School of Agriculture, Food and Ecosystem Sciences - Theses
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ItemModelling the biogeography of Australian Fungi( 2021)Biogeography – the study of biological patterns in space – has often overlooked the Kingdom Fungi in the past, because the geographic distributions of fungi are difficult to document and study. However, increasing availability of fungi data collected across large spatial scales, and development of modelling-based methods allowing the interpolation of patterns between sampled locations, have enabled for the first time the study of continental scale mycogeography (biogeography of fungi) using quantitative methods. Focusing on Australia, this thesis explores this new research direction in detail, by accessing fungi distribution data at continental scales, interrogating the issues and characteristics of such data and developing appropriate ways to deal with them, and studying the prominent biogeographic trends and patterns emerging from the data using the species archetype modelling approach. This thesis has several major findings. First, for studying continental-scale mycogeography, data based on observations and specimen collections are the most readily available, but contain errors in geocoordinates and taxonomy and require thorough quality filtering and taxonomic curation. The sampling effort of these data is incomplete in space and biased towards easier-to-access areas, and such biases need to be addressed in analyses. Methods for checking data quality and dealing with biases are proposed. Second, environmental DNA (eDNA) collections of fungi in the soil provide an important alternative source of data, but exploring these data in detail reveals that their spatial patterns are different from observational data on the same species, and archetypal patterns based on eDNA data can be biologically unrealistic, signalling issues in identifying sequences to species and in detection success. The need to better understand the caveats of eDNA data motivates future systematic side-by-side observational and eDNA surveys. Third, by using species archetype models to group species into archetypes according to their shared environmental responses, this thesis reveals several main archetypal distribution patterns across Australia. Specifically, spatial patterns of Australian fungi can be partitioned into those strongly aligning with the southeast and the southwest coastal regions, those occurring in the arid centre, and those occurring in either the dry or the wet tropical regions. These analyses produce the first continental scale quantitative maps linking fungi to regions, and provide important support for further research on these fungi. Finally, by applying the relatively new species archetype modelling approach on challenging datasets at a continental scale, this work produces a valuable methodological knowledge base on the use of the method, and identifies worthwhile directions for future development, such as developing new approaches for selecting the number of archetypes in the model. Overall, this thesis thoroughly explores and applies appropriate methods for processing data and recently developed analytical methods, and significantly advances knowledge on continental scale patterns of mycogeography. The knowledge produced by this thesis provides a foundation for further research in Australia, and demonstrates a novel approach for mycogeography suitable for applications across the globe.
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ItemEnvironmental filtering shapes plant turnover and species occurrence in post‐logging regrowth forest in southeastern Australia( 2021)Environmental factors play a more influential role in shaping plant community composition, while disturbance shapes plant community composition in southeastern Australian temperate forests. Plant communities in forests subjected to timber harvesting have been found to differ from wildfire sites in the montane forests of the Central Highlands in Victoria; however, a quantitative understanding of the factors that shape post harvesting plant communities is lacking. Quantifying the factors that shape plant community composition in post logging regrowth forest is important for understanding how timber harvesting influences plant biodiversity. Here, I aimed to explore the role environmental filtering species turnover and composition of the species in post logging regrowth forests. I focused my studies on the forested landscapes of southeastern Australia, where bushfires and timber harvesting are the primary catalysts for regeneration in Eucalyptus regnans, E. delegatensis, and high elevation mixed species forests. I investigated the post disturbance regeneration dynamics in these forests and sought to determine the direct impact of climate variability on regeneration and the interactive effects of climate, topography, and edaphic factors on the regeneration success of Eucalyptus. Untangling the roles of climate, topography and edaphic conditions on plant regeneration is important for understanding current and future risks of climate change to plant species richness. To test the influence of climatic, topographic, and edaphic variables on the