AIMC Topic: Mediterranean Sea
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Exploring the nexus between coastal tourism growth and eutrophication: Challenges for environmental management.
Marine pollution bulletin
Apr 16, 2025
Coastal tourism has witnessed rapid growth over the past two decades, often accompanied by increasing environmental concerns, particularly eutrophication in sensitive marine zones. This study explores the relationship between coastal tourism expansio...
Machine learning unveils large-scale impact of Posidonia oceanica on Mediterranean Sea water.
The Science of the total environment
Feb 22, 2025
Posidonia oceanica is a protected endemic seagrass of the Mediterranean Sea that fosters biodiversity, stores carbon, releases oxygen, and provides habitat to numerous sea organisms. Leveraging augmented research, we collected a comprehensive dataset...
Artificial neural network analysis of microbial diversity in the central and southern Adriatic Sea.
Scientific reports
May 27, 2021
Bacteria are an active and diverse component of pelagic communities. The identification of main factors governing microbial diversity and spatial distribution requires advanced mathematical analyses. Here, the bacterial community composition was anal...
Rummaging through the bin: Modelling marine litter distribution using Artificial Neural Networks.
Marine pollution bulletin
Sep 26, 2019
Marine litter has significant ecological, social and economic impacts, ultimately raising welfare and conservation concerns. Assessing marine litter hotspots or inferring potential areas of accumulation are challenging topics of marine research. Neve...
A machine learning algorithm for high throughput identification of FTIR spectra: Application on microplastics collected in the Mediterranean Sea.
Chemosphere
Jun 6, 2019
The development of methods to automatically determine the chemical nature of microplastics by FTIR-ATR spectra is an important challenge. A machine learning method, named k-nearest neighbors classification, has been applied on spectra of microplastic...
Modeling of Beta Diversity in Tunisian Waters: Predictions Using Generalized Dissimilarity Modeling and Bioregionalisation Using Fuzzy Clustering.
PloS one
Jul 6, 2015
Spatial patterns of beta diversity are a major focus of ecology. They can be especially valuable in conservation planning. In this study, we used a generalized dissimilarity modeling approach to analyze and predict the spatial patterns of beta divers...
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