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Record W2135548152 · doi:10.1139/cjfas-2012-0377

Predation of hatchery-cultured juvenile red king crabs (<i>Paralithodes camtschaticus</i>) in the wild

2012· article· en· W2135548152 on OpenAlexvenueno aff
Benjamin Daly, Ginny L. Eckert, Timothy D. White

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsnot available
FundersAlaska Department of Fish and GameNational Science Foundation
KeywordsPredationBiologyFisheryAnomuraDecapodaPopulationJuvenileHatcheryPredatorEcologyZoologyCrustaceanFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The ecologically and commercially important red king crab (Paralithodes camtschaticus) is depleted throughout much of the North Pacific and thought to be recruitment-limited, making it an appropriate candidate for stock enhancement efforts. Information on predation of newly settled red king crabs in nearshore habitats is needed to assess the feasibility of large-scale releases. We tethered hatchery-cultured red king crabs of two sizes (range: 1.75–4.08 mm carapace width) in the field for 24 h trials in July and September 2011 and used underwater video cameras to identify predators and predation susceptibility. We identified hermit crabs (Pagurus spp.), Alaskan ronquil (Bathymaster caeruleofasciatus), Arctic shanny (Sticheus punctatus), northern rock sole (Lepidopsetta polyxystra), and kelp greenling (Hexagrammos decagrammus) as predators. Survival did not vary by body size or deployment month; however, small crabs were consumed sooner than large crabs. Most predation events occurred in daylight hours, with the exception of Alaskan ronquil. Our results suggest stock enhancement efforts should consider predator assemblages when developing release strategies. Future studies should investigate spatial variation in predation pressure at multiple locations on broad temporal scales to optimize release strategies and understand population-level effects.

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)0.001
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 score0.049
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.024
GPT teacher head0.233
Teacher spread0.208 · 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

Citations19
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicCrustacean biology and ecologyFrench-language works237,207