Australian rainforests have been fragmented due to past climatic changes and more recently landscape change as a result of clearing for agriculture and urban spread. The subtropical rainforests of South Eastern Queensland are significantly more fragmented than the tropical World Heritage listed northern rainforests and are subject to much greater human population pressures. The Australian rainforest flora is relatively taxonomically rich at the family level, but less so at the species level. Current methods to assess biodiversity based on species numbers fail to adequately capture this richness at higher taxonomic levels. We developed a DNA barcode library for the SE Queensland rainforest flora to support a methodology for biodiversity assessment that incorporates both taxonomic diversity and phylogenetic relationships. We placed our SE Queensland phylogeny based on a three marker DNA barcode within a larger international rainforest barcode library and used this to calculate phylogenetic diversity (PD). We compared phylo- diversity measures, species composition and richness and ecosystem diversity of the SE Queensland rainforest estate to identify which bio subregions contain the greatest rainforest biodiversity, subregion relationships and their level of protection. We identified areas of highest conservation priority. Diversity was not correlated with rainforest area in SE Queensland subregions but PD was correlated with both the percent of the subregion occupied by rainforest and the diversity of regional ecosystems (RE) present. The patterns of species diversity and phylogenetic diversity suggest a strong influence of historical biogeography. Some subregions contain significantly more PD than expected by chance, consistent with the concept of refugia, while others were significantly phylogenetically clustered, consistent with recent range expansions.

The spatial distribution of genotypes at six enzyme loci was investigated in 17 natural populations of the temperate rainforest tree Atherosperina moschatum using spatial autocorrelation. The results from the different enzymes were consistent at each population as well as among populations, particularly at short distances. There were stronger associations overall between like homozygous trees than like heterozygous trees. Unlike trees were generally significantly negatively autocorrelated at short distances. Two consistent patterns of associations were found with increasing distances between trees. A highly consistent average patch length was found in most populations for the enzymes studied. The results suggest that there are small neighbourhood sizes m this species and therefore small stands are worth conserving. In addition, larger populations are unlikely to be homogenous. Therefore, conserving one part of a population may not adequately sample its genetic variability.

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