Effect of green macroalgal mats on burial depth of soft-shelled clams Mya arenaria
Bibliographic record
Abstract
Green macroalgal mats are becoming prevalent in many parts of the world, including on important clam-harvesting beaches in SW New Brunswick, Canada. Such mats (Enteromorpha sp. and Cladophora sp.) may be affecting populations of soft-shelled clams Mya arenaria (L.). We investigated the effect of these mats on burial depth of soft-shelled clams in the field (2 impacted sites with high algal cover and 2 reference sites with no algal mats) and laboratory. At impacted sites, burial depth was significantly shallower for clams under macroalgal mats than for those in areas clear of algae. In the comparison of areas clear of algae at impacted sites to the reference sites, clam burial depth was not significantly different; rather, burial depth varied between sites independent of site type. Field measurements of benthic respiration and total sulfides were significantly higher in areas in which algal mats were present than in areas in which they were absent. In an 8 d laboratory experiment, clams (4 per aquarium) were placed in sand (10 cm deep) and covered with 0, 2 or 6 cm of macroalgae. Clam burial depth quickly decreased under algae and remained significantly shallower under 2 and 6 cm of algae than in the control (no algae). Near the end of the experiment, we removed the algae, and burial depth quickly increased. At the end of the experiment, clam body mass and dissolved oxygen at the sediment surface did not differ significantly between treatments, although both variables showed a decreasing trend with increasing algal mat cover. Dissolved organic carbon in pore water at the end of the experiment was significantly higher in the 6 cm algal treatment than in the control and 2 cm algal aquaria. The presence of algal mats clearly affects burial depth of softshelled clams. This in turn may have impacts on predator-clam interactions and on the surrounding environment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".