Indirect effects of sea otters on rockfish (<i>Sebastes</i> spp.) in giant kelp forests
Bibliographic record
Abstract
Sea otters are a classic example of a predator controlling ecosystem productivity through cascading effects on basal, habitat-forming kelp species. However, their indirect effects on other kelp-associated taxa like fishes are poorly understood. We examined the effects of sea otter (Enhydra lutris) reintroduction along the west coast of Vancouver Island, Canada on giant kelp (Macrocystis pyrifera) distributions and the trophic niches and growth of two common kelp forest fishes, black (Sebastes melanops) and copper (S. caurinus) rockfishes. We sampled 47 kelp forests, and found that red sea urchins (Strongylocentrotus franciscanus) were eliminated in the presence of otters, and that kelp forests were 3.7 times deeper and 18.8 times larger. Despite order-of-magnitude differences in kelp forest size, adult black and copper rockfishes contained less kelp-derived carbon in their tissues (as measured by stable isotopes of C and N) in regions with otters. Adults of both species had higher mean trophic positions in the presence of otters, indicating more frequent consumption of higher trophic level prey such as fishes. Smaller trophic niche space of rockfishes in the presence of otters indicated a higher degree of trophic specialization. Juvenile black rockfishes rapidly shifted to higher kelp-carbon contents, trophic positions, and body condition factors after settling in kelp forests. The relationships of growth to length, percentage of kelp carbon, and trophic position varied between the two regions, indicating that potential effects of kelp forest size on trophic ontogeny may also affect individual performance. Our results provide evidence that the indirect effects of otters on rockfishes arise largely through the creation of habitat for fishes and other prey rather than a direct trophic connection through invertebrates or other consumers of kelp productivity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".