Research Tools to Investigate Movements, Migrations, and Life History of Sturgeons (Acipenseridae), with an Emphasis on Marine-Oriented Populations
Bibliographic record
Abstract
Worldwide, sturgeons (Acipenseridae) are among the most endangered fishes due to habitat degradation, overfishing, and inherent life history characteristics (long life span, late maturation, and infrequent spawning). As most sturgeons are anadromous, a considerable portion of their life history occurs in estuarine and marine environments where they may encounter unique threats (e.g., interception in non-target fisheries). Of the 16 marine-oriented species, 12 are designated as Critically Endangered by the IUCN, and these include species commercially harvested. We review important research tools and techniques (tagging, electronic tagging, genetics, microchemistry, observatory) and discuss the comparative utility of these techniques to investigate movements, migrations, and life-history characteristics of sturgeons. Examples are provided regarding what the applications have revealed regarding movement and migration and how this information can be used for conservation and management. Through studies that include Gulf (Acipenser oxyrinchus desotoi) and Green Sturgeon (A. medirostris), we illustrate what is known about well-studied species and then explore lesser-studied species. A more complete picture of migration is available for North American sturgeon species, while European and Asian species, which are among the most endangered sturgeons, are less understood. We put forth recommendations that encourage the support of stewardship initiatives to build awareness and provide key information for population assessment and monitoring.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.011 |
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".