School of BioSciences - Theses

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    The diversity and behaviour of Dermaptera (earwigs) in the southern Australian grain belt
    Stuart, Oliver ( 2018)
    Dermaptera (earwigs) are a cosmopolitan order of insects that have recently come to the attention of the Australian grain industry. Researchers have been sampling Dermapteran diversity and abundance across the southern Australian grain belt, but resolution of the sample is stifled by taxonomic impediment, particularly for specimens of the morphologically uniform Anisolabididae family. Molecular methods can provide much needed resolution to the study of Australian Dermaptera. I barcoded known Dermaptera species from across the southern Australian states to assess the utility of barcoding for Dermapteran biodiversity research. I also assessed the diversity of the Anisolabididae by combining morphological identification and DNA barcodes. I then estimated their phylogeny with a larger molecular dataset comprised of two mitochondrial and two nuclear gene fragments under a maximum-likelihood framework. Anisolabididae males were divided into seven morphospecies based on the shape of the forceps and parameres (a male genital structure), and these morphospecies were corroborated by barcodes (low within versus between-species genetic distance). Paramere shape distinguished two putative genera, Anisolabis Fieber and Gonolabis Burr. The molecular phylogeny did not support the monophyly of the genera, rather forming clades distinguished by the shape of the forceps. The evolutionary significance of paramere versus forceps morphology in Dermapteran taxonomy is discussed. Anisolabididae were only found in Western and South Australia and showed apparent endemism. Extending the study of Australian Anisolabididae beyond grains-producing regions may reveal a diverse endemic fauna, almost entirely unexplored heretofore.
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    Effects of fishing and climate change on the Chondrichthyan species in the Gulf of California region
    Garces-Garcia, Karla Cirila ( 2019)
    This thesis is composed of three data chapters and a general introduction and discussion. Each chapter, except for the general introduction and the general discussion is composed of an introduction, materials and methods, results, discussion, and conclusions. The aim of this study was to assess the vulnerability risk to fishing and climate change stressors of 106 species of chondrichthyans with ≥10% of their distribution within the EEZ off western Mexico. For my analysis, I determine the vulnerability of the chondrichthyan species inside the Gulf (GCI) and compare these results with those for two other contiguous broad regions with different oceanographic conditions, the region around the entrance to the Gulf of California (GCE) and Mexico’s remaining Pacific waters (MPW). I have built on existing approaches to provide, in a single framework, a vulnerability analysis and risk assessment of the Mexican chondrichthyan (sharks, rays, skates and chimaeras) fauna by combining three components of vulnerability risk to climate change (exposure, sensitivity and adaptive capacity) (ESA), together with three components of vulnerability risk to fishing stressors (exposure, productivity, and susceptibility) (EPS). Here, vulnerability is expressed as the risk of marked reduction of the population of chondrichthyans based on the knowledge of its biology and its exposure to stressors associated with fishing and climate change. For fishing stressors, I use the productivity of the chondrichthyan species, which is related to the maximum age of the species, and susceptibility, which derives from four parameters; availability, encounterability, selectivity, and post-encounter mortality. For climate change stressors, I use sensitivity, which has two parameters; rarity and habitat specificity as species attributes that contribute to this, and adaptive capacity. Adaptive capacity involves distributional flexibility and trophic level as relevant attributes. I assigned each species to one of six ecological groups (EGs), which is a flexible and novel way to allocate a large number of species based on habitat use, depth strata (shelf-inshore and shelf-offshore), habitat dependence (freshwater, reef substrate, and sandy substrate), and lifestyle (demersal or pelagic). For fishing stressors, I analyzed data sets from 2006 to 2017 for the prawn trawl fishery, the elasmobranch fishery (artisanal and semi-industrial) and for the sardine fishery, and published information on the sport-recreational fishing. These fisheries have the potential to reduce the size of the population of a chondrichthyan species by altering the mortality rate in the regions where the fisheries operate. I then characterised the fishing stressors in terms of fishing methods and the