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Record W2965505262 · doi:10.1111/eth.12924

Predator‐induced selection on urchin activity level depends on urchin body size

2019· article· en· W2965505262 on OpenAlexaff
Justin Pretorius, James L. L. Lichtenstein, Erika J. Eliason, Adrian C. Stier, Jonathan N. Pruitt

Bibliographic record

VenueEthology · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsMcMaster University
FundersNational Institute of General Medical SciencesFoundation for the National Institutes of HealthNational Science Foundation
KeywordsSea urchinBiologyPredationStrongylocentrotus purpuratusForagingEcologySpiny lobsterKelp forestPredatorKelpZoologyCrustacean

Abstract

fetched live from OpenAlex

Abstract Temporally consistent individual differences in behavior impact many ecological processes. We simultaneously examined the effects of individual variation in prey activity level, covering behavior, and body size on prey survival with predators using an urchin–lobster system. Specifically, we tested the hypothesis that slow‐moving purple sea urchins ( Strongylocentrotus purpuratus ) and urchins who deploy extensive substrate (pebbles and stones) covering behavior will out‐survive active urchins that deploy little to no covering behavior when pitted against a predator, the California spiny lobster ( Panulirus interruptus ). We evaluated this hypothesis by first confirming whether individual urchins exhibit temporally consistent differences in activity level and covering behavior, which they did. Next, we placed groups of four urchins in mesocosms with single lobster and monitored urchin survival for 108 hr. High activity level was negatively associated with survival, whereas urchin size and covering behavior independently did not influence survival. The negative effect of urchin activity level on urchin survival was strong for smaller urchins and weaker for large urchins. Taken together, these results suggest that purple urchin activity level and size jointly determine their susceptibility to predation by lobsters. This is potentially of great interest, because predation by recovering lobster populations could alter the stability of kelp forests by culling specific phenotypes, like foraging phenotypes, from urchin populations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.999

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.029
GPT teacher head0.253
Teacher spread0.224 · 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; both teacher heads agree on what is shown here.

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

Citations8
Published2019
Admission routes1
Has abstractyes

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