Metabarcoding data

Context

GBIF has recently launched the pilot phase for the Metabarcoding Data Programme, intended to improve GBIF’s integration of DNA metabarcoding data on biodiversity. In part a response to the ongoing effort to enrich the GBIF data model, the programme establishes a framework for GBIF nodes to support and engage communities of researchers who collect and manage such evidence using a newly developed tool, the Metabarcoding Data Toolkit (MDT).

Learning objectives

After completing this module, you should be able to perform the following:

  • Define and explain what DNA metabarcoding data are

  • Describe the significance of metabarcoding data

  • Identify the key components and workflow of metabarcoding data processing

  • Identify opportunities for working with the DNA community

  • Understand practical applications of metabarcoding for biodiversity monitoring.

  • Compare strengths and limitations of metabarcoding versus traditional methods.

  • Recognize the types of data produced and how such data could be mobilized through GBIF.

  • Demonstrate knowledge of the Metabarcoding Data Toolkit (MDT)

  • Standardize and format metabarcoding datasets

  • Publish metabarcoding datasets to GBIF

Trainers

The following trainers have developed the content for this topic:

Luke Jimu, Node Manager, Zimbabwe

Stephen Formel, Data Officer, OBIS Secretariat

Secretariat consultant: Tobias Guldberg Frøslev

Preparation

Complete the following activities to prepare for the onsite sessions:

  1. Explore the materials on the Metabarcoding data programme.

  2. Create an account on GBIF.org (if you don’t already have one).

  3. Login to https://mdt.gbif-test.org/ using your GBIF.org username/password.

Understanding DNA Metabarcoding in Biodiversity Research

This presentation introduces the training topic and provides a basis for understanding DNA metabarcoding in biodiversity research.

 

 

Decoding metabarcoding

For this activity, group members will look at practical applications of metabarcoding for biodiversity monitoring and compare strengths and limitations of metabarcoding versus traditional methods.

Instructions

  1. Appoint a recorder and a presenter.

  2. Select a scenario.

  3. Brainstorm answers to questions.

  4. Report back across groups.

Scenarios

Freshwater Monitoring

Scenario: A national park authority wants to monitor aquatic invertebrate diversity in rivers to assess ecosystem health.

Traditional approach: Kick-sampling, expert ID under microscope.

Task: Consider how metabarcoding could complement or replace this, what data it generates, and why it matters.

Soil Microbial Communities

Scenario: An agricultural research institute is studying soil microbes that contribute to nitrogen fixation and drought tolerance in crops.

Traditional approach: Culture-based methods.

Task: Discuss how metabarcoding improves coverage of microbial diversity and generates data usable for agri-biodiversity planning.

Invasive Species Detection

Scenario: A port authority is monitoring ballast water for invasive species introduction.

Traditional approach: Manual sampling and visual identification.

Task: Explore how metabarcoding could provide faster, broader detection.

Pollinator Communities

Scenario: A conservation NGO wants to identify pollinator species visiting crops in fragmented landscapes.

Traditional approach: Manual observation and specimen collection.

Task: Consider DNA metabarcoding of pollen loads as a method for detecting plant–pollinator networks.

Questions

  • Application: How could metabarcoding be applied in this scenario?

  • Comparison: Why might metabarcoding be better suited (or not) compared to traditional methods?

  • Data Types: What kinds of biodiversity data would this generate (e.g., species occurrence, relative abundance, community composition, functional diversity)?

  • GBIF Relevance: How could this data be mobilized to GBIF, and who would benefit from its use?

  • Challenges: What are potential obstacles (technical, capacity, data standards, cost, reference library gaps)?

At the conclusion of the activity, each group will select someone to report back in plenary.

From the Field to GBIF: Metabarcoding Data Mobilisation Workflow

This presentation examines the metabarcoding data mobilization workflow and introduces the Metabarcoding Data Toolkit.

 

 

Metabarcoding Data Toolkit (MDT)

For this activity, individuals will perform a series of steps using the MDT Sandbox (Demo Installation) and an example dataset to learn how the tool works.

Instructions

  1. Login to https://mdt.gbif-test.org/ with your GBIF login.

  2. Please bring up any points of confusion or questions you might have so we can discuss them as a group.

Action plan

The trainers will conclude the topic and offer an action plan for you to reflect on this topic post-training.