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Record W3166079924 · doi:10.1139/cjfas-2021-0023

The response of a brown trout (<i>Salmo trutta</i>) population to reintroduced Eurasian beaver (<i>Castor fiber</i>) habitat modification

2021· article· en· W3166079924 on OpenAlexvenueno aff
Robert Needham, Martin J. Gaywood, Angus Tree, Nick Sotherton, Dylan E. Roberts, Colin W. Bean, Paul S. Kemp

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsnot available
FundersNatural Environment Research CouncilUniversity of SouthamptonGame and Wildlife Conservation Trust
KeywordsElectrofishingSalmoBeaverBrown troutEcologyPopulationFisheryHabitatThreatened speciesAbundance (ecology)BiologyTroutFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Globally, freshwaters are the most degraded and threatened of all ecosystems. In northern temperate regions, beaver (Castor spp.) reintroductions are increasingly used as a low-cost and self-sustaining means to restore river corridors. River modifications by beavers can increase availability of suitable habitat for fish, including salmonids. This study investigated the response of a population of brown trout (Salmo trutta) to reintroduced Eurasian beaver (Castor fiber) habitat modifications in northern Scotland. The field site comprised two streams entering a common loch; one modified by beavers, the other unaltered. Electrofishing and PIT telemetry surveys indicated abundance of post-young-of-the-year (post-YOY) trout was higher in the modified stream. Considering juvenile year groups (YOY and post-YOY) combined, abundance and density varied with year and season. In the modified stream, fork length and mass were greater, there was a greater variety of age classes, and mean growth was positive during all seasons. Beavers had profound effects on the local brown trout population that promoted higher abundances of larger size classes. This study provides important insight into the possible future effect of beavers on freshwater ecosystems.

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)0.001
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 score0.035
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.018
GPT teacher head0.219
Teacher spread0.201 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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