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Record W2915267726 · doi:10.18174/470889

Best practices II : spatial distribution of the discards of the Dutch beam trawler fleet

2019· report· en· W2915267726 on OpenAlexaboutno aff
Thomas Brunel, R. Verkempynck, Jurgen Batsleer

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsDiscardsFishingSpatial distributionQuarter (Canadian coin)GeographyEnvironmental scienceOceanographyFisheryGeoreferenceNorth seaSampling (signal processing)Distribution (mathematics)Physical geographyStatisticsMathematicsComputer scienceGeologyBiology

Abstract

fetched live from OpenAlex

This study aims at describing the spatial distribution -and its temporal variations -of discarding intensity (i.e.expected weight of discards for a standard trawl haul) for the 6 main species discarded by the Dutch beam trawl fisheries.For each species, the spatial distribution (quarterly maps for the period 2013 to 2017) is estimated using statistical models that take spatial and temporal correlation into account, which also allowed to test for the effect of a number of factors related to geography, environment, fishing practices and operational aspects on discarding.The data used to fit those models came from the observer trips and self-sampling program conducted at Wageningen Marine Research and from discards sampling trips conducted by the fishing industry.As by-product, the models provide descriptors of the temporal and spatial scales at which the discards of a given species are structured.The distribution of the expected discards per haul for dab was highly variable from quarter to quarter, with generally high discarding intensity in front of the southern coast of the Netherlands in quarter 1, a discarding intensity which is high on the German bight and low in front of the Dutch coast in quarter 3, and variable distributions for quarter 2 and 4.For plaice, the distribution was more stable, with high values consistently observed in the south of the area (between the south of the Netherlands and England), with occasional hot spots on the German bight.For sole, discards were not observed on the north-western part of the area, and a hotspot of sole discarding was found consistently in front of the southern coast of the Netherlands, occasionally expanding towards England or to the northern coast of the Netherlands.Discarding of turbot first occurred with a low intensity along the coast from Belgium to Germany.After the fourth quarter of 2015, high discarding started to occur, first limited to the small area in the southern North Sea, but progressively expanding to a larger area in the southern and central part of the North Sea, while discarding intensity remained low in the northern part of the area and in front of England.The distribution discarding intensity for whiting was highly variably, characterised by hotspots suddenly appearing for most years in the fourth quarter, and disappear in the following first quarter.Discarding of rays occurred mainly in the western part of the area, especially in front of southern England, with an increasing level since the fourth quarter of 2016.The distributions observed and their variability were further discussed in the light the available information on the distribution and migration of the species and on the management measures potentially influencing discarding. AnnexesAnnexe 1 : spatial-

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.208
Threshold uncertainty score0.413

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.317
Teacher spread0.273 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreOther

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

Citations2
Published2019
Admission routes1
Has abstractyes

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