Landscape controls on the delivery of colluvial sediment to streams
Bibliographic record
Abstract
Many small mountainous watersheds are characterized by inefficient transfer of material within them, or disconnectivity. Understanding the relationship between landscape configuration and disconnectivity improves our ability to assess how sediment transfer processes, such as mass movements, and changes in their occurrence regime will travel through the landscape and alter its form and function. Published methods for quantitative assessment of disconnectivity measure either structural (the effect of landscape organization) or functional (direct measurement of material fluxes) indicators. Methods assessing the former are far more prevalent and work combining the two is rare. Additionally, metrics are infrequently developed based on the inefficiency of material transfer. We present a novel metric, the Disconnectedness Ratio, for quantitatively characterizing the influence of landforms on the sediment cascade which can be used to assess both structural and functional disconnectivity. We apply this methodology in a small, formerly glaciated watershed in British Columbia, Canada by utilizing an 84-year mass movement inventory to represent material fluxes. Our results highlight the importance of process-form relationships in disconnectivity dynamics. We find that most mass movements are intercepted, primarily by colluvial landforms, without reaching the valley bottom. The greater the contribution of colluvial processes to a landform's formation, the more effectively it buffers mass movements from the stream network. Additionally, we find that metrics for functional disconnectivity often disagree with those for structural disconnectivity and point to the importance of timescale in determining the relationship between the two. Finally, we present a conceptual framework for slope base systems to synthesize findings on the role of disconnectivity in process-form relationships. There is a need for future work to apply the Disconnectedness Ratio in more study sites at a variety of spatial and temporal scales to determine its utility and constrain its variance in a variety of watershed structures.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".