Data from: Suspended sediment causes feeding current arrests in the glass sponge Aphrocallistes vastus
Bibliographic record
Abstract
Bottom-contact trawling generates large, moving clouds of suspended sediments that can alter the behaviour of organisms adjacent to trawl paths. While increased suspended sediment concentrations (SSCs) are known to cause glass sponges to arrest filtration in lab studies, the response of sponges to sediment in situ is not yet known. Here we describe arrest behaviours in response to increased SSCs recorded from the glass sponge Aphrocallistes vastus at the Fraser Ridge sponge reef in the Strait of Georgia, British Columbia, Canada. We identified 23 arrests of the sponges’ feeding current during experimental disturbances that raised SSC to between 10 and 80 mg l-1. Single arrests lasted 4.25 ± 1.3 min (± SD) and were characterized by a 2 cm s-1 reduction in feeding current lasting 0.5 - 3 min (mean 1.91 ± 0.97 min, n = 19). In comparison, coughing arrests varied in length (31 ± 22.89 min) and lasted 4 - 15 min (10.46 ± 5.26 min, n = 4). Coughing arrests showed a distinctive on/off pattern as sponge filtration returned to normal excurrent velocities, distinguishing them from single arrests. The onset of both arrest types was correlated with elevated SSCs (r = -0.83 to -0.92). Natural SSCs at the reef averaged 4.4 mg l-1 and were correlated with tidal flow (r = 0.86 and 0.89). The combined data provide evidence that suspended sediments can stop glass sponge feeding in situ even at SSCs below those known to be generated by trawling.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.010 | 0.003 |
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".