Ecological effects of regime shifts in the Bering Sea and eastern North Pacific Ocean
Bibliographic record
Abstract
Abstract Large‐scale shifts occurred in climatic and oceanic conditions in 1925, 1947, 1977, 1989 and possibly 1998. These shifts affected the mix and abundance of suites of coexisting species during each period of relative environmental stability—from primary producers to apex predators. However, the 1989 regime shift was not a simple reversal of the 1977 shift. The regime shifts occurred abruptly and were neither random variations nor simple reversals to the previous conditions. Timing of these anomalous environmental events in the North Pacific Ocean appears to be linked to physical and biological responses in other oceanic regions of the world. Changes in the atmospheric pressure can alter wind patterns that affect oceanic circulation and physical properties such as salinity and depth of the thermocline. This, in turn, affects primary and secondary production. Data from the North Pacific indicate that regime shifts can have opposite effects on species living in different domains, or can affect similar species living within a single domain in opposite ways. Climatic forcing appears to indirectly affect fish and marine mammal populations through changes in the distribution and abundance of their predators and prey. Effects of regime shifts on marine ecosystems are also manifested faster at lower trophic levels. Natural variability in the productivity of fish stocks in association with regime shifts indicates that new approaches to managing fisheries should incorporate climatic as well as fisheries effects.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".