occurrence and abundance of Eucalyptus regeneration, I used machine learning models. Declines in number of seedling regeneration of eucalypt during the period of drought were greater in E. regnans and E. delegatensis than HEMS forests, suggesting that regeneration in the HEMS forests is more resistant to drought. I furthermore found that seasonal precipitation and temperature had the greatest influence on regeneration success of Eucalyptus. My findings highlight the importance of seasonal and annual climate variability on Eucalyptus regeneration and portend potential declines in regeneration success in a warmer and drier future, particularly for E. regnans and E. delegatensis. A fundamental requirement of sustainable forest management is that stands are adequately regenerated after harvesting. To date most research has focused on the regeneration of the dominant timber species and to a lesser degree on plant communities. Relatively few studies have explored the impact of regeneration success of the dominant tree species on plant community composition and diversity. Therefore, I quantified the influence of environmental filtering on plant species diversity in montane regrowth forests dominated by Eucalyptus regnans in mainland southeastern Australia. I found that Acacia density shaped plant biodiversity more than Eucalyptus density. I also found that edaphic factors, in particular soil nutrition and moisture availability, played a significant role in shaping species turnover and occurrence. My findings suggest that the density of Acacia is a key biotic filter that influences the occurrence of many understorey plant species and shapes plant community turnover. This should be considered when assessing the impacts of both natural and anthropogenic disturbances on plant biodiversity. In this thesis, I also explore the role of soil seedbank as a source of plant propagules in these forests. Our ecological understanding of plant community response to disturbance and environmental variation is largely restricted to the above ground species pool. Plant community composition often changes dramatically after disturbance due to mortality of above ground vegetation and recruitment of species that respond to a change in resource availability. To quantify the relative importance of environmental gradients on individual species occurrence and community composition, I used a joint analysis approach. In total there were 113 plant species in the combined species pool. A total of 39 species were shared between above ground and soil seedbank pools. There were 41 species exclusive to the above ground vegetation. Aridity was the main environmental covariate explaining plant community across all pools of plant diversity and across non woody and woody life forms. Environmental covariates explained more than 59 percent of the variance for 43 species in the combined species pool. The composition of the soil seedbank and above ground diversity was distinct, with low similarity 14 percent, which highlights the importance of the soil seedbank as a reservoir for plant diversity not captured in above ground vegetation. Finally, I aimed to quantify the influence of Acacia and Eucalyptus composition and configuration on species turnover to provide an important tool for mapping patterns of plant diversity in post disturbance forests. To achieve this, I combined remotely sensed UAS imagery with ground survey data of plant composition from post logging regrowth forests. I found that spatial predictions of forest configurations providing Eucalyptus and Acacia cover metrics such as spatial aggregation were useful in estimating understorey plant beta diversity. Significant relationships between the aggregation metrics derived from UAS imagery as well as site aridity and beta diversity were observed. Increasing aggregation of Acacia, aridity and number of Acacia patches had a significant negative effect on plant beta diversity, whereas number of patches of Eucalyptus had a positive influence. This research highlights how remote sensing can provide and improve measures of forest plant biodiversity in regrowth forests which can support forest managers and conservation efforts to quantify and map patterns of plant diversity at the stand scale and beyond. Overall, my findings highlight that post logging regrowth forests are systematically shaped by soil and climatic factors while also being filtered by stand structure and composition. I demonstrate the role of climate, topography, soil, and light availability in shaping plant communities in post logging regrowth forests. The success of eucalypt regeneration in the stand reinitiation phase influences overstorey composition and structure. I found that that soil nutrition and moisture availability played a significant role in shaping plant community composition at fine scales and aridity at broad scales. I further found that Acacia density shaped plant biodiversity more than Eucalyptus density. My study highlights the role of environmental filtering on plant community composition in post logging regrowth and how it must be considered when assessing the impacts of anthropogenic disturbances on plant biodiversity in the temperate forest of southeastern mainland Australia.
