The Effect of a Weak Asthenospheric Layer on Surface Kinematics, Subduction Dynamics and Slab Morphology in the Lower Mantle
Bibliographic record
Abstract
Abstract On Earth, the velocity at which subducting plates are consumed at their trenches (termed “subduction rate” herein) is typically 3 times higher than trench migration velocities. The subduction rate is also 5 times higher than estimated lower mantle slab sinking rates. Using simple kinematic analyses, we show that if this present‐day “kinematic state” operated into the past, the subducting lithosphere should have accumulated and folded beneath near‐stationary trenches. These predictions are consistent with seismic tomography, which images localized and widened lower‐mantle slab piles. They are, however, at odds with most dynamic‐subduction models, which predict rapid trench retreat and inclined slabs in the mantle transition zone. We test the hypothesis that a weak asthenospheric layer (WAL), between the lithosphere‐asthenosphere boundary and 220 km depth, compatible with geophysical constraints, can remedy the discrepancies between numerical models and observations. The WAL lubricates the base of the lithosphere, increases the subduction rate while reducing trench retreat. As a consequence, simulations featuring a WAL predict slab accumulation at the mantle transition zone, and thicker, folded slabs in the lower mantle. A WAL viscosity only 2–5 times lower than that of the adjacent mantle is sufficient to shift subduction regimes toward a mode of vertical slab sinking and folding beneath near‐stationary trenches, across a wide range of model parameters, producing surface and slab velocities close to those observed at the present‐day. These findings provide support for the existence of a weak asthenosphere beneath Earth's lithosphere, complementing independent evidence from various geophysical data.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".