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Record W4391454054 · doi:10.5751/es-13902-290109

The chronology of overfishing in a remote West-African coastal ecosystem

2024· article· en· W4391454054 on OpenAlex
Sidi Yahya Cheikhna Lemrabott, Anieke van Leeuwen, Theunis Piersma, Cheikh-Baye Braham, Abou Ciré Ball, António Araújo, Han Olff, El-Hacen El-Hacen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEcology and Society · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsnot available
Fundersnot available
KeywordsOverfishingGeographyEcosystemChronologyEnvironmental resource managementFisheryEcologyEnvironmental scienceFishingArchaeologyBiology

Abstract

fetched live from OpenAlex

Classic studies of marine overexploitation traditionally analyze cases of “fishing down the food web”: turning to smaller species at lower trophic levels after depleting the larger top predators. Much less documented, however, is the preceding phase in which higher trophic level species, previously not exploited or consumed locally, are increasingly added to the catch. Worldwide, this phase happened centuries ago due to technological developments and thus passed before scientific scrutiny and conservation awareness arose, leaving it largely unstudied. Here, we combine a historical reconstruction of fishery with a relatively recent fishing monitoring program to document this early phase in the Parc National du Banc d’Arguin in Mauritania, a marine protected area in Mauritania, West Africa. Long-term trends in mean trophic level of exploited species and total catches provide evidence for an increasing fishing pressure toward the top of the food web, and suggest that the state of “fishing down the food web” is now happening in this ecosystem. This involves the recent intensive targeting of rays and sharks. We show that their contribution to the local economy is marginal compared with the traditionally fished species.

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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.007
GPT teacher head0.250
Teacher spread0.243 · 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