Origins of The Santa Maria And Vandenberg Coastal Dune Sheets (~100-0 ka) Under Changing Sea Levels, Shoreline Orientations and Wave Directions: Long-Term Records of Coastal Sand Supply in South-Central California, USA
Bibliographic record
Abstract
Two large coastal dune sheets, including the Santa Maria dune sheet and Vandenberg dune sheet, have been analyzed for late-Quaternary distributions, ages and volumes of dune sand deposition. Six new thermoluminescence (TL) ages establish the age range of dune sand deposition from >106±21 ka to <4.1 ka in the study area. Seven late-Pleistocene TL and 14C dated mid-depth samples (≤30 m depth subsurface), yield a mean of 33 ka for the late-Pleistocene dune deposits. Both TL and 14C dated Holocene dune deposits establish a transition from weathered middle-Holocene dune deposits to unweathered latest-Holocene dune deposits after 4 ka. Marine sand supply to the large dune sheets occurred by 1) cross-shelf eolian transport during late-Pleistocene marine low-stands (70–13 ka), 2) shoreward wave transport during slowing of the Holocene marine transgression (9–5 ka), and 3) longshore littoral transport during the latest-Holocene marine high-sand (3.5–0 ka). Measured and dated dune deposit sections (n=66, ranging from 2 to 60 m depth) demonstrate substantial differences in preserved sand volumes between the two adjacent dune sheets, Santa Maria (~ 2,300x106 m3) and Vandenberg (~430x106 m3). Asymmetric distributions of dune deposit volumes between and within the dune sheets show that long-term sand supply was locally controlled by paleo-shoreline orientations relative to corresponding deep-water wave propagation directions (260–290° TN) from the North Pacific Low Pressure Area. Recently declining sand supplies and/or -trapping efficiencies in the dune sheet littoral subcells led to ongoing shoreline retreat (≥ 200 m) and under-cutting of late- Holocene eolian sand ramps at the south ends of the Santa Maria and Vandenberg dune sheets. The termination of transgressive cross-shelf sand supply and locally variable longshore retention of littoral sand confirm previously reported framework models of regional coastal sand supply. Such models help to identify shorelines that are most susceptible to future beach erosion from predicted sea level rise following ongoing global warming.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".