Commercial-scale Alternaria brown spot resistance screening as the first step in breeding new mandarins for Australia

Rapid screening tests and an appreciation of the simple genetic control of Alternaria brown spot (ABS) susceptibility have existed for many years, and yet the application of this knowledge to commercial-scale breeding programs has been limited. Detached leaf assays were first demonstrated more than 40 years ago and reliable data suggesting a single gene determining susceptibility has been emerging for at least 20 years. However it is only recently that the requirement for genetic resistance in new hybrids has become a priority, following increased disease prevalence in Australian mandarin production areas previously considered too dry for the pathogen. Almost all of the high-fruit-quality parents developed so far by the Queensland-based breeding program are susceptible to ABS necessitating the screening of their progeny to avoid commercialisation of susceptible hybrids. This is done effectively and efficiently by spraying 3-6 month old hybrid seedlings with a spore suspension derived from a toxin-producing field isolate of Alternaria alternate, then incubating these seedlings in a cool room at 25°C and high humidity for 5 days. Susceptible seedlings show clear disease symptoms and are discarded. Analysis of observed and expected segregation ratios loosely support the hypothesis for a single dominant gene for susceptibility, but do not rule out the possibility of alternative genetic models. After implementing the routine screening for ABS resistance for three seasons we now have more than 20,000 hybrids growing in field progeny blocks that have been screened for resistance to the ABS disease.

Efficacy of acibenzolar-S-methyl (Bion®) treatment of Australian commercial passionfruit, Passiflora edulis f. sp. flavicarpa, on resistance to Passionfruit woodiness virus (PWV) and activities of chitinase & β-1,3-glucanase

This greenhouse study investigated the efficacy of acibenzolar-S-methyl (Bion®) treatment of lower leaves of passionfruit, (Passiflora edulis f. sp. flavicarpa), on Passionfruit woodiness disease and activities of two pathogenesis-related proteins, chitinase and β-1,3-glucanase after inoculation with passionfruit woodiness virus (PWV). All Bion® concentrations reduced disease symptoms, but the concentration of 0.025 g active ingredient (a.i.)/l was the most effective, reducing disease severity in systemic leaves by 23, 29 and 30 compared with water-treated controls at 30, 40 and 50 days post inoculation (dpi) with PWV, respectively. Correspondingly, relative virus concentration as determined by DAS-ELISA in the upper, untreated leaves (new growth) above the site of inoculation at 50 dpi was reduced by 17 and 22 in plants treated with 0.025 and 0.05 g a.i./l, respectively. Bion® treatment and subsequent inoculation with PWV increased chitinase and β-1,3-glucanase activities in the new leaves above the site of inoculation at 30 dpi with PWV. It was concluded that optimal protective Bion® treatment concentrations were 0.025 and 0.05 g a.i./l.

Novel species of Cercospora and Pseudocercospora (Capnodiales, Mycosphaerellaceae) from Australia

Novel species of Cercospora and Pseudocercospora are described from Australian native plant species. These taxa are Cercospora ischaemi sp. nov. on Ischaemum australe (Poaceae); Pseudocercospora airliensis sp. nov. on Polyalthia nitidissima (Annonaceae); Pseudocercospora proiphydis sp. nov. on Proiphys amboinensis (Amaryllidaceae); and Pseudocercospora jagerae sp. nov. on Jagera pseudorhus var. pseudorhus (Sapindaceae). These species were characterised by morphology and an analysis of partial nucleotide sequence data for the three gene loci, ITS, LSU and EF-1α. Recent divergence of closely related Australian species of Pseudocercospora on native plants is proposed.

Polyphasic characterization of four new plant pathogenic Phyllosticta species from China, Japan, and the United States

The black rot disease of Vitis species and other host genera of Vitacease is caused by Phyllosticta ampelicida and allied taxa which is considered to be a species complex. In this paper, we introduce four new species of Phyllosticta, including two from the P. ampelicida complex, based on a polyphasic characterization including disease symptoms and host association, morphology, and molecular phylogeny. The phylogenetic analysis was conducted based on the ribosomal internal transcribed spacer (ITS) region and a combined multi-locus alignment of the ITS, actin (ACT), partial translation elongation factor 1-alpha (TEF-1), and glyceraldehydes 3-phosphate dehydrogenase (GPDH) gene regions. Our study confirms the phylogenetic distinctions of the four new species, as well as their phenotypic differences with known species in the genus.

