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New tools to evaluate plastic ingestion by northern fulmars applied to North Sea monitoring data 2002–2018

2021· article· en· W3140574154 on OpenAlexaffabout
J.A. van Franeker, Susanne Kühn, Tycho Anker‐Nilssen, Ewan W. J. Edwards, Fabrice Gallien, Nils Guse, Jenni Kakkonen, Mark L. Mallory, Will Miles, Kåre Olav Olsen, John Pedersen, Jennifer F. Provencher, Mervyn Roos, Eric Stienen, Daniel M. Turner, Willem M.G.M. van Loon

Bibliographic record

VenueMarine Pollution Bulletin · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsEnvironment and Climate Change CanadaAcadia University
FundersRijkswaterstaatMinistry of Infrastructure and Water Management
KeywordsMarine Strategy Framework DirectiveEnvironmental scienceArcticFisheryPlastic pollutionOceanographyNorth seaEcologyBiologyEcosystemPollutionGeology

Abstract

fetched live from OpenAlex

Monitoring plastic in stomachs of beached northern fulmars for OSPAR's Ecological Quality Objectives (EcoQOs) has been incorporated into the European Marine Strategy Framework Directive (MSFD). This paper aims to provide the appropriate tools to interpret the monitoring results. MSFD requires a data-derived threshold value (Fulmar-TV) representing 'Good Environmental Status'. Such Fulmar-TV was calculated from near-pristine Canadian Arctic data where 10.06% of fulmars exceeded the level of 0.1 g ingested plastic. This Fulmar-TV is almost identical to the earlier OSPAR EcoQO, arbitrarily set at 10%. The MSFD approach was evaluated for 2661 North Sea fulmars in 2002-2018. Between 2014 and 2018, 51% of 393 fulmars exceeded 0.1 g plastic, significantly above the proposed Fulmar-TV. Linear regression of individual ingested plastic mass over the 2009-2018 period indicates a significant decrease. Over the longer term 2002-2018, logistic regression of annual EcoQ% shows a significant decline and predicts compliance with the Fulmar-TV by 2054.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.013

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 head0.022
GPT teacher head0.230
Teacher spread0.208 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations64
Published2021
Admission routes2
Has abstractyes

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