Effect of water movement and substratum type on vegetative recruitment of the invasive green alga <i>Codium fragile</i> ssp. <i>tomentosoides</i>
Bibliographic record
Abstract
Abstract We examined the ability of vegetative propagules (small buds and branch fragments) of the green alga Codium fragile ssp. tomentosoides to attach and grow on natural substrata in laboratory and field experiments. In the laboratory, the probability of attachment (on coralline algae, mussel shell, smooth and rough rock) was greater for buds than excised apical branches (both ∼4 cm long) over 10 weeks, and greater in weak flow (1.3 cm s-1) than static conditions. Probability of attachment differed among substrata in flow (greater on coralline algae than smooth rock) but not static conditions. Attachment strength in flow was greater for buds than fragments (pooled over substrata). Growth was greater for fragments than buds in static conditions, but not in flow. Fragments grew more in static conditions than in flow. In a field experiment, buds were transplanted to three tide pools at different tidal heights on a rocky shore. After eight months, the proportion that attached and attachment strengths of transplants did not differ significantly among pools. However, transplants in the high pool grew less and were discolored and atypically branched compared to those in pools lower on the shore. These findings indicate that vegetative propagation may contribute to the invasive success of Codium fragile.
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 | 0.001 |
| 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".