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Heritability of anti‐predatory traits: vigilance and locomotor performance in marmots

2010· article· en· W2031721251 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.

Bibliographic record

VenueJournal of Evolutionary Biology · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversité de Sherbrooke
FundersSchool of Life Sciences and Biotechnology Division of Life Sciences, Korea UniversityNational Geographic Society
KeywordsVigilance (psychology)HeritabilityBiologyForagingTraitPredatorGenetic correlationPredationCorrelationGenetic variationZoologyEvolutionary biologyEcologyGeneticsGene

Abstract

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Animals must allocate some proportion of their time to detecting predators. In birds and mammals, such anti-predator vigilance has been well studied, and we know that it may be influenced by a variety of intrinsic and extrinsic factors. Despite hundreds of studies focusing on vigilance and suggestions that there are individual differences in vigilance, there have been no prior studies examining its heritability in the field. Here, we present one of the first reports of (additive) genetic variation in vigilance. Using a restricted maximum likelihood procedure, we found that, in yellow-bellied marmots (Marmota flaviventris), the heritability of locomotor ability (h(2)=0.21), and especially vigilance (h(2) = 0.08), is low. These modest heritability estimates suggest great environmental variation or a history of directional selection eliminating genetic variation in these traits. We also found a significant phenotypic (r(P) = -0.09 +/- 0.04, P = 0.024) and a substantial, but not significant, genetic correlation (r(A) = -0.57 +/- 0.28, P = 0.082) between the two traits (slower animals are less vigilant while foraging). We found no evidence of differential survival or longevity associated with particular phenotypes of either trait. The genetic correlation may persist because of environmental heterogeneity and genotype-by-environment interactions maintaining the correlation, or because there are two ways to solve the problem of foraging in exposed areas: be very vigilant and rely on early detection coupled with speed to escape, or reduce vigilance to minimize time spent in an exposed location. Both strategies seem to be equally successful, and this 'locomotor ability-wariness' syndrome may therefore allow slow animals to compensate behaviourally for their impaired locomotor ability.

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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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.503
Threshold uncertainty score0.100

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 head0.012
GPT teacher head0.226
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