Stream Meandering in Coastal Wetlands: Patterns, Processes, and Ecomorphodynamics Implications
Bibliographic record
Abstract
The sinuous channels that wind through tidal coastal wetlands resemble meandering rivers. However, features indicative of active meandering over time, such as oxbow lakes and meander cutoffs, are challenging to find in tidal realms. Specifically, while alluvial plains shaped by meandering rivers are filled with scars of meander cutoffs, tidal coastal settings have been perceived by geomorphologists for much of the past century as lacking morphological evidence of cutoff events, even though both environments exhibit similar meander-planform dynamics and width-adjusted migration rates. This led to the broad interpretation that tidal and fluvial meanders differ morphodynamically.We re-examined this conclusion by identifying, measuring, and compiling examples of meander cutoffs from various tidal coastal wetlands and fluvial floodplains worldwide. We suggest that cutoffs in tidal meanders are far more widespread than previously thought, and the shapes and geometric properties of tidal and river cutoffs are indeed remarkably similar. This indicates that while tidal and fluvial environments differ in many ways, they nevertheless share the same physical mechanism affecting meander morphodynamical evolution.The perceived scarcity of tidal cutoffs is likely a result of pronounced channel density and hydrological connectivity in coastal wetlands, coupled with the reduced size of most tidal channels and dense vegetation cover. Moreover, despite allegedly similar forming mechanisms, morphodynamic differences arise after meanders have cut off. We observe that tidal meanders remain preferentially connected to the channel from which they originated, preventing the formation of crescent-shaped oxbow lakes and thus making tidal cutoffs more difficult to detect.While these factors do not erase tidal meander cutoffs, they collectively inhibit oxbow-lake formation and render tidal cutoffs ephemeral, hardly detectable geomorphic features. We thus argue that similar morphodynamic processes drive cutoff formation in tidal and fluvial landscapes, with differences arising only during post-cutoff evolution. This bears important implications for understanding the ecomorphodynamics of coastal wetlands and predicting their long-term evolution.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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 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".