Historical demography of Lantana camara L. reveals clues about the influence of land use and weather in the management of this widespread invasive species

Weather is a general stochastic influence on the life history of weeds. In contrast, anthropogenic disturbance (e.g. land use) is an important deterministic influence on weed demography. Our aim with this study was to investigate the relative contributions of land use and weather on the demography of Lantana camara (lantana), a weed of agricultural and natural habitats, based on the intensive monitoring of lantana populations under three land uses (viz. farm[pasture], and burnt and grazed forests) in subtropical Australia. Lantana populations were growing vigorously across all land uses (asymptotic population growth rate, λ > 3). Examination of historical demography using retrospective perturbation analyses showed that weather was a strong influence on lantana demography with the transition from an El Niño (2008–09) to a La Niña (2009–10) year having a strong positive effect on population growth rate. This effect was most marked at the grazed site, and to a lesser extent at the burnt site, with seedling-to-juvenile and juvenile-to-adult transitions contributing most to these effects. This is likely the result of burning and grazing having eliminated/reduced interspecific competition at these sites. Prospective perturbation analyses revealed that λ was most sensitive to proportionate changes in growth transitions, followed by fecundity and survival transitions. Examination of context-specific patterns in elasticity revealed that growth and fecundity transitions are likely to be the more critical vital rates to reduce λ in wet years at the burnt and grazed forest sites, compared to the farm/pasture site. Management of lantana may need to limit the transition of juveniles into the adult stages, especially in sites where lantana is free from competition (e.g. in the presence of fire or grazing), and this particularly needs to be achieved in wet years. Collectively, these results shed light on aspects of spatial and temporal variation in the demography of lantana, and offer insights on its context-specific management.

Performance and physiological responses of combined t-bar and PIT tagged giant mud crabs (Scylla serrata)

Mud crabs (Scylla spp.) are intensively caught throughout South-East Asia and support a very substantial commercial, recreational fishing and aquaculture industry. Identification of individual animals is important to improve understanding and management of this species. However, tagging of crustaceans is difficult as they frequently molt and internal tags can pose a hazard to consumers. In this pilot study we tested a new method combining passive integrated transponder tags and t-bar tags externally. 45 giant mud crabs (Scylla serrata) were captured from the wild and kept in tanks for a maximum of 10 months. We inserted tags into the abdomen of 35 giant mud crabs and tested a modified method where the combined t-bar/PIT-tag was inserted into the muscle tissue of the rear leg between the dorsal carapace plate and the top of the abdominal flap. Tagged crabs with the modified method showed 85% tag retention for molting crabs. We tested the same method in the field where 852 individuals were tagged with combined t-bar/PIT-tags of which 82 were recaptured showing 100% tag retention but without any evidence of molting having occurred. The tested method of combined t-bar/PIT-tags in giant mud crabs can further improve monitoring for wild and aquaculture populations and can be deployed widely with low cost.

Bayesian analysis of community dynamics

Elucidating the mechanisms responsible for the patterns of species abundance, diversity, and distribution within and across ecological systems is a fundamental research focus in ecology. Species abundance patterns are shaped in a convoluted way by interplays between inter-/intra-specific interactions, environmental forcing, demographic stochasticity, and dispersal. Comprehensive models and suitable inferential and computational tools for teasing out these different factors are quite limited, even though such tools are critically needed to guide the implementation of management and conservation strategies, the efficacy of which rests on a realistic evaluation of the underlying mechanisms. This is even more so in the prevailing context of concerns over climate change progress and its potential impacts on ecosystems. This thesis utilized the flexible hierarchical Bayesian modelling framework in combination with the computer intensive methods known as Markov chain Monte Carlo, to develop methodologies for identifying and evaluating the factors that control the structure and dynamics of ecological communities. These methodologies were used to analyze data from a range of taxa: macro-moths (Lepidoptera), fish, crustaceans, birds, and rodents. Environmental stochasticity emerged as the most important driver of community dynamics, followed by density dependent regulation; the influence of inter-specific interactions on community-level variances was broadly minor. This thesis contributes to the understanding of the mechanisms underlying the structure and dynamics of ecological communities, by showing directly that environmental fluctuations rather than inter-specific competition dominate the dynamics of several systems. This finding emphasizes the need to better understand how species are affected by the environment and acknowledge species differences in their responses to environmental heterogeneity, if we are to effectively model and predict their dynamics (e.g. for management and conservation purposes). The thesis also proposes a model-based approach to integrating the niche and neutral perspectives on community structure and dynamics, making it possible for the relative importance of each category of factors to be evaluated in light of field data.

