Anadromous Sturgeons: Habitats, Threats, and Management
Bibliographic record
Abstract
Abstract. – Shortnose sturgeon Acipenser brevirostrum historically occurred in most major Atlantic Coast rivers from Saint Johns River, New Brunswick, Canada to St. John’s River, Florida. However, there are few records of shortnose sturgeon occurrences within North Carolina and none from the Neuse River. We conducted a 2-year intensive gill-net survey, following the National Marine Fisheries Service sampling protocol, and a reward program in order to determine their population status within the Neuse River. No shortnose sturgeon were observed, although 10 juvenile Atlantic sturgeon (506–992 mm fork length) were encountered. Habitat surveys of the lower Neuse River, where shortnose sturgeon would be expected to occur during summer, showed that bottom waters were severely hypoxic during June–September of 2001–2002. A juvenile Atlantic sturgeon tagged with an ultrasonic transmitter moved upstream of the unsuitable summer habitat and remained in a restricted area until late fall, when water quality improved due to increased flows and lower temperatures. We developed logistic regression models of watershed and river characteristics based on 36 Atlantic Coast rivers with a known presence or absence of shortnose sturgeon. Model predictions suggest that the Neuse River should contain a population of shortnose sturgeon based on the amount of physical habitat. We hypothesize that shortnose sturgeon have been extirpated from the Neuse River due to a lack of suitable summer habitat. Population recovery may be impossible until habitat quality can be improved.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".