scholarly journals Norwegian Taxonomy Initiative & Biodiversity Infrastructure

Author(s):  
Liselott Skarp ◽  
Eveliina Päivikki Kallioniemi ◽  
Ingrid Ertshus Mathisen

Norwegian Biodiversity Information centre (NBIC) shares information about Norwegian species, habitats and ecosystems. One of the key tasks is to maintain an updated taxonomical and nomenclatural backbone “Norwegian Taxonomic backbone” (Artsnavnebase) for species. Launched in 2009, the backbone contains more than 185 000 scientific names, as well as 45 000 names in Norwegian (two languages) and Northern Sami. “Norwegian Taxonomic backbone” delivers names and taxonomic information to scientific institutions and museums across the country and is used for both management and research purposes as well as by general public. Additionally, the database has contributed more than 33500 names to the construction of the Global Biodiversity Information Facility (GBIF) taxonomy. Another major task is the Norwegian Taxonomy Initiative (NTI) which was established in 2009 with the goal of improving knowledge about Norwegian biodiversity with special emphasis on poorly known species. In addition, the surveys provide information about distributions of species in Norway and their habitat requirements. NTI collaborates with Norwegian Barcode of Life (NorBOL) and contributes into building up a comprehensive library of standardized DNA sequences (DNA barcodes) and supports research school in biosystematics (ForBio). Swedish and Norwegian taxonomy initiatives work cooperatively to increase the collective knowledge on poorly known species, and as a result, more than 3 000 species new to the country in both Sweden and Norway has been found, of which about a third being new to science. NBIC is in a process of developing and collating a trait database “Trait bank” (Egenskapsbank) for Norwegian species and habitats. Trait bank will describe and combine information about species traits on morphology, physiology and ecology etc. The aim is to also store information about Norwegian habitat types described based on Nature in Norway -system and establish the connections between habitats and species using them. Species trait data relevant for Norwegian species will be extracted from existing databases and other data sources. The first information from this work will be made available through 2020 and is going to be useful for research, conservation and area planning.

2021 ◽  
Author(s):  
Manuela Mejía Estrada ◽  
Luz Fernanda Jiménez-Segura ◽  
Iván Soto Calderón

The Barcoding was proposed motivated by the mismatch between the low number of taxonomists that contrasts with the large number of species, the method requires the construction of reference collections of DNA sequences that represent existing biodiversity. Freshwater fishes are key indicators for understanding biogeography around the world. Colombia with 1610 species of freshwater fishes is the second richest country in the world in this group. However, genetic information of the species continues to be limited, the contribution to a reference library of DNA barcodes for Colombian freshwater fishes highlights the importance of biological collections and seeks to strengthen inventories and taxonomy of such collections in future studies. This dataset contributes to the knowledge on the DNA barcodes and occurrence records of 96 species of Freshwater fishes from Colombia. The species represented in this dataset correspond to an addition to BOLD public databases of 39 species. Forty-nine specimens were collected in Atrato bassin and 708 in Magdalena-Cauca bassin during the period of 2010 to 2020, two species (Loricariichthys brunneus and Poecilia sphenops) are considered exotic to the Atrato, Cauca and Magdalena basins and four species (Oncorhynchu mykiss, Oreochromis niloticus, Parachromis friedrichsthalii and Xiphophorus helleri) are exotic to Colombian hydrogeographic regions. All specimens are deposited in the CIUA collection at University of Antioquia and have their DNA barcodes made publicly available in the Barcode of Life Data System (BOLD) online database and the distribution dataset can be freely accessed through the Global Biodiversity Information Facility (GBIF).


2020 ◽  
Vol 8 ◽  
Author(s):  
Sonia Ferreira ◽  
José Manuel Tierno de Figueroa ◽  
Filipa Martins ◽  
Joana Verissimo ◽  
Lorenzo Quaglietta ◽  
...  

The use of DNA barcoding allows unprecedented advances in biodiversity assessments and monitoring schemes of freshwater ecosystems; nevertheless, it requires the construction of comprehensive reference collections of DNA sequences that represent the existing biodiversity. Plecoptera are considered particularly good ecological indicators and one of the most endangered groups of insects, but very limited information on their DNA barcodes is available in public databases. Currently, less than 50% of the Iberian species are represented in BOLD. The InBIO Barcoding Initiative Database: contribution to the knowledge on DNA barcodes of Iberian Plecoptera dataset contains records of 71 specimens of Plecoptera. All specimens have been morphologically identified to species level and belong to 29 species in total. This dataset contributes to the knowledge on the DNA barcodes and distribution of Plecoptera from the Iberian Peninsula and it is one of the IBI database public releases that makes available genetic and distribution data for a series of taxa. The species represented in this dataset correspond to an addition to public databases of 17 species and 21 BINs. Fifty-eight specimens were collected in Portugal and 18 in Spain during the period of 2004 to 2018. All specimens are deposited in the IBI collection at CIBIO, Research Center in Biodiversity and Genetic Resources and their DNA barcodes are publicly available in the Barcode of Life Data System (BOLD) online database. The distribution dataset can be freely accessed through the Global Biodiversity Information Facility (GBIF).


