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Record W4282976835 · doi:10.3989/scimar.05245.035

Effects on faunistic composition and population characteristics of decapod crustaceans after the implementation of a fisheries no-take area in the NW Mediterranean

2022· article· en· W4282976835 on OpenAlexfundno aff
Andrea Padilla, Laura Recasens, Marc Balcells, U. Fernández-Arcaya, Pere Abelló

Bibliographic record

VenueScientia Marina · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersEuropean Maritime and Fisheries FundEuropean Regional Development FundConsejo Superior de Investigaciones CientíficasMinisterio de Economía y CompetitividadGeneralitat de CatalunyaCanadian Institute for Theoretical Astrophysics
KeywordsCrustaceanTrawlingMediterranean climateHabitatFisheryBiodiversityPopulationBiologyEcologyGeographyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The establishment of fisheries no-take areas is considered an effective method for the recovery of populations of exploited species and their habitats. Here we study the faunistic composition of decapod crustaceans after the implementation of a no-take area in the Gulf of Roses (NW Mediterranean) in 2014. We studied the occurrence (presence/absence) and density of all decapod crustaceans sampled by trawling inside and outside a no-take area from March 2015 to July 2018. Sizes were assessed for all common species. A total of 33 species of decapod crustaceans were recorded. Four species showed significantly higher occurrences in the no-take area and three in the open area, while significantly higher densities were found for four species in the no-take area and three in the open area. Multivariate analysis showed marked differences between the no-take area and the open area, while also showing that the two areas were undergoing a divergence. The comparison of sizes between the two zones showed species-specific patterns that in many cases showed that both the smallest and the largest individuals were present in the no-take area, suggesting that the closing of this area would be important for recruitment and juvenile development, as well as for protection of large-sized individuals. All evidence indicates that the establishment of the no-take area has led to an improvement in biodiversity and species population descriptors.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.011
GPT teacher head0.248
Teacher spread0.238 · 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.

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

Citations3
Published2022
Admission routes1
Has abstractyes

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