Physical aspects: geological, oceanic and climatic conditions
Bibliographic record
Abstract
Key points Coastal wetlands exist on the edge of all continents except Antarctica; saltwater wetlands are covered by seawater daily or periodically; tidal range and period (once or twice/day) control the amount of submergence and oxygen supply to marsh biota; tidal vegetation includes halophytic salt marshes, mangroves, seagrass beds and brackish water reed-swamps; salt marshes dominate cooler regions (>30° latitude) and mangroves occupy equatorial regions; local variations follow salt gradients measured as parts per mille or dimensionless psu; coastal wetlands develop in wave-sheltered sites: estuaries, deltas, glaciated fiords, barrier lagoons and tectonic down-faults; sediment supply must compensate for erosion by storm tides (cyclones, hurricanes, typhoons); space is also needed for growth on emerging or submerging coasts; global-warming impacts and human population growth are increasing risks of flooding and erosion. What are coastal wetlands (saltwater wetlands)? The Ramsar Convention defines wetlands as areas of marsh, fen or peatland with water which is static or flowing, fresh, brackish or salt, including areas of marine water not deeper than 6 m. Coastal wetlands, however, exist only at the interface of the land and sea, occurring on shorelines marked by some degree of tidal inundation, i.e. the tidal marshes and mangrove swamps, as classified in Mitsch and Gosselink (2007), who provide a dictionary of the many terms used to classify wetlands. All saltwater wetlands are characterized by the presence of brackish or saline water derived from the mixing of marine and fresh waters – including salt marshes, mangroves, seagrass beds and brackish water reed-swamps. Of this suite of intertidal habitats, the best known is the salt marsh, which is the most accessible saltwater wetland and the focus of many classical ecological studies which began over 100 years ago, starting in 1903 in North America (Ganong, 1903) and 1917 in Wales (Doody, 2008).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.087 | 0.054 |
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".