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Several anthropogenic factors are responsible for the decline of Cystoseira sensu lato (hereafter Cystoseira) forests along Mediterranean coasts. Some Cystoseira species are already regionally extinct, and their decline has been widely recorded. Sustainable and efficient techniques for the restoration of Cystoseira are needed. In this context, the objectives of this study were i) to analyse the reproductive traits of three populations of Gongolaria barbata from three nearby donor sites in the northern Adriatic Sea, assessing the differences in their reproductive potential and reproductive success; and ii) to evaluate the outplanting success in terms of the effectiveness of G. barbata restoration, in relation to the different donor and receiving sites (Miramare MPA and in front of the Marine Biology Station Piran - MBSP) and implemented methods (ex situ and hybrid method combining a mesocosm cultivation and a suspended culture in the field). After 2 weeks of cultivation in mesocosms, half of the tiles with germlings were transported to the receiving sites and placed on suspended lantern nets (hybrid method), which were later (after 3 months) transferred to the seabed on concrete plates with protective cages. The remaining tiles were placed on the seabed on concrete plates with protective cages after a 4-week culture (ex situ method). At both sites, lantern nets and plates were randomly placed at 3 m depth. Thallus length was measured monthly in each treatment. Seedlings in suspended culture showed lower performance at the Miramare MPA, most likely due to the unfavourable environmental conditions. The satisfactory results obtained at MBSP demonstrate the efficiency of the hybrid method and confirm its potential to reduce the cost and time required for cultivation. Since unpredictable climatic events pose the greatest threat to restoration performance, these challenges must be considered when establishing new restoration practices. Moreover, herbivore regulation is extremely urgent and should be planned and implemented on a larger regional scale.

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.