Use of radiotelemetry to track threatened dorados Salminus brasiliensis in the upper Uruguay River, Brazil
Bibliographic record
Abstract
Little is known about the seasonal movements of fish that inhabit large rivers in South America, which makes it difficult to identify potential threats to fish populations associated with the proliferation of hydropower developments. Dorados Salminus brasiliensis (Characiformes) are large riverine piscivores that are targeted by recreational and commercial fishers and are considered regionally 'vulnerable' in Brazil due to overfishing, pollution, and habitat fragmentation. Here, we used radio telemetry to study the seasonal movements of dorados in the upper Uruguay River, Brazil, to provide the first information on large-scale migratory biology and to inform management and conservation actions. From November 2001 to July 2003, 73 dorados were radio-tracked using aerial surveys and 7 fixed radio telemetry stations installed in a section of the upper Uruguay River covering ~400 km. Despite use of an extensive radio telemetry array and aerial tracking, nearly 40% of fish tagged at the downstream site were never detected, suggesting unreported harvest, post-release mortality, or migration to tributaries or downstream reaches that extended beyond the tracking area, emphasizing the challenges of working in such a large study system in jurisdictions where research capacity and funding are limited. Nonetheless, this study yielded the first data on the migratory biology of dorados and revealed that a segment of the population is quite mobile and thus could be negatively impacted by river fragmentation, suggesting the need for management strategies that maintain connectivity (e.g. fish passage facilities).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".