Taxonomic resolution, functional traits, and the influence of species groupings on mapping Antarctic seafloor biodiversity

• Published in: Frontiers in Ecology and Evolution
• Main Authors: Jansen, J, Hill, NA, Dunstan, PK, Eleaume, MP, Johnson, CR
• Format: Article in Journal/Newspaper
• Language: English
• Published: Frontiers Research Foundation 2018
• Subjects: Biological Sciences; Ecology; Marine and Estuarine Ecology (incl. Marine Ichthyology); Antarctic; The Antarctic; Antarc*
• Online Access: https://www.frontiersin.org/articles/10.3389/fevo.2018.00081/full; https://doi.org/10.3389/fevo.2018.00081; http://ecite.utas.edu.au/126968

Benthic marine biodiversity on the Antarctic continental shelf is high and unique, yet its distributional patterns are still relatively poorly understood. Some of the main issues are that biological data are sparse, and that many species are rare and seem only weakly related to environmental conditions. Grouping species by taxonomic or functional similarity has historically been used to compensate for missing species identification, to generate a more widespread distribution of data-points, and this practice can help to gain a better understanding of the distribution of biodiversity. However, there are few guidelines on how to group species, the implicit assumptions about species associations in the groups are difficult to validate, and the information loss associated with grouping species is unknown. Here, we analyse whether grouping benthic macrofaunal species by taxonomic or functional similarity preserves distributional patterns seen in species distributions, using a model-based approach called species archetype model that groups species or other units based on the similarity in their responses to environmental factors. Using presence-absence data, the species archetype models identify twice as many assemblages when used on the highest taxonomic resolution data, than when applied to taxonomic data at lower resolution (e.g., class) or functional groups based on mobility, feeding type, and body shape. Further, confidence in the predictions of either taxonomic or functional groups is far less than for predictions based on the highest taxonomic resolution data. Although using functional groups is often thought to accumulate species with similar environmental responses, our analysis shows that functional groups may insufficiently resolve assemblage structure for presence-absence data. Model-based approaches provide key information to understanding the regional distribution of Antarctic marine biodiversity, and care needs to be taken when using a-priori groupings of species to make statements about the distribution of biodiversity.