Seasonal and ontological variation in diet and age-related differences in prey choice, by an insectivorous songbird
Data files
Aug 09, 2022 version files 4.16 GB
-
fastalist_chewRW.txt
-
oligo_chewRW.txt
-
README.txt
-
SD-CO1-1-290519_S1_L001_R1_001.fastq.gz
-
SD-CO1-1-290519_S1_L001_R2_001.fastq.gz
Abstract
The diet of an individual animal is subject to change over time, both in response to short-term food fluctuations and over longer time scales as an individual ages and meets different challenges over its life cycle. A metabarcoding approach was used to elucidate the diet of different life stages of a migratory songbird, the Eurasian reed warbler (Acrocephalus scirpaceus) over the 2017 summer breeding season in Somerset, UK. The faeces of adult, juvenile and nestling warblers were screened for invertebrate DNA, enabling the identification of prey species. Dietary analysis was coupled with monitoring of Diptera in the field using yellow sticky traps. Seasonal changes in warbler diet were subtle whereas age class had a greater influence on overall diet composition. Age classes showed high dietary overlap, but significant dietary differences were mediated through the selection of prey; i) from different taxonomic groups, ii) with different habitat origins (aquatic versus terrestrial) and iii) of different average approximate sizes. Our results highlight the value of metabarcoding data for enhancing ecological studies of insectivores in dynamic environments.
Methods
The dataset comprises the raw Paired-end Illumina sequencing reads from reed warbler dietary samples collected in Somerset in 2017. High-throughput sequencing was carried out on an Illumina MiSeq in 2019 at Cardiff University, Genomics Hub. Details of the bioinformatics pipeline used to process this data can be found with the publication (scripts in Supplemental Information). Along with the sequence data, an oligos file and fasta file are provided for use in the bioinformatics pipeline. These have the sample IDs and MID-tagged primers used in the Mothur step and for demultiplexing.
Usage notes
Files can be opened with any text editor. For details of the programs used in the bioinformatics pipeline, please refer to the original publication.