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Trophic structure of a boreal forest arthropod community revealed by stable isotope (δ<sup>13</sup>C, δ<sup>15</sup>N) analyses

2009· article· en· W2034226232 on OpenAlexaffabout
Pamela M. Bennett, Keith A. Hobson

Bibliographic record

VenueEntomological Science · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Saskatchewan
Fundersnot available
KeywordsTrophic levelBiologyEcologyArthropodOdonataTerrestrial ecosystemSpringtailEcosystem

Abstract

fetched live from OpenAlex

Abstract Terrestrial arthropods are important components of boreal ecosystems but relatively little is known about their trophic structure within communities. We measured δ13C and δ15N values in a broad range of arthropod taxa (Coleoptera, Diptera, Ephemeroptera, Homoptera, Hymenoptera, Lepidoptera, Odonata, Orthoptera, Araneae) from boreal forest in Prince Albert National Park, Saskatchewan, Canada. Isotopic measurements supported previous conventional investigations on foraging niches based on stomach content analysis and direct feeding observations but additional, new information was also obtained using the stable isotope approach. Significant differences were observed in both δ15N and δ13C values between various orders and families or superfamilies within orders. Higher variance in stable isotope values for scavengers (e.g. carrion beetles; Coleoptera, Silphidae) and generalists (e.g. ground beetles; Coleoptera, Carabidae) was found compared to specialists (e.g. grasshoppers; Orthoptera). Consistent isotopic differences between terrestrial and aquatic species were not found. However, aquatic insect δ13C values tended to be lower than those of their terrestrial counterparts. We discuss the potential for using stable isotope methods to reconstruct trophic linkages and interaction involving arthropods.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.021
GPT teacher head0.289
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations39
Published2009
Admission routes2
Has abstractyes

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