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Table S1Tasmannia lanceolata sample information for the range-wide chloroplast study (244 samples). The clade or subclade and haplotype determined for each sample is shown

Table S2Sample information for all Tasmannia taxa used as outgroups (16 samples). The haplotype determined for each sample is shown

Table S3 Single base pair nucleotide polymorphisms and insertions/ deletions characterising all 30 chloroplast DNA haplotypes observed in Tasmannia lanceolata, shown in comparison to the most frequent haplotype 1a. The number of T. lanceolata samples with each haplotype is shown in parentheses following the haplotype name. Vertical numbers indicate the bp position of each polymorphism in the complete sequence alignment. The states at variable sites in T. lanceolata are also shown for other Tasmannia species, Drimys and Pseudowintera. *T. xerophila includes T. xerophila subsp. xerophila, T. xerophila subsp. robusta and T. vickeriana which were identical for the thirty characters variable within T. lanceolata but differed for other characters not shown. ** T. stip./ purp. denotes the single samples of both T. stipitata and T. purpurescens which were identical for all characters variable within T. lanceolata and all other characters not shown

Table S4 Genbank accession numbers for all Tasmannia lanceolata haplotypes, variable sequences for other Tasmannia species and subspecies and outgroups.

Fig. S1 Fossil pollen record of Tasmannia lanceolata (Winteraceae) with the current distribution of the species shown in grey. Two macrofossil sites of the species are indicated by arrows. The pollen records of Tasmannia on mainland Australia may be other species of the genus not present in Tasmania.

Fig. S2 Estimates of climates for each of the 138 sample sites in Tasmania were made using BIOCLIM (Houlder et al. 2003). BIOCLIM created synthetic estimates of 35 climate parameters reflecting annual and seasonal temperature, precipitation, evaporation and moisture availability, from point locations (latitude, longitude and altitude), using a three dimensional spline based on long-term meteorological records. To summarise this large amount of inter-correlated data, principal components analysis was run on all 35 parameters.

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FilenameFormatSizeDescription
MEC_4725_sm_tables1.pdf715KSupporting info item
MEC_4725_sm_tables2.pdf277KSupporting info item
MEC_4725_sm_tables3.pdf332KSupporting info item
MEC_4725_sm_tables4.pdf256KSupporting info item
MEC_4725_sm_figs1.pdf483KSupporting info item
MEC_4725_sm_figs2.pdf123KSupporting info item

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.