Evidence map›Paper›PMID 35228599›Full record

ArticleScientific reports2022

Technological creep masks continued decline in a lobster (Homarus gammarus) fishery over a century.

Alf Ring Kleiven, Sigurd Heiberg Espeland, Stian Stiansen, Kotaro Ono, Fabian Zimmermann, Esben Moland Olsen

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

6 authors.

Alf Ring KleivenInstitute of Marine Research, Nye Flødevigveien 20, 4817, His, Norway. alf.ring.kleiven@hi.no.
Sigurd Heiberg EspelandInstitute of Marine Research, Bergen, Norway.
Stian StiansenInstitute of Marine Research, Nye Flødevigveien 20, 4817, His, Norway.
Kotaro OnoInstitute of Marine Research, Bergen, Norway.
Fabian ZimmermannInstitute of Marine Research, Bergen, Norway.
Esben Moland OlsenDepartment of Natural Sciences, Centre for Coastal Research, University of Agder, Kristiansand, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fishery-dependent data are frequently used to inform management decisions. However, inferences about stock development based on commercial data such as Catch-Per-Unit-Effort (CPUE) can be severely biased due to a phenomenon known as technological creep, where fishing technology improves over time. Here we show how trap improvement over nine decades has driven technological creep in a European lobster (Homarus gammarus) fishery. We combined fishing data, experimental fishing with contemporary and older trap types, and information on depletion effects during fishing seasons. The resulting standardized CPUE time series indicates a 92% decline in lobster abundance between 1928 and 2019 compared to 70% if technological creep is not corrected for. Differences are most pronounced within the last 40 years when the most substantial shift in gear technology occurred: an uncorrected CPUE index suggests an 8% increase in lobster abundance during this period, while the corrected CPUE index declined by 57%. We conclude that technological creep has masked a continuous stock decline, particularly in recent decades and largely driven by the shift from one- to two-chambered traps, as well as the ability of newer trap designs to capture larger lobsters. Our study confirms the importance of adequate standardization, including technological development, when using fishery dependent CPUE for monitoring and management of data-limited fisheries.

Indexed as

FisheriesNephropidaeTechnologyAnimals

Identifiers

PMID35228599
PMCPMC8885706

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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.