Gene flow from transgenic plant populations: models and applications for risk assessment

The future use of genetically modified (GM) plants in food, feed and biomass production requires a careful consideration of possible risks related to the unintended spread of trangenes into new habitats. This may occur via introgression of the transgene to conventional genotypes, due to cross-pollination, and via the invasion of GM plants to new habitats. Assessment of possible environmental impacts of GM plants requires estimation of the level of gene flow from a GM population. Furthermore, management measures for reducing gene flow from GM populations are needed in order to prevent possible unwanted effects of transgenes on ecosystems. This work develops modeling tools for estimating gene flow from GM plant populations in boreal environments and for investigating the mechanisms of the gene flow process. To describe spatial dimensions of the gene flow, dispersal models are developed for the local and regional scale spread of pollen grains and seeds, with special emphasis on wind dispersal. This study provides tools for describing cross-pollination between GM and conventional populations and for estimating the levels of transgenic contamination of the conventional crops. For perennial populations, a modeling framework describing the dynamics of plants and genotypes is developed, in order to estimate the gene flow process over a sequence of years. The dispersal of airborne pollen and seeds cannot be easily controlled, and small amounts of these particles are likely to disperse over long distances. Wind dispersal processes are highly stochastic due to variation in atmospheric conditions, so that there may be considerable variation between individual dispersal patterns. This, in turn, is reflected to the large amount of variation in annual levels of cross-pollination between GM and conventional populations. Even though land-use practices have effects on the average levels of cross-pollination between GM and conventional fields, the level of transgenic contamination of a conventional crop remains highly stochastic. The demographic effects of a transgene have impacts on the establishment of trangenic plants amongst conventional genotypes of the same species. If the transgene gives a plant a considerable fitness advantage in comparison to conventional genotypes, the spread of transgenes to conventional population can be strongly increased. In such cases, dominance of the transgene considerably increases gene flow from GM to conventional populations, due to the enhanced fitness of heterozygous hybrids. The fitness of GM plants in conventional populations can be reduced by linking the selectively favoured primary transgene to a disfavoured mitigation transgene. Recombination between these transgenes is a major risk related to this technique, especially because it tends to take place amongst the conventional genotypes and thus promotes the establishment of invasive transgenic plants in conventional populations.

Bayesian statistical analysis of bacterial diversity

Bacteria play an important role in many ecological systems. The molecular characterization of bacteria using either cultivation-dependent or cultivation-independent methods reveals the large scale of bacterial diversity in natural communities, and the vastness of subpopulations within a species or genus. Understanding how bacterial diversity varies across different environments and also within populations should provide insights into many important questions of bacterial evolution and population dynamics. This thesis presents novel statistical methods for analyzing bacterial diversity using widely employed molecular fingerprinting techniques. The first objective of this thesis was to develop Bayesian clustering models to identify bacterial population structures. Bacterial isolates were identified using multilous sequence typing (MLST), and Bayesian clustering models were used to explore the evolutionary relationships among isolates. Our method involves the inference of genetic population structures via an unsupervised clustering framework where the dependence between loci is represented using graphical models. The population dynamics that generate such a population stratification were investigated using a stochastic model, in which homologous recombination between subpopulations can be quantified within a gene flow network. The second part of the thesis focuses on cluster analysis of community compositional data produced by two different cultivation-independent analyses: terminal restriction fragment length polymorphism (T-RFLP) analysis, and fatty acid methyl ester (FAME) analysis. The cluster analysis aims to group bacterial communities that are similar in composition, which is an important step for understanding the overall influences of environmental and ecological perturbations on bacterial diversity. A common feature of T-RFLP and FAME data is zero-inflation, which indicates that the observation of a zero value is much more frequent than would be expected, for example, from a Poisson distribution in the discrete case, or a Gaussian distribution in the continuous case. We provided two strategies for modeling zero-inflation in the clustering framework, which were validated by both synthetic and empirical complex data sets. We show in the thesis that our model that takes into account dependencies between loci in MLST data can produce better clustering results than those methods which assume independent loci. Furthermore, computer algorithms that are efficient in analyzing large scale data were adopted for meeting the increasing computational need. Our method that detects homologous recombination in subpopulations may provide a theoretical criterion for defining bacterial species. The clustering of bacterial community data include T-RFLP and FAME provides an initial effort for discovering the evolutionary dynamics that structure and maintain bacterial diversity in the natural environment.

