Diffusivity in a marine macrophyte canopy: implications for submarine pollination and dispersal
Bibliographic record
Abstract
The dispersion and capture of differently shaped particles within a Zostera marina L. (eelgrass; Zosteraceae) bed were examined to understand submarine pollination and other dispersals. During periods of moderate flow in the canopy, the capture rate of "spherical" (the shape of ancestral pollen) and "filamentous" (the shape of eelgrass pollen) particles was greater for particles released at the top of the canopy (3.07 and 4.53% × 10(-5) cm(-2) of collector; i.e., percentage of particles captured normalized to collector area) and greater for filamentous than for spherical particles (4.51% × 10(-5) cm(-2) vs. 2.01% × 10(-5) cm(-2)). Estimates of the horizontal P (Joseph-Sendner diffusion velocity) and the vertical diffusivity (Gaussian K) of filamentous particles were small (P ≈ 4 × 10(-4) m/s; K ≈ 10(-4) m(2)/s) compared to theoretical values that do not consider plant canopies. These findings support the concept that eelgrass canopies modify the fluid dynamics (i.e., reduced turbulent mixing) within their canopies. These results indicate that 1000-10 000 Z. marina pollen are required to pollinate a single flower. Similarly, it was estimated that under some conditions, the probability of particle impaction on eelgrass vegetation approaches certainty. These results provide insight into the evolution of filamentous pollen and submarine pollination, as well as dispersal and other mass transport phenomena within macrophyte canopies.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".