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ItemInvestigation of bark properties and cambium cell viability of Eucalyptus in relation to heat exposure( 2021)Fire is integral to many temperate forest ecosystems. Given increasing occurrence of wildfires around the world, forest management applications such as low and moderate intensity burnings are required to reduce fuel loads to decrease the severity of wildfires. However, little is known about the effect of low to moderate intensity fires on vascular cambium necrosis in trees. During a fire, heat is transferred through the tree bark towards the vascular cambium (i.e., a vital tissue layer inside a tree stem which ensures the perennial growth of a tree) potentially increasing cambium temperature to lethal levels. As tree bark shields the vascular cambium from thermal damage, a better understanding of the bark traits that protect the vascular cambium during fires is required. Genus Eucalyptus is broadly distributed in fire-prone ecosystems thus, exhibits different fire adaptive traits such as post-fire regeneration strategies (i.e., resprouting via epicormic strands) and has a wide range of different bark types. As a native plant genus and the dominant species in open forests of southern Australia, Eucalyptus species present a great opportunity to investigate bark properties in relation to cambium cell viability. In this study, firstly, cambium sections were exposed to heat treatments in vitro to determine the best method to estimate a cell viability index (CVI) to allow a detailed investigation of heat degradation of cellular function in relation to fires. A tetrazolium reduction method (TTC method) was compared to a Neutral Red method applied to different tissue sizes to quantitatively determine CVI and to derive a critical temperature threshold for cambial cell viability in vitro (Chapter 2). The interactive effect of temperature and exposure time on cambium cell viability in vitro was investigated in the third Chapter. Based on findings of Chapters 2 and 3, properties of the bark i.e., bark thickness, moisture content, bark density, thermal diffusivity, and thermal conductivity of the three Eucalyptus species of contrasting bark types (E. obliqua - stringy bark, E. radiata - Fibrous bark and E. ovata - Smooth bark) were investigated in Chapter 4. In Chapter 4, stem sections of freshly felled trees were exposed to a fixed heat flux which simulated conditions of low to moderate intensity fires; thermocouples were inserted into sapwood, cambium and bark to measure the temperature and time to reach critical temperature of 60oC was recorded. Cell viability was measured against the untreated control samples. Bark properties of three species were measured and analyzed against cell damage. The key results of this study were: (i) Tetrazolium reduction method (TTC method) is the preferred method to assess cell viability of Eucalyptus species, while Neutral Red method can be used to cross check the results of the TTC method; (ii) Critical temperature for cambium cell viability is 60oC; (iii) A prolonged exposure to sublethal temperatures (40-50oC) causes similar effect as a short exposure to lethal temperatures (>50oC); (iv) Critical exposure time in-vitro for cambium cell viability of Eucalyptus species is 1-5 minutes; (v) Bark moisture and thickness play the major roles in regulating heat transfer through bark; (vi) A thicker, dryer, lower density and lower thermal conductivity stringy bark of E. obliqua shows greater insulation ability than the other two bark types tested; (vii) Critical exposure time for cambium cell viability in-vivo may vary between 20 to 40 minutes depending on bark type and bark thickness; (viii) Among the trees tested the radiant energy required for the cambium-phloem cells to reach critical temperature ranged between 3.5 and 13.6 MJ m-2; (ix) Prolonged exposure to low heat flux like 10 kW m-2 can also cause significant cambium damage. Findings of this study have provided significant insights in relation to properties of tree bark, to better understand the heat tolerance levels of Eucalyptus species during low to moderate intensity fires. The study developed a novel method to assess the cambium cell viability of Eucalyptus species following heat exposure. Overall, this study provides a better understanding for land managers to perform low intensity fuel reduction burns to avoid tree damage. Findings of this work will guide and expand future research on stem heat transfer models and fire behavior models to improve tree survival following fires.
