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Data from: Predator-prey interactions in the Arctic: DNA-metabarcoding reveals that nestling diet of snow buntings reflects arthropod seasonality

Cite this dataset

Stolz, Christian et al. (2023). Data from: Predator-prey interactions in the Arctic: DNA-metabarcoding reveals that nestling diet of snow buntings reflects arthropod seasonality [Dataset]. Dryad. https://doi.org/10.5061/dryad.rfj6q57gg

Abstract

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.

README: 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) 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

Methods

Please refer to the published paper associated with this dataset, which provides a detailed description of the data collection methods.

Funding

Svalbard Science Forum, Award: RiS ID 10909