Forest resources in the Ourika watershed are subject to several anthropogenic and climatic degradation factors. As for the human factor, this degradation of forest resources is explained by the bad practices exercised by the local population expressed by the cutting of live wood, carbonization, and overgrazing. In terms of the climatic factor, the decrease in the amount of rainfall and the increase in temperature contribute to the exacerbation of the degradation of these resources. In order to better understand the evolution of plant cover in a changing climate context, this study highlights an assessment of the impact of climate change on forest dynamics based on a process-based model at the forest landscape scale which makes it possible to simulate the changes according to growth, succession, disturbances (fire, wind, insects, etc), forest management, and land use change. This analysis is based on the use of the LANDIS-II model and the PnET-succession extension. Projections of the dynamics of forest communities are made using climate projections from the Japanese global circulation model adopted by Morocco (model for interdisciplinary research on climate – earth system models) and this by adopting the two climate scenarios , representative concentration pathways 4.5 and 8.5. The results obtained highlight the spatial distribution of the ecosystems studied after 100 years with a quantitative evaluation of the total average biomass of these resources as a function of climatic disturbances. In general, the estimated total biomass will decline over the coming years under the joint effect of the climate change and the aging of forest stands, while on the other hand, the distribution of potential areas for species settlement remains independent of the effect of these climate changes.

The Ourika watershed, located in the North-West of Moroccan High Atlas, has undergone several spatio-temporal changes and accelerated land use dynamics as a result of the interaction of climatic, topographic and anthropogenic factors. The objective of this study is to monitor the evolution of land use in the study area over the past 33 years. Landsat satellite imagery has been chosen for land cover mapping, providing a sufficient detail to identify land cover characteristics while providing more or less complete coverage of the area of action. Landsat 5 Thematic Mapper satellite images from 1987 and Landsat 8 Operational Land Imager from 2019 were used, with a spatial resolution of 30m. The images were treated and classified using Support Vector Machine algorithm (SVM) implemented on QGIS Geographic Information System software. The classification evaluation shows a Kappa coefficient of 85% and 84% and an overall accuracy of 95% and 94% for 1987 and 2019 respectively. Furthermore, the results showed a 10% decrease in the forest as well as a significant increase in the pasture, arboriculture, bare land and buildings with a respective percentage of 5.99%, 1.67%, 1.48% and 1.37% accordingly.

This article aims to shed light on the process of known degradation of the forest area of Benslimane province during the period 1990–2020 and to specify the most important human causes which contributed to it (quarries, extension of the built-up area, the impact of agricultural activities, grazing and collection of firewood), by using remote sensing techniques (spatial images for the years 1990–2000–2010–2020) to produce Land Cover maps. The following satellite images were used, Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 OLI, with a spatial precision of 30 m, the Semi-Automatic Classification Plugin (SCP) in QGIS was used for atmospheric correction, and the Spectral Angle Mapping algorithm for the images’ classification. The rating evaluation of the Kappa coefficient shows the following ratios for the years 1990–2000–2010–2020 respectively ; 0.89–0.90–0.90–0.93. The results showed that the forest area of Benslimane province has declined by 11.4% or about 6,027.7 ha between 1990–2020 at the rate of 200 ha/year, which has been turned into matorral land or bare land. This forest also lost 35.2% of its vegetative density and has become much sparser, while the original grazing areas surrounding it have been reduced by 50.4%. Moreover, the area of quarries increased by 1,097.4%, the percentage of built-up area increased by 328.2%, and the agricultural area expanded by 32.7%. These results can be used as preliminary data for future studies and can help policymakers focus on the real drivers of forest degradation, in order to develop interventions to ensure the sustainability of natural resources.

In Morocco, the phenomena of water erosion cause significant economic losses mainly linked to the silting up of dams, the degradation of equipment and socio-economic infrastructures, the loss of soil productivity and the insecurity of the population. The SWAT (Soil and Water Assessment Tool) model was used to estimate the quantities of sediments generated by the various erosive processes at the level of the Ourika watershed. The SWAT modeling, which is done with daily time steps, used as basic data; a Digital Elevation Model GDEM-ASTER (Global Digital Elevation-Advanced Space borne Thermal Emission and Reflection Radiometer) with 30 m of resolution, a land cover map developed from the Landsat 8 OLI (Operational Land Imager) satellite image of 2017 with 30 m of resolution and a soil map published by FAO (Harmonized World Soil Database). Also, daily meteorological data from the Tensift Water Basin Agency over a period from 1992 to 2001 were used. The results obtained showed that soil losses due to water erosion in the Ourika watershed reached an average of 9.18 t.ha-1.year-1. The model was calibrated and validated using the SWAT-CUP (SWAT Calibration and Uncertainty Procedures) software SUFI-2 (Sequential Uncertainty Fitting) and after several simulations and iterations a determination coefficient R2 of 0.76 was obtained.

Knowledge of mechanisms by which large mammals select rubbing trees (RT) is a major challenge for the effective management of forests and wildlife resources. In this study, we investigated this issue regarding the wild boar (Sus scrofa) in the Moroccan forested site of Sidi Boughaba as a case study. We used data from four sets of variables, namely topography, forest type, landscape composition, and microhabitat, measured at 58 rub and control trees, to determine the factors associated with the occurrence of RT by means of generalized linear mixed models. Our results showed that the RT occurrence increased with a high density of red juniper trees and declined with a distance to the nearest footpath. The variation partitioning analysis revealed that the pure fraction of microhabitat was the most robust in explaining this occurrence (adj. R 2 = 0.17, P < 0.001), followed by that of forest type (adj. R 2 = 0.05, P < 0.05). A scientific monitoring system must be set up to strike a balance between the availability of forest trees on the one hand and the pressure exerted by wild boars in this internationally important site on the other. It is imperative to test the geographical generality of our results in other Mediterranean forests.