School of Agriculture, Food and Ecosystem Sciences - Theses

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    Stormwater runoff retention and tree growth in passively irrigated street tree systems
    Hanley, Paul Anthony ( 2023-11)
    Urbanisation creates extensive impervious surface cover which alters natural hydrological cycles. Impervious surfaces generate large volumes of stormwater runoff, which degrades receiving waterway ecosystems when conventionally drained. To protect urban streams, runoff volumes need to be significantly reduced to restore pre-development flow regimes. Street trees have considerable potential to increase the demand for stormwater, by transpiring large volumes of water if irrigated with runoff via ‘passive irrigation’. Passive irrigation systems can also benefit trees by reducing drought stress and increasing growth and therefore providing shading and cooling benefits. However, lack of knowledge on system design and tree species selection is preventing widespread uptake of passive irrigation systems for street trees. This thesis aimed to identify the drivers of runoff retention, tree growth, water use and drought response, to inform the design of and tree species selection for passive irrigation systems. Runoff retention and tree growth were quantified for alternative system designs with different inlet types and storage volumes in the field. Using this data, runoff retention was also modelled for a range of soil exfiltration rates, climates and storage sizes. Tree water use, drought response and growth were assessed in a glasshouse study to inform species selection in relation to system storage. In the field, systems with inlets designed to exclude sediment captured less runoff. However, the exfiltration rate of the surrounding heavy clay soil ultimately limited runoff retention. Therefore, inlet selection will likely be driven by maintenance requirements and cost, rather than runoff retention. However, where storage volume was large relative to the contributing catchment area, or where exfiltration rates were faster, runoff retention was substantially greater. Passively irrigated trees in the field grew faster than control trees; however, this was likely due to trees having both adequate drainage, to avoid waterlogging, as well as an internal water storage. In the glasshouse study, trees with an internal water storage and low stomatal sensitivity showed lower drought induced leaf loss compared to those without, whereas trees with high stomatal sensitivity and an internal water storage showed lower drought stress and recovered rapidly after drought. This thesis demonstrated that passive irrigation systems have significant potential to reduce runoff volume entering waterways. However, large storage volumes will be required to facilitate exfiltration in heavy-textured soils. Passive irrigation systems can improve tree growth when waterlogging is avoided and internal water storage provided, which will likely increase evapotranspiration, runoff retention and canopy growth in the future. As per other stormwater control measures, maintenance requirements must be considered during design and greater oversight during construction is required to ensure systems perform as intended. Designs need to flexible and adapt to local soil and climate conditions. Matching tree species, or more accurately, tree water use strategies, to system design is required to ensure systems maintain function in future climates.
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    The influence of fire mosaics on insectivorous bats: From genes to communities
    Lo Cascio, Amanda Maria ( 2023-11)
    Australia is one of the most fire-prone countries in the world, with many ecosystems adapted to historical fire regimes. However, fire regimes are shifting, and significant changes to historical patterns of fire are recognised as a considerable threat to biodiversity. Inappropriate fire regimes have been linked to population declines of mammals across Australia. Despite this there are significant knowledge gaps in understanding how different components of the fire regime effect biodiversity, at different levels of biological organisation. This research examined the distribution and ecology of echolocating bat species (commonly referred to as microbats) in a fire-prone region of south-eastern Australia, to answer key questions of wider relevance to other fire-prone ecosystems. I explored the influence of the spatial pattern of different fire histories in the landscape – fire mosaics – on different levels of biological organisation, to draw inference on how fire-generated mosaics might affect the distribution of bat communities, individual species, populations, and genetic diversity. The research aims of this thesis were explored using a landscape scale field study, in the temperate forests and woodlands of south-western Victoria, Australia, which collected two types of microbat data. The first, an acoustic survey by means of passive acoustic detectors of 136 sites, spanning a range of fire histories, conducted over two seasons. The second a genetics study of 146 sites, also with a range of fire histories, over two seasons, which captured 647 individual bats. Passive acoustic detectors are often used to monitor echolocating bat species. However, identification of calls collected at large scales is hindered by substantial variation within and between species, and the considerable time investment needed to manually identify acoustic data. A