Fish on the move: connectivity of an estuary-dependent fishery species evaluated using a large-scale acoustic telemetry array
Bibliographic record
Abstract
Connectivity — movements of animals between and among numerous habitats — and the factors (rhythmic cycles and environmental variables) influencing connectivity of juvenile Lichia amia (Teleostei: Carangidae) were assessed in complementary acoustic telemetry studies in two geographically separated estuaries (620 km apart) in South Africa. The studies were conducted within a nationwide array of acoustic receivers moored in estuaries and coastal waters. Tagged fish in both the Kowie (n = 21) and Goukou (n = 17) estuaries displayed high levels of multiple habitat connectivity, with 81% and 76% visiting nearby marine and estuarine environments, respectively. The presence of tagged L. amia within the tagging estuaries was significantly influenced by river and sea temperature (Kowie) and river inflow and moon phase (Goukou). Tidal phase, time of day, and season were found to significantly influence marine excursions undertaken by Kowie- and Goukou-tagged fish. Our study provides an assessment of connectivity among multiple estuarine, port, and marine habitats, relating those movements to rhythmic cycles and environmental variables, and highlights the benefits of tracking animals using an extensive acoustic receiver array that spans multiple habitats.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".