DOI: 10.5061/dryad.cv8cr
title: Data from: Exposing the structure of an Arctic food web

description: How food webs are structured has major implications for their stability
 and dynamics. While poorly studied to date, arctic food webs are commonly
 assumed to be simple in structure, with few links per species. If this is
 the case, then different parts of the web may be weakly connected to each
 other, with populations and species united by only a low number of links.
 We provide the first highly resolved description of trophic link structure
 for a large part of a high-arctic food web. For this purpose, we apply a
 combination of recent techniques to describing the links between three
 predator guilds (insectivorous birds, spiders, and lepidopteran
 parasitoids) and their two dominant prey orders (Diptera and Lepidoptera).
 The resultant web shows a dense link structure and no compartmentalization
 or modularity across the three predator guilds. Thus, both individual
 predators and predator guilds tap heavily into the prey community of each
 other, offering versatile scope for indirect interactions across different
 parts of the web. The current description of a first but single arctic web
 may serve as a benchmark toward which to gauge future webs resolved by
 similar techniques. Targeting an unusual breadth of predator guilds, and
 relying on techniques with a high resolution, it suggests that species in
 this web are closely connected. Thus, our findings call for similar
 explorations of link structure across multiple guilds in both arctic and
 other webs. From an applied perspective, our description of an arctic web
 suggests new avenues for understanding how arctic food webs are built and
 function and of how they respond to current climate change. It suggests
 that to comprehend the community-level consequences of rapid arctic
 warming, we should turn from analyses of populations, population pairs,
 and isolated predator–prey interactions to considering the full set of
 interacting species.
description: Raw labeled reads from
 faecal samples of Calidris alpina, C. alba and Plectrophenax
 nivalisCollected while handling
 the birds or from the field while observing the birds. DNA extracted from
 individual pellets using Zymo Research Faecal Mini Kit. Sequenced using
 Ion Torrent PGM. FASTQ file header stands for:
 @READNUMBER;barcodelabel=SAMPLEID_COLLECTIONLOCALITY_DAY-MONTH-YEAR_BIRDSPECIES_BIRDAGE.labeled_reads_birds.fastqRaw labeled reads from samples of Pardosa glacialis, Xysticus deichmanni, X. labradorensis, Erigone arctica, and Emblyna borealisCollected from the field. DNA extracted from half individuals using Qiagen Animla Tissue Kit. Sequenced using Ion Torrent PGM. FASTQ file header stands for: @READNUMBER;barcodelabel=SAMPLEID. SampleID: Xd =labeled_reads_spiders.fastqOTU sequencesClustered to OTUs using USEARCH algorithm with default (97%) similarity. This way there is a little bit of oversplitting, and OTUs belonging to same biological species are clustered subsequently.label_otus.faReadmap linking trimmed reads and samplesThe readmap shows read count for each sample. The readmap is constructed using USEARCH software.readmap.tabTechnical data sheet for IonTorrent PGM runsThe data generated by Ion Torrent PGM for each run in the study.IonTorrent_Data_Sheet.pdfCommand pipeline used for bioinformaticsThe file contains all the commandds used in this study to generate the final data. The bioinformatics was carried out at servers on CSC - IT Center for SCience in Finland .Arctic_FoobWeb_commands_unix_csc.shThe final readmapThis readmap contains the final read counts for each sample. The difference to raw readmap is that some OTU's in this version have been clumped together. The information in this sheet was used as presense/absence data in the study.Readmap_final.xlsxQ20 reads from Spider samples for Spider data2Collected from the field. DNA extracted from half individuals. Sequenced using 454 pyrosequencing.Spider2_data.fasOTU sequences for Spider data2Clustered to OTUs using USEARCH algorithm with default (97%) similarity. This way there is a little bit of oversplitting, and OTUs belonging to same biological species are clustered subsequently.Spider2_label_otus.faReadmap linking trimmed reads and samples for Spider data2The readmap shows read count for each sample. The readmap is constructed using USEARCH software.Spider2_readmap.tabCommand pipeline used for bioinformatics for Spider data2The file contains all the commands used in this study to generate the final data. The bioinformatics was carried out at servers on CSC - IT Center for SCience in Finland .Spider2_commands_unix_csc.sh