pilot study designed to confirm the range of species present in the study area, along with the level of sampling needed to address the research aims, confirmed that the acoustic signature for many species overlapped. This meant that existing approaches for call identification would not be suitable for either automated or semi-automated identification of species from acoustic data. Therefore, as a first step, I developed a new method that allowed for much improved identification of species with overlapping call structures. This improvement then allowed for a semi-automated call identification approach, important for analysing large volumes of acoustic data collected across landscape scales. I built a machine learning classifier (Random Forest) from field collected data, to better differentiate acoustically overlapping species. The method improved overall classification success, including a 60% improvement for bats that navigate in open spaces (Chapter 2). The classifier was used to identify to species, a dataset containing 687,377 recordings over 1,632 detector nights collected at 136 sites. The results were used to model responses of species relative occurrence and specie richness to fire mosaic variables (Chapter 3). In Chapter 3, I determined how the amount, diversity, and configuration of fire influenced species richness and the relative occurrence of 13 individual species. Sites were primarily stratified to represent a range of fire age-classes: recently burnt (0-3 years post fire), early successional (4-10 years), mid successional (11-34 years) and late successional (>34 years). I built regression models for 13 species and species richness against different measures of the fire mosaic across six spatial scales (500 m – 5 km). Bat species richness responded positively to the diversity of fire age-class at all spatial scales, as did 9 out of 12 species, at one or more scales. Models of individual species responses to fire diversity indicated that the scale at which fire is measured can be important. The amount of a fire age-class was also an important determinant of relative occurrence for five species over a range of scales. Contrasting responses to fire configuration, displayed by closely related species, revealed that even subtle differences in wing morphology can contribute to differing responses of otherwise similar species. Next, I determined the influence of the fire mosaic on the genetic structure, connectivity, and diversity of two ecologically different species (Chapter 4). High resolution genetic data was derived from tissue samples collected from 280 individuals across 71 sites. This research employed emerging techniques in landscape genetics, to identify genetic variations among individuals within populations of two ecologically distinct species. I used a multi-step analytical approach. Firstly, for both species, a spatial admixture model was employed to establish likely ancestral populations. Secondly, these ancestral populations were then incorporated as random factors in Generalized Linear Mixed Models (GLMMs) to explore the correlation between genetic distance (indicative of genetic connectivity) and a range of fire metrics representing gradients of spatial patterns in fire history, availability of woodland habitat, and spanning six scales. Finally, GLMMs were used to determine the connection between individual genetic diversity and the same fire metrics across these six scales. High resolution genetic research yielded insights on the interplay between species' genetic patterns and the fire mosaic. The phylogenetic structure of Chalinolobus morio uncovered in this study supported the presence of male and female philopatry, a notable finding considering that such philopatry is rare among mammals. Conversely, the phylogenetic structure of Vespadelus vulturnus, coupled with decreased genetic connectivity and diversity, indicated that external constraints related to the fire mosaic likely disrupt the connectivity of habitat for this species. In summary, this research developed a new approach to surveying and monitoring echolocating bats species at large spatial scales. The approach is flexible and applicable to acoustic surveys more broadly. I quantified the influence of the spatial pattern of fire on insectivorous bats to define fire mosaics that benefit bat conservation. Areas of long unburnt vegetation were found to be important for several species. Importantly, the configuration and diversity of fire age-classes were also important drivers, in addition to the amount of habitat. Specific to this landscape patchy burns at the current scale of management will promote bat diversity. Specific to individual species conservation, this study found that maintaining ‘enough’ of the extent of an age-class to support roosting and foraging habitat varied among species. Genetic signatures uncovered differences between individual habitat selection and muti generational gene flow, important for the persistence of populations in the face of changing climates. Moreover, variation in the spatial scale or buffer zone that produced the strongest models highlighted the variety of ways that bat species perceive and interact with the landscape. This thesis highlights how this knowledge can be used to improve fire managed landscapes for conservation. This research frames the response of occurrence and genetic data to ecological understanding of species responses, and by doing so is applicable more generally to other fire managed ecosystems.
