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Aim To investigate the relationships between species attributes and genetic parameters in Australian plant species and to determine the associations in relation to predictions from population theory and previous global analyses.Location Continent of Australia. MethodsWe assembled a dataset of all known population genetic analyses of Australian plants based on neutral markers and catalogued them according to key species attributes, including range, abundance, range disjunction, biome and growth form; and genetic parameters, mean number of alleles per locus, observed and expected heterozygosity and population differentiation. We determined relationships between species attributes and genetic parameters using a maximum-likelihood, multimodel inference approach. Results We found many associations that were consistent with predictions. Species attributes with greatest effect on genetic diversity were range size, growth form, abundance and biome. The most important attributes influencing genetic differentiation were range disjunction and abundance. We found unexpected results in the effects of biome and growth form on genetic diversity, with greater diversity in the eastern biome of Australia, and lower diversity in shrubs compared to trees.Main conclusions Our analysis of genetic diversity of Australian plants showed associations consistent with predictions based on population genetics theory, with strong effects of range size, abundance and growth form. We identified a striking effect of range disjunction on population genetic differentiation, an effect that has received little attention in the literature. We also found some notable differences to global predictions, which were most likely explained by confounding effects across variables. This highlights that caution is needed when extrapolating trends from global analyses to regional floras. Identifying associations between species attributes and patterns of genetic diversity enables broadscale predictions to facilitate the inclusion of genetic considerations into conservation decision-making.

BackgroundIn order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS).ResultsThe PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks.ConclusionEucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

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Eucalypts are both a proven but largely unexplored source of woody biomass for biofuel production. Few of the some 900 species have been evaluated for cropping, yet among them are the most productive and versatile biomass species in the world, grown in over 90 countries, with species found to suit most tropical and temperate climates. The biology, science and technology underlying the breeding and growing of eucalypts and their potential for biofuel production are reviewed. How eucalypts meet sustainability and economic criteria for biofuel feedstocks, and the advantages of woody feedstocks broadly, are considered. Relevant aspects of eucalypt taxonomy, evolution, natural distribution, human dispersal, composition, domestication and biotechnology of the groups' potential as a biofuel feedstock resource are reviewed. Two case studies are outlined, illustrating species identification, domestication and harvesting processes where eucalypts are prospective biofuel feedstocks. Eucalypts are strong contenders as a universal woody biomass feedstock for biofuel.