We’re sorry, but GBIF doesn’t work properly without JavaScript enabled.
Our website has detected that you are using an outdated insecure browser that will prevent you from using the site. We suggest you upgrade to a modern browser.
{{nav.loginGreeting}}
  • Get data
      • Occurrences
      • GBIF API
      • Species
      • Datasets
      • Occurrence snapshots
      • Hosted portals
      • Trends
  • How-to
    • Share data

      • Quick-start guide
      • Dataset classes
      • Data hosting
      • Standards
      • Become a publisher
      • Data quality
      • Data papers
    • Use data

      • Featured data use
      • Citation guidelines
      • GBIF citations
      • Citation widget
  • Tools
    • Publishing

      • IPT
      • Data validator
      • Scientific Collections
      • Suggest a dataset
      • New data model ⭐️
    • Data access and use

      • Hosted portals
      • Data processing
      • Derived datasets
      • rgbif
      • pygbif
      • MAXENT
      • Tools catalogue
    • GBIF labs

      • Species matching
      • Name parser
      • Sequence ID
      • Relative observation trends
      • GBIF data blog
  • Community
    • Network

      • Participant network
      • Nodes
      • Publishers
      • Network contacts
      • Community forum
      • alliance for biodiversity knowledge
    • Volunteers

      • Mentors
      • Ambassadors
      • Translators
      • Citizen scientists
    • Activities

      • Capacity enhancement
      • Programmes & projects
      • Training and learning resources
      • Data Use Club
      • Living Atlases
  • About
    • Inside GBIF

      • What is GBIF?
      • Become a member
      • Governance
      • Implementation plan
      • Work Programme
      • Funders
      • Partnerships
      • Release notes
      • Contacts
    • News & outreach

      • News
      • Newsletters and lists
      • Events
      • Ebbe Nielsen Challenge
      • Graduate Researchers Award
      • Science Review
      • Data use
  • User profile

River sediments Metagenome

Dataset homepage

Citation

MGnify (2019). River sediments Metagenome. Sampling event dataset https://doi.org/10.15468/zcxqqk accessed via GBIF.org on 2023-01-26.

Description

Mining activities have introduced contamination to surrounding aquatic and terrestrial environments, causing adverse impacts to human health and the environment. Indigenous microbial communities are responsible for biogeochemical cycling in diverse environments, indicating the potential to remediate the contamination introduced by the mining activities. Antimony has been extensively mined in China and Sb contamination in mining areas has been frequently encountered. However, the microbial composition and structure in response to antimony contamination has remained overlooked. Here we selected a watershed heavily contaminated by an antimony tailing from an upstream mine. We obtained comprehensive geochemical data (specifically, physical-chemical properties and different antimony extraction fractions) from river water and sediments at different depths. In addition, the indigenous microbial communities were profiled by high-throughput sequencing from 16 sediment samples (535,390 valid reads).

Sampling Description

Sampling

Mining activities have introduced contamination to surrounding aquatic and terrestrial environments, causing adverse impacts to human health and the environment. Indigenous microbial communities are responsible for biogeochemical cycling in diverse environments, indicating the potential to remediate the contamination introduced by the mining activities. Antimony has been extensively mined in China and Sb contamination in mining areas has been frequently encountered. However, the microbial composition and structure in response to antimony contamination has remained overlooked. Here we selected a watershed heavily contaminated by an antimony tailing from an upstream mine. We obtained comprehensive geochemical data (specifically, physical-chemical properties and different antimony extraction fractions) from river water and sediments at different depths. In addition, the indigenous microbial communities were profiled by high-throughput sequencing from 16 sediment samples (535,390 valid reads).

Method steps

  1. Pipeline used: https://www.ebi.ac.uk/metagenomics/pipelines/4.1

Taxonomic Coverages

Geographic Coverages

Bibliographic Citations

Contacts

originator
Rutgers University
metadata author
Rutgers University
administrative point of contact
Rutgers University
What is GBIF? API FAQ Newsletter Privacy Terms and agreements Citation Code of Conduct Acknowledgements
Contact GBIF Secretariat Universitetsparken 15 DK-2100 Copenhagen Ø Denmark