Deposition and Long-Shore Transport of Dredge Spoils to Nourish Beaches: Impacts on Benthic Infauna of an Ebb-Tidal Delta
Bibliographic record
Abstract
Dredged materials from maintenance and deepening of inlets on coastal barriers are typically transported for disposal in deep water or on land. An alternative is to treat dredged materials as a resource, placing them on the ebb-tidal delta or subtidal shoals at depths where they are retained within the long-shore transport system and can nourish eroding down-drift beaches. Deposition of sediments onto subtidal shoals may, however, bury and selectively kill populations of benthic invertebrates, or indirectly alter assemblages by modifying sediment characteristics. Core sampling of the eastern (control) and western (disturbed) sides of Beaufort Inlet, North Carolina, twice before and once 8 months after a large (660,000 m3) disposal revealed significant coarsening of sediments and associated changes to assemblages of benthic macroinvertebrates in response to the perturbation. Impacts to sediments and macroinverte-brates were closely correlated and, although greatest where sediment was directly deposited, extended over a wider (at least 1 km to the east) area than the deposition. Of the taxa comprising faunal assemblages, spionid polychaetes were most affected by the disposal, declining in abundance. These results, which tie the deposition and dispersal of coarse sediments on an ebb-tidal delta to changes in benthos, imply a biological cost that may be less than that of direct nourishment of biologically productive intertidal beaches.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".