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Record W4414210709 · doi:10.3390/ani15182640

Cetacean Habitat Use and Occurrence in Fort-de-France Bay (Martinique)

2025· article· en· W4414210709 on OpenAlexaff
Coline Violo, Anatole Gros-Martial, Célia Ortolé, Marion Poupard, Morjane Safi, Benjamin de Montgolfier

Bibliographic record

VenueAnimals · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité du Québec à Rimouski
FundersOffice Français de la Biodiversité
KeywordsBayHabitatBaseline (sea)Marine habitatsMarine protected areaSpatial ecology

Abstract

fetched live from OpenAlex

While coastal species have been widely studied, active port areas in tropical island regions with intense maritime traffic remain critical, but habitats for cetaceans within the Caribbean have not been thoroughly studied. This study examines the spatial and temporal patterns of habitat use and the characteristics of groups of six cetacean species in the Bay of Fort-de-France in Martinique, an area with heavy marine traffic. Data were collected from 2018 to 2022 through systematic boat-based surveys. We analyzed standardized observations of group occurrence, size, behavior, and depth preference across different subzones of the bay. Our results reveal that Stenella attenuata and Stenella longirostris are the most frequently observed species, exhibiting distinct seasonal patterns, while other species occur more sporadically. Group sizes and behavioral patterns vary significantly across zones and depths. Larger, more interactive groups are generally observed in shallow areas. Several species’ preference for nearshore waters highlights the ecological value of the bay and the potential risks posed by anthropogenic pressures, such as noise, collisions, and habitat degradation. Our findings underscore the importance of considering cetacean habitat use in port management strategies. This study provides essential baseline knowledge to support conservation efforts and the development of mitigation measures that reconcile economic activities with the protection of marine biodiversity.

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 score0.088
Threshold uncertainty score0.512

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 head0.018
GPT teacher head0.263
Teacher spread0.246 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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