Performance and physiological responses of combined t-bar and PIT tagged giant mud crabs (Scylla serrata)

Mud crabs (Scylla spp.) are intensively caught throughout South-East Asia and support a very substantial commercial, recreational fishing and aquaculture industry. Identification of individual animals is important to improve understanding and management of this species. However, tagging of crustaceans is difficult as they frequently molt and internal tags can pose a hazard to consumers. In this pilot study we tested a new method combining passive integrated transponder tags and t-bar tags externally. 45 giant mud crabs (Scylla serrata) were captured from the wild and kept in tanks for a maximum of 10 months. We inserted tags into the abdomen of 35 giant mud crabs and tested a modified method where the combined t-bar/PIT-tag was inserted into the muscle tissue of the rear leg between the dorsal carapace plate and the top of the abdominal flap. Tagged crabs with the modified method showed 85% tag retention for molting crabs. We tested the same method in the field where 852 individuals were tagged with combined t-bar/PIT-tags of which 82 were recaptured showing 100% tag retention but without any evidence of molting having occurred. The tested method of combined t-bar/PIT-tags in giant mud crabs can further improve monitoring for wild and aquaculture populations and can be deployed widely with low cost.

Induced carotenoid accumulation in Dunaliella salina and Tetraselmis suecica by plant hormones and UV-C radiation

Carotenoids prevent different degenerative diseases and improve human health. Microalgae are commercially exploited for carotenoids, including astaxanthin and β-carotene. Two commercially important microalgae, Dunaliella salina and Tetraselmis suecica, were treated with plant hormones salicylic acid (SA) and methyl jasmonate (MJ), or by UV-C radiation (T. suecica only) and a combination thereof. Significant increases in total carotenoids were found for D. salina and T. suecica after treatment with MJ (10 μmol/L) and SA (70–250 μmol/L), respectively. T. suecica also had significant increases in total carotenoids following UV-C radiation compared to control cultures. Among the carotenoids, lutein was the highest induced carotenoid. A combination of these two treatments also showed a significant increase in total carotenoids and lutein for T. suecica, when compared to controls. Plant hormones and UV-C radiation may be useful tools for increasing carotenoid accumulation in green microalgae although the responses are species- and dose-specific and should be trialed in medium to large scale to explore commercial production.

Assessment of functional forms of crop yield loss models of invasive plant species applied in decision support tools and bioeconomic modelling

AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.

Development of type I genetic markers from expressed sequence tags in highly polymorphic species

Expressed sequence tag (EST) databases provide a primary source of nuclear DNA sequences for genetic marker development in non-model organisms. To date, the process has been relatively inefficient for several reasons: - 1) priming site polymorphism in the template leads to inferior or erratic amplification; - 2) introns in the target amplicon are too large and/or numerous to allow effective amplification under standard screening conditions, and; - 3) at least occasionally, a PCR primer straddles an exon–intron junction and is unable to bind to genomic DNA template. The first is only a minor issue for species or strains with low heterozygosity but becomes a significant problem for species with high genomic variation, such as marine organisms with extremely large effective population sizes. Problems arising from unanticipated introns are unavoidable but are most pronounced in intron-rich species, such as vertebrates and lophotrochozoans. We present an approach to marker development in the Pacific oyster Crassostrea gigas, a highly polymorphic and intron-rich species, which minimizes these problems, and should be applicable to other non-model species for which EST databases are available. Placement of PCR primers in the 3′ end of coding sequence and 3′ UTR improved PCR success rate from 51% to 97%. Almost all (37 of 39) markers developed for the Pacific oyster were polymorphic in a small test panel of wild and domesticated oysters.

Projecting future expansion of invasive species: Comparing and improving methodologies for species distribution modeling

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

Placental infection with Ureaplasma species is associated with histologic chorioamnionitis and adverse outcomes in moderately preterm and late-preterm infants

Objective The human Ureaplasma species are the microbes most frequently isolated from placentae of women who deliver preterm. The role of Ureaplasma species has been investigated in pregnancies at <32 weeks of gestation, but currently no studies have determined the prevalence of ureaplasmas in moderately preterm and late-preterm (hereafter, “moderate/late preterm”) infants, the largest cohort of preterm infants. Methods Women delivering moderate/late preterm infants (n = 477) and their infants/placentae (n = 535) were recruited, and swab specimens of chorioamnion tissue, chorioamnion tissue specimens, and cord blood specimens were obtained at delivery. Swab and tissue specimens were cultured and analyzed by 16S ribosomal RNA polymerase chain reaction (PCR) for the presence of microorganisms, while cord blood specimens were analyzed for the presence of cytokines, chemokines, and growth factors. Results We detected microorganisms in 10.6% of 535 placentae (443 were delivered late preterm and 92 were delivered at term). Significantly, Ureaplasma species were the most prevalent microorganisms, and their presence alone was associated with histologically confirmed chorioamnionitis in moderate/late preterm and term placentae (P < .001). The presence of ureaplasmas in the chorioamnion was also associated with elevated levels of granulocyte colony-stimulating factor (P = .02). Conclusions These findings have important implications for infection and adverse pregnancy outcomes throughout gestation and should be of major consideration for obstetricians and neonatologists.