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Record W1999929976 · doi:10.1111/eff.12120

Density‐dependent territory size and individual growth rate in juvenile<scp>A</scp>tlantic salmon (<i><scp>S</scp>almo salar</i>)

2014· article· en· W1999929976 on OpenAlexafffund
Amanda A. Lindeman, James W. A. Grant, Cyndy M. Desjardins

Bibliographic record

VenueEcology Of Freshwater Fish · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of OttawaConcordia UniversityCarleton University
FundersInstitute of Materials Research and EngineeringNatural Sciences and Engineering Research Council of CanadaFaculty of Arts and SciencesConcordia University
KeywordsTerritorialitySalmoPopulation densityRange (aeronautics)JuvenileGrowth ratePopulation sizeDensity dependenceEcologyBiologyPopulationEnvironmental scienceFisheryFish <Actinopterygii>MathematicsDemographyGeometry

Abstract

fetched live from OpenAlex

Abstract Whether territoriality regulates population size depends on the flexibility of territory size, but few studies have quantified territory size over a broad range of densities. While juvenile salmonids in streams exhibit density‐dependent mortality and emigration, consistent with space limitation, there has been relatively little study of how territory size and individual growth rate change over a broad range of densities, particularly in field experiments. Consequently, we manipulated the density (range = 0.25–8 m −2 ) of young‐of‐the‐year ( YOY ) Atlantic salmon ( Salmo salar ) in mesh enclosures erected in a natural stream to test whether (i) territory size is fixed, decreases continuously or decreases towards an asymptotic minimum size as density increases; and (ii) individual growth rate decreases as a negative power curve with density as in observational field studies. Territory size decreased with increasing density, consistent with an asymptotic minimum size of about 0.13 m 2 for a 5‐cm fish. Individual growth rate also decreased with density, although the magnitude of decrease was steeper than in observational studies. Our results suggest a limit to how small territories can be compressed, which will set the upper limit to the local density in a habitat. The density‐dependent changes in territory size and individual growth rate will both play a role in the regulation of stream 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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.007
GPT teacher head0.187
Teacher spread0.180 · 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.

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
Published2014
Admission routes2
Has abstractyes

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