bathymetric range of deployment of the fishing gear (Chapters 1, 3 and 4). For climate change stressors, I obtained data sets from several sources to show trends in the past oceanographic conditions and how they may vary in response to climate change. I then characterised the oceanography of the Gulf of California and adjacent waters. My assessment is based on observed changes from 1960 to 2017, and projected changes. In the period from 1960 to 2017 two important phenomena that warm the sea surface water occurred; “El Nino” and “El Blob”. The latter is a phenomenon related to a warm mass of water as a result of high levels of atmospheric pressure and of which origin is detected in the Gulf of Alaska in 2013. The name “Blob” echos the 1958 horror film which describes a character that keeps growing as it consumes everything in its path just as this warming event did (Cornwall, 2019). The “El Blob” was detected until several months later 2013, so it is unknown whether “El Blob” can occur again with the same or higher intensity. The other timescales are based on projected changes by 2055 and by 2099 using low (2.6), medium (4.5) and high (8.5) emissions scenarios from the RCP (representative concentration pathway) family. Because of a temperature gradient in coastal waters increasing from north-western Mexico to southwestern Mexico (Chapter 2), I established ten contiguous ‘subregions’ in these waters (Chapter 4). This allowed me to evaluate the risk associated with the attribute 'distributional flexibility' of the chondrichthyan species and to determine thermal tolerance range categories as follows: all waters (AW), cool waters (CW), warm waters (WW) or Gulf of California water (GoCw). These categories provided a basis for projecting how chondrichthyan distributions might change in response to climate change. I identified a total of 54 species of sharks, 48 species of rays and 4 species of chimaeras, which belong to 3 superorders, 12 orders, and 33 families. Based on the thermal tolerance range indicated by the current presence-absence of each species in the subregions, a total of 35 chondrichthyan species are distributed in all Mexican waters (AW), suggesting the species are adapted to the full range of temperatures currently occurring in Mexican waters. The majority of these are commercial shark species and these are the least likely species to redistribute out of Mexican waters as waters warm progressively northward as climate change progresses. A total of 31 species were classed CW (i.e., favouring cooler waters) and likely to reduce their distributional range northwards as Mexican waters warm in response to climate change. The majority of these are also commercial shark species. On the other hand, 34 species of chondrichthyans were classed WW (i.e., favouring warm waters), and are likely to expand their distribution northwards within Mexican waters. The majority of these are ray species, some of them of commercial importance. One species of shark, one species of ray and one species of chimaera are distributed only in the GoC waters, and another species of shark and two species of rays are distributed in only inside and outside the GoC in the adjacent MP-C subregion. The ecological groups (developed for all three regions) are shelf-inshore, shelf-reef, shelf-sand (<75 m), shelf-sand (75–150 m), pelagic waters and bathyal (>150 m). A total of 46 species were allocated to the ecological group ‘shelf-sand (<75m)’, 14 species were allocated to the ecological group ‘shelf-sand (75–150 m)’, and 22 species to the ecological group ‘pelagic waters’. Some of these species are demersal and others swim near the bottom or may swim up in the water column. A total of 19 species of chondrichthyans are in the ecological group ‘bathyal (>150 m)’, one species is in the ecological group ‘shelfinshore’, and 4 species were allocated to the ecological group ‘shelf-reef’. Vulnerability risk varies among the current chondrichthyan species, among ecological groups and among fishing and climate change stressors. For total vulnerability to fishing stressors, there were 10 species in the GCI and GCE regions, and 40 species in the MPW region at medium vulnerability risk. I determined 33 species in the GCI and GCE regions, and one species in the MPW region were at high vulnerability risk. For climate change (CC) stressors in the whole of western Mexico, a total of 15 and 10 species were at medium vulnerability risk under the medium and high emissions scenarios, respectively, and 10 species were at high vulnerability risk under the high emission scenario. The species allocated in the EG shelf-sand (<75 m) are highly vulnerable to the combination of fishing and CC stressors in all three regions for all the CC scenarios. In contrast, the species allocated in the EG bathyal (>150 m) are at low vulnerability but varies for species allocated to the other EGs.
