Bivalve-enhanced nitrogen removal from coastal estuaries
Bibliographic record
Abstract
Interest in use of bivalves to remediate estuarine eutrophication has increased in recent years. High variation among data sets, substantial focus on particle removal, and insufficient links to anthropogenic nitrogen (N) sources encouraged this empirical examination of N removal by bivalves from estuaries receiving different N loads. We determined the capacity of the oyster Crassostrea virginica to remove N by comparing N assimilated into tissues with anthropogenic N from land or available in phytoplankton. Oyster growth yielded 0.2–0.4 g N in tissues and depended on estuary-specific conditions. δ 15 N values confirmed that N in oyster tissues derived from local anthropogenic sources. At representative restoration and aquaculture conditions (≤400 oysters·m –2 at 0.5%–1.0% of estuary area), estimated N removal was ≤15% of land-derived loads and <1% of phytoplankton N. N removal via biogeochemical processes was negligible during grow-out, but became important after oysters attained harvestable size. This study explicitly demonstrates that oysters assimilated land-derived N, but suggests that bivalve bioremediation consider trade-offs between intensity of planting, ecological effects, and available space.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".