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Evaluate the Effect of Topographic Factors and Lithology on Forest Cover Distribution: a Case Study of the Moroccan High Atlas

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Abstract

Understanding the relationship between the spatial distribution of forest vegetation and influencing factors provides valuable information to decision-makers in land planning, for the sustainable development of forests and efficient monitoring of environmental and ecological issues. This paper aims to understand the effect of topographic factors and lithology on forest cover distribution around Bin El Ouidane dam in the High Atlas Mountains of Morocco, using remote sensing, Geographical Information Systems (GIS), field observation, and statistical analysis. The forest vegetation was quantified by calculating the Normalized Vegetation Difference Index (NDVI) from Operational Land Imager (OLI) images. The NDVI was classified according to the density of forest vegetation into four levels: bare soil, low density of forest cover, moderate density of forest cover, and high density of forest cover. The correlation analysis between NDVI, interpreted as forest densities and topographic parameters (elevation, slope, and aspect), derived from the Digital Elevation Model (DEM), showed that elevation has the most significant positive correlation with forest density, with r = 0.563 and a p-value less than 0.05. Additionally, moderate and high densities of forest vegetation are optimal in the terrain aspect of the South-East and North-West, respectively. However, the NDVI variation cannot be interpreted only by altitude and terrain aspect. The Spectral Angle Mapper (SAM) classification has been used to map and to separate the forest vegetation types. The statistical results of the analysis of variance (ANOVA) showed that the altitude is the most important topographic factor affecting the distribution of forest species. The analysis of frequency histograms revealed that Holm oaks are increasing at high altitudes, and are more abundant in the North-West, while the Thuya species prefer moderate altitudes and are more abundant in the South-East-facing aspects. In our study area, the Holm oak develops on limestone formations. On the contrary, Thuya does not thrive in lithological conditions, and is found with a decreasing level of predominance on limestones, marls-limestones, and sandstones, respectively. The conclusion of the study shows that a combination of topographic factors and lithological conditions affects the spatial distribution of forest vegetation. The adaptation of the forest species to specific topography and lithological conditions should be considered for forest management. It can be helpful in selecting potential sites for reforestation of these species, for conservation of the natural resources, including water and soil.

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Acknowledgements

We thank U.S. Geological Survey (USGS) for providing the Landsat OLI and ASTER images. As well, we gratefully acknowledge the anonymous referees for accepting to review the manuscript.

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Authors and Affiliations

  1. Laboratory of Applied Geology, Geomatic and Environment, Department of Geology, Faculty of Sciences Ben M’sik, Hassan II University of Casablanca, Sidi Othmane, B.P. 7955, Casablanca, Morocco

    Soufiane Maimouni, Mostafa Oukassou & Saida El Moutaki

  2. Private University of Marrakesh, Km 13 Amizmiz road 42312, Marrakesh, Morocco

    Lamia Daghor

  3. Centre Eau Terre Environnement, INRS, 490 la Couronne, Quebec, G1K 9A9, Canada

    Rachid Lhissou

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  1. Soufiane Maimouni
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  2. Lamia Daghor
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  4. Saida El Moutaki
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  5. Rachid Lhissou
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Contributions

All the authors participated in the elaboration of this article. Soufiane Maimouni developed the used methodology. The manuscript was written by Soufiane Maimouni, Lamia Daghor, and Rachid Lhissou. The obtained results were discussed in contribution with Mostafa Oukassou and Saida El Moutaki.

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Correspondence to Soufiane Maimouni.

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Maimouni, S., Daghor, L., Oukassou, M. et al. Evaluate the Effect of Topographic Factors and Lithology on Forest Cover Distribution: a Case Study of the Moroccan High Atlas. Environ Model Assess 26, 787–801 (2021). https://doi.org/10.1007/s10666-021-09785-3

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