Status of shortnose sturgeon, Acipenser brevirostrum, in the Neuse River, North Carolina
Bibliographic record
Abstract
The purpose of the research was to determine if shortnose sturgeon, Acipenser brevirostrum, occur within the Neuse River, North Carolina. Shortnose sturgeon historically occurred in most major Atlantic Coast rivers from Saint Johns River, New Brunswick, Canada to St. Johns River, Florida. Anecdotal evidence suggests that a population of shortnose sturgeon once occurred in the Neuse River, North Carolina, but their current status was unknown. In compliance with the National Marine Fisheries Service shortnose sturgeon sampling protocol, a two-year intensive gillnet survey was conducted in order to determine the population status of shortnose sturgeon within the Neuse River. Habitat surveys showed that the lower Neuse River, where shortnose sturgeon would be expected to occur during summer, was severely hypoxic in June - September of 2001 - 2002. No shortnose sturgeon were observed during the two-year survey (> 200 h of netting effort) although four juvenile Atlantic sturgeon were encountered. These two species occupy similar habitats in other river systems. A juvenile Atlantic sturgeon tagged with a transmitter moved upstream of the unsuitable habitat and remained in a restricted area until late fall, when water quality improved due to increased flows and lower temperatures.\n\nThe probability of detection for varying population sizes of shortnose sturgeon was calculated in order to determine if adequate sampling had been completed to conclude an absence of shortnose sturgeon in the Neuse River. The detection analysis stated that a population size of 50 or more individuals should be detected in 200 h of netting effort. Therefore, based on our sampling efforts, we hypothesize that shortnose sturgeon are extirpated from the Neuse River. We believe that poor water quality is a key factor in the extirpation of shortnose sturgeon in the Neuse River. Population recovery may be impossible until habitat quality can be improved.\n\nFinally, we observed that shortnose sturgeon have a disjunct distribution with an absence spanning from Chesapeake Bay to Pamlico Sound tributaries. Logistic regression models based on river characteristics were developed to help predict presence of shortnose sturgeon within a river system. River characteristics included in the models: total length, estimated watershed area above the fall line, and distance to the first dam. These characteristics described size of the river system, available spawning habitat, and blockage to spawning migration. Current models suggested that large river systems with sufficient spawning habitat and no blockages to migration are more likely to contain a population of shortnose sturgeon. The models predict that the Neuse River should contain a population of shortnose sturgeon; therefore, leading to further evidence that poor water quality within the Neuse River may be the key factor to the recovery of the species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".