2022 ◽  
Vol 10 ◽  
Author(s):  
Manuela Mejía-Estrada ◽  
Luz Fernanda Jiménez-Segura ◽  
Marcela Hernández-Zapata ◽  
Iván Soto Calderón

The Barcode of Life initiative was originally motivated by the large number of species, taxonomic difficulties and the limited number of expert taxonomists. Colombia has 1,610 freshwater fish species and comprises the second largest diversity of this group in the world. As genetic information continues to be limited, we constructed a reference collection of DNA sequences of Colombian freshwater fishes deposited in the Ichthyology Collection of the University of Antioquia (CIUA), thus joining the multiple efforts that have been made in the country to contribute to the knowledge of genetic diversity in order to strengthen the inventories of biological collections and facilitate the solution of taxonomic issues in the future. This study contributes to the knowledge on the DNA barcodes and occurrence records of 96 species of Colombian freshwater fishes. Fifty-seven of the species represented in this dataset were already available in the Barcode Of Life Data System (BOLD System), while 39 correspond to new species to the BOLD System. Forty-nine specimens were collected in the Atrato River Basin and 708 in the Magdalena-Cauca asin during the period 2010-2020. Two species (Loricariichthys brunneus (Hancock, 1828) and Poecilia sphenops Valenciennes, 1846) are considered exotic to the Atrato, Cauca and Magdalena Basins and four species (Oncorhynchus mykiss (Walbaum, 1792), Oreochromis niloticus (Linnaeus, 1758), Parachromis friedrichsthalii (Heckel, 1840) and Xiphophorus helleri Heckel, 1848) are exotic to the Colombian hydrogeographic regions. All specimens are deposited in CIUA and have their DNA barcodes made publicly available in the BOLD online database. The geographical distribution dataset can be freely accessed through the Global Biodiversity Information Facility (GBIF).


Author(s):  
Katharine Barker ◽  
Jonas Astrin ◽  
Gabriele Droege ◽  
Jonathan Coddington ◽  
Ole Seberg

Most successful research programs depend on easily accessible and standardized research infrastructures. Until recently, access to tissue or DNA samples with standardized metadata and of a sufficiently high quality, has been a major bottleneck for genomic research. The Global Geonome Biodiversity Network (GGBN) fills this critical gap by offering standardized, legal access to samples. Presently, GGBN’s core activity is enabling access to searchable DNA and tissue collections across natural history museums and botanic gardens. Activities are gradually being expanded to encompass all kinds of biodiversity biobanks such as culture collections, zoological gardens, aquaria, arboreta, and environmental biobanks. Broadly speaking, these collections all provide long-term storage and standardized public access to samples useful for molecular research. GGBN facilitates sample search and discovery for its distributed member collections through a single entry point. It stores standardized information on mostly geo-referenced, vouchered samples, their physical location, availability, quality, and the necessary legal information on over 50,000 species of Earth’s biodiversity, from unicellular to multicellular organisms. The GGBN Data Portal and the GGBN Data Standard are complementary to existing infrastructures such as the Global Biodiversity Information Facility (GBIF) and International Nucleotide Sequence Database (INSDC). Today, many well-known open-source collection management databases such as Arctos, Specify, and Symbiota, are implementing the GGBN data standard. GGBN continues to increase its collections strategically, based on the needs of the research community, adding over 1.3 million online records in 2018 alone, and today two million sample data are available through GGBN. Together with Consortium of European Taxonomic Facilities (CETAF), Society for the Preservation of Natural History Collections (SPNHC), Biodiversity Information Standards (TDWG), and Synthesis of Systematic Resources (SYNTHESYS+), GGBN provides best practices for biorepositories on meeting the requirements of the Nagoya Protocol on Access and Benefit Sharing (ABS). By collaboration with the Biodiversity Heritage Library (BHL), GGBN is exploring options for tagging publications that reference GGBN collections and associated specimens, made searchable through GGBN’s document library. Through its collaborative efforts, standards, and best practices GGBN aims at facilitating trust and transparency in the use of genetic resources.


