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Record W6976746762 · doi:10.60692/hnh6x-xbc73

Life‐history, exploitation and extinction risk of the data‐poor Baraka's whipray (Maculabatis ambigua) in small‐scale tropical fisheries

2020· article· en· W6976746762 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2020
Typearticle
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsOverexploitationOverfishingFishingFisheries managementMaximum sustainable yieldExtinction (optical mineralogy)Range (aeronautics)

Abstract

fetched live from OpenAlex

Abstract The Baraka's whipray ( Maculabatis ambigua ) is a major constituent of small‐scale fisheries catch in the south‐western Indian Ocean. Despite this, little is known of its life‐history or exploitation status. We provide the first estimates of crucial life‐history parameters and the maximum intrinsic population growth rate r max , using specimens collected from small‐scale fisheries landings in Kenya, Zanzibar and Madagascar (with northern Madagascar representing a range extension for this species). We assess the relative risk of overexploitation by combining r max with estimates of total Z , fishing F , and natural M mortality, and an estimate of the exploitation ratio E . The data indicate that Baraka's whipray is a medium‐sized, fast‐growing, early maturing species, with a relatively long lifespan. This results in a high r max relative to many other elasmobranchs, which when combined with estimates of F suggests that the species is not at imminent risk of extinction. Yet, estimates of exploitation ratio E indicate likely overfishing for the species, with full recruitment to the fishery being post‐maturation and exploitation occurring across a broad range of age and size classes. Thus, Baraka's whipray is unlikely to be biologically sustainable in the face of current fisheries pressures. This paper makes an important contribution to filling the gap in available data and is a step towards developing evidence‐based fisheries management for this species. Further, it demonstrates a simple and widely applicable framework for assessment of data‐poor elasmobranch exploitation status and extinction risk.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score0.455

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 communication0.0000.002
Open science0.0010.001
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 head0.063
GPT teacher head0.193
Teacher spread0.130 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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