Legacy Vegetation and Drainage Features Influence Sediment Dynamics and Tidal Wetland Recovery After Managed Dyke Realignment
Bibliographic record
Abstract
Managed dyke realignment (MR) is a nature-based technique that shifts dyke systems farther inland, allowing for restoration of tidal flow and tidal wetland vegetation. While restoration of tidal flow can result in rapid sediment accretion and vegetation recovery, dykelands on the east coast of Canada are often agricultural, with legacy vegetation and ditches present upon initiation of MR. We combined measurements of sediment flux and accretion, digital surface and drainage network models, and vegetation mapping to understand the effects of legacy features on geomorphological evolution and restoration trajectory at a Bay of Fundy MR site. Removal of legacy vegetation and channels in a borrow pit allowed comparison with unaltered areas. Magnitudes of volumetric change from erosion at the channel mouth were similar to gains on the borrow pit, suggesting that channel mouth erosion could represent a significant sediment subsidy for restoring the marsh platform. Pre-existing pasture vegetation is likely to have slowed wetland vegetation establishment, suggesting that mowing prior to MR may speed recovery. Repeated high resolution vertically precise aerial surveys allowed understanding of the effects of elevation and proximity to the drainage network on spatial and temporal variability in marsh surface elevation increase and vegetation recovery.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".