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Record W2261555347 · doi:10.1093/beheco/arv038

Shifts in movement behavior of spawning fish under risk of predation by land-based consumers

2015· article· en· W2261555347 on OpenAlexafffund
Marc Pépino, Marco A. Rodríguez, Pierre Magnan

Bibliographic record

VenueBehavioral Ecology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersNatural Sciences and Engineering Research Council of CanadaMinistère des TransportsGroupe de recherche interuniversitaire en limnologie
KeywordsPredationBiologyMovement (music)EcologyTrade-offForagingPopulationMortality rateReproductionDemographyFishery

Abstract

fetched live from OpenAlex

Animals confront behavioral trade-offs whenever the movements required to attain suitable sites for reproduction or resource acquisition also increase exposure to predators. Hence, the consequences of such trade-offs should be considered in analyses of movement behavior. The objective of this study was to quantitatively link shifts in movement behavior of stream fish during the reproductive season to risk of mortality from land-based tetrapod predators. We tagged 30 brook trout with internal radio transmitters and extensively recorded both movement patterns and mortality from predation over the entire spatial range of the population. Our main result is that most of the individuals (19/30) had marked shifts in movement behavior, characterized by alternating periods of low and high movement rates, which were associated with marked shifts in mortality rate. Mortality rate increased from 0.016/day during periods of low movement rate (8.0 m/day; sheltering state) to 0.071/day during periods of high movement rate (91.0 m/day; searching state). Furthermore, individuals presenting no movement shift had low movement rate (9.6 m/day) and high mortality rate (0.096/day), in association with a preference for spawning ground. Mortality rates at the time of spawning were substantially greater than those previously reported in the literature and depended strongly on the movement state of the individuals and their use of spawning ground. Our quantitative analyses highlight the influence of within-individual variation in prey movement on risk of predation by land-based consumers.

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 score0.037
Threshold uncertainty score0.978

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)0.0010.000

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 head0.026
GPT teacher head0.269
Teacher spread0.243 · 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

Citations17
Published2015
Admission routes2
Has abstractyes

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