fast publication using the Biodiversity Data Journal (BDJ), and its authoring platform, the Pensoft Writing Tool (PWT). We selected a sample of 630 specimens and 10 species of a highly diverse group of parasitoid wasps (Hymenoptera: Braconidae, Microgastrinae) from the Nearctic region and used the information in BOLD to uncover a significant number of new records (of locality, provinces, territories and states). By converting specimen information (such as locality, collection date, collector, voucher depository) from the BOLD platform to the Excel template provided by the PWT, it is possible to quickly upload and generate long lists of "Material Examined" for papers discussing taxonomy, ecology and/or new distribution records of species. For the vast majority of publications including DNA barcodes, the generation and publication of ancillary data associated with the barcoded material is seldom highlighted and often disregarded, and the analysis of those data sets to uncover new distribution patterns of species has rarely been explored, even though many BOLD records represent new and/or significant discoveries. The introduction of journals specializing in – and streamlining – the release of these datasets, such as the BDJ, should facilitate thorough analysis of these records, as shown in this paper.

R script to clean raw GBIF records, perform Getis-Ord Gi* analysis, and create maps. The vector shapefile including the number total clean GBIF records per one-degree squared grid cell is also included here.

The purpose of this dataset is to evaluate the impact of fires on endangered species biodiversity in California's southwest desert. Species data was downloaded from the Global Diversity Information Facility (GBIF). Wildland fires were downloaded from the National Interagency Fire Network

Known occurrences of the weed 'witchweed', Striga asiatica, harvested from the GBIF data registry (www.gbif.net). The raw data returned by the data registry were edited to filter out records lacking geographic coordinates, as well as to limit the area of analysis to Africa.

This dataset contains metadata for all GBIF datasets from 2018 and 2019, and lists of all citing articles. Metadata fields include title, description, DOI, citation count, creation and update timestamps. A random sample of 1000 datasets was generated for content analysis that includes manually collected information on citing articles for each cited datasets and download counts. The data was analyzed to study data citation and reuse practices in the field of biodiversity.

Invasive species - American bullfrog (Lithobates catesbeianus) in Flanders, Belgium (Post 2018) is a species occurrence dataset published by the Research Institute for Nature and Forest (INBO). The dataset contains over 24600 occurrences (40 % of which are American bullfrogs) sampled between 2019 until now, in the months April to October. The occurrences were collected through fieldwork and the framework of bullfrog management. Captured bullfrogs were almost always removed from the environment and humanely killed, while the other occurrences are recorded bycatch, which were released upon catch (see bibliography for detailed descriptions of the methods). Therefore, caution is advised when using these data for trend analysis, distribution range calculation, or other. Issues with the dataset can be reported at https://github.com/inbo/sk-analyse

We strongly believe an open attitude is essential for tackling the IAS problem (Groom et al. 2015). To allow anyone to use this dataset, we have released the data to the public domain under a Creative Commons Zero waiver (http://creativecommons.org/publicdomain/zero/1.0/). We would appreciate it however if you read and follow these norms for data use (http://www.inbo.be/en/norms-for-data-use) and provide a link to the original dataset (https://doi.org/10.15468/daf62d) whenever possible. If you use these data for a scientific paper, please cite the dataset following the applicable citation norms and/or consider us for co-authorship. We are always interested to know how you have used or visualized the data, or to provide more information, so please contact us via the contact information provided in the metadata, opendata@inbo.be or https://twitter.com/LifeWatchINBO.