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ItemFactors influencing consumer response to wet and dry-aged mutton( 2021)Mutton is the term used to describe the meat from older ovines (older than 2 years); this meat is considered to have inferior eating quality when compared to lamb and as a result returns to producers are reduced for mutton animals. The sheepmeat industry seeks to improve returns for mutton, and the application of dry ageing to mutton is proposed as a post mortem intervention that will add value. As dry aged mutton is a novel product, the consumer response to this product is largely unknown. To assess the viability and feasibility of dry aged mutton products, this thesis investigated the retail opportunity for dry aged mutton from the perspective of the consumer, producer and foodservice. The thesis also developed understanding of the influence of ageing method and meat quality factors on consumer eating quality assessment and liking, as well as the extrinsic consumer related factors affecting consumer response to dry aged mutton. These investigations leveraged both qualitative and quantitative consumer methodologies, with the overarching aim of developing insights that would address knowledge gaps in the developing dry aged mutton supply chain. A cross cultural study comparing responses to sheepmeat from Asians (export market consumers) and Australians (domestic market consumers) found these groups assess meat quality differently; Australians rely on labels, are sceptical of provenance stories and prefer Australian product. Asian consumers make quality assessments based on visual attributes and find provenance stories compelling, but they were not particularly compelled by the “Australian made” label. These findings indicate different marketing strategies are required for the two markets. For both consumer groups the recommended channel for dry aged mutton products would be foodservice or retail butchers as these outlets take away the uncertainty associated with purchasing and preparing an unfamiliar product. The development of dry aged mutton dishes in collaboration with chefs followed by consumer assessment of the dishes for liking, premiumness and fit to foodservice outlet demonstrated that these products were well liked by consumers, could be considered premium, and that dry aged mutton was a versatile product that suited a wide range of foodservice outlets ranging from casual to fine dining. An ageing trial lasting 8 weeks and comparing wet and dry aged mutton leg and loin found that yield was reduced in the dry aged treatment as opposed to the wet aged, and that these losses increased with ageing period. There was opportunity to mitigate yield losses by selecting carcases that were heavier, had increased levels of subcutaneous fat, and by fabrication of retail cuts from dry aged primals. Consumers (n=540) assessed the eating quality (tenderness, juiciness, liking of flavour and overall liking) of the longissimus thoracis et lumborum (LTL) and semimembranosus (SM) derived from the ageing trial according to MSA sensory protocols (total sample n = 3240). No differences in consumer ratings were found due to ageing method but extending the ageing period beyond 14 days improved eating quality for both muscles. Consumers most often graded LTL as “better than every day quality” and they were willing to pay (WTP) 36.60 AUD/Kg for this grade, SM was most often graded as “good everyday day quality” and WTP was 26.90 AUD/Kg. These prices were similar to current Australian retail pricing for lamb, and if mutton can achieve these prices, it would be a significant price uplift. The ageing trial result of “no effect of ageing method on eating quality” was unexpected. A check all that apply (CATA) investigation into the consumer characterised flavour profile of wet and dry aged mutton confirmed that consumers can differentiate ageing treatments; dry aged mutton was associated with increased caramel and roasted flavours while the wet aged mutton was associated with increased sheepy and metallic flavours. Further subsequent investigations into the consumer related factors affecting the eating quality assessments of the MSA ageing trial indicated that consumers could be segmented according to their liking for mutton. Agglomerative hierarchical cluster analysis revealed 3 consumer clusters; Cluster 1 (n = 219) appreciated mutton and rated it highly, Cluster 2 (n = 235) found mutton acceptable and Cluster 3 (n =79) did not like mutton. Preference maps were prepared for the three clusters; all three clusters were found to prefer LTL over SM, but Cluster 1 demonstrated a preference for dry aged mutton over wet aged, Cluster 2 had no ageing method preference and Cluster 3 preferred wet aged mutton over dry aged mutton. Characterisation of these clusters indicate that consumer familiarity with mutton and ethnicity has a role to play in the observed preference patterns. The thesis concludes that dry aged mutton has value as a premium niche product targeted at those consumers who appreciate mutton, and that there is an opportunity for mutton in local and export markets (not dry aged) that warrants further industry exploration, especially for the LTL which has good eating quality.