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    Molecular Tool Development For Gene Characterisation and Phylogenetic Inference in Fungi
    Urquhart, Andrew Stewart ( 2019)
    Fungal species impact humans in many areas, some positively and others negatively. Some fungi are agents of disease in plants or animals, yet others find diverse beneficial uses in industry and food production. A greater understanding of fungal biology is a pressing requirement because it will allow us to ameliorate the negative effects of certain species and enhance currently beneficial interactions, as well as to identify new uses for fungi. With this in mind, this thesis has focused on the development of new molecular tools and approaches that will improve capabilities for gene characterisation and phylogenetic inference in fungi. This work has extended across several species including the canola pathogen Leptosphaeria maculans, the heat tolerant ascomycete Paecilomyces variotii and the species in the order Mucorales. In L. maculans I utilised novel tools including CRISPR-Cas9 to identify pathogenicity genes. After evaluating the efficiency of identifying pathogenicity genes using a combination of RNA-sequencing based prediction and CRISPR-Cas9 targeted disruption of putative pathogenicity genes, I turned to a more conventional approach using T-DNA mutagenesis and forward genetics to screen for mutants with altered pathogenicity. I paired this with whole genome sequencing to identify T-DNA integration events, and in this way identified three new pathogenicity genes, one encoding a Sit4 Associated Protein (SAP), one encoding a flavoprotein, and one encoding a heat repeat protein. In Paecilomyces variotii I developed all the tools required to work effectively at the genetic level. These include two genome sequences and techniques for transformation, targeted gene disruption and sexual crossing. Using these tools, I then examined interesting aspects of the biology of this organism including discovering Repeat Induced Point (RIP) mutation for the first time in the Eurotiales and uncovering the genetic basis for the biosynthesis of the secondary metabolite viriditoxin. In the final chapters of this thesis I describe some of my work uncovering diversity among Australian Mucorales species. This has included the discovery of a new species of Pilaira, a new species of Syncephalastrum and a comprehensive examination of the genus Backusella.
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    Speciation and secondary contact in a colourful agamid, Ctenophorus decresii
    Dong, Caroline Mei-Xu ( 2019)
    Colour polymorphism, the co-existence of multiple heritable colour morphs within an interbreeding population, is thought to promote rapid phenotypic evolution and speciation. This is based on the importance of colour signals in reproductive isolation in combination with the underlying genetic architecture of polymorphism, where morphs are predicted to be governed by few genes of major effect. This prediction is supported by empirical data and stems from how colour morphs often differ in suites of co-adapted traits. During secondary contact between populations that differ in morphs, there is expected to be a high probability of genetic incompatibilities between morphs due to a breakdown of adaptive genetic correlations. Furthermore, colour signal divergence may also be accompanied by changes in behaviour and/or mating preferences leading to incompatibilities between populations which differ in morphs. These factors together may facilitate the formation of reproductive isolation and ultimately lead to speciation. In this thesis, I investigated divergence and the outcome of secondary contact between lineages of the tawny dragon, Ctenophorus decresii, which differ in morph number and type. Ctenophorus decresii is a sexually dimorphic agamid lizard endemic to South Australia, and comprises two genetically distinct and geographically structured lineages: northern and southern. I tested for differences in colour vision between the lineages, which differ in a sexual signal, male throat coloration, particularly in the absence or presence of ultraviolet (UV) reflectance. The northern lineage is colour polymorphic with four discrete throat morphs which lack significant UV reflectance: orange, yellow, orange-yellow (orange centre surrounded by yellow), and grey. Southern lineage males are monomorphic with blue throats and a strong UV reflectance peak. Male throat coloration is an important intraspecific sexual signal, as it is emphasised in territorial and courtship displays. I investigated whether lineages differ in visual sensitivity to UV wavelengths by measuring retinal opsin protein expression of four cone opsin genes (SWS1, SWS2, RH2, LWS) using droplet digital PCR. I found that lineages did not differ in gene expression of the four opsins and discussed this in the context of conserved visual sensitives in terrestrial systems. The lineages meet in a contact zone where multi-locus genetic data suggested the presence of hybrids and potential barriers to gene flow. Using extensive field surveys, male phenotype data, genomic single nucleotide polymorphisms (SNPs), and a mitochondrial (mtDNA) marker, I investigated the outcome of secondary contact between the lineages. Furthermore, I captive-bred pure and first generation (F1) hybrid offspring to characterise colour traits independent of exogenous selection. I found that the contact zone is narrow and several generations old with no parental forms or F1 hybrids present. The northern mtDNA haplotype was prevalent in hybrids, and there were high frequencies of backcrossing to the northern lineage but not to the southern lineage, indicating genetic incompatibilities. The northern throat polymorphism was maintained, without any loss of morphs, whereas the southern throat morph was absent. This contrasted with the more intermediate throat phenotype of captive-bred F1 hybrids, particularly in ultraviolet reflectance, suggesting strong selection for the northern throat phenotype within the contact zone. The viability and fitness of F1 hybrids have consequences for contact zone dynamics, and ultimately whether species boundaries are eroded or maintained. I performed pure and reciprocal cross F1 hybrids in a laboratory setting and measured parental reproductive traits and offspring fitness traits. I found that northern females have a higher reproductive output with more, larger clutches per breeding season and lower embryonic mortality. Although pure and hybrid offspring did not differ in individual fitness traits, hybrids produced from a combination of northern females and southern males exhibited higher fitness in more categories (i.e. growth rate, bite force, sprint speed). These factors in combination may contribute to the prevalence of northern lineage mtDNA haplotypes in the contact zone. Finally, I taxonomically separated the northern and southern lineages of C. decresii sensu lato on the basis of differentiation in morphology and male coloration, genetic divergence with restricted gene flow, and geographic structuring. This revision results in C. decresii sensu stricto (previously southern lineage) and C. modestus (previously northern lineage). I evaluated morphological traits of the type specimen of Amphibolurus modestus (Ahl 1926), previously a synonym of C. decresii sensu lato, and determined that it represented a specimen of the northern lineage. Therefore, I formally re-instated and re-described Ctenophorus modestus (Ahl 1926). The addition of this species to the C. decresii species group, which now comprises six species, supports the notion that geographic divergence in male coloration is an important component to speciation in this group.
