Comparing large-scale bioregions and fine-scale community-level biodiversity predictions from subtidal rocky reefs across south-eastern Australia


Correspondence author. E-mail:


1. In the absence of knowledge of the large-scale structure and distribution of marine biota, bioregionalisations, that is, spatial classifications of data on a range of environmental and/or biological attributes, are often viewed as one of the most appropriate frameworks within which to develop networks of marine protected areas (MPAs). However, despite their potential usefulness, few studies have assessed whether bioregionalisations can be used for management of species other than those it was derived from or whether bioregionalisations capture fully fine-scale community-level biodiversity patterns.

2. We investigated the large-scale structure and distribution of demersal fishes and macroinvertebrates in south-eastern Australia, using rank abundance distributions (RADs). We used a recently developed community modelling method that allows their multivariate distribution to vary according to environmental gradients, assessing the congruency of mapped biogeographic patterns between the different taxa, and in the light of the Interim Marine and Coastal Regionalisation for Australia (IMCRA).

3. A clear pattern in our analysis based on RADs showed a large difference in assemblage structure (i.e. in abundance, richness and evenness) between South Australia, where assemblages were generally more species rich and even, and Victoria and Tasmania, where assemblages were generally more species poor and uneven. The strong longitudinal pattern in species richness and evenness was generally congruent for both demersal fishes and macroinvertebrates and related to regional differences in oceanography.

4. We found that the regions of highest species richness were found in the ‘core’ bioregions rather than ‘transition’ bioregions as defined in the IMCRA and for both taxa. Moreover, we found that not all assemblage structures were equally alike and that South Australia had the greatest range of unique assemblage structures.

5.Synthesis and applications. While bioregionalisations are typically based on data from a single taxon, our findings highlight that they can be used as a surrogate for biological patterns seen in other taxa. Bioregionalisations, however, may not capture fully fine-scale community-level biodiversity patterns, and this may compromise the ability of protected area networks to protect the full variability in assemblage types. We suggest that it may be necessary to validate existing regionalisations with additional data and analyses such as the RAD analyses conducted here.