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Record W2950694759 · doi:10.1038/s41598-019-44869-x

Biotelemetry reveals migratory behaviour of large catfish in the Xingu River, Eastern Amazon

2019· article· en· W2950694759 on OpenAlexafffund
Lisiane Hahn, Eduardo G. Martins, Leonardo D. Nunes, Luís Fernando da Câmara, Domingos Garrone‐Neto

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFish biology, ecology, and behavior
Canadian institutionsUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaLiber Ero FoundationGovernment of Canada
KeywordsAmazon rainforestCatfishTributaryHydroelectricityGeographyFisheryDry seasonLoricariidaeEcologyBiologyFish <Actinopterygii>Cartography

Abstract

fetched live from OpenAlex

We used a combination of radio and acoustic telemetry to assess the movements of large catfish (Pimelodidae) in the Xingu River, a clearwater tributary of the Amazon River in Brazil. A total of 121 Phractocephalus hemioliopterus and 61 Pseudoplatystoma punctifer were tagged for monitoring within a 685 km segment, including the Belo Monte Hydroelectric Complex (BMHC), between February 2013 and July 2015. Long distance upstream movements were detected for P. hemioliopterus (up to 347 km) and for P. punctifer (up to 164 km) mainly during the transition between dry season and the rising water period. Both species moved through a long segment of rapids previously thought to function as barriers to migration. Several individuals exhibited long-distance bidirectional movements. Some tagged fish never left the release zone, indicating mortality, tag loss or resident individuals, which would characterize partial migration. The findings show evidence of migratory behaviour for large catfish within the Xingu River, emphasizing the influence of the hydrologic cycle on their movements. As part of the study area has become partially dewatered due to the BMHC, findings support the need of adequate management strategies to allow the movements of large catfish between spawning and feeding sites in the Xingu River.

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)0.003
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 score0.056
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.249
Teacher spread0.237 · 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

Citations26
Published2019
Admission routes2
Has abstractyes

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