Impacts of eutrophication and oil spills on the Gulf of Finland herring stock
Bibliographic record
Abstract
The Baltic Sea is one of the world’s most stressed sea areas. Major threats to the ecosystem include eutrophication and oil spills. The progression of anthropogenic nutrient enrichment is lengthy and gradual, while oil spills cause rapid changes in the system, with varying impact time. We quantify the impact of eutrophication and the key ecological covariates on the population dynamics of the major pelagic fish stock, the Baltic herring (Clupea harengus membras), in the Gulf of Finland. The full life cycle of herring is represented with a probabilistic state-space model. Moreover, we analyse the impact of the oil spill from M/T Antonio Gramsci in 1987 on herring survival. The results confirm impact of the spill on the early life-stage survival; the observed high frequency of malformed herring larvae in surveys signaled elevated mortality of the year class. The optimal July–August chlorophyll a concentration for herring reproduction is approximately 5 μg·L−1. This level is currently exceeded, suggesting recruitment impairment due to eutrophication. The herring stock was also recruitment-overfished. Analysis suggests deceleration of herring growth as salinity descends below 6 psu.
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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 | 0.002 |
| 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 | 0.001 | 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".