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Omnivory, vertical food‐web structure and system productivity: stable isotope analysis of freshwater planktonic food webs

2012· article· en· W4231634828 on OpenAlexafffund

Bibliographic record

VenueFreshwater Biology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaFetzer Institute
KeywordsPlanktivoreTrophic levelFood webProductivityZooplanktonEcologyPlanktonTrophic cascadePhytoplanktonTrophic state indexOmnivoreIsotope analysisBiologyPrimary producersEnvironmental scienceδ15NStable isotope ratioPredationδ13CNutrient

Abstract

fetched live from OpenAlex

Summary 1. The energetic hypothesis proposes that the vertical structure of food webs should increase in height with increasing system productivity. I measured the trophic positions and extent of trophic separation between the invertebrate planktivores Mysis relicta and Chaoborus spp. and their putative zooplankton prey along a gradient of lake productivity with the use of stable nitrogen isotopes. 2. In lakes of low productivity, these planktivores were found to be herbivorous, becoming omnivorous at intermediate lake productivities, and only able to be truly zooplanktivorous as lakes approached mesotrophy. A subsequent secondary analysis of literature data revealed that the strength of top‐down trophic cascades among these organisms increased with lake productivity as reflected by relationships between the abundance of planktivores and that of phytoplankton. 3. Increased omnivory under conditions of low productivity, effectively shortening the vertical structure of food webs as predicted by the energetic hypothesis, may produce increased community stability.

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)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.213
Teacher spread0.204 · 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

Citations25
Published2012
Admission routes2
Has abstractyes

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