Nonconsumptive Predator Effects on Prey Demography: Recent Advances Using Intertidal Invertebrates
Bibliographic record
Abstract
Predators influence prey demography through consumption, but the mere presence of predators may trigger behavioural changes in prey that, if persistent or intense, may also influence prey demography. A tractable system to study such nonconsumptive effects (NCEs) of predators involves intertidal invertebrates. This mini review summarises recent research using barnacles and mussels as prey and dogwhelks as predators. The field manipulation of dogwhelk density revealed that pelagic barnacle larvae avoid benthic settlement near dogwhelks, which limits barnacle recruitment, a relevant outcome because recruitment is the only source of population replenishment for barnacles, as they are sessile. This avoidance behaviour is likely triggered by waterborne dogwhelk cues and may have evolved to limit future predation risk. Increasing densities of barnacle recruits and adults can prevent such NCEs from occurring, seemingly because benthic barnacles attract conspecific larvae through chemical cues. Barnacle recruit density increased with the abundance of coastal phytoplankton (food for barnacle larvae and recruits), so barnacle food supply seems to indirectly limit dogwhelk NCEs. By inhibiting barnacle feeding, dogwhelk cues also limited barnacle growth and reproductive output. Wave action weakens dogwhelk NCEs likely through hydrodynamic influences. Dogwhelk cues also limit mussel recruitment, as mussel larvae also exhibit predator avoidance behaviour. The NCEs on recruitment are weaker for mussels than for barnacles, possibly because mussel larvae can detach themselves after initial settlement, an ability that barnacle larvae lack. Overall, these field experiments provide evidence of predator NCEs on prey demography for coastal marine systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".