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    A metabolic engineering approach for iron and zinc biofortification of bread wheat (Triticum aestivum L.): impacts on plant growth, grain nutrition and food processing
    Beasley, Jesse Taylor ( 2019)
    Human iron (Fe) and zinc (Zn) deficiencies are among the most prevalent nutritional disorders in the world and manifest as a range of health issues including fatigue, impaired cognitive development and increased mortality. Micronutrient supplements and fortificants are frequently used to increase human Fe and Zn intakes yet these strategies require continuous investment and frequently miss rural populations; improving the density and/or bioavailability of Fe and Zn in staple crops (a process known as biofortification) represents a powerful alternative. Bread wheat (Triticum aestivum L.) is cultivated on more land than any other crop and is processed into a range of food products to supply ~20% of the daily calories consumed by humans. The wheat grain is mostly comprised of starch and protein, with micronutrients such as Fe and Zn concentrated in the outer aleurone layer of the grain. In the aleurone layer, Fe and Zn are complexed to compounds that inhibit their absorption (bioavailability) in the human gut and the aleurone layer is removed during grain milling to produce white flour. White flour (representing the inner wheat endosperm) contains low concentrations of dietary Fe and Zn, and high consumption of either wholemeal flour or white wheat flour coincides with high prevalences of human Fe and Zn deficiencies. Generating Fe and Zn biofortified wheat through conventional breeding in modern wheat cultivars is hindered by inherently low grain Fe and Zn concentrations and a lack of genetic variation for these traits. Nicotianamine (NA) is a low-molecular weight metal chelator present in all higher plants with high affinity for Fe2+, Zn2+, and other divalent metal cations. In graminaceous plant species such as wheat, NA serves as the biosynthetic precursor to 2’-deoxymugineic acid (DMA), a root-secreted mugineic acid family phytosiderophore that chelates ferric iron (Fe3+) in the rhizosphere for subsequent uptake by the plant. Both NA and/or DMA are the major chelators of Fe within white wheat flour, and NA is known to enhance Fe bioavailability in cereal grain. For these reasons, increasing the biosynthesis of NA/DMA through upregulation of nicotianamine synthase (NAS) genes has emerged as a popular strategy for Fe and Zn biofortification of cereal crops. In this study we employed constitutive expression (CE) of the rice (Oryza sativa L.) nicotianamine synthase 2 (OsNAS2) gene in bread wheat to upregulate the biosynthesis of NA and DMA, and evaluate plant growth, grain nutrition and food processing properties of CE-OsNAS2 wheat. Our lead CE-OsNAS2 wheat transgenic event (CE-1) demonstrated higher concentrations of Fe, Zn, NA and DMA in wholemeal flour, white flour and white bread, altered distribution of Fe in the grain, and higher white flour Fe bioavailability relative to null segregant (NS) control. Protein composition, dough rheology and breadmaking properties were similar between CE-1 and NS white flour, and a chicken (Gallus gallus) feeding study over a period of six weeks demonstrated that chickens consuming CE-1 white flour had improved Fe status, intestinal morphology and microbial populations relative to chickens that consumed NS white flour. Multi-location confined field trial (CFT) evaluation over three field seasons demonstrated no differences between CE-1 and NS agronomic performance apart from plant height. Throughout all CFTs, grain yield was negatively correlated with grain Fe, Zn, and protein concentrations yet not correlated with grain NA and DMA concentrations. White flour Fe bioavailability was positively correlated with white flour NA concentrations, and we determined NA to be the strongest enhancer of in vitro Fe bioavailability identified to date. Together these results suggest the proportion of Fe that is chelated to enhancers of bioavailability (such as NA and DMA) should be prioritized in future crop biofortification efforts and highlight new strategies for developing Fe and Zn biofortified wheat as a more nutritious staple food.
