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Record W3003674617 · doi:10.1093/icesjms/fsz222

Extinction risk and conservation of critically endangered angel sharks in the Eastern Atlantic and Mediterranean Sea

2019· article· en· W3003674617 on OpenAlexafffund
Julia M. Lawson, Riley A. Pollom, Cat A. Gordon, Joanna Barker, Eva Meyers, H. Zidowitz, Jim R. Ellis, Àlex Bartolí, Gabriel Morey, Sarah Fowler, David Jiménez‐Alvarado, Sonja V. Fordham, Rowland Sharp, Ali R. Hood, Nicholas K. Dulvy

Bibliographic record

VenueICES Journal of Marine Science · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsSimon Fraser University
FundersDisney Conservation FundMohamed bin Zayed Species Conservation FundInland Fisheries IrelandSave Our Seas FoundationUniversidad de Las Palmas de Gran CanariaCanada Research ChairsFauna and Flora InternationalUniversity of ExeterNatural Resources Wales
KeywordsOverfishingThreatened speciesCritically endangeredEndangered speciesHabitat destructionGeographyExtinction (optical mineralogy)FisheryHabitatPopulationEcologyFishingMediterranean climateMediterranean seaBiology

Abstract

fetched live from OpenAlex

Abstract Understanding the details of local and regional extinctions allows for more efficient allocation of conservation activities and resources. This involves identifying where populations persist, where populations may still be present, and where populations may be locally extinct. Three threatened angel sharks occur in the Eastern Atlantic and Mediterranean Sea: Sawback Angelshark (Squatina aculeata), Smoothback Angelshark (Squatina oculata), and Angelshark (Squatina squatina). Population sizes and geographic ranges of these species have been reduced due to overfishing and habitat loss, placing them among the world s most threatened chondrichthyans. We revise distribution maps, review global status, and present a Conservation Strategy to protect and restore these angel shark populations by minimizing fishing mortality, protecting critical habitat, and mitigating human disturbance. Updated distributions reveal that a halving of the geographic extent may have occurred for all three species, with potential declines of 51% for Sawback Angelshark, 48% for Smoothback Angelshark, and 58% for Angelshark. While 20 national and international management measures are now in place for Angelshark, only half of these include the other two species. We encourage further conservation action to adopt and develop this Conservation Strategy to restore angel shark populations to robust levels and safeguard them throughout their range.

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)0.002
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 score0.017
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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

Citations63
Published2019
Admission routes2
Has abstractyes

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