Invasive bryozoan alters interaction between a native grazer and its algal food
Bibliographic record
Abstract
The epiphytic bryozoan Membranipora membranacea encrusts the surface of kelp blades, causing recurrent large-scale defoliation events in kelp beds off the Atlantic coast of Nova Scotia, Canada. The gastropod Lacuna vincta grazes kelp, creating perforations that weaken blade tissues and increase the fragmentation rate. We assess the interaction between M. membranacea and L. vincta by measuring the grazing rate of snails on bryozoan-encrusted and non-encrusted kelp (Saccharina latissima) in no-choice and choice experiments in the laboratory conducted in November and December 2010. There was no effect of diet on grazing rate in no-choice experiments. In choice experiments, however, L. vincta grazed significantly more non-encrusted than encrusted kelp (7.1 versus 1.1 mg snail−1 d−1), and grazing rate of non-encrusted kelp was almost twice that in the no-choice experiment (3.8 mg snail−1 d−1), indicating that snails may avoid colonies of M. membranacea on partially encrusted kelp blades. We found no effect of diet on growth, reproduction and survival of snails maintained for four weeks on encrusted or non-encrusted kelp. By concentrating grazing damage on non-encrusted areas of blades, L. vincta may act synergistically with M. membranacea to increase the likelihood of blade breakage and canopy loss. This indirect effect of the invasive bryozoan could augment its direct effect on the standing biomass of native kelp beds and detrital export to adjacent communities.
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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".