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    A comparison of the inferential, computational, and predictive performance of joint species distribution models
    Wilkinson, David Peter ( 2019)
    The standard correlative species distribution model accounts for the effect of the environment on species distributions without explicitly accounting for the effect of species interactions. Community ecology, in contrast, studies species co-occurrence patterns without accounting for the co-occurrence that could be explained by the shared response of species to the environment. Joint species distribution models (JSDMs) are a relatively recent development in the ecological literature that extend the single species distribution model framework to model multiple species simultaneously while accounting for species co-occurrence, and are an exciting prospect for bridging the gap between these two disciplines. Research into JSDMs is still in its early stages as a field and we have identified six outstanding problems in the literature that are potentially hampering the wider uptake of JSDMs by the wider ecological community. The confluence of statistical and computational advancements has led to the rapid development of JSDMs, and the proposal of several models and implementations. These models are statistically complex but, while well defined as stand-alone studies, are described using a diverse array of model notation, terminology, and symbols. This often conflicting notation makes comparing the different JSDM implementations a daunting task to most ecologists who are trying to identify which model is best suited to their purpose. In this thesis I develop and present a clearly-defined, singular notation for the description of JSDMs and use it to elucidate the similarities and differences between seven different JSDM implementations. All of the newly proposed JSDM implementations have been presented on completely different datasets to each other and thus any measure of inferential performance is not directly comparable. Without a direct comparison potential practitioners are unable to make an informed decision about the performance of these models. In this thesis I conduct a direct comparison of seven JSDM implementations on six datasets to assess their inferential performance. I found that all JSDMs identified similar species-environment relationships to each other. All JSDMs identified species co-occurrence patterns in the same direction but with different strengths and uncertainties. The newly proposed JSDMs have been implemented using a variety of software with different default or suggested parameters for model fitting. In addition to being fit to datasets of a varying size it is difficult to directly compare the computational performance of different implementations. Potential practitioners are going to be influenced by factors such as how fast a model can run and the size of dataset it is capable of feasible fitting to. In this thesis I perform a direct comparison of seven JSDMs on six datasets to directly assess their computational performance. I found a greater difference in computational performance between JSDMs than for inferential performance. I found evidence that scaling issues due to the size of datasets, and thus the number of parameters to estimate, was more prevalent for some implementations than others. A comparison of effective sample size in their respective Markov chain Monte Carlo regimes also indicated that some implementations are far more computationally efficient than others. The use of JSDMs for prediction has only recently begun to be addressed in the literature, but has almost exclusively focussed on environment-only prediction types akin to those of single species models. The multivariate nature of JSDMs, however, allows for new, community-level predictions to be used. To date none of these prediction types have a formal definition for JSDMs. In this thesis I present four types of prediction that can be applied with JSDMs. Marginal predictions are environment-only predictions that do not account for the residual associations between species. Joint predictions are a community-level prediction that can return either a probability of observing a particular assemblage or generate a series of plausible assemblages at a site. These two prediction types can then be conditioned upon the known occurrence states of one or more species at a site, and thus present conditional marginal and conditional prediction types respectively. Single-species models have been subject to substantial research into the evaluation of their prediction, but this has seen minimal to date for JSDMs. In this thesis I present five classes of evaluation metrics that assess different aspects of species distributions and the community assemblage process. Threshold-independent and threshold-dependent metrics operate at the species-level, community dissimilarity and species richness metrics operate at the community-level, and likelihood-based metrics which assess model fit. The literature on JSDM prediction has to date been limited in its comparisons of predictive performance. Studies have either compared a limited number of models, a subset of evaluation metrics, and/or generally only considered environment-only prediction types. In this thesis I present a comparison of predictive performance for six JSDMs and two stacked single-species models. I fit the models to 22 real and simulated datasets, predict with the four prediction types I have defined for JSDMs, and evaluate these predictions with up to 32 metrics from five classes. I found that likelihood-based metrics suggested the JSDMs were better fit to the data but that the other metric classes generally showed them to underperform compared to the standard stacked single species model for all prediction types. The stacked single species model with the SESAM constraint was found to consistently outperform all other models. This suggests an interesting avenue of future research by applying this constraint to JSDM predictions.
