Predictive mapping of soft bottom benthic biodiversity using a surrogacy approach

A key requirement for informed marine-zone management is an understanding of the spatial patterns of marine biodiversity, often measured as species richness, total abundance or presence of key taxa. In the present study, we focussed on the diversity of benthic infauna and applied a predictive modelling approach to map biodiversity patterns for three study sites on the tropical Carnarvon shelf of Western Australia. A random forest decision tree model was used to generate spatial predictions of two measures of infaunal diversity, namely, species richness and total abundance. Results explained between 20% and 37% of the variance of each measure. The modelling process also identified potential physical surrogates for species richness and abundance, with sediment physical properties ranked as most important across the study region. Specifically, coarse-grained heterogeneous sediments were associated with higher infaunal species richness and total abundance. Seabed topographic properties were also important at the local scale. The study demonstrated the value of a surrogacy approach to the prediction of biodiversity patterns, particularly when the number of biological samples was limited. Such an approach may facilitate an understanding of ecosystem processes in the region and contribute to integrated marine management.

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