We are pleased to share that DIGI4ECO partners, Universitat Politècnica de Catalunya (UPC), Institute of Marine Science (ICM-CSIC), Stazione Anton Dhorn (SZN) and GEOMAR have proceeded to a new achievement within the context of DIGI4ECO project.
The article “10-Years of imagery from a cabled-observatory reveals a decreasing trend in coastal fish biodiversity” has been published at “Science of The Total Environment” Journal, by ELSEVIER.
The authors of the article are: Marco Francescangeli , Jacopo Aguzzi, Damianos Chatzievangelou, Morane Clavel-Henry, Nixon Bahamon, Nathan J. Robinson, Enoc Martínez, Albert Garcia Benadí , Daniel M. Toma, Joaquin Del Rio and its respective DOI is the following: https://doi.org/10.1016/j.scitotenv.2024.178139
The abstract of the publication can be found below:
Abstract:
Monitoring the effects of climate change and other multi-years processes on coastal ecosystems require long-term datasets that may extend into decades. One tool to achieve this are cabled seafloor observatories that can collect continual streams of environmental and biological data as long as the equipment is maintained. Here, we used 10-years of time-lapse images (every 30 mins) from the OBSEA seafloor cabled observatory located at 20 m depth, four km offshore from Vilanova i la Geltrú (Spain) coast, to characterize temporal trends in fish community dynamics. These temporal trends were compared to in situ and remotely-sensed (MODIS-Aqua) data on temperature, salinity, and chlorophyll-a concentration (Chl-a). We observed a reduction in fish diversity over time and an increase in species turnover. Specifically, there was a decrease in the relative abundance of fish species at the lowest trophic levels alongside an increase in predators, suggesting a top-down effect. Of temperature, salinity, and Chl-a, only salinity exhibited a significant change over time. Nevertheless, the Generalized Additive Models (GAMs) revealed significant correlations between fish biodiversity indices and both temperature and Chl-a. Following models results we concluded that environmental variables affected the local fish community only at seasonal level. Including more environmental variables, such as fishing activity and pollution, in the applied models may help explain the detected decreases in biodiversity.
You can reach the full article following this link: https://www.sciencedirect.com/science/article/abs/pii/S0048969724082974?via%3Dihub