The dwarf eelgrass Zostera noltei Hornemann (Z. noltei) is the most dominant seagrass in semi-enclosed coastal systems of the Atlantic coast of Morocco. The species is experiencing a worldwide decline and monitoring the extent of its meadows would be a useful approach to estimate the impacts of natural and anthropogenic stressors. Here, we aimed to map the Z. noltei meadows in the Merja Zerga coastal lagoon (Atlantic coast of Morocco) using remote sensing. We used a random forest algorithm combined with field data to classify a SPOT 7 satellite image. Despite the difficulties related to the non-synchronization of the satellite images with the high tide coefficient, our results revealed, with an accuracy of 95%, that dwarf eelgrass beds can be discriminated successfully from other habitats in the lagoon. The estimated area was 160.76 ha when considering mixed beds (Z. noltei-associated macroalgae). The use of SPOT 7 satellite images seems to be satisfactory for long-term monitoring of Z. noltei meadows in the Merja Zerga lagoon and for biomass estimation using an NDVI–biomass quantitative relationship. Nevertheless, using this method of biomass estimation for dwarf eelgrass meadows could be unsuccessful when it comes to areas where the NDVI is saturated due to the stacking of many layers.

The influence of age and sex on the bioaccumulation of heavy metals in Apodemus sylvaticus was studied in Merja Zerga lagoon in northern Morocco. Five trace metal elements (Zn, Pb, Cr, Cu and Fe) were quantitatively analyzed by Varian AA 240 atomic absorption spectroscopy with graphite furnace in three organs (Liver, Kidney and Heart) from animals of different age and sex. The maximum metal level of the analyzed samples was recorded in adults and was limited to 46.62 μg/g for Pb and 35.1 μg/g for Cu, while it reached 22.69 μg/g, 7.59 μg/g and 6.78 μg/g for Cr, Zn and Fe, respectively. Highly significant differences were found for bioaccumulation of heavy metals according to animal ages and no significant differences were observed between the two sexes among the studied animals. Our results revealed also the existence of a strong correlation (r > 0.65) between the majority of biometric parameters and the trace element concentrations. In general, we found that age is a critical factor in estimating the level of heavy metal pollution. Other characteristics such as habitat, feeding habits and anti-predator behavior of the species need to be studied.

Seagrass is a vital structural and functional element of the marine environment worldwide and is highly valued for its ecological benefits. Monitoring the evolution of the seagrass habitat is essential to understand how this coastal ecosystem changes, and to develop good environmental management practices. For the present study, two remote sensing methods were used to map and monitor Zostera noltei Hornemann, 1832 ( Z. noltei ), in the Merja Zerga lagoon from 2010 to 2020. These methods which are the random forest algorithm and the object-oriented classification, were convenient to provide significant results. The first approach employed Sentinel-2 images from 2018 to 2020, which were used to extract information on changes in Z. noltei (commonly called dwarf eelgrass) distribution and aboveground biomass estimation. The second involved three orthophotography (orthophoto) mosaics from the years 2010, 2016, and 2018, which were analyzed to map the distribution of the species. It was revealed that Z. noltei coverage has increased by 212 ha since 2010, with most of the growth occurring in the center and upstream part of the lagoon. The mean aboveground biomass of dwarf eelgrass in the lagoon was 78.5 DW/m² in 2018, 92.6 DW/m² in 2019, and 115.2 g DW/m² in 2020. The approach used in this study has provided important insights into the dynamic and mean biomass of Z. noltei in the Merja Zerga lagoon. It is therefore a valuable, non-destructive method that uses freely-available Sentinel-2 satellite data.

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