Exploring the decline of oyster beds in Atlantic Canada shorelines: potential effects of crab predation on American oysters (Crassostrea virginica)
Bibliographic record
Abstract
Atlantic Canada’s American oyster ( Crassostrea virginica ) beds, while economically and ecologically important, have been in decline over the past few decades. Predation by crabs, in particular by the European green crab ( Carcinus maenas ), has been proposed as one of the potential causes of such decline. Hence, this study examined oyster mortality levels in multiple beds across Prince Edward Island (PEI) and then experimentally assessed the contribution of green crab predation to oyster mortality. Results from surveys conducted in 10 estuaries across PEI in 2014 indicate that the probability of mortality for small oysters was significantly higher when green crabs were present then in areas without green crabs. This probability of mortality was significantly less when there was the presence of alternative prey like natural mussel beds ( Mytilus edulis ). The odds of oyster mortality were also higher when beds had rock crabs ( Cancer irroratus ) compared to beds with no rock crabs. Given the potential importance of green crab predation, its influence was assessed in 2015 using two field experiments with tethered oysters. Our results indicate that odds of small oyster mortality occurring were much higher in green crab inclusion cages than in the open environment and the exclusion cages. These results reaffirm that oysters up to ~40 mm SL are vulnerable to predation, and at least some of the mortality affecting these oysters can be causally attributed to green crab predation. Green crab predation rates upon small oysters are relevant given the economic benefits and ecosystem services provided by these bivalves. They highlight the need for the industry to consider mitigation measures and potentially adapt their oyster growing strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".