Data from: Mechanisms underlying predator-driven biotic resistance against introduced barnacles on the Pacific coast of Hokkaido, Japan
Bibliographic record
Abstract
Introduced species are a major threat to coastal ecosystems worldwide. Thus, understanding biotic resistance (i.e. the ability of native species to limit introduced species) is a central goal of invasion biology. This paper examines mechanisms underlying biotic resistance. Consumption can limit introduced prey provided that native predators prefer such prey. Furthermore, predator nonconsumptive effects (NCEs), mediated through predator-released cues perceived by prey, can limit prey recruitment, a key demographic process for prey populations. However, information on predator NCEs is largely absent in the context of recruitment in introduced prey. Working on the Pacific coast of Hokkaido (Japan), we addressed this knowledge gap using native predatory dogwhelks (Nucella lima) that prey on native barnacles (Chthamalus dalli) and introduced barnacles (Balanus glandula). We experimentally examined dogwhelk preferences for barnacles in the laboratory and dogwhelk NCEs on barnacle recruitment in the field. We found that N. lima preferred B. glandula over C. dalli, likely as B. glandula prey is more profitable, as suggested by previous findings in congeneric dogwhelks. Moreover, we found that N. lima NCEs limited recruit density in C. dalli and B. glandula, likely as barnacle larvae moved away from dogwhelk cues to reduce future predation risk. Our study suggests that predator prey preferences and predator nonconsumptive limitation of prey recruitment are two mechanisms that can contribute to predator-driven biotic resistance against introduced prey.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".