Changes in vertical distribution and aggregative behaviour in response to population density for larval sea urchins (<i>Strongylocentrotus droebachiensis</i>) and sea stars (<i>Asterias rubens</i>)
Bibliographic record
Abstract
Abstract We examined the effects of the presence of larval conspecifics on larval vertical distribution of four‐arm and six‐arm plutei of Strongylocentrotus droebachiensis and bipinnaria of Asterias rubens, in laboratory experiments, by manipulating population density. Larvae were introduced to experimental columns (10 × 10 × 30 cm) at one of two or three population densities (S. droebachiensis: 0.1 and 10 larvae·ml−1; A. rubens: 0.1, 1 and 10 larvae·ml−1). Subsequent changes in vertical distribution were determined from images of the larvae in the columns illuminated by a 532‐nm laser and captured by a high‐resolution camera. Larvae of both species were found higher in the water column in the high than in the low and intermediate population densities. The relationship between vertical swimming velocity and nearest neighbour distance (NND) was measured for four‐arm plutei of S. droebachiensis, and used to determine a range in distances among individuals that may affect potential interactions. The variation in swimming velocity decreased with increasing proximity below a threshold distance among individuals of 10 mm, which was greater than the estimated distance in the high population density. We suggest that the increased larval aggregation near the water surface under high population density is the result of a behavioural response to conspecifics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".