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Record W2790217338 · doi:10.1111/evo.13444

Exposure to predators does not lead to the evolution of larger brains in experimental populations of threespine stickleback

2018· article· en· W2790217338 on OpenAlexaff
Kieran Samuk, Jan Y Xue, Diana J. Rennision

Bibliographic record

VenueEvolution · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSticklebackPredationBiologyLimnetic zoneVertebrateBrain sizePredatorSelection (genetic algorithm)GasterosteusEvolutionary biologyNatural selectionEcologyZoologyAdaptation (eye)Fish <Actinopterygii>NeuroscienceGeneFishery

Abstract

fetched live from OpenAlex

Natural selection is often invoked to explain differences in brain size among vertebrates. However, the particular agents of selection that shape brain size variation remain obscure. Recent studies suggest that predators may select for larger brains because increased cognitive and sensory abilities allow prey to better elude predators. Yet, there is little direct evidence that exposure to predators causes the evolution of larger brains in prey species. We experimentally tested this prediction by exposing families of 1000-2000 F2 hybrid benthic-limnetic threespine stickleback to predators under naturalistic conditions, along with matched controls. After two generations of selection, we found that fish from the predator addition treatment had significantly smaller brains (specifically smaller telencephalons and optic lobes) than fish from the control treatment. After an additional generation of selection, we reared experimental fish in a common environment and found that this difference in brain size was maintained in the offspring of fish from the predator addition treatment. Our results provide direct experimental evidence that (a) predators can indeed drive the evolution of brain size--but not in the fashion commonly expected and (b) that the tools of experimental evolution can be used to the study the evolution of the vertebrate brain.

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 score0.062
Threshold uncertainty score0.990

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 head0.014
GPT teacher head0.258
Teacher spread0.244 · 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

Citations23
Published2018
Admission routes1
Has abstractyes

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