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Record W3001414577 · doi:10.1051/kmae/2019046

Contrasting trends between species and catchments in diadromous fish counts over the last 30 years in France

2020· article· en· W3001414577 on OpenAlexaff
Marion Legrand, Cédric Briand, Laëtitia Buisson, Gwenaël Artur, Didier Azam, Aurore Baisez, David Barracou, Nicolas Bourré, L. Ray Carry, Anne‐laure Caudal, Fabien Charrier, Jérémie Corre, Eric Croguennec, Sophie Der Mikaélian, Quentin Josset, Laëtitia Le Gurun, Frédéric Schaeffer, Pascal Laffaille

Bibliographic record

VenueKnowledge and Management of Aquatic Ecosystems · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsShipping Federation of Canada
FundersAgence française pour la biodiversitéRégion NormandieAgence de l'eau Loire-BretagneOffice National de l’Eau et des Milieux AquatiquesAgence de l'Eau Seine-Normandie
KeywordsFish migrationSalmoStockingFisheryDrainage basinPetromyzonAlosaTaxonRange (aeronautics)GeographyEcologyBiologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The decline and collapse of populations have been reported for a large range of taxa. Diadromous fishes migrate between fresh water and the sea and encounter many anthropogenic pressures during their complex life cycle. In spite of being of ecological, cultural and economic interest, diadromous fishes have been in decline for decades in many parts across the world. In this study, we investigated the change in five diadromous fish counts in France over a 30-year period using 43 monitoring stations located in 29 rivers across 18 catchments. Our hypothesis was that the counts of these species evolved in a contrasting way between catchments. We also tested the effect of five drivers potentially contributing to the observed trends: catchment, latitude, presence of commercial fisheries, improvement of ecological continuity and salmon stocking. We found contrasting trends in fish counts between species at the national scale, with some taxa increasing ( Anguilla anguilla and Salmo trutta ), some showing a slight increase ( Salmo salar ) and some decreasing ( Alosa spp. and Petromyzon marinus ). For each taxon, except Anguilla anguilla , we highlighted a significant catchment effect indicating contrasting trends between catchments and stations. However, we found no significant effect of catchment characteristics for any of the studied taxa.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.015
GPT teacher head0.226
Teacher spread0.211 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations18
Published2020
Admission routes1
Has abstractyes

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