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.
Raw labeled reads from faecal samples of Calidris alpina, C. alba and Plectrophenax nivalis
Collected 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.fastq
Raw labeled reads from samples of Pardosa glacialis, Xysticus deichmanni, X. labradorensis, Erigone arctica, and Emblyna borealis
Collected 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.fastq
OTU sequences
Clustered 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.fa
Readmap linking trimmed reads and samples
The readmap shows read count for each sample. The readmap is constructed using USEARCH software.
readmap.tab
Technical data sheet for IonTorrent PGM runs
The data generated by Ion Torrent PGM for each run in the study.
IonTorrent_Data_Sheet.pdf
Command pipeline used for bioinformatics
The 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.sh
The final readmap
This 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.xlsx
Q20 reads from Spider samples for Spider data2
Collected from the field. DNA extracted from half individuals. Sequenced using 454 pyrosequencing.
Spider2_data.fas
OTU sequences for Spider data2
Clustered 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.fa
Readmap linking trimmed reads and samples for Spider data2
The readmap shows read count for each sample. The readmap is constructed using USEARCH software.
Spider2_readmap.tab
Command pipeline used for bioinformatics for Spider data2
The 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