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).

Obiettivi di apprendimento

Dopo aver completato questo modulo, dovreste essere in grado di:

  • 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.

Piano d’azione

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