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    Understanding the mechanisms that underpin animal responses to fire
    Santos, Julianna Leticia ( 2023-11)
    Fire is a key ecological and evolutionary process that shapes biodiversity patterns worldwide. However, changes to fire patterns are among the most significant threats to biodiversity. Understanding how animals respond to variations in fire regimes is critical for addressing biodiversity loss and creating opportunities for effective conservation management. The overarching aim of this thesis was to develop a new understanding of the mechanisms underpinning animal responses to fire regimes. To do this, I first developed a demographic framework for classifying mechanisms by which inappropriate fire regimes drive declines in animal populations. I then applied this framework in Australian-wide systematic reviews of research papers and policy documents to elucidate how inappropriate fire regimes are driving declines of Australian mammalian and reptilian taxa threatened with extinction. Finally, I conducted field studies in semi-arid ecosystems in southern Australia to investigate how variation in the temporal and spatial characteristics of fire shapes abundance and genetic diversity of small mammals and reptiles. Through systematic reviews, I found that inappropriate fire regimes threaten 88% and 43% of Australian threatened mammals and squamates, respectively. Across mammals and reptiles, inappropriate fire regimes were primarily characterised by intense, large, and frequent fires, mainly through their impacts on survival rates shortly after fire. I also found that several species are threatened by a lack of fire. Low fire frequency was linked to mechanisms that impact survival or reproductive success, indicating that some species are not getting the ‘right kind of fire’. Predation by introduced species, climate change and extreme weather, and weed invasion were documented or predicted to interact with fires and exacerbate mammalian and reptilian declines. By focusing on processes that are relevant to animal populations, the demographic framework that I developed can help diagnose causes of population declines in ecosystems that experience fire and help examine the consequences of alternative management actions. I collected field data on animal abundance and genetic diversity at 58 sites that varied in the temporal and spatial dimensions of fire. I employed non-linear regression to investigate the influence of fire mosaics on abundance and genetic diversity of two Australian mammals – an insectivorous marsupial, mallee ningaui (Ningaui yvonneae), and an omnivorous rodent, Bolam’s mouse (Pseudomys bolami) – and two Australian squamates – the ground-dwelling mallee military dragon (Ctenophorus fordi), and the fossorial southern sandslider (Lerista labialis). Empirical modelling indicated that the temporal and spatial dimensions of fire influence animal abundance and genetic diversity in different ways. For example, the abundances of the mammal P. bolami were linked to sites surrounded by diverse post-fire age-classes, while the abundance of N. yvonneae was correlated with the amount of mid-to-late stage vegetation (>11 years since fire). The abundance of C. fordi was associated with mid-stage vegetation (25 to 50 years since fire), while L. labialis was more abundant in late-stage vegetation (>75 years since fire). However, both reptile species also occurred in recently burnt areas (<10 years since fire). Exploring both abundance and genetic data revealed new insights into animal associations with pyrodiversity. Genetic diversity of N. yvonneae and C. fordi was positively associated with fire frequency, indicating that fire may actually contribute to gene flow throughout animal populations. Overall, these results support inferences that maintaining mid and late-stage vegetation would result in high abundances for different species. However, small-scale burns could boost movement and gene flow in the landscape. This thesis demonstrates how mechanistic approaches help improve the understanding of relationships between fire and biodiversity. The demographic framework I developed connects changes in animal populations to fire-regime characteristics, offering valuable insights for exploring conservation actions and policies. The field studies I conducted unveiled novel perspectives on how temporal and spatial dimensions of fire influence abundance and genetic diversity of animals and the kinds of fire mosaics that contribute to animal conservation. Fire regimes influence animal survival, reproduction and movement in many ways, and more research into species ecology is needed to address the global biodiversity crisis. Ultimately, examining connections between changes in animal ecology and evolution and the characteristics of fire regimes will promote conservation actions that address causes of biodiversity loss.
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    The role of genetic variation and post-translational modification of casein proteins: Understanding the interplay of cow genetics, protein structure and function
    Hewa Nadugala, Barana Rangana Abeysinghe ( 2024-02)
    Casein is a heterogeneous mix of four major proteins identified as alphas1-casein, alphas2-casein, beta-casein, and kappa-casein. All caseins in bovine milk are present as genetic variants and some are further complicated by post-translational modifications, specifically phosphorylation and glycosylation. Evidence suggests that both genetic variants and post-translational modifications affect protein structure. However, the role of casein genetic variation and post-translational modifications in the functional properties of casein is not fully understood. The effects of glycosylation on protein-protein interaction in purified kappa-casein have been investigated through amyloid fibril formation using unglycosylated (UG) and twice glycosylated (2G) kappa-casein B. The role of genetic variation and glycosylation of kappa-casein in interfacial and coagulation properties has been investigated through whipping, foaming, and rennet-induced coagulation of bovine milk. Results showed that both kappa-casein (AA, AB, BB) and beta-casein (A1A1, A1A2, A2A2) genetic variants have little impact on the whipping and foaming properties; however, the kappa-casein B variant demonstrated a heightened rate of curd firming and final curd firmness without affecting the rennet coagulation time. Glycosylation increases the amyloid fibril formation rate, foamability, rennet-induced coagulation time, and decreases the whipping performance of skim milk. Differences in protein secondary structure caused by the attachment of glycans within the kappa-casein molecule are believed to lead to differences in surface activity, spread and packing of protein at the liquid-air interface and hinder enzymatic action.
