Do shark declines create fear‐released systems?
Bibliographic record
Abstract
We illustrate the theoretical plausibility that fishery removal of sharks can indirectly alter predation pressure on different fish species via the behavioural responses of mesoconsumers released from predator intimidation. Our dynamic state variable model of foraging decisions by harbour seals, a mesopredator, predicted indirect effects of the removal of Pacific sleeper sharks on two species consumed by seals, Pacific herring and walleye pollock, as mediated by seal behaviour. Herring, a fatty fish, form near‐surface aggregations that often are ephemeral and widely dispersed. Pollock are found in the deeper strata preferred by sharks and have lower energy density than herring, but also are larger and their more continuous distribution potentially makes them the more predictable resource for seals. During simulations, predation risk from sharks produced an asymmetric trophic cascade mediated by the seal's underutilisation of deeper, riskier strata. Risk management by seals reduced mortality on pollock, which required riskier access in deep strata, while increasing mortality on herring, which could be accessed with less risk in shallow strata. This effect, however, attenuated if herring were scarcer and seal energy state was poor. During shark removal scenarios, seals shifted to deeper strata, increasing pollock consumption and substantially decreasing use of herring; the proportional change was greatest if seals were in good energy state. Prior studies have addressed how shark declines might affect community structure through density responses by species consumed by sharks; earlier models incorporating antipredator behaviour of the mesopredator (i.e. Ecosim/Ecospace) allow for activity reduction but not for the spatial shifts that altered the asymmetric trophic cascade in our simulations. Our results suggest that shark declines might have stronger ecological consequences than previously recognised if we account for spatial and diet shifts by mesoconsumers released from shark intimidation.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".