Topography and flooding of Coastal Ecosystems on the Yukon-Kuskokwim Delta, Alaska: Implications for Sea-Level Rise
Bibliographic record
Abstract
We measured surface elevations, stage of annual peak flooding, and sedimentation along 10 toposequences across coastal ecosystems on the Yukon-Kuskokwim (Y-K) Delta in western Alaska during 1994-1998 to assess some of the physical processes affecting ecosystem distribution. An ecotype was assigned to each of 566 points, and differences in elevations among 24 ecotypes were analyzed within individual toposequences and across the 40 X 40-km study area. Elevations of vegetated ecotypes along the longest toposequence rose only ~ 1 m over a distance of 7.5 km, and mean elevations of most ecotypes across the study area were within 0.5 m of mean higher-high water (1.47 m), During 1994 to 1998, monitoring of annual peak stage using crest gauges revealed flooding from the highest fall storm surge reached 2.58 m (1.11 m above mean higher-high tide). In each year, only the highest surface was unaffected by flooding. Mean annual sedimentation rates for the various ecotypes were 8.0 mm/y on tidal flats, 1.4 to 3.8 mm/y on the active floodplain, 0.1-0.2 mm/y on the inactive floodplain, and 0 mm/y on the abandoned floodplain. If sea levels in the Bering Sea rise ~0.5 m by 2100, as predicted by some on a global basis, large portions of the coastal margin of the delta could be regularly inundated by water during high tides, and even the highest ecotypes could be affected by storm surges. Predicting the extent of future inundation is difficult, however, because of the changes in the ground surface elevation through sedimentation, organic matter accumulation, and permafrost development.
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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) | 0.000 | 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 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".