Contribution to the Modeling of the Organic Matter of Moroccan Forest Soils within the Context of Global Change: Case study of the Central Plateau
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Equipe Sciences Géomatiques (SGEO), Laboratoire du Génie des Systèmes (LAGES), Ecole Hassania des Travaux Publics (EHTP), Casablanca, Morocco
Laboratoire de Biotechnologie et Physiologie Végétales, Centre de Biotechnologie Végétale et Microbienne, Biodiversité et Environnement, Faculté des Sciences, Université Mohammed V de Rabat, Rabat 10000, Morocco
Laboratoire des Productions Végétale, Animales et Agro-industrie, Equipe de Botanique, Biotechnologie et Protection des Plantes, Faculté des Sciences, Université Ibn Tofail, Kénitra, Morocco
Unit of Biodiversity and Valorization of Plant Resources, Faculty of Science and Technology, University of Nouakchott, Nouakchott, Mauritania
Independent researcher, Rabat, Morocco
Laboratoire D'aménagement et de Sylviculture, Département de Biologie, Chimie et Géographie, Université de Québec à Rimouski, Rimouski, Canada
Soltane Moulay Slimane University, Mghila Beni Mellal, Morocco
Interdisciplinary Laboratory LIRBEM, Department of Life and Earth Sciences, Ecole Normale Supérieure, Cadi Ayyad University, Marrakech, Morocco
Corresponding author
Youssef Dallahi   

Equipe Sciences Géomatiques (SGEO), Laboratoire du Génie des Systèmes (LAGES), Ecole Hassania des Travaux Publics (EHTP), Casablanca, Morocco
Ecol. Eng. Environ. Technol. 2023; 8:261-271
Organic matter is a major component of soil. It is of considerable ecological importance given its role in determining soil health, influencing ecosystem productivity and climate. For this reason, it is essential to carry out studies to evaluate its dynamics in natural ecosystems. In this study, we aimed to explore the dynamics of soil organic matter (SOM) in forest ecosystems of the Central Plateau in Morocco, as well as to investigate the potential of spectral vegetation indices in modeling SOM. To this end, soil samples for analysis were collected from 30 sites across three vegetation types, including cork oak, Barbary thuja and scrub (matorral). In addition, the normalized difference vegetation index (NDVI) was extracted from Landsat 8 images to be used to model SOM using linear regression. Our results showed a weak although statistically significant (α < 0.05) correlation between NDVI and SOM at 0.45. In addition, only the scrub type showed a statistically significant (α < 0.05) relationship between its corresponding SOM and NDVI, and was therefore retained for modeling. Vegetation type had a statistically strong influence (α < 0.01) on SOM, with cork oak and garrigue ecosystems having the highest and lowest SOM contents with 5.61% and 2.36%, respectively. In addition, the highest SOM contents were observed under slightly acidic pH soils on mild, warm slopes at high altitude sites, while the lowest were found in lowland areas with predominantly weakly evolved soil.
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