Is more better? Sediment production, weathering, and erosion inferred from multiple geochemical proxies and comprehensive field measurements in mountain catchments
Bibliographic record
Abstract
Weathering in mountain landscapes produces sediment with size distributions that evolve as particles are transported down hillslopes, delivered to channels, and carried downstream. The evolving sizes influence rates of river incision into bedrock, which in turn set sediment residence times on hillslopes, with implications for the sizes of sediment produced by weathering. Hence, variations in sediment size are central to feedbacks that link climate, tectonics, and erosion in mountain landscape evolution. However, few studies have quantified how sediment sizes evolve during transport across catchments, focusing instead on rates of erosion and weathering. Yet recent modeling suggests that spatial variations in sediment size can lead to bias in erosion rates from conventional techniques, further highlighting the importance of understanding how sediment size evolves across landscapes. Here we show how a more complete and unbiased picture of sediment production, weathering, and erosion can be obtained by combining field measurements of sediment size together with conventional geochemical proxies in an integrative model that accounts for spatial variations in erosion, weathering, and sediment mixing, while incorporating effects of both abrasion and fragmentation during transport in channels. Our measurements, from a catchment draining the steep eastern Sierra Nevada, California, include particle size distributions of sediment from widely distributed locations. These measurements represent sediment that is produced on hillslopes and delivered to channels, reflecting the combined effects of the initial sediment size distribution (set by bedrock fracture spacing) and subsequent weathering on slopes. Our measurements also include cosmogenic nuclide concentrations and apatite-helium ages in 11 size classes, from sand to boulders, sampled from the creek. The cosmogenic nuclides reveal residence times of sediment in the catchment, while the apatite-helium ages reveal source elevations of sediment eroded into the stream. When combined together, the cosmogenic nuclide and apatite-helium data can be used to quantify altitudinal variations in erosion rates and sediment size distributions. Our measurements from catchment slopes indicate that hillslope sediment size decreases with decreasing elevation, reflecting altitudinal trends in physical, chemical, and biological weathering and producing downvalley fining in hillslope sediment supply. Cosmogenic nuclides in stream sediment decrease by two-fold with increasing particle size, indicating that erosion rates calculated using traditional techniques are sensitive to the size sampled from the creek. Apatite-helium ages suggest that the smallest and largest sizes sediment sizes in the stream originate from lower elevations, where slopes are gentler and soil-mantled. In contrast, coarse gravel and cobbles appear to originate from higher in the catchment, where slopes are steeper and bare bedrock is exposed. The differences in altitudinal trends in sediment size implied by the apatite-helium data and the direct observations from catchment slopes can be reconciled by accounting for particle fragmentation and abrasion during transport from hillslope sources to the sampling point in the creek. Our analysis indicates that each of the unique sources of information in our study are necessary for a complete and unbiased understanding of spatial variations in the production of sediment across the full range of sizes and their evolution during transport across the catchment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".