Patterns in vertical distribution and their potential effects on transport of larval benthic invertebrates in a shallow embayment
Bibliographic record
Abstract
Measurements of larval vertical distributions at high temporal and spatial resolutions as well as larval behavioural responses to environmental characteristics are needed to parameterize bio-physical models of larval dispersal or transport.We studied larval vertical distribution for 7 taxonomic groups (gastropods, bivalves, polychaetes, bryozoans, asteroids, carideans and brachyurans), with different morphology, swimming abilities and life-history strategies, and examined whether these vary with physical or biological factors and periodic cycles (diel period and tidal state) in the field.Using a pump, we collected plankton samples at 6 depths (3, 6, 9, 12, 18 and 24 m), over a 36 and a 26 h period.Temperature, salinity, fluorescence and current velocity were measured concurrently.Larval vertical distribution varied among taxonomic groups, but 4 patterns could be distinguished: (1) larvae exclusively in the mixed layer (asteroids), (2) larvae predominantly below the thermocline, halocline and pycnocline (gastropods, bivalves, polychaetes), (3) larvae associated predominantly with the fluorescence maximum (bryozoans and carideans) and (4) larval distribution varying dielly (gastropods, polychaetes, carideans and brachyurans).Based on flow velocities and depending on distribution, asteroid larvae were likely to be transported farther than those of bryozoans and carideans, while direction and magnitude of transport varied for the other larvae.For most taxonomic groups, behaviour observed in the field agreed with measured laboratory responses to relevant cues.For asteroids and bivalves, simple beha vioural parameters can be generated that can be utilized to improve the accuracy of biophysical models.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".