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Record W2590574971 · doi:10.1139/cjfas-2016-0047

Interactions between local population density and limited habitat resources determine movements of juvenile Atlantic salmon

2017· article· en· W2590574971 on OpenAlexvenueno aff
Maxim Teichert, Anders Foldvik, Sigurd Einum, Anders G. Finstad, Torbjørn Forseth, Ola Ugedal

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNorges Forskningsråd
KeywordsSalmoJuvenilePopulation densityFisheryDensity dependencePopulationHabitatBiologyEcologyOncorhynchusCompetition (biology)Juvenile fishFish <Actinopterygii>Environmental science

Abstract

fetched live from OpenAlex

Competition for limited resources and the resulting density-dependent processes are key factors in driving stream salmonid population dynamics. Here we test for the combined effects of density and shelter availability on the movement of juvenile Atlantic salmon (Salmo salar) in a Norwegian river. Individually marked, hatchery-reared salmon juveniles were released at 26 sites along a 2.5 km long stretch and recaptured after 12 months. The spatial variation in shelter availability and density of salmonids was quantified prior to the release. We found no effect of released fish number on the number of marked salmon moving more than 12.5–112.5 m away from their release site. However, the ratio of pre-experiment fish density per shelter was positively related to the number of movers. Thus, fish that were released at sites where the amount of shelter was low relative to the density of the pre-experiment population were more likely to move. These results support the prediction from smaller scale experimental studies that shelter availability may act to determine local carrying capacity in stream-living salmonid populations.

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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.022
GPT teacher head0.233
Teacher spread0.211 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

Explore more

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