Abstract

AbstractAimMarine forests of brown macroalgae create essential habitats for coastal species and support invaluable ecological services. Here, we provide the first global analysis of species richness and endemicity of both the kelp and fucoid biomes.LocationGlobal.Time periodContemporary.Major taxa studiedMarine forests of brown macroalgae, formed by kelp (here defined as orders Laminariales, Tilopteridales and Desmarestiales) and fucoid (order Fucales), inhabiting subtidal and intertidal environments.MethodsWe coupled a large dataset of macroalgal observations (420 species, 1.01 million records) with a high‐resolution dataset of relevant environmental predictors (i.e., light, temperature, salinity, nitrate, wave energy and ice coverage) to develop stacked species distribution models (stacked SDMs) and yield estimates of global species richness and endemicity.ResultsTemperature and light were the main predictors shaping the distribution of subtidal species, whereas wave energy, temperature and salinity were the main predictors of intertidal species. The highest regional species richness for kelp was found in the north‐east Pacific (maximum 32 species) and for fucoids in south‐east Australia (maximum 53 species), supporting the hypothesis that these regions were the evolutionary sources of global colonization by brown macroalgae. Locations with low species richness coincided between kelp and fucoid, occurring mainly at higher latitudes (e.g., Siberia) and the Baltic Sea, where extensive ice coverage and low‐salinity regimes prevail. Regions of high endemism for both groups were identified in the Galapagos Islands, Antarctica, South Africa and East Russia.Main conclusionsWe estimated the main environmental drivers and limits shaping the distribution of marine forests of brown macroalgae and mapped biogeographical centres of species richness and endemicity, which largely coincided with the expectation from previous evolutionary hypotheses. The mapped biodiversity patterns can serve as new baselines for planning and prioritizing locations for conservation, management and climate change mitigation strategies, flagging threatened marine forest regions under different climate change scenarios.

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