Inferring Species Interactions From Co-occurrence Networks With Environmental DNA Metabarcoding Data in a Coastal...

Area of Science:

• Ecology
• Environmental Science
• Molecular Ecology

Background:

• Understanding biotic interactions is crucial for predicting ecosystem vulnerability to climate change.
• Environmental DNA (eDNA) metabarcoding enables exploration of interspecific interactions in ecological communities.
• The reliability of co-occurrence networks derived from eDNA for representing biotic interactions requires validation.

Purpose of the Study:

• To compare the spatio-temporal variability in structure and complexity of co-occurrence networks and food webs.
• To evaluate the ability of eDNA-derived co-occurrence networks to detect ecological processes.
• To assess the representation of different interaction types within eDNA-derived networks.

Main Methods:

• Utilized 60 eDNA samples from a North Sea coastal ecosystem, covering vertebrates and other eukaryotes.
• Constructed and analyzed co-occurrence networks and food webs.
• Compared topological characteristics and identified highly connected species across spatial and temporal subsets.

Main Results:

• Consistent trends were observed in topological characteristics between eDNA co-occurrence networks and food webs.
• eDNA co-occurrence networks demonstrated an ability to detect real ecological processes.
• Trophic interactions constituted a minority of significant co-occurrences in the networks.

Conclusions:

• eDNA-derived co-occurrence networks offer support for inferring ecological interactions.
• Further research is needed to differentiate interaction types and address methodological limitations like species detection uncertainty.
• Ecological complexities, such as generalist predator behavior and non-trophic interactions, may influence network structures.