Abundance and Size Structure of Shortnose Sturgeon in the Altamaha River, Georgia
Bibliographic record
Abstract
Abstract Endangered Shortnose Sturgeon Acipenser brevirostrum inhabit large tidal rivers along the Atlantic coastline of North America, ranging from the St. John River, Canada, southward to the St. Johns River, Florida. Currently, long‐term assessments of the abundance and age structure of southern populations are completely lacking. To address this information gap, we assessed recent changes in Shortnose Sturgeon abundance and age structure by sampling with anchored entanglement gear in the Altamaha River, Georgia, during summer in 2004–2010. To estimate abundance, we used the Huggins closed‐capture model in Program MARK. We assessed size structure by interpreting the first, second, and third quartiles of the FL of individuals captured during each year. In total, we captured 1,737 Shortnose Sturgeon (72 recaptures). Total estimated abundance was variable, ranging from 1,206 individuals (95% lognormal confidence interval [CI] = 566–2,759) in 2009 to 5,551 individuals (95% CI = 2,804–11,304) in 2006. Much of the annual variation in total abundance was attributable to wide variations in juvenile abundance, which ranged from a low of 62 individuals (95% CI = 24–181) in 2009 to a high of 3,467 individuals (95% CI = 1,744–7,095) in 2006. Annual shifts in size structure were indicative of rapid population turnover, probably resulting from a combination of mortality and permanent emigration. Although the Altamaha River Shortnose Sturgeon population shares several characteristics with northern populations (e.g., variable juvenile abundance and stable adult abundance), our results suggest that southern populations are more susceptible to decline because of their accelerated life cycle and inherently lower abundances.
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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 | 0.000 | 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".