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Behavioural trade‐offs between growth and mortality explain evolution of submaximal growth rates

2006· article· en· W1484404377 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Animal Ecology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British ColumbiaUniversity of ManitobaUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaFreshwater Fisheries Society of British Columbia
KeywordsPredationForagingTroutBiologyTrade-offEcologyRainbow troutGrowth rateFisheryFish <Actinopterygii>

Abstract

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1. The importance of body size and growth rate in ecological interactions is widely recognized, and both are frequently used as surrogates for fitness. However, if there are significant costs associated with rapid growth rates then its fitness benefits may be questioned. 2. In replicated whole-lake experiments, we show that a domestic strain of rainbow trout (artificially selected for maximum intrinsic growth rate) use productive but risky habitats more than wild trout. Consequently, domestic trout grow faster in all situations, experience greater survival in the absence of predators, but have lower survival in the presence of predators. Therefore, rapid growth rates are selected against due to increased foraging effort (or conversely, lower antipredator behaviour) that increases vulnerability to predators. In other words, there is a behaviourally mediated trade-off between growth and mortality rates. 3. Whereas rapid growth is beneficial in many ecological interactions, our results show the mortality costs of achieving it are large in the presence of predators, which can help explain the absence of an average phenotype with maximized growth rates in nature.

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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 score0.003
Threshold uncertainty score0.421

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 head0.016
GPT teacher head0.237
Teacher spread0.221 · 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