Context-dependant survival of the invasive seaweed Codium fragile ssp. tomentosoides in kelp bed and urchin barren habitats off Nova Scotia
Bibliographic record
Abstract
This study examines the fate of the invasive alga Codium fragile ssp.tomentosoides at destructive grazing fronts of the green sea urchin Strongylocentrotus droebachiensis along the margins of algal beds and in barren grounds formed in the wake of these fronts.We monitored the first reported encounter between an urchin front and an algal bed containing C. fragile, and conducted a series of manipulative experiments at a grazing front and in a barrens habitat.Urchin density had a significant effect on survival of C. fragile.At low densities, urchin fronts were more likely to bypass the invasive alga, though urchins following behind the front eventually consumed most individuals.Urchins' preferred food, laminarian kelps, affected the survival time of C. fragile by slowing the forward propagation of the front, but did not divert urchins from consuming C. fragile.The presence of dense stands of the unpalatable macroalgae Desmarestia viridis and periods of high water temperature and wave action appeared to facilitate the survival of C. fragile by affecting urchin foraging behaviour.Our results suggest that, although urchins have the potential to exert strong control over populations of C. fragile, the outcome of interactions between the 2 species is likely to depend on their biotic and abiotic context.
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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 | 0.000 |
| 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".