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Biodiversity-Ecosystem Function experimental stu- dies focusing on marine systems are few and produce contrasting outcomes. Here, we provide experimental proofs on how communities, on a natural gradient of diversity, respond under stressful conditions in inter- tidal habitats. In August 2017 a field experiment was performed in Western Sicily (Italy) in a site charac- terized by tidal pools whose biodiversity structure and composition change as a function of the distance from the low tide mark. The pools closer to the sea are more stable from a thermal and oxic point of view and characterized by high algal biodiversity. Those further from the sea are highly variable with extreme conditions and are poorer in species. We chose 12 pools – homogeneous in size and geometry – and, to know the environmental fluctuations, we measured, for 24 hours at the minute resolution, the oxygen concentration (through an oximeter) and the tem- perature (using thermos-loggers). Then, we carried out a manipulative experiment, follow the same field procedures, to investigate the effects of a climatic event (heat wave) in combination with anthropogenic stress (increased gasoline concentra- tion). We used community metabolism (oxygen consumption, mg/L) as a proxy of functioning. At the end of the treatments, we characterized the bio- diversity contained in each pool by scraping 3 quad- rats 10 x 10 cm and related it to community metabolism. No difference was observed in the metabolism between treated and controlled in high diversity pools; whilst significant differences have been found in low diversity pools for the climatic stressor. Regarding to the chemical stressor, no remarkable difference has been found. Interestingly, these results show that under the action of a disturbance, the functioning – as expressed by oxy- gen consumption – can be altered over time. The richer the community increases the ability to restore the control conditions, while the poorer pools were unable to do so.

Global warming, through increasing temperatures, may facilitate the spread and proliferation of outbreak-forming species which may find favourable substrate conditions on artificial aquaculture structures. The presence of stinging organisms (cnidarian hydroids) in the facilities fouling community are a source of pollution that can cause critical problems when in-situ underwater cleaning processes are performed. Multiple stressor experiments were carried out to investigate the cumulative effect on farmed mussels' functional traits when exposed to realistic stressful conditions, including presence of harmful cnidarian cells and environmental conditions of increasing temperature and short-term hypoxia. Exposure to combined stressors significantly altered mussels' performance, causing metabolic depression and low filtering activity, potentially delaying, or inhibiting their recovery ability and ultimately jeopardizing organisms' fitness. Further research on the stressors properties and occurrence is needed to obtain more realistic responses from organisms to minimize climate change impacts and increase ecosystem and marine economic activities resilience to multiple stressors.

Macroalgal forests are one of the most productive and valuable marine ecosystems, but yet strongly exposed to fragmentation and loss. Detailed large-scale information on their distribution is largely lacking, hindering conservation initiatives. In this study, a systematic effort to combine spatial data on Cystoseira C. Agardh canopies (Fucales, Phaeophyta) was carried out to develop a Habitat Suitability Model (HSM) at Mediterranean scale, providing critical tools to improve site prioritization for their management, restoration and protection. A georeferenced database on the occurrence of 20 Cystoseira species was produced collecting all the available information from published and grey literature, web data portals and co-authors personal data. Data were associated to 55 predictor variable layers in the (ASCII) raster format and were used in order to develop the HSM by means of a Random Forest, a very effective Machine Learning technique. Knowledge about the distribution of Cystoseira canopies was available for about the 14% of the Mediterranean coastline. Absence data were available only for the 2% of the basin. Despite these gaps, our HSM showed high accuracy levels in reproducing Cystoseira distribution so that the first continuous maps of the habitat across the entire basin was produced. Misclassification errors mainly occurred in the eastern and southern part of the basin, where large gaps of knowledge emerged. The most relevant drivers were the geomorphological ones, followed by anthropogenic variables proxies of pollution and urbanization. Our model shows the importance of data sharing to combine a large number of spatial and environmental data, allowing to individuate areas with high probability of Cystoseira occurrence as suitable for its presence. This approach encourages the use of this modelling tool for the prediction of Cystoseira distribution and for supporting and planning conservation and management initiatives. The step forward is to refine the spatial information of presence-absence data about Cystoseira canopies and of environmental predictors in order to address species-specific assessments.