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Record W2301405993 · doi:10.1002/eco.1735

Fish feeding niche characterization over space and time in a natural boreal river

2016· article· en· W2301405993 on OpenAlexaffabout
Jaclyn M. Brush, Karen E. Smokorowski, Jérôme Marty, Michael Power

Bibliographic record

VenueEcohydrology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans CanadaUniversity of Waterloo
Fundersnot available
KeywordsNicheEnvironmental scienceBorealEcologyFish <Actinopterygii>Ecological nicheHydrology (agriculture)FisheryBiologyHabitatGeology

Abstract

fetched live from OpenAlex

Abstract Few studies have examined the temporal variability of fish feeding niche in response to variable flows and temperature or the temporal consistency of spatial differences in fish feeding niche within natural rivers. Using a 10‐year dataset from the boreal Batchawana River in Northern Ontario, we found that fish feeding niche was temporally invariant in the lower sampled river reaches but increased over time in the upper reaches of the river. A significant relationship between the standard deviations of mean δ 15 N and mean daily summer flow was found. No other significant relationships between measures of flow or temperature variability and variability in δ 13 C or δ 15 N were observed. Fish feeding niche was significantly larger in the lower than in the upper Batchawana River, but there were no significant differences in mean fish community δ 13 C or δ 15 N between reaches. Fish assemblage δ 13 C, δ 15 N and standard ellipse area were consistent among years within river reaches despite flow and temperature variability over the same years. Results highlight that in natural undisturbed rivers, fish feeding niche appears to be temporally invariant in the face of naturally imposed environmental variability. Copyright © 2016 John Wiley &amp; Sons, Ltd.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.003
GPT teacher head0.182
Teacher spread0.179 · 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

Citations2
Published2016
Admission routes2
Has abstractyes

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