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Optimizing a Novel eDNA-Based Framework for Reef Fish Biodiversity Monitoring Using an Autonomous Filtration System

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Summary

Environmental DNA (eDNA) metabarcoding offers a scalable solution for fish biodiversity monitoring in remote marine ecosystems. This study presents an optimized field workflow, enhancing data accuracy and comprehensiveness compared to traditional methods.

Keywords:
French PolynesiaeDNAfish biodiversitymetabarcodingnanopore

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Area of Science:

  • Marine biology
  • Environmental science
  • Molecular ecology

Background:

  • Environmental DNA (eDNA) metabarcoding is a powerful tool for biodiversity assessment.
  • Challenges remain in implementing eDNA methods in remote marine environments.

Purpose of the Study:

  • To develop and validate a field-adapted eDNA metabarcoding workflow for fish biodiversity monitoring in coral reefs.
  • To optimize sampling and analysis methods for remote aquatic ecosystems.

Main Methods:

  • Utilized large-volume water sampling with a custom autonomous underwater filtration system.
  • Optimized filter porosity (1.2 μm) and water volume (20 L) for optimal fish eDNA yield.
  • Employed mitochondrial 12S rRNA gene amplification and Oxford Nanopore Technologies sequencing.
  • Developed a high-resolution 12S reference database for French Polynesian fish species.
  • Compared eDNA data with visual census observations across various reef habitats and temporal scales.

Main Results:

  • The optimized workflow demonstrated high efficiency in collecting fish eDNA.
  • eDNA metabarcoding provided a more comprehensive assessment of fish biodiversity richness than visual census.
  • Significant temporal biodiversity structures were identified, including diel variations.
  • The method proved scalable and cost-efficient for remote biodiversity monitoring.

Conclusions:

  • A fully integrated eDNA metabarcoding workflow was validated for diverse and remote marine ecosystems.
  • This approach enables high-resolution spatial and temporal biodiversity monitoring.
  • The study provides a cost-efficient framework for long-term biodiversity assessments in challenging environments.