Data from: Active buoyancy adjustment increases dispersal potential in benthic marine animals
Bibliographic record
Abstract
1. While the study of dispersal and connectivity in the ocean typically centers on pelagic species and planktonic larval stages of benthic species, the present work explores an overlooked locomotor means in post-settlement benthic stages that redefines their dispersal potential. 2. Members of the echinoderm class Holothuroidea colonize a diversity of marine environments worldwide, where they play key ecological and economical roles, making their conservation a priority. Holothuroids are commonly called sea cucumbers or sea slugs to reflect their slow movements and are assumed to disperse chiefly through pelagic larvae. 3. The present study documents and explores their unexpected ability to actively modify their buoyancy, leading them to tumble or float at speeds orders of magnitudes faster than through benthic crawling. Two focal species representing different taxonomic orders, geographic distributions and reproductive strategies were studied over several years. 4. Active buoyancy adjustment (ABA) was achieved through a rapid increase in seawater to flesh ratio by up to 740%, leading to bloating, and simultaneously detachment from the substrate. It occurred as early as 6 months post settlement in juveniles and was recorded in wild adult populations. In experimental trials, ABA was triggered by high conspecific density, decreasing salinity and increasing water turbidity. Based on field video footage, ABA-assisted movements generated speeds of up to 90 km d-1. 5. These findings imply that displacement during planktonic larval stages may not supersede the locomotor capacity of benthic stages, challenging the notion of sedentarity. Combining the present results and anecdotal reports, ABA emerges as a generalized means of dispersal among benthic animals, with critical implications for worldwide management and conservation of commercially and ecologically significant species.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.104 | 0.035 |
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".