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Record W4211184253 · doi:10.3389/fevo.2022.810069

Predation Scars Reveal Declines in Crab Populations Since the Pleistocene

2022· article· en· W4211184253 on OpenAlexafffund
Kristina M. Barclay, Lindsey R. Leighton

Bibliographic record

VenueFrontiers in Ecology and Evolution · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of VictoriaUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPredationFisheryPleistoceneEcologyPopulationApex predatorGeographyBiologyFisheries managementFishingPaleontology

Abstract

fetched live from OpenAlex

Despite growing concerns over global fisheries, the stock status of most commercially exploited species are poorly understood. Fossil data provide pre-anthropogenic baselines for data-poor fisheries, yet are underutilized in fisheries management. Here, we provide the first use of predation traces to assess the status of fisheries (crab). We compared crab predation traces on living individuals of the crab prey gastropod, Tegula funebralis , to Pleistocene individuals from the same regions in southern California. There were fewer crab predation traces on modern gastropods than their Pleistocene counterparts, revealing reductions in crab abundances today compared to the Pleistocene. We conclude that: (1) regardless of the cause, immediate actions are required to avoid further population reductions of commercially exploited crabs in southern California, (2) predation traces are a rapid, cost-effective method to assess otherwise data-poor fisheries, and (3) the inclusion of fossil data provides key new insights for modern resource and fisheries management.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.639

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 communication0.0000.000
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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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

Citations9
Published2022
Admission routes2
Has abstractyes

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