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Record W2141569718 · doi:10.1093/beheco/arm133

Survival benefits and divergence of predator-induced behavior between pumpkinseed sunfish ecomorphs

2007· article· en· W2141569718 on OpenAlexaff
Beren W. Robinson, Andrew J. Januszkiewicz, Jens C. Koblitz

Bibliographic record

VenueBehavioral Ecology · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsLepomisPredationBiologyPredatorJuvenileEcologyPelagic zonePhenotypic plasticityEcomorphologyForagingHabitat

Abstract

fetched live from OpenAlex

Resource use is widely thought to influence adaptive phenotypic divergence, whereas other ecological factors, such as predation, are frequently overlooked, particularly in studies of polyphenism in fishes. Juvenile pumpkinseed sunfish (Lepomis gibbosus) reared with predatory walleye (Sander vitreus) increase body depth and dorsal spine length, indicating that developmental responses to predation can shape phenotype. Body form responses to the same predator cues though have also evolutionarily diverged between sunfish ecomorphs that coexist in single lake populations by inhabiting either littoral or pelagic habitats, suggesting that predation risk varies between habitats. Here, we test if prior exposure to predator cues influences the development of behavior in juvenile pumpkinseed sunfish, if behavioral responses to the same predator cues vary between ecomorphs, and if induced phenotypic variation affects survival under predation. Behavior depended strongly on prior exposure to predator cues, but this effect varied between sunfish ecomorphs, indicating that ecomorphs have different responses to the same predator cues. Predator-induced phenotypes had higher survival than control phenotypes under simulated littoral but not pelagic conditions. Predator-induced phenotypic responses are candidate-inducible defenses, and divergent responses between ecomorphs suggest that they can evolve in response to selection imposed by differences in habitat-specific predation risk.

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 score0.279
Threshold uncertainty score0.400

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 head0.073
GPT teacher head0.287
Teacher spread0.214 · 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

Citations20
Published2007
Admission routes1
Has abstractyes

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