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Seasonal pattern of depth selection in smallmouth bass

2009· article· en· W2101586352 on OpenAlexafffundabout
Cory D. Suski, Mark S. Ridgway

Bibliographic record

VenueJournal of Zoology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsTrent UniversityMinistry of Natural Resources and Forestry
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicropterusDiel vertical migrationThermoclineBass (fish)BiologyFisheryOceanographySpawn (biology)EcologyGeology

Abstract

fetched live from OpenAlex

Abstract The current study used a stationary acoustic telemetry array to monitor the depth selection of adult smallmouth bass Micropterus dolomieu in a large, oligotrophic lake in Ontario, Canada. At an annual scale, smallmouth bass demonstrated regular, seasonal changes in inhabited depths: fish occupied shallow water during the summer (2–5 m depth) and descended to deeper water (12–15 m depth) during winter under ice. Smallmouth bass remained above the thermocline in the summer, seasonal depth patterns did not vary across fish size and movements to and from seasonal depths were closely linked to the development and degradation of the thermocline. At finer time scales, smallmouth bass exhibited diel vertical migrations in summer, with fish moving to <2 m at night, and then descending to 3–5 m during the day. This pattern remained constant during the summer period examined, and varied with size such that larger fish remained deeper than smaller fish. During winter, depth did not vary across the 3‐month monitoring period ( c . 14 m), but small (<2 m) changes in depth were observed periodically, suggesting limited movements were occurring. Results are further discussed in the context of climate change and reproductive success for this species.

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 score0.011
Threshold uncertainty score0.604

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 head0.009
GPT teacher head0.222
Teacher spread0.214 · 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

Citations27
Published2009
Admission routes3
Has abstractyes

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