Surrogate taxa are used widely to represent attributes of other taxa for which data are sparse or absent. Because surveying and monitoring marine biodiversity is resource intensive, our understanding and management of marine systems will need to rely on the availability of effective surrogates. The ability of any marine taxon to adequately represent another, however, is largely unknown because there are rarely sufficient data for multiple taxa in the same region(s). Here, we defined a taxonomic group to be a surrogate for another taxonomic group if they possessed similar assemblage patterns. We investigated effects on surrogate performance of (1) grouping species by taxon at various levels of resolution, (2) selective removal of rare species from analysis, and (3) the number of clusters used to define assemblages, using samples for 11 phyla distributed across 1189 sites sampled from the seabed of Australia's Great Barrier Reef. This spatially and taxonomically comprehensive data set provided an opportunity for extensive testing of surrogate performance in a tropical marine system using these three approaches for the first time, as resource and data constraints were previously limiting. We measured surrogate performance as to how similarly sampling sites were divided into assemblages between taxa. For each taxonomic group independently, we grouped sites into assemblages using Hellinger distances and medoid clustering. We then used a similarity index to quantify the concordance of assemblages between all pairs of taxonomic groups. Surrogates performed better when taxa were grouped at a phylum level, compared to taxa grouped at a finer taxonomic resolution, and were unaffected by the exclusion of spatially rare species. Mean surrogate performance increased as the number of clusters decreased. Moreover, no taxonomic group was a particularly good surrogate for any other, suggesting that the use of any one (or few) group(s) for mapping seabed biodiversity patterns is imprudent; sampling several taxonomic groups appears to be essential for understanding tropical/subtropical seabed communities. Consequently, where resource constraints do not allow complete surveying of biodiversity, it may be preferable to exclude rare species to allow investment in a broader range of taxonomic groups.