scholarly journals Dataset from the Snakes (Serpentes, Reptiles) collection of the Museu Paraense Emílio Goeldi, Pará, Brazil

2019 ◽  
Vol 7 ◽  
Author(s):  
Ana Lúcia da Costa Prudente ◽  
Lorran Ramos ◽  
Timóteo Silva ◽  
João Sarmento ◽  
Angelo Dourado ◽  
...  
Keyword(s):  
Amazon Region ◽  
Public Consultation ◽  
Amazon Rainforest ◽  
Global Biodiversity Information Facility ◽  
Global Biodiversity ◽  
Biodiversity Information

We present a dataset with information from the snake collection of the Museu Paraense Emílio Goeldi, known as the “Ophidia Collection”. This collection currently has 26,728 specimens of snakes, including 9 families, 66 genera and 220 species. For the most part, it represents material from the Amazon Region. Specimens are preserved mostly in wet (alcohol) preparation, with some samples preserved in dry form, as is the case of the shells and skeletons of turtles. The dataset is now available for public consultation on the Global Biodiversity Information Facility portal (https://doi.org/10.15468/lt0wet). The Herpetological collection of Museu Paraense Emílio Goeldi comprises the largest collection of its kind in the Amazon region with about 100,000 specimens of amphibians and reptiles (chelonians, alligators, lizards, snakes and amphisbaenians). This collection currently has 26,728 specimens of snakes, including 9 families, 66 genera and 220 species, some of which are endemic to the Amazon rainforest region. The Museu Paraense Emílio Goeldi is the second oldest institution of science in Brazil in activity, founded in 1866.

scholarly journals Harvestmen occurrence database (Arachnida, Opiliones) of the Museu Paraense Emílio Goeldi, Brazil

2019 ◽  
Vol 7 ◽  
Author(s):  
Valéria da Silva ◽  
Manoel Aguiar-Neto ◽  
Dan Teixeira ◽  
Cleverson Santos ◽  
Marcos de Sousa ◽  
...  
Keyword(s):  
Public Consultation ◽  
Biodiversity Data ◽  
Global Biodiversity Information Facility ◽  
The Third ◽  
The World ◽  
Northern Brazil ◽  
Global Biodiversity ◽  
The Government ◽  
Biodiversity Information ◽  
Brazilian Biodiversity

We present a dataset with information from the Opiliones collection of the Museu Paraense Emílio Goeldi, Northern Brazil. This collection currently has 6,400 specimens distributed in 13 families, 30 genera and 32 species and holotypes of four species: Imeri ajuba Coronato-Ribeiro, Pinto-da-Rocha & Rheims, 2013, Phareicranaus patauateua Pinto-da-Rocha & Bonaldo, 2011, Protimesius trocaraincola Pinto-da-Rocha, 1997 and Sickesia tremembe Pinto-da-Rocha & Carvalho, 2009. The material of the collection is exclusive from Brazil, mostly from the Amazon Region. The dataset is now available for public consultation on the Sistema de Informação sobre a Biodiversidade Brasileira (SiBBr) (https://ipt.sibbr.gov.br/goeldi/resource?r=museuparaenseemiliogoeldi-collection-aracnologiaopiliones). SiBBr is the Brazilian Biodiversity Information System, an initiative of the government and the Brazilian node of the Global Biodiversity Information Facility (GBIF), which aims to consolidate and make primary biodiversity data available on a platform (Dias et al. 2017). Harvestmen or Opiliones constitute the third largest arachnid order, with approximately 6,500 described species. Brazil is the holder of the greatest diversity in the world, with more than 1,000 described species, 95% (960 species) of which are endemic to the country. Of these, 32 species were identified and deposited in the collection of the Museu Paraense Emílio Goeldi.

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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