Performance of <scp>DNA</scp> Metabarcoding vs. Morphological Methods for Assessing Intertidal Turf and Foliose Algae Diversity

Large biogeographical shifts in marine communities are taking place in response to climate change and biological invasions yet we still lack a full understanding of their diversity and distribution. An important example of this is turf and foliose algae that are key coastal primary producers in several regions and are expanding into new environments. Traditionally, monitoring turf and foliose algae communities involves species identification based on morphological traits, which is challenging due to their reduced dimensions and highly variable morphology. Molecular methods promise to revolutionise this field, but their effectiveness in detecting turf and foliose algae has yet to be tested. Here, we evaluate the performance of DNA metabarcoding (COI and rbcL markers) and morphological identification (in situ and photoquadrat) to describe intertidal turf and foliose algae communities along the Portuguese coast. Both molecular markers detected more taxa than the morphological methods and showed greater discrimination of turf and foliose algae communities between regions, matching our knowledge of the geographical and climatic patterns for the region. In sum, our multi-marker metabarcoding approach was more efficient than morphology-based methods in characterising turf and foliose algae communities along the Portuguese coast, differentiating morphologically similar species, and detecting unicellular organisms. However, certain taxa that were identified by in situ and photoquadrat approaches were not detected through metabarcoding, partly due to lack of reference barcodes or taxonomic resolution. Metabarcoding emerges as a valuable tool for monitoring these communities, particularly in long-term programmes requiring accuracy, speed, and reproducibility.