Delineating marine ecological units: a novel approach for deciding which taxonomic group to use and which taxonomic resolution to choose

Aim Ecological maps are increasingly used to support marine management and conservation. However, the biological datasets used to produce these maps are typically limited to taxonomic groups identified to the specific taxonomic levels available. Ecological units should, however, reflect the broader marine ecosystem, independent of the datasets used. This study assessed the influence of taxonomic groups and taxonomic resolution on the process of ecological mapping. Location Estuary and Gulf of St Lawrence ( EGSL ), Canada. Methods A dataset of more than 200 taxa of benthic macrofauna was used to create a set of biological matrices corresponding to different taxonomic groups (i.e. vertebrates, invertebrates, arthropods, echinoderms, molluscs, all taxa) and different taxonomic levels from species to class. Multivariate regression trees ( MRT s) were used to identify environmental drivers of taxa distribution and to create ecological maps. Similarity between maps was assessed using pairwise comparisons. First, the relationships between the two classification legends were assessed using association plots on the partitions in the corresponding trees. Then, the spatial agreement of ecological units believed to represent the same habitat types was quantified and mapped. Results The comparison across different taxonomic groups showed a substantial level of similarity between ecological maps, indicating that ecological units defined for a specific taxonomic group can be considered to some extent as representative of the entire benthic macrofauna. Moreover, little information was lost when working at the family rather than species level, and common patterns of community distribution could still be distinguished at the class level. Main conclusions Using a novel spatially explicit approach for comparing ecological maps, this study demonstrates that datasets limited by taxonomic breadth or resolution can perform nearly as well as more extensive datasets. These simplifications should improve our ability to manage marine ecosystems.