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Record W1997930910 · doi:10.1139/f01-132

Effect of predation on the low-density dynamics of vendace: significance of the functional response

2001· article· en· W1997930910 on OpenAlexvenueno aff
Outi Heikinheimo

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPerchPredationBrown troutSalmoBiologyFisheryFishingPiscivorePelagic zonePopulationEcologyFunctional responsePopulation densityDensity dependencePredatorFish <Actinopterygii>

Abstract

fetched live from OpenAlex

During the past 20 years, there have been prolonged vendace (Coregonus albula) recessions in several Finnish lakes. Hypotheses have been proposed that predation by brown trout (Salmo trutta m. lacustris) or perch (Perca fluviatilis) on young-of-the-year vendace could prevent the recovery of the vendace stocks from a low-density state. In this study, dynamic modelling was applied to examine the effect of predation, assuming a dome-shaped spawning stock–recruitment relationship for vendace, type II or III functional responses to predation by brown trout and perch, and a constant rate of fishing. The results showed that the form of the functional response is crucial in determining the significance of the predation on vendace stocks that have a steep dome-shaped stock–recruitment relationship. In all cases, however, predation by perch had more effect than that by brown trout, probably due to perch occupying the pelagic zone when the vendace stock is sparse. This may make the mortality of vendace increase with decreasing population density (depensatory mortality) at certain density levels.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.197
Teacher spread0.188 · 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

Citations27
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicFish Ecology and Management Studies→French-language works237,207→