Fault Throw and Regional Uplift Histories From Drainage Analysis: Evolution of Southern Italy
Bibliographic record
Abstract
Abstract Landscapes can record elevation changes caused by multiple tectonic processes. Here, we show how coeval histories of spatially coincident normal faulting and regional uplift can be deconvolved from river networks. We focus on Calabria, a tectonically active region incised by rivers containing knickpoints and knickzones. Marine fauna indicate that Calabria has been uplifted by >1 km since ∼0.8–1.2 Ma, which we used to calibrate parameters in a stream power erosional model. To deconvolve the local and regional uplift contributions to topography, we performed a spatiotemporal inversion of 994 fluvial longitudinal profiles. Uplift rates from fluvial inversion replicate the spatial trend of rates derived from dated Mid‐Late Pleistocene marine terraces, and the magnitude of predicted uplift rates matches the majority of marine terrace uplift rates. We used the predicted uplift history to analyze long‐term fault throw, and combined throw estimates with ratios of footwall uplift to hanging wall subsidence to isolate the nonfault related contribution to uplift. Increases in fault throw rate—which may suggest fault linkage and growth—have been identified on two major faults from fluvial inverse modeling, and total fault throw is consistent with independent estimates. The temporal evolution of nonfault related regional uplift is similar at three locations. Our results may be consistent with toroidal mantle flow generating uplift, perhaps if faulting reduces the strength of the overriding plate. In conclusion, fluvial inverse modeling can be an effective technique to quantify fault array evolution and can deconvolve different sources of uplift that are superimposed in space and time.
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How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".