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    Genetics and genomics of myrtle rust resistance in Eucalyptus globulus Labill
    Runa, Fatima Akter ( 2023-08)
    Myrtle rust poses a substantial threat to the Myrtaceae rich ecosystems and dependent industries around the world. This disease is caused by the fungal pathogen Austropuccinia psidii Beenken, which has a wide range of hosts in Myrtaceae. This risk is particularly high in Australia, where most native ecosystems contain significant Myrtaceae floristic elements, comprising 88 genera and 2,253 species across the continent. In Australia alone, myrtle rust has approximately 400 host species. As a result of the myrtle rust incursion in Australia in 2010, species loss has been observed, while the broader ecological consequences are still unfolding. Several economically important industries such as nurseries, essential oil production, the national forest industries, and the wood product supply which are predominantly based on eucalypt species, are under imminent threat. Breeding for disease resistance is considered the only reasonable mitigation response. It requires extensive phenotypic characterisation of germplasm and dissection of trait architecture at the genomic level to enable strategic selection decisions. Eucalyptus globulus is a native Australian species that is naturally distributed in the islands of Tasmania and South-Eastern Australia. It is also an economically valuable plantation species, making up over half of the national hardwood plantation estate (over 442,000 hectares in the year 2018-19). This thesis aims to investigate the genetic and genomic architecture of myrtle rust resistance in Eucalyptus globulus and its suitability for molecular breeding. About 8,514 breeding-origin individuals were thoroughly characterised by generating a large progeny trial. The components of the myrtle rust resistance trait were dissected at the phenotypic level, and their heritabilities were estimated using the Linear Mixed Effect Model and the Generalised Linear Mixed Model. This study found a high (0.53) narrow sense heritability estimate for the categorical myrtle rust resistance trait indicating its suitability for breeding. A basic Genomic Prediction study was conducted on 3,615 breeding-origin individuals using 0.85 million genome-wide distributed markers, applying the Bayesian statistical program BayesR3 to estimate the predictive ability and assess the suitability of this advanced form of molecular breeding for this trait. High predictive ability (average: 0.60) was observed, implying that genomic selection for myrtle rust can increase breeding efficiency by eliminating the need for expensive and time-consuming progeny trials. A Genome-Wide Association Study (GWAS) was conducted with 1,791 breeding and native-origin individuals to dissect the trait architecture at the genomic level using the Bayesian statistical program BayesR3. Genome-wide highly associated regions were identified for the components of myrtle rust resistance, validating the previously identified major QTLs in Eucalyptus spp. Additionally, possible genetic mechanisms are discussed based on the functional annotation of the positional candidate genes.