2020 ◽  
Vol 8 ◽  
Author(s):  
Sonia Ferreira ◽  
Rui Andrade ◽  
Ana Gonçalves ◽  
Pedro Sousa ◽  
Joana Paupério ◽  
...  

The InBIO Barcoding Initiative (IBI) Diptera 01 dataset contains records of 203 specimens of Diptera. All specimens have been morphologically identified to species level, and belong to 154 species in total. The species represented in this dataset correspond to about 10% of continental Portugal dipteran species diversity. All specimens were collected north of the Tagus river in Portugal. Sampling took place from 2014 to 2018, and specimens are deposited in the IBI collection at CIBIO, Research Center in Biodiversity and Genetic Resources. This dataset contributes to the knowledge on the DNA barcodes and distribution of 154 species of Diptera from Portugal and is the first of the planned IBI database public releases, which will make available genetic and distribution data for a series of taxa. All specimens have their DNA barcodes made publicly available in the Barcode of Life Data System (BOLD) online database and the distribution dataset can be freely accessed through the Global Biodiversity Information Facility (GBIF).


Author(s):  
Raul Sierra-Alcocer ◽  
Christopher Stephens ◽  
Juan Barrios ◽  
Constantino González‐Salazar ◽  
Juan Carlos Salazar Carrillo ◽  
...  

SPECIES (Stephens et al. 2019) is a tool to explore spatial correlations in biodiversity occurrence databases. The main idea behind the SPECIES project is that the geographical correlations between the distributions of taxa records have useful information. The problem, however, is that if we have thousands of species (Mexico's National System of Biodiversity Information has records of around 70,000 species) then we have millions of potential associations, and exploring them is far from easy. Our goal with SPECIES is to facilitate the discovery and application of meaningful relations hiding in our data. The main variables in SPECIES are the geographical distributions of species occurrence records. Other types of variables, like the climatic variables from WorldClim (Hijmans et al. 2005), are explanatory data that serve for modeling. The system offers two modes of analysis. In one, the user defines a target species, and a selection of species and abiotic variables; then the system computes the spatial correlations between the target species and each of the other species and abiotic variables. The request from the user can be as small as comparing one species to another, or as large as comparing one species to all the species in the database. A user may wonder, for example, which species are usual neighbors of the jaguar, this mode could help answer this question. The second mode of analysis gives a network perspective, in it, the user defines two groups of taxa (and/or environmental variables), the output in this case is a correlation network where the weight of a link between two nodes represents the spatial correlation between the variables that the nodes represent. For example, one group of taxa could be hummingbirds (Trochilidae family) and the second flowers of the Lamiaceae family. This output would help the user analyze which pairs of hummingbird and flower are highly correlated in the database. SPECIES data architecture is optimized to support fast hypotheses prototyping and testing with the analysis of thousands of biotic and abiotic variables. It has a visualization web interface that presents descriptive results to the user at different levels of detail. The methodology in SPECIES is relatively simple, it partitions the geographical space with a regular grid and treats a species occurrence distribution as a present/not present boolean variable over the cells. Given two species (or one species and one abiotic variable) it measures if the number of co-occurrences between the two is more (or less) than expected. If it is more than expected indicates a signal of a positive relation, whereas if it is less it would be evidence of disjoint distributions. SPECIES provides an open web application programming interface (API) to request the computation of correlations and statistical dependencies between variables in the database. Users can create applications that consume this 'statistical web service' or use it directly to further analyze the results in frameworks like R or Python. The project includes an interactive web application that does exactly that: requests analysis from the web service and lets the user experiment and visually explore the results. We believe this approach can be used on one side to augment the services provided from data repositories; and on the other side, facilitate the creation of specialized applications that are clients of these services. This scheme supports big-data-driven research for a wide range of backgrounds because end users do not need to have the technical know-how nor the infrastructure to handle large databases. Currently, SPECIES hosts: all records from Mexico's National Biodiversity Information System (CONABIO 2018) and a subset of Global Biodiversity Information Facility data that covers the contiguous USA (GBIF.org 2018b) and Colombia (GBIF.org 2018a). It also includes discretizations of environmental variables from WorldClim, from the Environmental Rasters for Ecological Modeling project (Title and Bemmels 2018), from CliMond (Kriticos et al. 2012), and topographic variables (USGS EROS Center 1997b, USGS EROS Center 1997a). The long term plan, however, is to incrementally include more data, specially all data from the Global Biodiversity Information Facility. The code of the project is open source, and the repositories are available online (Front-end, Web Services Application Programming Interface, Database Building scripts). This presentation is a demonstration of SPECIES' functionality and its overall design.


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