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    The long-term consequences of island arks for endangered species and recipient communities
    Jolly, Christopher James ( 2019)
    The strategy of conserving threatened species away from mainland threats on offshore ‘island arks’ is particularly common in Australia and New Zealand but has been used worldwide to conserve a broad range of taxa. This strategy, however, has consequences for both the species being conserved and the recipient community. The effects of invasive species can be complex, and the assisted colonisation of species to islands—a species invasion of sorts—could cause a myriad of unintended and unpredictable consequences, for both the introductee, and its recipient community. In this thesis, I set out to examine the consequences of ‘island arks’ as a conservation measure for both the endangered species being conserved and the recipient island community into which it is introduced. To do this, I exploit the introductions of an endangered marsupial predator, the northern quoll (Dasyurus hallucatus), to a number of ‘island arks’ in the Northern Territory, Australia. Northern quolls have suffered dramatic recent declines throughout northern Australia due to the invasion of a toxic invasive cane toads (Rhinella marina). In 2003, to prevent their extinction in the Northern Territory, insurance populations of quolls were established on two toad- and predator-free islands (Astell and Pobassoo) off North East Arnhem Land. In 2017, we established a new ‘island ark’ population of toad-smart quolls on Indian Island, near Darwin. These ‘island ark’ populations provided fertile ground to explore the consequences of island isolation on quolls (Astell Island) and also the impacts quolls have as a novel predator on an ‘island ark’ (Indian Island). In my first data chapter (Chapter 2), I document an unsuccessful reintroduction of northern quolls from Astell Island to southern Kakadu National Park on the Australian mainland. Although quolls that were trained to be ‘toad-smart’ survived longer than quolls that received no training, the reintroduction ultimately failed because of predation by dingoes (a native top-order predator). The aim of this study, and of my entire PhD at the time, was to determine whether toad-aversion training could instil multi-generational recovery from toads in northern quolls. The failure of this reintroduction due to predators, rather than cane toads, motivated a change in perspective and direction. I began to question whether the conservation of quolls on a predator-free ‘island ark’ may have resulted in unintended maladaptation for mainland reintroduction. Indeed, a follow up study (Chapter 3) determined, that after only 13 generations isolated on this ‘island ark’, quolls did not appear to recognise the scent of dingoes and cats; predators with which quolls had coevolved alongside on the Australian mainland for at least 3500 and 130 years, respectively. Unlike their isolated island conspecifics, wild-caught and captive-born mainland quolls (from populations with continuous exposure to predators) both recognised and avoided the scent of cats and dingoes. I also found (Chapter 4) that using instrumental conditioning to re-establish antipredator behaviours in ‘island ark’ conserved quolls was not straightforward: training protocols that were logistically and ethically feasible did not work, suggesting that the protocols were inadequate or that it is difficult to train individuals that have totally lost predator recognition. A conservation introduction of quolls to an additional island (Indian Island) then provided a unique opportunity for a detailed investigation of the direct and indirect impacts of an introduced novel predator on a recipient ‘island ark’ community. In Chapter 5, I first establish some basic properties of the system: that behaviour of the prey species is both repeatable, and not correlated with their detection rate. This is important given that individuals are assumed to have homogenous detection probabilities in most population estimation models. And in Chapter 6, I document a trophic cascade driven by quolls that elicits shifts in both population size and behaviour of naive prey (grassland melomys). After the arrival of quolls on Indian Island, the survival and abundance of grassland melomys (Melomys burtoni) rapidly declined, and behavioural traits of populations invaded by quolls changed. Although quoll-invaded melomys populations remained consistently more neophobic than quoll-free populations, boldness in quoll-invaded melomys converged with that of quoll-free populations through time. Quoll-exposed melomys populations exhibited lower per-capita seed take rates, and rapidly developed an avoidance of seeds associated with quoll scent, with discrimination playing out over a spatial scale of tens of metres. My study of this ‘island ark’ provides a rare insight into the rapid ecological and behavioural shifts enacted by prey to mitigate the impacts of a novel predator and shows that trophic cascades can be strongly influenced by behavioural as well as numerical responses. Globally, we face a rapidly accelerating extinction crisis. In many cases in situ conservation is difficult, if not impossible. Isolationist conservation measures, where threatened species are removed from the threatening process—captive populations, conservation fences, and ‘island arks’—are often necessary to halt the extinction of the most critically endangered species. We must, however, undertake these actions with a long-term plan, and with awareness of potential consequences. Central to such considerations is the phenotype: we need to move beyond population size as a sole monitoring criterion. The value of more quolls, for example, is dramatically undermined if increased population size is associated with a shift towards maladaptive phenotypes. Similarly, the trophic cascade that results from the introduction of a new predator is not driven solely by the predator’s demographic impact, but also by the behavioural shifts in prey resulting from that impact. Phenotypes, particularly behavioural phenotypes, can change rapidly in response to conservation actions. We would be wise to use that knowledge, or risk unanticipated consequences.