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    Wheat grain protein content assessment via plant traits retrieved from airborne hyperspectral and satellite remote sensing imagery
    Longmire, Andrew Robert ( 2023-11)
    Wheat (Triticum spp.) is crucial to food security. The source of a major proportion of humans’ total dietary carbohydrates and protein, it is among the world’s most widely grown crops and receives concomitantly large quantities of nitrogen (N) fertiliser. Wheat grain protein content (GPC; %) is a key to food quality, determining the baking quality of bread, the cooking quality of pasta, and the nutritional value of food products. For these reasons, wheat is classified and growers are typically paid predominantly on the basis of GPC, setting its farm income value. Global population growth encourages a justified focus on increasing yields. However, because grain proteins are diluted by carbohydrate (CHO) additions in the latter part of growing seasons, GPC is in an inverse relationship with yield: Improved yields are attended by the risk of reducing GPC. Moreover, GPC is influenced by interacting genetic and agronomic factors, soil properties and weather conditions that affect crops’ physiological status and stress levels and can therefore exhibit great spatial variability. Of the vast quantities of nitrogen (N) applied to wheat crops, a variable but substantial proportion is lost, inducing environmental damage and financial costs, which should be averted. Accurate GPC prediction could reduce N losses, assist in crop management decisions, and improve farm incomes. Nitrogen is central to proteins and can be strategically supplied to crops in order to achieve GPC benchmarks a precision agriculture (PA) approach. In such scenarios, estimates of GPC potential in advance of harvest could guide fertiliser dosing, improving fertiliser efficiency and potentially reducing costs. In contrast, where strategic fertiliser applications are not favoured, crop management could benefit from prior knowledge through strategic harvesting aimed at maximising payments per unit of grain at receival. However, GPC is a complex variable, influenced by multiple plant traits, themselves affected by soil and moisture conditions and whose effects change through the growing season. While remote sensing (RS) is likely the only practicable method of estimating GPC during seasons, and shows potential, prediction is complex and success has been limited. To make progress, it is necessary to more robustly identify imaging spectroscopy-based physiological traits closely associated with GPC. Traits with known physiological links to GPC, and which can be retrieved from imaging spectroscopy, include leaf area index (LAI) and chlorophyll (Ca+b). Further inspection of these and other RS traits may advance research relevant to PA. The inverse relationship of GPC to CHO assimilation permits the hypothesis that indicators of plant stress can improve GPC estimation. Such stress indicators, including the pigments anthocyanins and carotenoids, can be accurately retrieved along with other biophysical and biochemical quantities from hyperspectral (HS) remote sensing but their relationship to GPC had yet to be tested. Solar-induced fluorescence (SIF), emitted from the photosystems in proportion to instantaneous photosynthetic rate, was also untested as a GPC predictor. Moreover, in addition to the traits themselves, retrieval of plant traits by inversion of radiative transfer models (RTM) also remained untried for GPC estimation. Finally, the crop water stress indicator (CWSI), a proxy for evapotranspiration and hence carbon assimilation, should also show an association with GPC. Because a large majority of GPC studies have been conducted exclusively in the context of experimental plots, it is appropriate to extend research into the commercial cropping domain, populated to date by only two previous studies. This expansion is facilitated by the recent advent of spatially explicit GPC monitoring during crop harvests. While lacking the ultra-high spectral and spatial resolution of airborne HS sensing, satellite RS, in particular the Sentinel-2 (S2) platforms, possess advantages with respect to broadacre PA. These include a focus on reflectance bands adapted to vegetation sensing, appropriate spatial resolution, and frequent return times. This thesis presents results from piloted HS flights and ground campaigns at two dryland field experiments with divergent water supply and wide-ranging N fertiliser treatments, and from HS flights over 17 commercial fields planted to either bread (T. aestivum L.) or durum (T. turgidum subsp. durum (Desf.) Husn.) wheat, across two years in the southern Australian wheat belt. Imagery was acquired with airborne hyperspectral and thermal sensors, with spatial resolutions of approx. 0.3 m and 0.5 m for experimental plots and 1 m / 1.7 m in commercial fields. Leaf clip measurements, leaf and grain samples were collected from plots and through a transect in one field. In commercial fields, ~40,000 records obtained from harvester-mounted protein monitors. CWSI, SIF, vegetation indices and PRO4SAIL RTM inverted parameters were retrieved for each plot and GPC record location. Sentinel-2 (S2) timeseries (TS) were subsequently acquired for > 6,000 ha of commercial dryland wheat fields, inclusive of those included in HS campaigns, also in south-east Australia and through two consecutive years of dissimilar rainfall. In this case, growers provided ~92,000 GPC data points from harvester-mounted protein monitors. For each, Ca+b, leaf dry matter, leaf water content (Cw) and LAI were retrieved from the S2 images by radiative transfer model inversion. A gradient boosted machine learning algorithm was applied to analyse these traits’ importance to GPC and to predict GPC in 30% of samples unseen by the algorithm in training. From HS analyses, the photochemical reflectance index (PRI) related to xanthophyll pigments was consistently associated with GPC at both leaf and canopy scale in the plots and transect. In the commercial crops, a gradient boosted machine learning algorithm (GBM) ranked CWSI as the strongest indicator of GPC under severe