Temporal patterns of gelatinous zooplankton distribution and environmental drivers in the south-western Mediterranean Sea
- 1. University of Sciences and Technology Houari Boumediene, Faculty of Biological Sciences- Laboratory of Biological Oceanography and the Marine Environment-Pelagic Ecosystem Team. BP 32, El Alia, Bab-Ezzouar, Algiers, Algeria
- 2. University of Sciences and Technology Houari Boumediene, Faculty of Biological Sciences- Laboratory of Biological Oceanography and the Marine Environment-Fisheries Team. BP 32, El Alia, Bab-Ezzouar, Algiers, Algeria
Description
This study aims to investigate the distribution of gelatinous zooplankton in relation to environmental parameters along the coastal regions of Algeria in the south-western Mediterranean Sea. A total of 48 species were recorded from nine sampling stations located in the central (Sidi Fredj) and western (Habibas Islands) sectors of the Algerian coast. The results showed that the seasonal distribution of gelatinous species exhibits significant variations. Amongst cnidarians, P. noctiluca, M. atlantica and A. tetragona are the most abundant species. Chaetognaths are primarily represented by F. enflata and P. friderici. Tunicates display high diversity, with T. democratica, O. longicauda and D. nationalis as the most abundant species. Lastly, in molluscs, H. inflatus and L. trochiformis are the most abundant species. The nMDS and ANOSIM analysis reveal significant differences in the ecological community structures between the Habibas Islands and Sidi Fredj. Redundancy analysis results show relationships between different marine species and environmental variables, such as temperature, chlorophyll a and salinity. The studied species exhibit positive or negative correlations with these variables, suggesting an influence of these factors on their abundance and distribution. This study enhances our understanding of the factors that govern the distribution and dispersal of gelatinous zooplankton in the Mediterranean Sea and has significant implications for predicting changes in the distribution of these species under future environmental scenarios.
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