Data from: Advancing the integration of multi-marker metabarcoding data in dietary analysis of trophic generalists

The application of DNA metabarcoding to dietary analysis of trophic
generalists requires using multiple markers in order to overcome problems
of primer specificity and bias. However, limited attention has been given
to the integration of information from multiple markers, particularly when
they partly overlap in the taxa amplified, and vary in taxonomic
resolution and biases. Here we test the use of a mix of universal and
specific markers, provide criteria to integrate multi-marker metabarcoding
data and a python script to implement such criteria and produce a single
list of taxa ingested per sample. We then compare the results of dietary
analysis based on morphological methods, single markers, and the proposed
combination of multiple markers. The study was based on the analysis of
115 faeces from a small passerine, the Black Wheatears (Oenanthe leucura).
Morphological analysis detected far fewer plant taxa (12) than either a
universal 18S marker (57) or the plant trnL marker (124). This may partly
reflect the detection of secondary ingestion by molecular methods.
Morphological identification also detected far fewer taxa (23) than when
using 18S (91) or the arthropod markers IN16STK (244) and ZBJ (231),
though each method missed or underestimated some prey items. Integration
of multi-marker data provided far more detailed dietary information than
any single marker and estimated higher frequencies of occurrence of all
taxa. Overall, our results show the value of integrating data from
multiple, taxonomically overlapping markers in an example dietary dataset.