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There are evidences of how climate change is affecting seaweeds distribution and the ecosystems services they provide. Therefore, it is necessary to consider these impacts when managing marine areas. One of the most applied tools in recent years to deal with this are species distribution models, however there are still some challenges to solve, such as the inclusion of hydrodynamic predictors and the application of effective, transferable and user-oriented methodologies.

Five species (Saccorhissa polyschides, Gelidiurn spinosum, Sargassurn muticum, Pelvetia canaliculata and Cystoseira baccata) in Europe and 15 variables were considered. Nine of them were projected to the RCPs 4.5 and 8.5 for the mid-term (2040-2069) and the long term (2070-2099). Algorithms for each species were applied to generate models that were assessed by comparison of probabilities and observations (area under the curve, true skill statistics, Boyce index, sensitivity, correct classification rate), niches overlap (Schoener's D, Hellinger's I), geographical similarity (interquartile range) and ecological realism.

Models built demonstrated very good predictive accuracy and sensitivity, without overfitting risk. A medium overlap in the historical and RCPs environmental conditions were obtained, therefore the models can be considered transferable and results accurate because only some isolated points were detected as outliers, corresponding to low probabilities.

The areas of S. polyschides and G. spinosum have been identified to be dramatically reduced, meanwhile S. muticum and C. baccata were predicted to expand their range. P. canaliculata was expected to keep its sites of presence but with a decrease in its probability of occurrence. For all species it was remarkable the importance of hydrodynamic variables and parameters representing extreme conditions. Spatially predictions of the potential species and areas at risk are decisive for defining management strategies and resource allocation. The performance and usefulness of the approach applied in this study have been demonstrated for algae with different ecological requirements (from upper littoral to subtidal) and distributional patterns (native and invasive), therefore results can be used by marine planners with different goals: marine protected areas designation, monitoring efforts guiding, invasions risk assessment or aquaculture facilities zonation.