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Record W4377989727 · doi:10.1139/cjfas-2022-0124

Temporal community structure and seasonal climatic migration of coastal sharks and large teleost fishes in the northeast Gulf of Mexico

2023· article· en· W4377989727 on OpenAlexvenueno aff
Cheston T. Peterson, R. Dean Grubbs

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsnot available
Fundersnot available
KeywordsAbiotic componentSeagrassCommunity structureHabitatEcologyGeographyJuvenileSeasonalityTaxonFisheryBiology

Abstract

fetched live from OpenAlex

We conducted monthly fishery-independent sampling using scientific gillnets and longlines at two seagrass shoals and surrounding soft-bottom habitat in the northeast Gulf of Mexico. Using non-metric multidimensional scaling, we explored the effects of abiotic variables on temporal patterns of fish community structure, analyzed temporal patterns using permutational multivariate analysis of variance, and tested for cyclicity in community structure. Additionally, we used generalized additive models to explore the effects of environmental variables on immigration and emigration phases of dominant taxa. We found strong seasonality and cyclicity in assemblages captured by both gear types, with depauperate winter communities and diverse assemblages in warmer month. Our results suggest that temperature may determine the timing of immigration and duration of the residency period of dominant taxa, but photoperiod may cue immigration and emigration in adults when the purpose of those migrations includes predicable reproductive functions (e.g., parturition). We found evidence of partial migration in juvenile life stages of some coastal sharks and hypothesize that rising temperatures due to climate change may have variable effects on residency patterns over ontogeny.

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)0.001
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 score0.054
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.015
GPT teacher head0.221
Teacher spread0.206 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicIchthyology and Marine BiologyFrench-language works237,207