Evaluating the effects of anthropogenic pressure on the marine environment is one of the focal objectives in identifying strategies for its use, conservation and restoration. In this paper, we assessed the effects of chemical pollutants, grain size and plastic litter on functional traits, biodiversity and biotic indices. The study was conducted on the benthic communities of three harbours in the central Mediterranean Sea: Malta, Augusta and Syracuse, subjected to different levels of anthropogenic stress (high, medium and low, respectively). Six traits were considered, subdivided into 22 categories: reproductive frequency, environmental position, mobility, life habit, feeding habit and bioturbation. Functional diversity indices analysed were: Functional Divergence, Quadratic Entropy, Functional Evenness and Functional Richness. To assess the trait responses to environmental gradients, we applied RLQ analysis, which considers simultaneously the relationship between three components: environmental data (R), species abundances (L) and species traits (Q). From our analyses, significant relationships (P-value = 0.0018 for permutation of samples, and P-value = 0.00027 for permutation of species) between functional traits and environmental data were highlighted. The trait categories significantly influenced by environmental variables were those representing feeding habits and mobility. In particular, the first category was influenced by chemical pollutants (organotin compounds and polycyclic aromatic hydrocarbons) and grain size (silt and sand), while the latter category was influenced only by chemical pollutants. Pearson correlations performed for functional vs biotic and diversity indices confirmed the validity of the chosen conceptual framework for harbour environments. Finally, linear models assessing the influence of stressors on functional parameters underlined the link between environmental data vs benthic and functional indices. Our results highlight the fact that functional trait analysis provides a useful and fast method for detecting in greater depth the effects of multiple stressors on functional diversity in marine ecosystems.
