Snail leaps and bounds: drivers of the diel movement pattern of a large invertebrate, the Caribbean queen conch (<i>Lobatus gigas</i>), in a marginal inshore habitat
Bibliographic record
Abstract
Understanding the relationship between the movements of animals and their environment is crucial for fisheries and species management. There is currently a lack of detailed information about the movement of slow-moving benthic species, especially for species of ecological or commercial importance. Here we document the relationship between diel movement and environmental parameters in a groundwater-fed coastal inlet for the queen conch (Lobatus gigas (Linnaeus, 1758)), an important fishery resource of the Caribbean region, using three-dimensional accelerometers and video cameras. Our results show immature queen conch (n = 9) spend most of their active time grazing, exhibiting two main distinct movements that we characterize as a leap and a drift that are mostly used to access new foraging resources. When overturned, they flip, producing a movement with the highest acceleration recorded to limit exposure and restore normal position. Movement patterns appear to be significantly affected by the oxygen concentration of the bottom water, with lower activity during low-oxygen levels in the morning (probability of 0.75 of observing 0 movement per hour) and maximum activity during the afternoon when oxygen concentration is at its maximum (probability of 0.80 of observing >10 movements per hour). Salinity and temperature had little effect on movement patterns. Our results confirm that highly variable marginal habitats like groundwater-fed inlets are suitable for juvenile conch growth and should be included in efficient conservation plans.
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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 | 0.000 |
| 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) | 0.002 | 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".