Climate, tectonics or morphology: what signals can we see in drainage basin sediment yields?
Bibliographic record
Abstract
Abstract. Sediment yields from river basins are typically considered to be controlled by tectonic and climatic drivers. However, climate and tectonics can operate simultaneously and the impact of autogenic processes scrambling or shredding these inputs can make it hard to unpick the role of these drivers from the sedimentary record. Thus an understanding of the relative dominance of climate, tectonics or other processes in the output of sediment from a basin is vital. Here, we use a numerical landscape evolution model (CAESAR) to specifically examine the relative impact of climate change, tectonic uplift (instantaneous and gradual) and basin morphology on sediment yield. Unexpectedly, this shows how the sediment signal from significant rates of uplift (10 m instant or 25 mm a−1) may be lost due to internal storage effects within even a small basin. However, the signal from modest increases in rainfall magnitude (10–20%) can be seen in increases in sediment yield. In addition, in larger basins, tectonic inputs can be significantly diluted by regular delivery from non-uplifted parts of the basin.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".