Spatial distribution of brown shrimp (<i>Farfantepenaeus aztecus</i>) on the northwestern Gulf of Mexico shelf: effects of abundance and hypoxia
Bibliographic record
Abstract
We used fishery-independent hydrographic and bottom trawl surveys on the northwestern Gulf of Mexico shelf from 19832000 to test for density dependence and effects of hypoxia (dissolved oxygen ≤ 2.0 mg·L1) on the spatial distribution of brown shrimp (Farfantepenaeus aztecus). Spatial distribution of shrimp was positively related to abundance on the Texas shelf but negatively related to abundance on the Louisiana shelf. Density dependence was weak, however, and may have been due to factors other than density-dependent habitat selection. Males were distributed over a broader area and further offshore than were females, though differences in spatial distribution between sexes were not large (~10%15%). Large-scale hypoxia (up to ~20 000 km2) on the Louisiana shelf occurs in regions of typically high shrimp density and results in substantial habitat loss (up to ~25% of the Louisiana shelf), with shifts in distribution and associated high densities both inshore and offshore of the hypoxic region. We discuss these results in terms of the generality of density-dependent spatial distributions in marine populations and potential consequences of habitat loss and associated shifts in distribution due to low dissolved oxygen.
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".