Habitat-mediated direct and indirect interactions in a marine sedimentary system from Atlantic Canada
Bibliographic record
Abstract
Trophic cascades focusing on direct (consumptive) effects have been well studied in marine ecosystems. However, less attention has been given to cascades involving indirect interactions embedded in distinct habitats. We focused on the interactions between a non-indigenous predator (the green crab Carcinus maenas), a consumer (the mud crab Panopeus herbstii), and a prey species (juvenile eastern oysters Crassostrea virginica). These interactions were studied in 3 small yet distinct habitats of increasing complexity: bare sediments, patches of blue mussels Mytilus edulis (BM), and a unique habitat consisting of giant Irish moss Chondrus crispus and mussels combined (IMBM). In the field, green crab predation rates on mud crabs were estimated in each of the abovementioned habitats using tethering experiments. The results showed that green crab foraging was most effective in bare sediments and least effective in IMBM, i.e. the least and most complex habitats, respectively. Trials conducted in the laboratory with mud crabs foraging over oysters showed a similar outcome: oyster mortality rates declined with increased habitat complexity. However, when trials were conducted in the presence of a green crab, this pattern reversed, and oyster mortality was lowest in bare sediments. Mud crab behavior was consistent with these results: in the presence of a green crab, mud crabs were less active and spent more time sheltering, whereas in its absence, the opposite pattern was observed, especially in bare sediments. These behaviorally driven indirect interactions are dependent on the presence of a non-indigenous predator and mediated by the type of habitat.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".