Mesograzer interactions with a unique strain of Irish moss Chondrus crispus: colonization, feeding, and algal condition-related effects
Bibliographic record
Abstract
Marine macroalgae are exposed to multiple sources of stress. As a result, perennial macroalga habitats have become depleted in many coastlines. Here, we investigated the role of mesograzers in the sharp decline of a unique strain ofChondrus crispus(the giant Irish moss) found solely in a lagoon in Atlantic Canada. This study was prompted by damage resembling grazing scars that appeared on the fronds as the population declined, for which no grazer had been identified. We identified potential grazers of the seaweed by deploying 4 types of experimental clumps of giant Irish moss and sampling the epifauna that colonized them. Laboratory assays were then run with an abundant species, the amphipodGammarus oceanicus, to measure feeding rates and test whether this mesograzer is capable of consuming the alga and creating measurable damage.G. oceanicus readily consumed the Irish moss at a grazing rate of 5.24 mg amphipod-1d-1and created deep lateral grazing wounds similar to those observed in the field. An additional experiment was conducted to assess whether a co-acting stressor in the lagoon, the accumulation of fine sediments, could explain the appearance and spatially patchy distribution of the damage in the population. Giant Irish moss fronds that had been buried under sediment lost twice as much biomass as those that had not. These results suggest that grazer activity and declining conditions in the lagoon have a negative and additive effect on this unique strain of Irish moss, with clear implications for its restoration.
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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 | 0.001 |
| 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".