John N.A. Hooper & Merrick Ekins, Commonwealth of Australia and Queensland Museum, 2004.

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Collation and validation of museum collection databases related to the distribution of marine sponges in northern Australia (PDF - 11.94 MB)

About the report

Australian museums and other marine collections agencies now hold extensive collections of sponges (Phylum Porifera) and associated digital data that have demonstrated utility towards recognising and defining areas of high biodiversity value (‘hotspots’).

Amalgamation of the Queensland Museum sponge database (c.30,000 records) with recent collections (of a subset of 721 ‘surrogate’ species) from the tropical fauna by the Australian Institute of Marine Science, Museums and Art Galleries of the Northern Territory and Western Australian Museum, has produced a significant database of c.3,800 ‘species’ (OTUs) from c.4,000 localities, representing 425 genera, 120 families, 26 orders and 3 classes of Porifera, with 2,248 species living in tropical waters and analysed in this study.

This dataset is to be made available online through a nationally distributed database OZCAM (www.ozcam.gov.au).

Point specimen data of the ‘surrogate’ species are accompanied by modelled geographic and depth distributions using the CSIRO CAAB system, together with digital descriptions of species to ensure compliance with taxonomic identifications across all agencies, with the intention that all 3,800 or so currently known (collected) species will eventually have similar digital information available on-line, irrespective of whether or not they have yet been formally described in the scientific literature (a painfully slow and exacting, but ultimately essential process).

This amalgamated tropical sponge dataset was analysed descriptively using GIS, and numerically using statistical tools, to identify, test and define major changes (β-diversity) in species richness, species composition and community structure of marine sponges across the Australian tropics.

It is anticipated that these data will eventually contribute to an integrative project for bioregionalisation of the tropical fauna based on numerous biotic and abiotic datasets.