water stress, while SIF, PRI and inverted biochemical constituents anthocyanins and carotenoids were consistently important under more moderate growing conditions. Structural parameters inverted from HS were not prominent except under severe drought when CWSI was omitted from models. Statistically significant results were obtained for GPC estimation in unseen samples, with best relationships between predicted and observed GPC of R2 = 0.80 and RMSE = 0.62 in a model built with thermal and physiological traits obtained from the HS and thermal imagery. Trait importance in S2 analyses was consistent with that seen from HS, in that the rankings of physiological, structural and water stress indicators were aligned: severe drought increased the importance of water stress measures relative to other traits, but in milder conditions physiological traits were emphasised. Airborne SIF added substantially to model skill from single-image S2, particularly in moderate conditions. While coefficients of determination varied substantially according to water stress, error metrics invariably sat within a tight range, under 1 % GPC. Overall, these predictive modelling results, obtained at within-field scale and in challenging conditions, place the current study among others in the same research domain, most of which consider either plot or regional scales. The strongest relationships between predicted and observed GPC (R2 = 0.86, RMSE = 0.56 %), in a model built from five S2 images across a season, were better than those from single-date hyperspectral (HS). In severe water stress, LAI was the main predictor of GPC early in the season, but this switched to Cw later. In milder conditions, importance was more evenly distributed both through the years and between traits, and predictive skill was lower. S2 TS had a clear accuracy advantage over single-date S2, and approached that of HS, especially in benign conditions, emphasising its previously unexplored potential for large-scale GPC monitoring. The methods developed are a novel contribution and can be proposed as a useful basis for future research.
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    Flow and geomorphic drivers of instream plants and their biogeomorphic role in riverine ecosystems
    McKendrick, Scott Alexander ( 2023-12)
    Streams are important ecosystems providing multiple benefits to both biodiversity and humans. Despite their importance, many streams are severely degraded globally, driven by anthropogenic impacts such as flow regulation, urbanisation and channelisation. Instream vegetation is a critical component of the stream ecosystem providing many benefits to biota such as provision of habitat and refuge, primary production and nutrient cycling. Instream plants also act as ecosystem engineers, impacting sediment, propagule and organic matter transport and deposition. Despite their importance, many gaps exist in our understanding of the flow and geomorphic drivers of instream plants, and their biogeomorphic role. Field surveys, glasshouse trials and an experiment were combined to investigate questions related to identifying the flow and geomorphic drivers of instream vegetation, and how instream vegetation interacts with propagule and sediment transport. First, a range of streams were surveyed for instream vegetation and geomorphic components, with further geomorphic complexity and flow metrics calculated. Relationships were then investigated between the metrics and amphibious and aquatic vegetation. I then ran an experiment to assess propagule bank and sown seed emergence under a range of flooding durations and frequencies to assess relationships between flow regime and early plant recruitment. Finally, two glasshouse studies were undertaken to assess different preferential deposition locations for propagules, fine sediment and organic matter and the potential for emergent and aquatic plants to act as ecosystem engineers. More frequent flood events with a steeper rate of rise (flashier flows) were negatively associated with amphibious vegetation outcomes but less so for aquatic species. Greater geomorphic complexity, including less bank incision and more stream width and depth variation, were positively associated with instream vegetation outcomes, however, increasingly flashy flows reduced these benefits. More frequent, short flood events also reduced plant recruitment from propagules, however, effect sizes were small, suggesting a range of species may recruit under flashy flows provided other factors are suitable (e.g. refuge from high flow velocity). Greater geomorphic complexity and instream vegetation patches were also associated with more propagule, fine sediment and organic matter deposition, although bare bank samples were also highly retentive. Building on the previous study, emergent vegetation and aquatic vegetation both trapped more propagules, fine sediment and organic matter compared with non-vegetated stream locations. Importantly, however, this trapping function diminished from rural to urban streams. The findings from this thesis suggest that geomorphic complexity promotes instream vegetation outcomes, at least partially through greater deposition of propagules in a range of channel locations. Further deposition of fine sediment and organic matter likely improves recruitment of instream plants. Flashy flow regimes need to be addressed, however, if increasing instream vegetation is a priority in stream restoration, likely through various stormwater control measures. My findings also provide evidence for the importance of instream vegetation on propagule, fine sediment and organic matter deposition. Combined, these results highlight the biogeomorphic importance of instream plants, with their potential to trap propagules, fine sediment and organic matter leading to biogeomorphic succession and driving stream morphodynamics. Both passive and active revegetation approaches may be used to promote the benefits of instream plants, but further research is required. Ultimately, my research highlights the importance of instream vegetation and how to effectively restore instream plants to promote biogeomorphic processes that aid in process-based stream restoration.
