Approaches to integrating genetic data into ecological networks.

Area of Science:

• Ecology
• Molecular Biology
• Bioinformatics

Background:

• Molecular tools are increasingly used to study trophic interactions.
• Network ecology aims to represent these interactions in a structured format.
• DNA data offers new possibilities for constructing detailed interaction networks.

Purpose of the Study:

• To demonstrate and compare three DNA-based methods for building ecological interaction networks.
• To discuss the analytical considerations for each method.
• To construct the first molecular-based network of networks.

Main Methods:

• Sanger sequencing for single specimen identification.
• Targeting multiple DNA loci for complex identifications from samples like feces.
• DNA metabarcoding with analysis of sequence data (MOTU, BLAST, BIN association) for mixed templates.

Main Results:

• Sanger sequencing provides quantifiable and well-resolved networks.
• Multi-locus DNA methods offer good resolution but challenging quantification.
• DNA metabarcoding is complex but enables analysis of mixed samples, yielding a large network of 3,304 interactions.

Conclusions:

• Different DNA-based methods have varying strengths and weaknesses for network ecology.
• The study presents a comprehensive molecular-based network of interactions.
• This research provides a framework for integrating molecular data into ecological network analysis.