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    The quantitative genetics of insecticide resistance in Drosophila melanogaster
    Battlay, Paul ( 2019)
    While understanding insecticide resistance in Drosophila melanogaster is informative for controlling pest insects that threaten agricultural yields and vector deadly diseases, it also serves as a powerful model of microevolution which can be interrogated with an exceptionally powerful genetic toolkit. The Drosophila Genetic Reference Panel (DGRP) provides the opportunity to study population-genetic signatures of natural selection in individuals that can be repeatedly measured for a range of phenotypes. In this work, genomic and transcriptomic data from the DGRP are compared with phenotypes from nine insecticidal compounds against the background of genome-wide signals of selection. The two most prominent signatures of selection in the population are attributable to insecticides from a single, widely-used chemical class, the organophosphates. Evidence suggests that insecticide-based selection is limited to these two loci, however the genetic bases of insecticide phenotypes appear to be complex. Insecticide-associated variation includes both structural effects through amino acid substitution and chimeric gene formation, and regulatory effects on transcript abundance by cis- and trans-acting factors. Resistance mechanisms exhibiting pleiotropic effects on insecticides from different chemical classes is found to be rare; one such case is correlated with constitutive, modular regulation of oxidative stress-related transcripts, the genetic basis of which is mapped to multiple trans-acting factors. Comparisons of the results from the DGRP with diverse population genomics data suggests that the outcomes of these analyses are applicable to populations of D. melanogaster worldwide.
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    Computational biology methods for identifying leaderless secretory proteins in Arabidopsis thaliana and other plant species
    Lonsdale, Andrew Gregory ( 2019)
    Leaderless secretory proteins (LSPs) are proteins that are secreted yet lack the classical canonical signal peptide sequences and, therefore, by definition are undergoing unconventional protein secretion (UPS). We cannot necessarily assume all such proteins found in plant secretomes are LSPs due to the high possibility of cellular contamination arising from cellular disruption, leading to a mix of LSPs and contaminant proteins that are both characterised by the absence of signal peptides. The aims of this Thesis are to use computational biology methods to identify LSPs. In Chapter 1 the current knowledge of secretory pathways (LSPs and UPS) in plants, motifs for secretion, the difficulties of isolating the plant secretome (cell wall/apoplastic fluids) without contamination, and the lack of appropriate bioinformatics tools for plants to distinguish them from LSPs is reviewed. Chapter 2 evaluates a commonly used computational tool, SecretomeP which was trained on mammalian data and is the most widely used prediction tool for LSPs, including in plant studies. Exploring whether this tool is applicable to plants required using conventionally secreted proteins as a proxy, and evaluations were made on SecretomePs premise that conventional and unconventional secretory proteins will share properties. By removing the signal peptide from sequence data, the research shows a bias in scores due to the signal peptide, and only a marginally higher true positive rate compared to false positives. The use of the tool on further plant studies was not recommended and suggested previous inferences of plant LSP status based solely on SecretomeP predictions needed to be re-evaluated. This work was published as ”Better Than Nothing? Limitations of the Prediction Tool SecretomeP in the Search for Leaderless Secretory Proteins (LSPs) in Plants” (Lonsdale et al., 2016) Chapter 3 details the creation of a putative LSP database for Arabidopsis thaliana by taking the entire proteome and applying a workflow of collating annotation, literature observation and experimental relationships between proteins. This results in a framework to identify proteins without signal peptides that have been observed (unclassified set) or unobserved (non-secreted set) and compare them to conventionally secreted proteins that have been observed (secreted set) or unobserved (theoretically secreted sets). Protein-protein interactions, GO term and PFAM distributions that are similar between the secreted and unclassified protein sets are used to create confidence lists of putative LSPs. In Chapter 4 new prediction tools were created. Firstly, a SecretomeP-like tool is created using the properties of the observed secreted set, with signal peptides removed. Lessons from Chapter 2 on SecretomeP allowed the bias to be minimized. Secondly, tools were created based on the candidate list from the putative LSP database. Each tool is based on a Random Forest (RF) using protein-derived features and trained on subsets of the LSP database. Consensus predictions between them on new data was used to identify further LSP candidates. Additional reporting tools provide a convenient way to map data from the LSPDB onto new sequences, and the results of these tools on LSPs from plants and other organisms shown. In Chapter 5 additional putative candidates for LSPs in Arabidopsis and other species were identified by applying the tools and databases to additional data excluded from the original database created in Chapter 3, including recent cell wall proteomes, secretory pathway experiments and analysis of extracellular vesicles. In conclusion, Chapter 6 discusses the limitations of the computational methods developed, and suggestions for improvement to predict LSPs in plants for further experimental investigation and confirmation of location.
