Validating metabarcoding-based biodiversity assessments with multi-species occupancy models: A case study using...

Area of Science:

• Ecology
• Molecular Ecology
• Environmental Science

Background:

• Environmental DNA (eDNA) metabarcoding is a powerful tool for biodiversity assessment.
• However, imperfect detection rates in eDNA data can lead to biased ecological assessments.
• Existing methods often overlook sources of variation, impacting data reliability.

Purpose of the Study:

• To develop and present a robust analytical framework for eDNA metabarcoding data.
• To address challenges of imperfect detection and environmental variation in biodiversity assessments.
• To enhance the inferential power and reliability of eDNA-based ecological studies.

Main Methods:

• Development of a multi-scale, multi-species occupancy model.
• Incorporation of factors accounting for imperfect detection.
• Application and validation using a coastal marine case study.

Main Results:

• The developed occupancy model effectively accounts for imperfect detection in eDNA data.
• The model improves ecological inference by integrating environmental and experimental variations.
• Demonstrated enhanced inferential power in a coastal marine biodiversity assessment.

Conclusions:

• Occupancy models are crucial for accurate analysis of eDNA metabarcoding data.
• Accounting for detection probability significantly improves ecological inference and sampling design.
• This approach empowers practitioners to better utilize high-resolution biodiversity data from next-generation sequencing.