Beach ridge formation and landward migration along the isostatically rising coastlines of Hudson Bay
Bibliographic record
Abstract
While most global coasts suffer from a loss of landmass due to sea-level rise and coastal transgression, the Arctic and Sub-Arctic coastlines of Hudson Bay and James Bay witness a reverse phenomenon due to post-glacial rebound. The carbon-rich peatlands Hudson Bay Lowland, that emerged from the retraction of the Tyrell Sea, are witnessing the highest rate of vertical upliftment on the planet. The continual reshaping of the coastline by multiple physical forcings is readily visible by the contiguous and recurrent pattern of raised beach ridges imprinted on the rising land far from the present-day coastline. These beach ridges, formed through the interplay of coastal sea ice dynamics and then preserved above sea-level by uplift, hold back terrestrial runoff and are thus critical to the extensive wetland-saltmarsh ecosystems that provide important habitats for waterfowl and wildlife. This study examines the intricate process behind the formation and modification of these geomorphological units using remote sensing techniques. The study includes the use of various remote sensing products to determine ice duration (Canadian Ice Service- Ice Charts), change detection of ridge dimensions and vectors (Landsat Images), elevation (SRTM and ICESat-2), rate of vertical upliftment (glacial isostasy models) and ice motion in the nearshore zone (GOES). Remote sensing observations reveal that the beach ridges originate offshore on mudflats due to ice scouring and gradually, pushed by sea ice, move shoreward, and often merge and build up existing ridges but sometimes initiating a new beach ridge sequence. The current study documents the impact of changing ice regime on the landward movement of beach ridges on the tidal flats. We find that the seaward point of origin on the tidal flats, and the rate at which the ridges expand and finally merge with the coastline vary greatly across the coastline. The slope of the coast and the dynamics of the sea ice in the nearshore zone are key factors leading to this variability.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".