Effect of hypoxia on habitat quality of striped bass (<i>Morone saxatilis</i>) in Chesapeake Bay
Bibliographic record
Abstract
Eutrophication-induced hypoxia may affect both benthic and pelagic organisms in coastal systems. To evaluate the effect of hypoxia on pelagic striped bass (Morone saxatilis), we quantified the growth rate potential (GRP) of age-2 and age-4 fish in Chesapeake Bay during 1996 and 2000 using observed temperature, dissolved oxygen, and prey abundance information in a spatially explicit bioenergetics modeling framework. Regions of the Bay with bottom hypoxia were generally areas with high quality habitat (i.e., GRP > 0 g·g–1·day–1), primarily because prey fish were forced into warm, oxygenated surface waters suitable for striped bass foraging and growth. In turn, by concentrating fish prey above the oxycline and removing bottom waters as a refuge, hypoxia likely enhanced striped bass predation efficiency and contributed to the recovery of striped bass during the mid-1990s, a time when the striped bass fishery also was closed. This short-term positive effect of hypoxia on striped bass, however, appears to have been counterbalanced by a long-term negative effect of hypoxia in recent years. Ultimately, hypoxia-enhanced predation efficiency, combined with an abundance of striped bass due to restricted harvest, appears to be causing overconsumption of prey fishes in Chesapeake Bay, thus helping to explain poor growth and health of striped bass in recent years.
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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 | 0.000 |
| 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 | 0.000 |
| 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".