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    Spatially analysing tree crown growth in cities: modelling progress towards canopy cover targets and sensitivity to rainfall gradients
    Rettondini Torquato, Patricia ( 2023-10)
    Urban forests can play a significant role in mitigating some of the negative impacts of urbanization. Thus, canopy cover targets are becoming increasingly important for cities, to maximize the benefits of trees in urban environments. To meet these targets, selecting tree species that can thrive in the city is important, especially in the face of climate change. Climate- and trait-based approaches for selecting urban tree species are increasingly common as global datasets become freely available, but the logic of their selections are rarely validated. Validating these approaches could involve measuring tree crown growth in cities to assess species' suitability for future planting. Species-specific growth models can facilitate comparisons among species and cities located across environment gradients. Furthermore, these models can be used to predict urban forest canopy cover development and the time needed to reach set targets. This thesis spatially analysed remote sensed urban forest crown polygon data with georeferenced tree inventory data to identify individual tree crown growth in new residential areas of Melbourne. Specifically, I aimed to i) develop species-specific growth models and assess growth rate differences among species and between rainfall zones; ii) test climate- and trait-based approaches for species selection; and iii) predict canopy cover in a residential precinct over a 30-year period. Species-specific models were developed for the 20 common street tree species in two distinct rainfall zones. Species showed four different growth responses at 10 years after planting based on average crown area and sensitivity to rainfall: Fast and consistent growth; Fast but sensitive growth; Slow and consistent growth; Slow and sensitive growth. Urban forest managers can use this information to identify tree species to plant in drier or irrigated (passive or active) areas to better achieve canopy cover targets. The measured crown growth sensitivity to rainfall was used to examine i) the relationship with climate metrics based on occurrence data extracted from a global database and an urban tree database; and ii) with trait-based metrics as indications of stress tolerance strategies. Metrics derived from climate- and trait-based metrics were found to be weak predictors of tree crown growth sensitivity in these two areas of Melbourne. Finally, tree crown growth models were applied to three planting scenarios, based on the number of trees planted in the streetscapes and parks of a typical new residential precinct over a 30-year period. Results show that although canopy cover can be improved by prioritising the planting of more large trees, canopy cover target cannot be achieved in new residential areas. This thesis highlights the significance of developing not only species-specific growth models but also zone-specific growth models to improve urban tree canopy cover prediction accuracy. Further, results indicate limitations of climate- and trait-based approaches, emphasizing the need for a more comprehensive assessment of species vulnerability in urban areas. These methods can be replicated for a wide range of species, climates, and site conditions. By increasing our knowledge of species-specific growth patterns, we can develop more effective approaches to urban tree selection and canopy expansion in changing climates.
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    Early life-stage nutrition and its effects on growth, immune competence, and metabolic characteristics of the developing dairy cow
    Ockenden, Emma May ( 2023-08)
    The primary objective of dairy heifer rearing is to produce resilient replacement cows with a high milk production potential. Early life nutrition is widely understood to affect development of physiological systems in all species; it is therefore essential that effective calf rearing strategies are in place to ensure a productive and profitable dairy industry. The research detailed in this thesis evaluated the effects of different pre- and postweaning nutritional strategies that lead to parameters linked to superior resilience of Holstein-Friesian dairy cows. Growth, Immune competence, and metabolic characteristics were compared with the use of repeat immune challenges in dairy replacement heifers reared under various pre- and postweaning nutritional strategies from birth until 20 months of age. Results indicate a positive influence of accelerated preweaning nutrition on growth and the immune development of dairy cows, and therefore do not support the current industry feeding practices.
