Empirical, spatially explicit natural mortality and movement rate estimates for the threatened Gulf sturgeon (<i>Acipenser oxyrinchus desotoi</i>)
Bibliographic record
Abstract
Understanding mortality rates and movement patterns across a species’ distribution can provide key insight necessary for developing effective conservation, recovery, and management plans. We directly estimated site fidelity and natural mortality rates for the threatened Gulf sturgeon (Acipenser oxyrinchus desotoi) across a large portion of their range in the northern Gulf of Mexico using acoustic telemetry methods and a simulation-tested, multistate mark–recapture model. Our results suggest that fidelity rates to riverine habitats used during spring and summer are high, but natural mortality rates vary widely. Our results are highly relevant for managing this species. The high fidelity rates, coupled with supporting genetic analyses, suggest that management of individual riverine populations of Gulf sturgeon should be considered. The need for individual river-based management is exacerbated by the variation in natural mortality rates among rivers. The reasons for these differences in mortality are unclear, but are an important area of future research because higher mortality rates may impede recovery of some Gulf sturgeon populations to stated management targets.
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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 | 0.001 | 0.003 |
| 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".