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Record W2129660839 · doi:10.1139/f07-189

Seasonal variations in stable isotope ratios of juvenile coho salmon (<i>Oncorhynchus kisutch</i>) from western Washington rivers

2008· article· en· W2129660839 on OpenAlexvenueno aff
William L. Reichert, Correigh M. Greene, Robert E. Bilby

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsOncorhynchusJuvenileFish migrationFisheryTributaryChinook windTroutEscapementBiologySmoltificationSalmoOverwinteringNutrientSalmonidaeEcologyFish <Actinopterygii>Geography

Abstract

fetched live from OpenAlex

Salmon carcasses provide a marine derived nutrient (MDN) subsidy to river systems, but the extent to which it affects juvenile salmon growth is unclear. To evaluate temporal and spatial nutrient contributions from watershed sources and MDNs using stable isotopes, Skagit River (Washington, USA) juvenile coho salmon (Oncorhynchus kisutch) were collected. Muscle samples were taken from fry through smolts to measure temporal changes in δ15N and δ13C. δ15N and δ13C levels declined from emergence until fall, when they approached values for resident cutthroat trout (Oncorhynchus clarkii) collected above anadromous barriers. Muscle δ13C was highly variable and did not increase subsequently. However, coho salmon δ15N increased during the winter. March coho salmon parr δ15N levels suggested high variability in carcass availability for consumption. During the next spring, δ15N levels again declined. In Griffin Creek, a Snoqualmie River tributary, a significant relationship between carcass density and δ15N and δ13C levels was found in March coho salmon parr. At high spawner densities, some parr δ15N exceeded carcass values; however, parr δ13C increased moderately. These findings show that stable isotope data provide insights on seasonal sources of nutrients. In addition, results indicate that March coho salmon parr δ15N levels would be a useful index of carcass availability for overwintering juvenile consumption.

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 score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.014
GPT teacher head0.209
Teacher spread0.195 · 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

Citations14
Published2008
Admission routes1
Has abstractyes

Explore more

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