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Record W4236276502 · doi:10.21203/rs.3.rs-48910/v1

Movement Patterns of Atlantic Tarpon (Megalops atlanticus) in Brewers Bay, St. Thomas US Virgin Islands

2020· preprint· en· W4236276502 on OpenAlexaff
Mareike D. Duffing Romero, Jordan K. Matley, Jiangang Luo, Jerald S. Ault, Simon J. Pittman, Richard S. Nemeth

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBayGeographyFisheryOceanographyBiologyGeologyArchaeology

Abstract

fetched live from OpenAlex

Abstract Background Atlantic tarpon (Megalops atlanticus) are highly migratory species ranging along continental and insular coastlines of the Atlantic Ocean. Despite broad geographic distribution and importance as recreational fisheries, little is known about space-use patterns of tarpon within the Eastern Caribbean. Acoustic telemetry was used to track tarpon (n=14, 61- 95cm-FL) from September 2015 to February 2018 in St. Thomas, U.S. Virgin Islands to understand horizontal and vertical movements during diel, crepuscular and seasonal periods and under different environmental conditions. ResultsEight tarpon were transient while four had >80% residency and average activity space of 0.76 km2 (range = 0.075-1.174 km2) within a small (~1.8km2) bay. Tarpon occurred in <18 m depth with occasional movements to deeper water, including during hurricanes. Activity was greater during day compared to night, with peaks during crepuscular periods. During the day tarpon primarily utilized the waters along the St. Thomas airport and at night tarpon typically remained in a small shallow lagoon. However, when temperatures in the lagoon exceeded 30 °C, tarpon moved to cooler, deeper waters outside the lagoon. ConclusionThis study showed distinct and mostly non-overlapping home ranges except when seasonally abundant food sources were present and provided a unique perspective on the effects of extreme environmental conditions on tarpon movement and habitat use. These metrics are useful for management of tarpon, particularly under changing climatic conditions.

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 score0.314
Threshold uncertainty score0.625

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.047
GPT teacher head0.331
Teacher spread0.284 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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