Assessment of forest dieback on the Moroccan Central Plateau using spectral vegetation indices

Abstract

Cork oak forests in Morocco are rich in resources and services thanks to their great biological diversity, playing an important ecological and socioeconomic role. Considerable degradation of the forests has been accentuated in recent years by significant human pressure and effects of climate change; hence, the health of the stands needs to be monitored. In this study, the Google Engine Earth platform was leveraged to extract the normalized difference vegetation index (NDVI) and soil-adjusted vegetation index, from Landsat 8 OLI/TIRS satellite images between 2015 and 2017 to assess the health of the Sibara Forest in Morocco. Our results highlight the importance of interannual variations in NDVI in forest monitoring; the variations had a significantly high relationship (p < 0.001) with dieback severity. NDVI was positively and negatively correlated with mean annual precipitation and mean annual temperature with respective coefficients of 0.49 and − 0.67, highlighting its ability to predict phenotypic changes in forest species. Monthly interannual variation in NDVI between 2016 and 2017 seemed to confirm field observations of cork oak dieback in 2018, with the largest decreases in NDVI (up to − 38%) in December in the most-affected plots. Analysis of the influence of ecological factors on dieback highlighted the role of substrate as a driver of dieback, with the most severely affected plots characterized by granite-granodiorite substrates.

Impact of climate and demographic changes on the vegetation of the M’goun Geopark UNESCO of Morocco (1984-2021)

“…This variability underscores the complex nature of the Atlas climate and its influence on the dynamics of this vegetation class in particular and generally the vegetation cover. Vegetation degradation in the region can be attributed to several factors, including natural tree mortality caused by climate warming, irregular precipitation patterns, and aging plants (Dallahi et al, 2023). Additionally, deforestation for wood and charcoal, soil erosion and depletion, pollution, and the widespread use of wood for building new houses due to a lack of infrastructure for accessing modern construction materials.…”

Susceptibility Mapping of Unhealthy Trees in Jiuzhaigou Valley Biosphere Reserve

“…For instance, Jump et al [16] discovered that tree dieback can lead to a decrease in water content and Leaf Area Index (LAI). Dallahi et al [17] assessed forest dieback using the Normalized Difference Vegetation Index (NDVI); Eitel et al [18] found that the Normalized Difference Red-edge Index (NDRE) can be used to monitor early red-edge increase; Gitelson et al [19] found a strong correlation between the Green Normalized Difference Vegetation Index (GNDVI) and chlorophyll a, and Wojtowicz et al [20] used GNDVI to identify the vegetation infected with leaf rust; Gupta and Pandey [21] analyzed and mapped forest health using Anthocyanin Reflectance Index 1 (ARI1). Typically, researchers fit vegetation indices to field data to reflect forest health conditions.…”

“…Although machine learning algorithms can be effective for monitoring forest species [27][28][29], there may be some limitations in terms of vegetation health. Vegetation indices for forest health mapping actually correspond to the proportion of unhealthy trees within sample plots using medium-resolution (2 m-30 m) remote sensing images [17,[30][31][32][33][34]. In areas where the probability of unhealthy tree occurrence is low, such sample data is difficult to obtain, which is because a single pixel typically corresponds to approximately 100 square meters in medium-resolution image (i.e., Sentinel-2 image).…”

Contribution to the Modeling of the Organic Matter of Moroccan Forest Soils within the Context of Global Change: Case study of the Central Plateau

“…Thus, understanding the distribution of SOC on the soil surface and its influencing factors further improves the understanding of the subsurface carbon cycle mechanism and enhances the understanding of the soil carbon sink function. In Moroccan ecosystems, despite great floristic and pedological diversity, forest resources are often severely degraded, resulting in organic and mineral impoverishment of soils (Roose, 2002;Badraoui, 2016;Dallahi et al, 2023). Thus, the acquisition of data on the dynamics of SOM will make it possible to understand the functioning of ecosystems according to their management mode and thus to avoid the progression of forest degradation, and even promote their restoration.…”