The ghost of a giant – Six hypotheses for how an extinct megaherbivore structured kelp forests across the North Pacific Rim
Bibliographic record
Abstract
Abstract Aim The global decline of megafauna is believed to have had significant and widespread ecological impacts. One such extinction of likely important consequence is the 18th century extinction of the Steller’s sea cow (Hydrodamalis gigas); however, little has been written about how the loss of this megaherbivore may have impacted coastal ecosystem dynamics. Drawing on historical evidence, sea cow biology, kelp forest ecology, and the ecology of extant sirenians, we propose several discrete hypotheses about the effects Steller’s sea cows may have had on kelp forest dynamics of the North Pacific. Location North Pacific Ocean. Time period Pre‐1760s. Major taxa studied Steller’s sea cow (Hydrodamalis gigas). Results & conclusions The evidence we review suggests that Steller’s sea cows exerted substantial direct and indirect influences on kelp forests, likely affecting the physical ecosystem structure, productivity, nutrient cycling, species interactions, and export of nutrients to surrounding ecosystems. This suggests that kelp forest dynamics and resilience were already significantly altered prior to the influence of more recent and well‐known stressors, such as industrial fishing and climate change, and illustrates the important ecological roles that are lost with megafaunal extinction.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".