Data from 2010 to 2018 can be found here: https://doi.org/10.15468/2hqkqn

This dataset contains the digitized treatments in Plazi based on the original journal article Stöhr, Sabine (2024): Taxonomic analysis of the genital plates and associated structures in Ophiuroidea (Echinodermata). European Journal of Taxonomy 933: 1-98, DOI: 10.5852/ejt.2024.933.2525, URL: https://europeanjournaloftaxonomy.eu/index.php/ejt/article/download/2525/11335

This dataset contains the digitized treatments in Plazi based on the original journal article Andena, Sergio R., Carpenter, James M., Pickett, Kurt M. (2009): Phylogenetic analysis of species of the neotropical social wasp Epipona Latreille, 1802 (Hymenoptera, Vespidae, Polistinae, Epiponini). ZooKeys 20 (20): 385-398, DOI: 10.3897/zookeys.20.79

The Southern Ocean is a remote, hostile environment where conducting marine biology is challenging, so we know relatively little about this important region, which is critical as a habitat for breeding and foraging of many marine endotherms. Scientists from around the world have been tracking seals, penguins, petrels, whales and albatrosses for more than two decades to learn how they spend their time at sea. The Retrospective Analysis of Antarctic Tracking Data (RAATD), was initiated by the SCAR Expert Group on Marine Mammals (EG-BAMM) in 2010. This team has assembled tracking data shared by 38 biologists from 11 different countries to accumulate the largest animal tracking database in the world, containing information from 15 species, containing over 3,400 individual animals and almost 2.5 million at-sea locations. Analysing a dataset of this size brings its own challenges and the team is developing new and innovative statistical approaches to integrate these complex data. When complete RAATD will provide a greater understanding of fundamental ecosystem processes in the Southern Ocean, help predict the future of top predator distribution and help with spatial management planning.

Original provider: Yonat Swimmer

Dataset credits: Data provider Fisheries Bycatch Research Group Originating data center Satellite Tracking and Analysis Tool (STAT)

Supplemental information: Visit STAT's project page for additional information.

This dataset is a summarized representation of the telemetry locations aggregated per species per 1-degree cell.

This dataset contains the digitized treatments in Plazi based on the original journal article Bertani, Rogério (2023): Taxonomic revision and cladistic analysis of Lasiodora C. L. Koch, 1850 (Araneae, Theraphosidae) with notes on related genera. Zootaxa 5390 (1): 1-116, DOI: 10.11646/zootaxa.5390.1.1, URL: https://www.mapress.com/zt/article/download/zootaxa.5390.1.1/52544

This dataset contains the digitized treatments in Plazi based on the original journal article Amr, Zuhair S., Abu, Mohammad A., Qumsiyeh, Mazin, Eid, Ehab (2018): Systematics, distribution and ecological analysis of rodents in Jordan. Zootaxa 4397 (1): 1-94, DOI: 10.11646/zootaxa.4397.1.1

Type specimens have high scientific importance because they provide the only certain connection between the application of a Linnean name and a physical specimen. Many other individuals may have been identified as a particular species, but their linkage to the taxon concept is inferential. Because type specimens are often more than a century old and have experienced conditions unfavourable for DNA preservation, success in sequence recovery has been uncertain. This study addresses this challenge by employing next-generation sequencing (NGS) to recover sequences for the barcode region of the cytochrome c oxidase 1 gene from small amounts of template DNA. DNA quality was first screened in more than 1800 century-old type specimens of Lepidoptera by attempting to recover 164-bp and 94-bp reads via Sanger sequencing. This analysis permitted the assignment of each specimen to one of three DNA quality categories – high (164-bp sequence), medium (94-bp sequence) or low (no sequence). Ten specimens from each category were subsequently analysed via a PCR-based NGS protocol requiring very little template DNA. It recovered sequence information from all specimens with average read lengths ranging from 458 bp to 610 bp for the three DNA categories. By sequencing ten specimens in each NGS run, costs were similar to Sanger analysis. Future increases in the number of specimens processed in each run promise substantial reductions in cost, making it possible to anticipate a future where barcode sequences are available from most type specimens.

Original provider: Paolo Casale

Dataset credits: Data provider WWF Italy's Sea Turtle Network Originating data center Satellite Tracking and Analysis Tool (STAT)

Supplemental information: Visit STAT's project page for additional information.

This dataset is a summarized representation of the telemetry locations aggregated per species per 1-degree cell.