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Record W2033008259 · doi:10.1073/pnas.1316990111

Complementary molecular information changes our perception of food web structure

2014· article· en· W2033008259 on OpenAlexafffund
Helena Wirta, Paul D. N. Hebert, Riikka Kaartinen, Sean W. J. Prosser, Gergely Várkonyi, Tomas Roslin

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Guelph
FundersKoneen SäätiöGenome CanadaOntario GenomicsOntario Genomics InstituteGovernment of CanadaElla ja Georg Ehrnroothin SäätiöHelsingin Yliopisto
KeywordsPerceptionGlobeSpace (punctuation)Food webComputer scienceArcticEcologyData scienceGeographyBiologyTrophic levelNeuroscience

Abstract

fetched live from OpenAlex

How networks of ecological interactions are structured has a major impact on their functioning. However, accurately resolving both the nodes of the webs and the links between them is fraught with difficulties. We ask whether the new resolution conferred by molecular information changes perceptions of network structure. To probe a network of antagonistic interactions in the High Arctic, we use two complementary sources of molecular data: parasitoid DNA sequenced from the tissues of their hosts and host DNA sequenced from the gut of adult parasitoids. The information added by molecular analysis radically changes the properties of interaction structure. Overall, three times as many interaction types were revealed by combining molecular information from parasitoids and hosts with rearing data, versus rearing data alone. At the species level, our results alter the perceived host specificity of parasitoids, the parasitoid load of host species, and the web-wide role of predators with a cryptic lifestyle. As the northernmost network of host-parasitoid interactions quantified, our data point exerts high leverage on global comparisons of food web structure. However, how we view its structure will depend on what information we use: compared with variation among networks quantified at other sites, the properties of our web vary as much or much more depending on the techniques used to reconstruct it. We thus urge ecologists to combine multiple pieces of evidence in assessing the structure of interaction webs, and suggest that current perceptions of interaction structure may be strongly affected by the methods used to construct them.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.101

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.252
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations173
Published2014
Admission routes2
Has abstractyes

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