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Record W2973221307 · doi:10.1111/1365-2664.13497

Body shape is related to the attempt rate and passage success of brook trout at in‐stream barriers

2019· article· en· W2973221307 on OpenAlexaff
Elsa Goerig, Ben A. Wasserman, Theodore Castro‐Santos, Eric P. Palkovacs

Bibliographic record

VenueJournal of Applied Ecology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNational Science Foundation
KeywordsCulvertTroutSalvelinusFontinalisHabitatSTREAMSEcologyFish <Actinopterygii>BiologyFisheryGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract The ability to move between habitats has important implications for fitness in many species. In‐stream barriers such as culverts can impede movements of riverine fishes and thus reduce connectivity between habitats. The ability of fish to overcome barriers is related to the features of the environment and the barrier itself, but also to physiological, morphological and behavioural traits of the fish. Among these, body shape varies among and within species, and influences swimming ability, a key component of passage performance through culverts. We conducted an experimental study on wild brook trout ( Salvelinus fontinalis ) to assess the effects of individual body shape on attempt rate and passage success through culverts on six streams. A more streamlined body shape was associated with an increased motivation to enter and ascend the culverts, and, to a lesser extent, with the probability of successful passage once an attempt was staged. Motivation and successful passage were also influenced by the density of conspecifics below the culvert, time of day, fish body size and water velocity. Policy implications. While fish body shape is expected to influence swimming performance, our research shows the most important effect of body shape to be on an individual's motivation to stage passage attempts at culverts. This study points to an important connection between behaviour and morphological traits that influence passage success and suggests that in‐stream barriers may be an important agent of selection on behaviour and morphology in wild fish populations.

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 score0.027
Threshold uncertainty score0.997

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)0.0040.000

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 head0.003
GPT teacher head0.200
Teacher spread0.197 · 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 routes1
Has abstractyes

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