Adult Prey Neutralizes Predator Nonconsumptive Limitation of Prey Recruitment
Bibliographic record
Abstract
Recent studies have shown that predator chemical cues can limit prey demographic rates such as recruitment. For instance, barnacle pelagic larvae reduce settlement where predatory dogwhelk cues are detected, thereby limiting benthic recruitment. However, adult barnacles attract conspecific larvae through chemical and visual cues, aiding larvae to find suitable habitat for development. Thus, we tested the hypothesis that the presence of adult barnacles (Semibalanus balanoides) can neutralize dogwhelk (Nucella lapillus) nonconsumptive effects on barnacle recruitment. We did a field experiment in Atlantic Canada during the 2012 and 2013 barnacle recruitment seasons (May-June). We manipulated the presence of dogwhelks (without allowing them to physically contact barnacles) and adult barnacles in cages established in rocky intertidal habitats. At the end of both recruitment seasons, we measured barnacle recruit density on tiles kept inside the cages. Without adult barnacles, the nearby presence of dogwhelks limited barnacle recruitment by 51%. However, the presence of adult barnacles increased barnacle recruitment by 44% and neutralized dogwhelk nonconsumptive effects on barnacle recruitment, as recruit density was unaffected by dogwhelk presence. For species from several invertebrate phyla, benthic adult organisms attract conspecific pelagic larvae. Thus, adult prey might commonly constitute a key factor preventing negative predator nonconsumptive effects on prey recruitment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".