DOI: 10.5061/dryad.rfj6q57gg
title: Data from: Predator-prey interactions in the Arctic: DNA-metabarcoding reveals that nestling diet of snow buntings reflects arthropod seasonality

description: Tundra arthropods are of considerable ecological importance as a seasonal
 food source for many arctic-breeding birds. Dietary composition
 and food preferences are rarely known, complicating assessments
 of ecological interactions in a changing environment. In our field study,
 we investigated nestling diet of snow buntings (Plectrophenax
 nivalis (L., 1758)) breeding in Svalbard. We collected  faecal
 samples from 8-day-old nestlings and assessed dietary composition by
 DNA-metabarcoding. Simultaneously, the availability of potential
 prey arthropods was measured by pitfall-trapping. Molecular analyses of
 nestling faeces identified 31 arthropod taxa in the diet, whose
 proportions changed throughout the brood-rearing period. Changes
 in nestling diet matched varying abundances and emergence
 patterns of the tundra arthropod community. Snow buntings provisioned
 their offspring mainly with Diptera (true flies) based on both
 presence/absence and relative read abundance of diet items. At
 the beginning of the season in June, Chironomidae (non-biting midges) and
 the scathophagid fly Scathophaga furcata (Say, 1823) dominated
 the diet, whereas the muscid fly Spilogona dorsata (Zetterstedt, 1845)
 dominated the diet later in July. When accounted for availability, muscid
 flies were selected positively amongst the most often provisioned
 food taxa. Our study demonstrates the ecological role of the snow
 bunting as a generalist arthropod predator and highlights
 DNA-metabarcoding as a non-invasive technique for diet analyses with high
 taxonomical precision if sufficient DNA-sequence libraries are
 available.
description: Please refer to the published paper associated with this dataset,
 which provides a detailed description of the data collection
 methods.
description: # Title of Dataset Data from: Predator-prey interactions in the Arctic:
 DNA-metabarcoding reveals that nestling diet of snow buntings reflects
 arthropod seasonality The dataset consists of 1. Raw count-data from
 pitfall trapping (pitfall.csv) 2. Raw sequencing-data (raw_fastq.zip with
 fastq-files of all samples and metadata information) 3. Metadata
 information for the faecal samples (metadata_feacal_samples.csv ) 4. Raw
 output from mBRAVE-analysis (mBRAVE_data.tsv) 5. List of species with
 assigned linnean names (species_names.csv) Please refer to the published
 paper associated with this dataset, which provides a detailed description
 of the data collection methods. ## Description of the data and file
 structure pitfall.csv includes all pitfall trap samples in rows, with Date
 (date when pitfall trap samples were collected), Habitat (wet/dry) and
 taxa (counts per sample) as columns. Please refer to appendix A of the
 published papers associated with this dataset for more information on
 pitfall sampling. raw_fastq.zip includes 23 fastq-files from single-end
 1x300bp Illumina NextSeq 500 sequencing of snow bunting faecal samples.
 Please refer to the published paper associated with this dataset for more
 information on molecular methods. 01.fastq 02.fastq 03.fastq 04.fastq
 05.fastq 06.fastq 07.fastq 08.fastq 09.fastq 10.fastq 11.fastq 12.fastq
 13.fastq 14.fastq 15.fastq 16.fastq 17.fastq 18.fastq 19.fastq 20.fastq
 21.fastq 22.fastq NEG.fastq metadata_feacal_samples.csv includes all
 faecal samples as rows and sample_identifier (name of fastq-file),
 nest_location (Endalen/Isdammen), nest_nr (1 to 9), date (date of faecal
 sampling), type (sample from chick or fresh defecation from the nest),
 coord.X and coord.Y (X and Y geographic coordinates in EPSG:4326-WGS84
 format) as columns. NEG refers to the negative control (distilled water).
 Please refer to the published paper associated with this dataset for more
 information on faecal sample collection procedures. mBRAVE_data.tsv
 includes the raw output of the mBRAVE analyses on the above fastq-files as
 run in January 2021 (please refer to mBRAVE
 ([www.mbrave.net](http://www.mbrave.net)) and the published paper
 associated with this dataset for more information). Since BOLD-databases
 get regularly updated, a re-run of the analysis with the same mBRAVE
 parameters could likely lead to slightly different analyses results,
 therefore we include this file in the dataset as well. Note that DRYAD
 does not allow empty cells; we have therefore modiefied the original
 output by inserting "NA" in all empty cells of the mBRAVE-output
 (empty species/genus rows). species_names.csv includes all the names of
 species retained after mBRAVE and manual filtering as rows and species
 (name of species in mBRAVE-output), bin_uri (Barcode-Identification-Number
 in BOLD, mBRAVE-output), Svalbard_species (Linnean name assigned by the
 authors that is presented in the publication associated with this dataset)
 and orig_description (Name and year of the original description of the
 Svalbard_species) as columns. Note that Stur & Ekrem 2020 refers to
 not formally described species as presented in Stur, E., & Ekrem, T.
 (2020). The Chironomidae (Diptera) of Svalbard and Jan Mayen. Insects,
 11(3), 183. doi: 10.3390/insects11030183 ## Sharing/Access information
 Links to other publicly accessible locations of the data: * only on DRYAD
 Data was derived from the following sources: * the data is original