scholarly journals The Insect database in Dokdo, Korea: An updated version includes 22 newly recorded species on the island and one species in Korea

2020 ◽  
Author(s):  
Jihun Ryu ◽  
Young-Kun Kim ◽  
Sang Jae Suh ◽  
Kwang Shik Choi
Keyword(s):  
East Coast ◽  
First Record ◽  
Time Constraints ◽  
Small Islands ◽  
Volcanic Island ◽  
Global Biodiversity Information Facility ◽  
Insect Fauna ◽  
Insect Survey ◽  
Global Biodiversity ◽  
Biodiversity Information

Dokdo, an island toward the East Coast of South Korea, comprises 89 small islands. Dokdo is a volcanic island created by a volcanic eruption that promoted the formation of Ulleungdo (located in the East sea), which is ~87.525 km away from Dokdo. Dokdo is an important island because of geopolitics; however, because of certain investigation barriers such as weather and time constraints, the awareness of its insect fauna is less compared to that of Ulleungdo. Dokdo’s insect fauna was obtained as 10 orders, 74 families, and 165 species until 2017; subsequently, from 2018 to 2019, 23 unrecorded species were discovered via an insect survey. As per a recent study, the database of insect species on Dokdo has been identified as 10 orders, 81 families, 188 species, and 23 undetermined species. This database has been registered to the Global Biodiversity Information Facility (GBIF; www.GBIF.org), and is the first record for Dokdo’s insect fauna.

scholarly journals The Insect database in Dokdo, Korea: An updated version in 2020

2021 ◽  
Vol 9 ◽  
Author(s):  
Jihun Ryu ◽  
Young-Kun Kim ◽  
Sang Jae Suh ◽  
Kwang Shik Choi
Keyword(s):  
East Coast ◽  
First Record ◽  
Time Constraints ◽  
Small Islands ◽  
Global Biodiversity Information Facility ◽  
Insect Fauna ◽  
Insect Survey ◽  
Global Biodiversity ◽  
Volcanic Islands ◽  
Biodiversity Information

Dokdo, a group of islands near the East Coast of South Korea, comprises 89 small islands. These volcanic islands were created by an eruption that also led to the formation of the Ulleungdo Islands (located in the East Sea), which are approximately 87.525 km away from Dokdo. Dokdo is important for geopolitical reasons; however, because of certain barriers to investigation, such as weather and time constraints, knowledge of its insect fauna is limited compared to that of Ulleungdo. Until 2017, insect fauna on Dokdo included 10 orders, 74 families, 165 species and 23 undetermined species; subsequently, from 2018 to 2019, we discovered 23 previously unrecorded species and three undetermined species via an insect survey. As per our recent study, the database of insect species on Dokdo has been expanded to 10 orders, 81 families, 188 species and 23 undetermined species. This database has been registered in the Global Biodiversity Information Facility (GBIF; www.GBIF.org) and is the first record for insect fauna on Dokdo.

scholarly journals The InBIO Barcoding Initiative Database: DNA barcodes of Portuguese Diptera 01

2020 ◽  
Vol 8 ◽  
Author(s):  
Sonia Ferreira ◽  
Rui Andrade ◽  
Ana Gonçalves ◽  
Pedro Sousa ◽  
Joana Paupério ◽  
...  
Keyword(s):  
Species Level ◽  
Distribution Data ◽  
Dna Barcodes ◽  
Online Database ◽  
Global Biodiversity Information Facility ◽  
Life Data ◽  
Tagus River ◽  
Global Biodiversity ◽  
Biodiversity Information ◽  
Dipteran Species

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).

scholarly journals Using Global Biodiversity Information Facility Occurrence Data for Automated Invasive Alien Species Risk Mapping 

2020 ◽  
Vol 4 ◽  
Author(s):  
Amy Davis ◽  
Tim Adriaens ◽  
Rozemien De Troch ◽  
Peter Desmet ◽  
Quentin Groom ◽  
...  
Keyword(s):  
Alien Species ◽  
Vascular Plants ◽  
Invasive Alien Species ◽  
Risk Assessments ◽  
Sampling Effort ◽  
Global Biodiversity Information Facility ◽  
Global Biodiversity ◽  
Risk Maps ◽  
Species Occurrences ◽  
Biodiversity Information

To support invasive alien species risk assessments, the Tracking Invasive Alien Species (TrIAS) project has developed an automated, open, workflow incorporating state-of-the-art species distribution modelling practices to create risk maps using the open source language R. It is based on Global Biodiversity Information Facility (GBIF) data and openly published environmental data layers characterizing climate and land cover. Our workflow requires only a species name and generates an ensemble of machine-learning algorithms (Random Forest, Boosted Regression Trees, K-Nearest Neighbors and AdaBoost) stacked together as a meta-model to produce the final risk map at 1 km2 resolution (Fig. 1). Risk maps are generated automatically for standard Intergovernmental Panel on Climate Change (IPCC) greenhouse gas emission scenarios and are accompanied by maps illustrating the confidence of each individual prediction across space, thus enabling the intuitive visualization and understanding of how the confidence of the model varies across space and scenario (Fig. 2). The effects of sampling bias are accounted for by providing options to: use the sampling effort of the higher taxon the modelled species belongs to (e.g., vascular plants), and to thin species occurrences. use the sampling effort of the higher taxon the modelled species belongs to (e.g., vascular plants), and to thin species occurrences. The risk maps generated by our workflow are defensible and repeatable and provide forecasts of alien species distributions under further climate change scenarios. They can be used to support risk assessments and guide surveillance efforts on alien species in Europe. The detailied modeling framework and code are available on GitHub: https://github.com/trias-project.

Development and Deployment of an Ethnobotanical and Phytochemical Knowledge Database of Malaysia

2013 ◽  
Vol 64 (2) ◽  
Author(s):  
Shakina Mohd Talkah ◽  
Iylia Zulkiflee ◽  
Mohd Shahir Shamsir
Keyword(s):  
Scientific Literature ◽  
Pharmaceutical Compounds ◽  
South East Asia ◽  
Online Database ◽  
Global Biodiversity Information Facility ◽  
Knowledge Database ◽  
Global Biodiversity ◽  
Digital Knowledge ◽  
Biodiversity Information ◽  
Scientific Name

Currently, all the information regarding ethnobotanical, phytochemical and pharmaceutical information of South East Asia are scattered over many different publications, depositories and databases using various digital and analogue formats. Although there are taxonomic databases of medicinal plants, they are not linked to phytochemical and pharmaceutical information which are often resides in scientific literature. We present Phyknome; an ethnobotanical and phytochemical database with more than 22,000 species of ethnoflora of Asia. The creation of this database will enable a biotechnology researcher to seek and identify ethnobotanical information based on a species’ scientific name, description and phytochemical information. It is constructed using a digitization pipeline that allow high throughput digitization of archival data, an automated dataminer to mine for pharmaceutical compounds information and an online database to integrated these information. The main functions include an automated taxonomy, bibliography and API interface with primary databases such as Global Biodiversity Information Facility (GBIF). We believe that Phyknome will contribute to the digital knowledge ecosystem to elevate access and provide tools for ethnobotanical research and contributes to the management, assessment and stewardship of biodiversity. The database is available at http://mapping.fbb.utm.my/phyknome/.

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