Storm-triggered landslides in the Peruvian Andes and implications for topography, carbon cycles, and biodiversity
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. In this study, we assess the geomorphic role of a rare, large-magnitude landslide-triggering event and consider its effect on mountain forest ecosystems and the erosion of organic carbon in an Andean river catchment. Proximal triggers such as large rain storms are known to cause large numbers of landslides, but the relative effects of such low-frequency, high-magnitude events are not well known in the context of more regular, smaller events. We develop a 25-year duration, annual-resolution landslide inventory by mapping landslide occurrence in the Kosñipata Valley, Peru, from 1988 to 2012 using Landsat, QuickBird, and WorldView satellite images. Catchment-wide landslide rates were high, averaging 0.076 % yr−1 by area. As a result, landslides on average completely turn over hillslopes every ∼ 1320 years, although our data suggest that landslide occurrence varies spatially and temporally, such that turnover times are likely to be non-uniform. In total, landslides stripped 26 ± 4 tC km−2 yr−1 of organic carbon from soil (80 %) and vegetation (20 %) during the study period. A single rain storm in March 2010 accounted for 27 % of all landslide area observed during the 25-year study and accounted for 26 % of the landslide-associated organic carbon flux. An approximately linear magnitude–frequency relationship for annual landslide areas suggests that large storms contribute an equivalent landslide failure area to the sum of lower-frequency landslide events occurring over the same period. However, the spatial distribution of landslides associated with the 2010 storm is distinct. On the basis of precipitation statistics and landscape morphology, we hypothesise that focusing of storm-triggered landslide erosion at lower elevations in the Kosñipata catchment may be characteristic of longer-term patterns. These patterns may have implications for the source and composition of sediments and organic material supplied to river systems of the Amazon Basin, and, through focusing of regular ecological disturbance, for the species composition of forested ecosystems in the region.
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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 it