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Estimating the scale of fish feeding movements in rivers using δ<sup>13</sup><i>C</i>signature gradients

2008· article· en· W1995825301 on OpenAlexafffund
Joseph B. Rasmussen, Véronique Trudeau, Geneviève R Morinville

Bibliographic record

VenueJournal of Animal Ecology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsDawson CollegeUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInvertebrateSalmoPeriphytonEcologyEnvironmental scienceSpatial ecologyScale (ratio)Isotopic signatureMovement (music)Abundance (ecology)Fish <Actinopterygii>BiologyFisheryGeographyStable isotope ratioNutrientCartography

Abstract

fetched live from OpenAlex

1. Isotopic signatures of consumers provide a time integration of their feeding history, and as a result of movements, are often out of line with signatures of their local resources. Such disequilibrium can be useful for inferring the spatial scale of consumer movement. 2. delta(13)C signatures of dissolved inorganic carbon as well as periphyton and invertebrates, exhibit pronounced gradients along rivers. We outline an analytical framework to estimate the spatial scale of movement of riverine fish by comparing the slopes of their delta(13)C signature gradients to that of the stream invertebrates they consume. For free-ranging juvenile Atlantic salmon (Salmo salar L.), unconstrained by barriers, delta(13)C signatures departed considerably from invertebrate signatures, and along-stream slopes were as little as half those recorded for stream invertebrates. Movement estimates for these fish, based on their signature slopes, are approximately 20 km. 3. By contrast, stream resident salmonids (whose movements are constrained by physical barriers) and sedentary taxa such as sculpins and sticklebacks, have carbon signatures much closer to invertebrate signatures where they were collected. For these groups, our method yields negligible estimates of movement, similar to those of invertebrates. 4. Although this method cannot provide precise estimates of how much individual organisms move, or reveal details of movement history, it may provide an effective complement to telemetric and other methods of studying movement.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.347

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)0.0000.000

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 head0.014
GPT teacher head0.231
Teacher spread0.217 · 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.

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

Citations55
Published2008
Admission routes2
Has abstractyes

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