Opportunistic predation by small fishes on epibiota of jetty pilings in urban waterways
Bibliographic record
Abstract
Epibiota were sampled on nine small jetties in the tidal, urban canals of south‐east Queensland, Australia, to determine if the small fishes that are associated with these jetties prey on the epibiota on the pilings of the jetties and whether these fishes depend on the epibiota as a source of food. Epibiota was dominated by barnacles, filamentous and foliose algae and ranged in thickness from 4 to 11 mm. The two species of fishes that associated most closely with jetty pilings, Pandaka lidwilli (Gobiidae) and Monodactylus argenteus (Monodactylidae), were sampled twice during the day and twice during the night for analysis of stomach contents. During the day, the diet of P. lidwilli was dominated by amphipods ( c. 70%, by mass of organic content), with copepods, bivalves and bryozoans each contributing <10%. At night, amphipods contributed less ( c. 45%) and copepods more ( c. 35%). The diet of M. argenteus was dominated by filamentous algae (55%) and amphipods (20%) during the day and filamentous algae (70%) and barnacle cirri (23%) at night. Epibiota, therefore, made a substantial contribution to the diet of the fishes but were not the sole source of food for either species. As jetties were the only structures that supported epibiota in the area, fishes probably sourced their epibiota from the pilings of the jetties. Whether fishes depended on the epibiota was, therefore, tested using a manipulative before‐after‐control‐impact (BACI) study. Three jetties were assigned randomly to each of three treatments: (1) epibiota removed from pilings, (2) epibiota cut and damaged (a procedural control) and (3) epibiota left undisturbed. Abundances of P. lidwilli and M. argenteus around jetty pilings remained similar across all treatments from before to after the removal of epibiota. These results indicate that although fishes consumed epibiota on the jetties, they did not depend on the epibiota of the jetties for food.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".