Seasonality of Retreat Rate of a Wave‐Exposed Marsh Edge
Bibliographic record
Abstract
Abstract Wave‐driven erosion of marsh boundaries is a major cause of marsh loss, but little research has captured the effect of seasonal differences on marsh‐edge retreat rates to illuminate temporal patterns of when the majority of this erosion is occurring. Using five surface models captured over a study year of a marsh with a steep escarped boundary in South San Francisco Bay, we find a pronounced seasonal signal, where rapid marsh retreat in the spring and summer is driven by a strong sea breeze but little change is found in the marsh‐edge position in the fall and winter. We found accretion in the mudflat transition region close to the marsh boundary in the calmer seasons however, suggesting intertwined morphodynamics of mudflats and the eroding marsh‐scarp. We observed large spatial heterogeneity in retreat rates within seasons, but less on longer (annual and decadal) timescales. The relationship between marsh‐edge retreat rates and properties of the wave field nearby is explored and contextualized against extant relationships, but our results speak to the difficulty in addressing spatial erosion/accretion variability on short (seasonal) timescales with simple models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".