Precipitous declines in pinto abalone (Haliotis kamtschatkana kamtschatkana) abundance in the San Juan Archipelago, Washington, USA, despite statewide fishery closure
Bibliographic record
Abstract
Pinto abalone ( Haliotis kamtschatkana kamtschatkana ) index stations in the San Juan Archipelago were systematically monitored by the Washington Department of Fish and Wildlife from 1992 through 2006. During this period, abalone abundance declined by 77% and the mean shell length (SL) increased 10.4 mm. Abalone densities at all index stations are currently well below the threshold of 0.15 abalone·m–2 required for successful fertilization. From 1992 to 1996, 16% of individuals encountered measured <90 mm SL, while only 6% of the individuals from 2003 to 2006 were in this small size class. Similarly, the number of those >114 mm SL was greater in the 2000s than in the 1990s. The mean SL of all live abalone observed in the 1990s (107.62 ± 0.87 mm) was significantly different from the mean SL of empty shells (114.21 ± 2.1 mm), but no difference was detected between the mean SLs of empty shells and live abalone in the 2000s (114.97 ± 1.42 mm). Taken together, these data suggest recruitment failure from an Allee response to low population densities.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".