Predicted Responses of Beaches, Bays, and Inner-Shelf Sand Supplies to Potential Sea Level Rise (0.5-1.0 m) in Three Small Littoral Subcells in the High-Wave-Energy Northern Oregon Coast, USA
Bibliographic record
Abstract
Three small subcells (Nehalem, Tillamook, and Netarts) totaling ~55 km shoreline length in the high-wave energy northern Oregon coast are evaluated for potential beach sand loss from sea level rise (SLR) of 0.5–1.0 m during the next century. The predicted erosion is based on beach sand displacement from the narrow beaches (average ~120 m width) to increased submarine accommodation spaces in the innermost-shelf (to 30 m water depth) and in the subcell estuaries (Tillamook Bay, Netarts Bay, and Nehalem Bay), following predicted near-future SLR. Beach sand sources from local rivers, paleo-shelf deposits, and/or sea cliff retreat are discriminated by distinctive heavy-mineral tracers. Modern beach sands in the study area are derived from river sand (~75 %) and paleo-shelf sand (~25 %). The supplies of paleo-shelf sand to the beaches have largely diminished in late-Holocene time. The river-enriched beach sands have been transported offshore to the inner-shelf (0–50 m water depth) to fill increasing accommodation space in the inner-shelf during latest-Holocene conditions of relative SLR (1.0 m ka-1). To evaluate the beach sand response to future SLR, representative beach profiles (n=17) and intervening beach segment distances were compiled to yield beach sand volumes above mean lower low water (MLLW) or shallower wave-cut platforms ‘bedrock’. Across-shore cross-sectional areas, as averaged for each subcell, are as follows; Cannon Beach (304 m2), Tillamook (683 m2), and Netarts (227 m2). Littoral sand displacements to the adjacent innermost-shelf (to 30 m water depth) and the marine-dominated areas of the three estuaries are based on assumed vertical sand accretion rates of 1.0 m per century and a conservative value of 0.5 m per century. The filling of such submarine accommodation spaces will displace all active-beach sand reserves in all three subcells for either the 1.0 m or 0.5 m thickness accommodation space scenarios. Large beach sand deficits, primarily from the filling of offshore accommodation spaces, could cause further retreat of soft-shorelines, including barrier spit and beach plain/dune deposits, in the Tillamook subcell (150-280 m) and in the southern half of the Netarts subcell (370-770 m). The accommodation space approach used to predict beach sand volume loss from future SLR should have broad applicability in complex littoral systems worldwide.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".