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    The mechanisms through which fire shapes plant life cycles in heathlands
    Plumanns Pouton, Ella ( 2023-11)
    Fire is a key driver of plant diversity, and many plants have adaptations that help them thrive in fire–prone ecosystems. However, changes to fire activity threaten thousands of plants worldwide. To understand the future of plant populations under fire regime changes, empirical research on fire’s influence on demographic processes is required. This thesis explored how patterns of fire influence plant species across their life cycle, from seeds to mature life stages, and how this relates to plant functional traits. I examined a Mediterranean-type heathland ecosystem as a case study, to examine the mechanisms through which fires impact plants at different life-stages, including those that take place above and below ground. I established 57 study sites in Gariwerd, southeastern Australia, which has experienced substantial variation in fire history. First, I investigated whether knowledge of plant traits can be used to make robust predictions for how fire influences plant relative abundance. I deductively assigned species to plant functional types, based on their persistence traits, establishment capacity, and the timing of key life stages, and made a priori predictions on how relative abundance changes as a product of time since fire. Using empirical data I collected on species relative abundance, I then built nonlinear models to test species’ model conformity to a priori predictions for plant functional types. Predictions of the direction of changes in relative abundance (increase or decrease from 0-81 years since fire) were correct for 18 of 24 species modelled. Predictions of the shape of changes in relative abundance were not as accurate, but still useful: 13 out of 24 species showed ‘excellent’ conformity with shape predictions, 7 ‘good’ conformity, and 4 ‘poor’. This suggests plant functional types can be used to generalise fire responses across species that share similar traits, and thus inform fire management and biodiversity conservation. Second, I examined how fire severity and time since fire interact to influence plant maturity. I collected data on the proportion of plants that had reached reproductive maturity at a site. I used this field data, alongside satellite-based fire severity mapping, to build non-linear models of plant-fire relationships. The results indicated that the proportion of mature plants was influenced by time since fire, regardless of fire severity. For example, for Banksia marginata, the proportion of mature plants increased from 13% (1-year post-fire) to 58% (15 years post-fire), and maturity of this species showed minimal variation between low and high severity fire. Interestingly, no relationships were observed between time since fire and the relative abundance of plants. That is, only when plant life stages were considered, did I detect an effect of fire on plants. Ecological studies that distinguish between plant life stages will help to predict the impacts of fire on populations and enhance decision-making. Third, I investigated how time since fire and mean fire interval influence canopy seedbank production, based on a suite of plant traits. I surveyed all individual plants with canopy cones present at each of the 57 study sites. On each mature individual, I measured plant height and width, and counted the number of cones. I sampled a subset of these cones across individual plants, and then germinated them in a laboratory trial. I used regression models to explore the relationship between fire frequency and variables relating to different aspects of canopy seedbank production. The interval between fires influenced canopy seedbank production and viability. For example, no canopy cones were observed on plants at short mean fire intervals: such as fire intervals more frequently than every 18 years for the obligate seeder tree Callitris rhomboideia. Quantifying the fire intervals which supports canopy seedbanks provides a new understanding of an important above ground process and helps to determine how frequently to burn ecosystems containing serotinous species. Last, I examined how time since fire and fire frequency influence the occurrence of different species in the soil seedbank and, again, examined ecological relationships through the lens of plant traits. I sampled the soil seedbank at 57 sites, treated soil samples with heat and smoke product to promote germination, and grew seedlings in a germination trial lasting 14 months. I used non-linear modelling to explore relationships between fire and species occurrence. Fire frequency influences the occurrence of species in the soil seedbank, and the nature of these relationships depends on plant traits such as plant and seed longevity. For example, frequent fires (every <15 years) will reduce the occurrence of herbaceous species with long-lived seed. However, for other types of plants, such as perennials with short-lived seed, I observed no relationship between fire and soil seedbank occurrence, demonstrating many species have soil seedbanks resilient to frequent fires. Overall, my research advances understanding of how fire impacts different species and groups of plants across their life cycle. Notably, a mix of field research, laboratory studies and empirical models provide evidence that the traits of plants can be used to identify how fire affects species in the soil and canopy seedbanks, and as juvenile and mature plants. By examining plant life stages above and below ground, this work also helps to define the fire regimes that support plants in the heathy woodlands of Gariwerd. Because it is based on mechanisms, I anticipate that the trait-based approaches I have developed and tested could be used to understand and predict fire-related changes in plant populations in a wide range of ecosystems.