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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".