Cοntributiοn à l'étude des relatiοns entre cοrtèges de végétatiοn et prοcessus hydrοgravitaires : applicatiοns aux falaises des Vaches Νοires, (Νοrmandie,France)
Bibliographic record
Abstract
In Normandy, the Vaches Noires cliffs are a unique coastal area, characterised by badlands morphology and high hydrogravitational instability (landslides, mudflows, gully erosion, etc.). In this context, vegetation plays an ambivalent role, recognised in scientific literature, sometimes constrained by the instability of the slopes, sometimes actively contributing to their stabilisation. This thesis aims to understand how vegetation communities influence the eco-morphodynamic trajectories of cliffs, using a systemic approach with orthophotographs and regular field monitoring accompanied by a variety of instruments. A typology of vegetation communities was established based on botanical surveys and eco-geomorphological profiles. This typology was compared with a diachronic analysis of vegetation cover (1955–2023) and monitoring of vegetation community dynamics (2021–2025), in particular using high-resolution mapping based on drone remote sensing (2 to 5 cm/pixel). These data made it possible to characterise recolonisation trajectories, taking into account vegetation communities and hydrogravitational processes.In situ monitoring (pits, humidity and temperature sensors, camera traps, etc.) has highlighted the differentiated action of plant communities on surface formations and hydrology: passive effects (protection against runoff, sediment trapping) and active effects (root reinforcement, infiltration, mechanical blocking). The results show that plant colonisation does not follow a linear succession, but rather an unstable continuum alternating between reconquest, stagnation and reinitialisation linked to the diversity of hydrogravitational processes. This work highlights the role of vegetation communities as indicators and agents of slope dynamics. It helps to clarify the framework of biorhexistasy as applied to marl coasts and opens up prospects for monitoring unstable cliffs by integrating plant resilience into the analysis of eco-morphodynamic trajectories.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".