No abstract

Le complexe récifal de l'anticlinal de Cap-Guir d'âge kimméridgien, repose sur des calcaires bioclastiques qui scellent le récif oxfor-dien. Il englobe des dépôts récifaux, d'avant récif et d'arrière récif, de répartition inégale en allant d'Est en Ouest du secteur étudié. Une lentille bioconstruite, soit la mieux exposée dans ce secteur, à fait l'objet d'une étude détaillée. Elle est constituée par des coraux, des stomatoporidés et des chaetetidés associés à des encroûtements algaires et/ou microbiens. Ces organismes sont bien conservés suite à une lithifaction précoce, due à l'activité intense de microbialites au sein du bioherme. Cette bioconstruction est relayée vers l'Est par une masse de calcaire bréchique à organismes basculés ou fragmentés en bioclastes qui sont souvent attaqués par des biophages. Il s'agit de brèche d'arrière récif. On assiste aussi à la persistance de boursouflures moins bio-construites alternant avec des masses de sables bioclastiques ou des bio-accumulations, jusqu'à l'apparition plus à l'Est de calcaires massifs et très fin à rares bioclastes et ostracodes de milieu lagunaire. Le récif de Cap-Guir a joué durant le Kimméridgien inférieur le rôle d'une barrière paléogéographique, permettant la distinction de l'Ouest vers l'Est de faciès d'avant récif, d'arrière récif et d'une crête récifale.

This study focuses on the morphotectonics of the Central High Atlas in Morocco through analysis of morphotectonic indices recorded by topography, drainage networks, and longitudinal stream profiles. The methods used in this work were stream lengthgradient index (SLI), normalized steepness index, area-altitude relations (hypsometric curves), mountain front sinuosity, drainage basin shape ratio, and asymmetry factor. The aim is to identify the role of recent tectonic activity resulting in the uplift of the Atlas chain in general and the Central High Atlas in particular. The analysis of the main rivers in the study area using linear geomorphic proxies revealed the presence of several knickpoints (about 28) most likely related to recent tectonic activity; further, the spatial distribution of SLI values reveals the presence of many anomalous zones, which are distinguished by elevated values that are perfectly aligned with major faults. The calculation of areal geomorphic proxies supports and confirms these findings. The results obtained show that the study area has been influenced by recent tectonics, and that some areas of the Central High Atlas have experienced a recent uplift due probably to a reactivation of several thrust and oblique-slip faults, then the high topography can be explained by a compressive component of the transpressional geodynamic regime suggested in the Plio-Quaternary period.

Assessing and mapping the vulnerability of gully erosion in mountainous and semi-arid areas is a crucial field of research due to the significant environmental degradation observed in such regions. In order to tackle this problem, the present study aims to evaluate the effectiveness of three commonly used machine learning models: Random Forest, Support Vector Machine, and Logistic Regression. Several geographic and environmental factors including topographic, geomorphological, environmental, and hydrologic factors that can contribute to gully erosion were considered as predictor variables of gully erosion susceptibility. Based on an existing differential GPS survey inventory of gully erosion, a total of 191 eroded gullies were spatially randomly split in a 70:30 ratio for use in model calibration and validation, respectively. The models’ performance was assessed by calculating the area under the ROC curve (AUC). The findings indicate that the RF model exhibited the highest performance (AUC = 89%), followed by the SVM (AUC = 87%) and LR (AUC = 87%) models. Furthermore, the results highlight those factors such as NDVI, lithology, drainage, and density were the most influential, as determined by the RF, SVM, and LR methods. This study provides a valuable tool for enhancing the mapping of soil erosion and identifying the most important influencing factors that primarily cause soil deterioration in mountainous and semi-arid regions.