Evidence map›Paper›PMID 42228730›Full record

ArticlePloS one2026

Identification of métiers in a multi-gear, multi-species fishery.

Pedro Leitão, Margarida Castro, Aida Campos

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Pedro LeitãoCentro de Ciências do Mar do Algarve (CCMAR/CIMAR LA), Campus de Gambelas, Universidade do Algarve, Faro, Portugal.ORCID https://orcid.org/0000-0003-1279-5552
Margarida CastroCentro de Ciências do Mar do Algarve (CCMAR/CIMAR LA), Campus de Gambelas, Universidade do Algarve, Faro, Portugal.
Aida CamposCentro de Ciências do Mar do Algarve (CCMAR/CIMAR LA), Campus de Gambelas, Universidade do Algarve, Faro, Portugal.ORCID https://orcid.org/0000-0002-5972-6266

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate, gear-specific data is essential for fisheries management to quantify fishing pressure and ecosystem impacts, particularly in multi-gear fleets. In this study, we used electronic logbooks and sales notes from 2014 to 2023 to analyze the Portuguese multi-gear coastal fleet, obtaining information at a haul level. The objective was to identify and validate métiers down to level 6 according to the European Commission's definition (a combination of gear specifications, target species, fishing area, and season). This fleet comprises approximately 500 vessels using various types of traps, nets, and longlines to catch around 200 species of fish and invertebrates. We identified 28 métiers across six main gear types. The most representative métier is the octopus (Octopus vulgaris) trap fishery, followed by the European hake (Merluccius merluccius) gillnet and the black scabbardfish (Aphanopus carbo) longline fisheries. A strong association was found between most métiers and variables such as fishing season, fishing area, depth, and sediment type. Traps and nets were mostly used in the northwest area, in mixed sediments or sand, whereas longlines were mostly operated in the central west area, in steeper slopes on sandy and rocky bottoms. The study highlights the complexity of quantifying gear-specific fishing effort in multi-gear fisheries, where technical interactions occur, and competitive relationships exist between different fishing fleets and gears that exploit the same fish stocks.

Indexed as

FisheriesFishesAnimalsConservation of Natural ResourcesEcosystemPortugalSeasons

Identifiers

PMID42228730
PMCPMC13229354

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.