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EN
Several studies on the assessment of soil organic carbon (SOC) stocks have been carried out at the global level. However, reliable information on SOC stocks is not readily available at the regional level. In addition, very few studies have assessed the factors responsible for the variation of SOC stocks, in particular the effect of plant communities. For this purpose, the main objective was to analyze the effects of three plant communities and ecological parameters on the SOC stock in the Mamora forest. Specifically, the authors looked to examine the relationships between SOC stock and plant communities and to define the main parameters that directly influence SOC stock. Ten soil profiles with three replications were sampled at each plant community, from which SOC stock was determined. To assess the effect of plant communities on SOC stocks, phytosociological surveys were carried out according to the phytosociological stigma method developed by Braun-Blanquet. The results show that the SOC stocks in cork oak soils are characterized by high variability, with values ranging from 55 t•ha-1 to 95 t•ha-1. Indeed, the findings of this study showed that the SOC stocks fluctuated significantly with plant communities. In addition, SOC stocks were also affected by the interactions between plant communities, the amount of litter and the density of the cork oak stand. These outcomes of this study highlight the critical need to incorporate community-specific carbon values into future carbon sequestration modeling.
EN
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, the authors 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, the 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. The obtained 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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