Allocasuarina tree hosts determine the spatial distribution of hypogeous fungal sporocarps in three tropical Australian sclerophyll forests

Across three tropical Australian sclerophyll forest types, site-specific environmental variables could explain the distribution of both quantity (abundance and biomass) and richness (genus and species) of hypogeous fungi sporocarps. Quantity was significantly higher in the Allocasuarina forest sites that had high soil nitrogen but low phosphorous. Three genera of hypogeous fungi were found exclusively in Allocasuarina forest sites including Gummiglobus, Labyrinthomyces and Octaviania, as were some species of Castoreum, Chondrogaster, Endogone, Hysterangium and Russula. However, the forest types did not all group according to site-scale variables and subsequently the taxonomic assemblages were not significantly different between the three forest types. At site scale, significant negative relationships were found between phosphorous concentration and the quantity of hypogeous fungi sporocarps. Using a multivariate information theoretic approach, there were other more plausible models to explain the patterns of sporocarp richness. Both the mean number of fungal genera and species increased with the number of Allocasuarina stems, at the same time decreasing with the number of Eucalyptus stems. The optimal conditions for promoting hypogeous fungi sporocarp quantity and sporocarp richness appear to be related to the presence and abundance of Allocasuarina (Casuarinaceae) host trees. Allocasuarina tree species may have a higher host receptivity for ectomycorrhizal hypogeous fungi species that provide an important food resource for Australian mycophagous animals.

Characterization of north-eastern Australian environments using APSIM for increasing rainfed maize production

Recurring water stresses are a major risk factor for rainfed maize cropping across the highly diverse agro-ecological environments of Queensland (Qld) and northern New South Wales (NNSW). Enhanced understanding of such agro-ecological diversity is necessary to more consistently sample target production environments for testing and targeting release of improved germplasm, and to improve the efficiency of the maize pre-breeding and breeding programs of Qld and New South Wales. Here, we used the Agricultural Production Systems Simulator (APSIM) – a well validated maize crop model to characterize the key distinctive water stress patterns and risk to production across the main maize growing regions of Qld and NNSW located between 15.8° and 31.5°S, and 144.5° and 151.8°E. APSIM was configured to simulate daily water supply demand ratios (SDRs) around anthesis as an indicator of the degree of water stress, and the final grain yield. Simulations were performed using daily climatic records during the period between 1890 and 2010 for 32 sites-soils in the target production regions. The runs were made assuming adequate nitrogen supply for mid-season maize hybrid Pioneer 3153. Hierarchical complete linkage analyses of the simulated yield resulted in five major clusters showing distinct probability distribution of the expected yields and geographic patterns. The drought stress patterns and their frequencies using SDRs were quantified using multivariate statistical methods. The identified stress patterns included no stress, mid-season (flowering) stress, and three terminal stresses differing in terms of severity. The combined frequency of flowering and terminal stresses was highest (82.9%), mainly in sites-soils combinations in the west of Qld and NNSW. Yield variability across the different sites-soils was significantly related to the variability in frequencies of water stresses. Frequencies of water stresses within each yield cluster tended to be similar, but different across clusters. Sites-soils falling within each yield cluster therefore could be treated as distinct maize production environments for testing and targeting newly developed maize cultivars and hybrids for adaptation to water stress patterns most common to those environments.

Identification of intersectional Corymbia hybrids based on seedling morphology improves with parental divergence

Differences in morphology have provided a basis for detecting natural interspecific hybridisation in forest trees for decades but have come to prominence again more recently as a means for directly measuring gene flow from planted forests. Here we examined the utility of seedling morphology for hybrid discrimination in three hybrid groups relevant to the monitoring of gene flow from plantings of Corymbia (L.D. Pryor & L.A.S. Johnson ex Brooker) taxa in subtropical Australia. Thirty leaf and stem characters were assessed on 907 8-month old seedlings from four parental and six hybrid taxa grown in a common garden. Outbred F1 hybrids between spotted gums (Corymbia citriodora subspecies variegata, C. citriodora subspecies citriodora and Corymbia henryi) tended to more closely resemble their maternal Corymbia torelliana parent and the most discriminating characters were the ratio of blade length to maximum perpendicular width, the presence or absence of a lignotuber, and specific leaf weight. Assignment of individuals into genealogical classes based on a multivariate model limited to a set of the more discriminating and independent characters was highest in the hybrid group, where parental taxa were genetically most divergent. Overall power to resolve among outbred F1 hybrids from both parental taxa was low to moderate, but this may not be a limitation to its likely major application of identifying hybrids in seedlots from native spotted gum stands. Advanced generation hybrids (outbred F2 and outbred backcrosses) were more difficult to resolve reliably due to the higher variances of hybrid taxa and the tendency of backcrosses to resemble their recurrent parents. Visual assessments of seedling morphology may provide a filter allowing screening of the large numbers needed to monitor gene flow, but will need to be combined with other hybrid detection methods to ensure hybrids are detected.