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    Predicting pest issues from common and curious pests of crop seedlings in south-eastern Australian
    Douglas, Joshua Heath ( 2019)
    Over fourty species of invertebrate pests can be pests of emerging crop seedlings in south-eastern Australia. Some species are a common and widespread issue for farmers, while others only sporadically cause damage. The inability to predict potential pest problems is a key reason why insecticides are commonly applied to fields prior to sowing (applied as seed treatments or bare-earth sprays) and/or post-sowing (foliar sprays) in a prophylactic manner. This thesis investigates factors which predict the risk of pest problems arising from two common pests and two emerging sporadic pests of crop seedlings. The common pests are the earth mites, the redlegged earth mite, Halotydeus destructor and the blue oat mite, Penthaleus destructor. The emerging pests are the Portuguese millipede, Ommatoiulus moreleti and the common pillbug, Armadillidium vulgare. These species are a curious problem as they generally feed on decaying plant matter and have only recently been recognised as emerging pests. Sampling was conducted to assess the capacity to predict the abundance of the damaging autumn generation of the major pest mites, H. destructor and P. major, at a field level. Across the fields sampled, abundances of both mites showed limited association with a range of common agronomic and environmental field variables of known biological importance. The abundance of H. destructor could however be divided in to risk categories when fields were grouped in to categories of field type. These categories were valid across two years and two farming regions. The abundance of P. major, by contrast showed a regional association. The first pest step in understanding the pest status of O. moreleti and A. vulgare was to understand their ability to damage common crop seedlings. Under shadehouse conditions, this study found O. moreleti has a limited ability to feed on a range of crop seedlings. A. vulgare can damage a wide range of crops, although some crops are only susceptible in the first days of seedling establishment. This finding was supported by pest reports from fields across southern Australia over the past decade. Lupinus angustinus was the most susceptible crop seedlings for O. moreleti. This appears to be due to the removal of deterrent chemicals in commercial breeding as well the thickness or strength of leaf tissue. The fitness benefits of feeding on seedlings appear to vary between crop seedlings. In controlled studies, the level damage was found to be influenced by the lifestage and sex of the individual, while the presence of crop stubbles as alternate food sources were not found to influence the level of damage in controlled studies. To understand the role of water stress on the pest status of A. vulgare, I conducted controlled trials on the influence of dry environmental conditions on the level of feeding damage A. vulgare caused to canola. I hypothesised water stress would result in individuals increasing their feeding on plants, as they searched for water. Conversely, I found individuals kept in environments with low ambient humidity caused less damage. Field monitoring observations were made over the course of the thesis to provide the basis for further research on the population dynamics of O. moreleti. While stubble is known to be important in influencing population sizes, I also found evidence that soil-type has an important effect on O. moreleti numbers. Interestingly, abundances were found to vary greatly between years in some crop fields. This appears to be due to seasonal population dynamics, with O. moreleti leaving fields and, in some cases, not returning. The research conducted in this thesis points to ways to guide monitoring and sustainable management practices. Farm managers should use the association of damaging abundances of H. destructor with field-type to predict pest risk at a farm level. The research on A. vulgare and O. moreleti helps to explain why these species are a sporadic pest risk, given they are limited in their ability to damage crop seedlings. This knowledge will assist in the development of pest management programs for O. moreleti and A. vulgare. The studies on the association of environmental and agronomic factors should be used to guide future research to understand the many remaining knowledge gaps.