Comparison of Predatory Capabilities of Invasive European Green Crabs ( <i>Carcinus maenas</i> ) and Native Red Rock Crabs ( <i>Cancer productus</i> ) Preying Upon a Common Native Bivalve ( <i>Leukoma staminea</i> )
Bibliographic record
Abstract
ABSTRACT Invasive predators are a large concern throughout invaded ranges as they commonly compete with native predators and overconsume prey items. European green crabs ( Carcinus maenas ) have a long history of causing the decline of native species populations, many of which are important fishery species, and damaging ecosystems on the Atlantic coast of North America. These invasive crabs are expected to have similar impacts on the Pacific coast of North America. Comparing the predatory capabilities of green crabs with the native red rock crab ( Cancer productus ) on an abundant native bivalve species ( Leukoma staminea , littleneck clam) will help predict how increased predation pressure due to an introduced predator might affect local prey populations. In‐laboratory predator–prey experiments were conducted to examine the behaviour and capabilities of both red rock crabs and green crabs preying upon the littleneck clam. Most red rock crabs broke into clams quickly, typically in less than 10 min, whereas green crabs were unable to damage any size class of bivalve despite overlapping in crusher chelae size with the native crabs. Successful attacks resulted in stereotypic predation traces (consistent in shape and repetitively caused by predatory attack) that are commonly found in the field. Green crabs and red rock crabs utilized different attack strategies while grappling. Because green crabs grappled the clams, in some cases for extensive periods of time, it is probable that they recognise L. staminea as a prey item. Fully‐grown L. staminea are likely in a size refuge from green crab predation. Future work should investigate the interactions between European green crabs and younger, smaller, size‐classes of Leukoma staminea .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".