The use of genetic correlations to evaluate associations between SNP markers and quantitative traits

Open-pollinated progeny of Corymbia citriodora established in replicated field trials were assessed for stem diameter, wood density, and pulp yield prior to genotyping single nucleotide polymorphisms (SNP) and testing the significance of associations between markers and assessment traits. Multiple individuals within each family were genotyped and phenotyped, which facilitated a comparison of standard association testing methods and an alternative method developed to relate markers to additive genetic effects. Narrow-sense heritability estimates indicated there was significant additive genetic variance within this population for assessment traits ( h ˆ 2 =0.28to0.44 ) and genetic correlations between the three traits were negligible to moderate (r G = 0.08 to 0.50). The significance of association tests (p values) were compared for four different analyses based on two different approaches: (1) two software packages were used to fit standard univariate mixed models that include SNP-fixed effects, (2) bivariate and multivariate mixed models including each SNP as an additional selection trait were used. Within either the univariate or multivariate approach, correlations between the tests of significance approached +1; however, correspondence between the two approaches was less strong, although between-approach correlations remained significantly positive. Similar SNP markers would be selected using multivariate analyses and standard marker-trait association methods, where the former facilitates integration into the existing genetic analysis systems of applied breeding programs and may be used with either single markers or indices of markers created with genomic selection processes.

Factors associated with calf mortality in tropically adapted beef breeds managed in extensive Australian production systems

Data from 9296 calves born to 2078 dams over 9 years across five sites were used to investigate factors associated with calf mortality for tropically adapted breeds (Brahman and Tropical Composite) recorded in extensive production systems, using multivariate logistic regression. The average calf mortality pre-weaning was 9.5% of calves born, varying from 1.5% to 41% across all sites and years. In total, 67% of calves that died did so within a week of their birth, with cause of death most frequently recorded as unknown. The major factors significantly (P < 0.05) associated with mortality for potentially large numbers of calves included the specific production environment represented by site-year, low calf birthweight (more so than high birthweight) and horn status at branding. Almost all calf deaths post-branding (assessed from n = 8348 calves) occurred in calves that were dehorned, totalling 2.1% of dehorned calves and 15.9% of all calf deaths recorded. Breed effects on calf mortality were primarily the result of breed differences in calf birthweight and, to a lesser extent, large teat size of cows; however, differences in other breed characteristics could be important. Twin births and calves assisted at birth had a very high risk of mortality, but <1% of calves were twins and few calves were assisted at birth. Conversely, it could not be established how many calves would have benefitted from assistance at birth. Cow age group and outcome from the previous season were also associated with current calf mortality; maiden or young cows (<4 years old) had increased calf losses overall. More mature cows with a previous outcome of calf loss were also more likely to have another calf loss in the subsequent year, and this should be considered for culling decisions. Closer attention to the management of younger cows is warranted to improve calf survival.

Otolith morphology of four mackerel species (Scomberomorus spp.) in Australia: Species differentiation and prediction for fisheries monitoring and assessment

Four species of large mackerels (Scomberomorus spp.) co-occur in the waters off northern Australia and are important to fisheries in the region. State fisheries agencies monitor these species for fisheries assessment; however, data inaccuracies may exist due to difficulties with identification of these closely related species, particularly when specimens are incomplete from fish processing. This study examined the efficacy of using otolith morphometrics to differentiate and predict among the four mackerel species off northeastern Australia. Seven otolith measurements and five shape indices were recorded from 555 mackerel specimens. Multivariate modelling including linear discriminant analysis (LDA) and support vector machines, successfully differentiated among the four species based on otolith morphometrics. Cross validation determined a predictive accuracy of at least 96% for both models. An optimum predictive model for the four mackerel species was an LDA model that included fork length, feret length, feret width, perimeter, area, roundness, form factor and rectangularity as explanatory variables. This analysis may improve the accuracy of fisheries monitoring, the estimates based on this monitoring (i.e. mortality rate) and the overall management of mackerel species in Australia.