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Record W4408824616 · doi:10.5194/oos2025-911

Bottlenose dolphin (Tursiops truncatus) aggregations at Cocos Island National Park, Puntarenas, Costa Rica, between 2017-2022

2025· preprint· en· W4408824616 on OpenAlexaboutno aff
Karol Ulate, Geiner Golfín

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsBottlenose dolphinFisheryGeographyNational parkBiologyArchaeology

Abstract

fetched live from OpenAlex

The bottlenose dolphin (Tursiops truncatus) is a common cetacean along the eastern Pacific coast, spanning from Canada to Chile. While widely distributed, the species exhibits region-specific adaptations influenced by environmental and biological factors. In Costa Rica, bottlenose dolphins form a neritic population in the coastal waters of Golfo Dulce and Golfo de Nicoya, whereas Cocos Island hosts a pelagic population that has developed distinct morphological traits due to their diet. Although Cocos Island is geographically remote, threats such as bycatch still affect cetacean populations. While the feeding behavior of these dolphins is relatively well-documented, there is little information on their distribution patterns and social structures. This study aims to enhance conservation efforts in international waters of the Eastern Tropical Pacific, by investigating the spatiotemporal distribution of bottlenose dolphin aggregations at Cocos Island. Monitoring was conducted from 2017 to 2022 using the Protocol for the Ecological Monitoring (PRONAMEC) of Aggregations of Aquatic Mammals, developed by Costa Rica’s National System of Conservation Areas. The study area, Cocos Island National Park, was divided into four quadrants, each surveyed over a four-day monitoring effort. A total of 36 field trips were carried out: 20 during the rainy season and 16 in the dry season. For each dolphin sighting, observers recorded the group composition (adults, juveniles, pups), geographical location, date, and time. Statistical analysis was performed to identify significant differences in sightings per field trip across seasons, quadrants, and years, as well as variations in group size and composition. Results indicated a slight decrease in the number of sightings per field trip over the years but an increase in individuals per sighting. Although trends were observed, no significant differences were found between the first and last years of monitoring or between seasons. Aggregations generally comprised three to five individuals, with the northeastern quadrant showing the highest number of sightings per field trip, followed by the southwestern. A significant difference was found only between the northeastern and northwestern quadrants during the rainy season. Groups with only adults were the most frequently observed by statistical differences. The marked increase in individuals per sighting in 2020 and 2021 may be related to the suspension of fishing activities and reduced tourism during the COVID-19 pandemic. The consistent presence of juveniles and pups across all quadrants and seasons suggests that Cocos Island serves as a critical habitat for feeding, reproduction, and juvenile development. However, this pattern was not observed in 2022, when juveniles and pups were notably absent. The distribution pattern, especially in the northeastern and southwestern quadrants, suggests that dolphins may rely on nearby seamounts as feeding grounds, given their high productivity. Continued monitoring is recommended to corroborate these trends over time and to support conservation efforts in this vital marine area.

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)0.000
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 score0.208
Threshold uncertainty score0.414

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.001
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 head0.033
GPT teacher head0.288
Teacher spread0.255 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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