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Due to multiple impacts, Cystoseira forests are experiencing a significant decline, which is affecting the ecosystem services they provide. Despite conservation efforts, there is an urgent need to develop best practices and large-scale restoration strategies. To implement restoration actions, we developed an ex situ protocol for the cultivation of Cystoseira. amentacea var. stricta, aimed at reducing the time needed for laboratory culture, thus avoiding prolonged maintenance and minimizing costs. Specifically, we tested the effects of temperature, light and substratum on settlement and growth of early life stages using a factorial experiment. Temperature (20 and 24°C) and photoperiod (15L:9D) were selected to reflect the conditions experienced in the field during the reproductive period. Two light intensities (125 and 250 μmol photons m-2s-1) were selected to mimic the condition experienced in the absence of canopy (i.e. barren-higher light intensity) or in the understory (lower light intensity) during gamete release. The tested substrata were flat polished pebbles and rough clay tiles. The release of gametes and the successive survival and development of embryo and germlings were followed for two weeks. Regardless of the culture conditions, rougher tiles showed higher zygote settlement, but the substrata did not affect the successive development. Zygote mortality after one week averaged 50% and at the end of the second week, embryonic survival was higher under lower light and temperature conditions, which also determined the growth of larger embryos.

Habitat classifications provide guidelines for mapping and comparing marine resources across geographic regions. Calcareous bio-concretions and their associated biota have not been exhaustively categorized. Furthermore, for management and conservation purposes, species and habitat mapping is critical. Recently, several developments have occurred in the field of predictive habitat modeling, and multiple methods are available. In this study, we defined the habitats constituting northern Adriatic biogenic reefs and created a predictive habitat distribution model. We used an updated dataset of the epibenthic assemblages to define the habitats, which we verified using the fuzzy k-means (FKM) clustering method. Redundancy analysis was employed to model the relationships between the environmental descriptors and the FKM membership grades. Predictive modelling was carried out to map habitats across the basin. Habitat A (opportunistic macroalgae, encrusting Porifera, bioeroders) characterizes reefs closest to the coastline, which are affected by coastal currents and river inputs. Habitat B is distinguished by massive Porifera, erect Tunicata, and non-calcareous encrusting algae (Peyssonnelia spp.). Habitat C (non-articulated coralline, Polycitor adriaticus) is predicted in deeper areas. The onshore-offshore gradient explains the variability of the assemblages because of the influence of coastal freshwater, which is the main driver of nutrient dynamics. This model supports the interpretation of Habitat A and C as the extremes of a gradient that characterizes the epibenthic assemblages, while Habitat B demonstrates intermediate characteristics. Areas of transition are a natural feature of the marine environment and may include a mixture of habitats and species. The habitats proposed are easy to identify in the field, are related to different environmental features, and may be suitable for application in studies focused on other geographic areas. The habitat model outputs provide insight into the environmental drivers that control the distribution of the habitat and can be used to guide future research efforts and cost-effective management and conservation plans.