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ItemUsing data mining to improve the prediction of key nitrogen loss from terrestrial ecosystems( 2021)Nitrogen (N) losses through nitrification, denitrification and nitrate leaching in terrestrial ecosystems reduce fertiliser N use efficiency (NUE), affect environmental quality and human health. In the past 50 years, many individual studies both on-site and in laboratories have been carried out to investigate N loss from different pathways. However, field measurements of N dynamics are generally time-consuming, expensive and some of the processes are quite difficult to measure. Process-based models have been developed to better understand the complex, multivariate and unpredictable N cycling by integrating soil, environmental and management factors. However, the performances of these models are restricted by data availability, inconsistent responses of N loss to key drivers, difficulty of parameter derivation and limited capacity of larger scale simulation. To address the limitations of process-based models, improve the prediction and simulation of N losses, increase NUE and environmental quality, comprehensive databases of N loss from different pathways were compiled by data mining, advanced machine learning models were developed to reflect the linkage between N loss pathways and soil, environmental and climatic conditions on global scale. The research reported in this thesis quantified the nitrification rate (Rnit) and the fraction of nitrous oxide (N2O) from nitrification (fN2O_nit), denitrification and associated N2O, dinitrogen (N2) production, the contribution of N2O from autotrophic nitrification, heterotrophic nitrification and denitrification and nitrate (NO3-) leaching, investigated the key drivers of N loss from each pathway, performed global performed accurate global prediction of nitrification rate and the fraction of N2O from nitrification, NO3-N leaching with fewer input variables using data mining, machine learning models and 15N tracing experiment. Findings include: Data mining and machine learning were integrated to predict R_nit and fN2O_nit. According to the compiled global database on Rnit and fN2O_nit, the average potential Rnit in the topsoil was 1.4 kg N ha-1 d-1, and fN2O_nit was from 0.004 to 9.19% (average 0.46%). The machine-learning based stochastic gradient boosting (SGB) model outperformed three widely used process-based models in estimating R_nit and N2O emission from nitrification by using the same input variables. SGB technique was then applied for global prediction of Rnit and fN2O_nit with only a few input variables (R2 = 0.76 and 0.55, respectively). The potential Rnit was driven by long-term mean annual temperature, soil C/N ratio and soil pH, whereas fN2O_nit by mean annual precipitation, soil clay content, soil pH, soil total N. The global fN2O_nit varied by over 200 times (0.006-1.2%), it should be adjusted according to edaphic and environmental conditions when used in process-based models or global climate models in projecting N2O emissions. A global assessment of soil denitrification rate, N2O/(N2O+N2), and their driving factors and mitigation strategies was conducted based on 225 studies (3367 observations). N loss through denitrification varied greatly across land uses and climatic regions with an average of 0.25 kg N ha-1d-1. The average emission factor of denitrification (EFD) was 4.8%. The wide range of N2O/(N2O+N2) (mean: 0.33) demonstrated that the adoption of a fixed ratio in some process-based models for estimating N2 emissions from denitrification is not suitable. N2 loss accounted for 67% of total denitrification. N loss as N2, although harmless to the environment, deserves more attention from the perspective of improving NUE. Soil denitrification rate was significantly related to soil WFPS, NO3- content and soil temperature and soil oxygen (O2) content. N2 emissions were significantly correlated with latitude, WFPS, soil mineral N and soil oxygen content. Soil oxygen content, NO3- content, organic C, C/N ratio and WFPS were the key drivers of N2O/(N2O+N2) ratio. The meta-analysis showed that optimizing N application rates, using ammonium-based fertilizers compared to nitrate-based fertilizers, biochar amendment and application of nitrification inhibitors could effectively reduce soil denitrification rate and associated N2 emissions by 34-219% and 15-226%, respectively. These findings highlight that N loss via soil denitrification and N2 emissions cannot be neglected, and that mitigation strategies should be adopted to reduce N loss and improve N use efficiency. Our study provides a solid foundation to large-scale estimations of denitrification and the refinement of relevant parameters used in the submodels of denitrification in process-based models. The contribution of N2O production pathways and its driving factors in forest soils were investigated by global data analysis and an incubation experiment with 15N tracing technique in both Australia and worldwide. Based on 13 forest soils sampled within Australia, forest soils in temperate areas had the highest N2O emission rate (19.5 ug N kg-1 soil d-1), followed by subtropical and arid soils (3.84 and 3.80 ug N kg-1 soil d-1, respectively). Heterotrophic nitrification dominated N2O production in Australian forest soils; its contribution followed the order of arid (78%) > subtropical (69%) > temperate (59%). N2O from heterotrophic nitrification was negatively related to MAT and the contribution of heterotrophic nitrification to N2O production was negatively related to soil TN and TC. These results partially agreed with the global literature data synthesis, which showed that in addition to heterotrophic nitrification (42%), denitrification (43.5%) was also a key pathway of N2O production in global forest soils. Globally, soil pH, moisture content, total N content, total C content and MAT contributed to heterotrophic nitrification and denitrification to N2O production. A machine learning model (NLNO3 model) was developed based on a global literature-based database of NO3-N leaching from field experiments (1818 observations) to predict NO3-N leaching from agroecosystems. The NLNO3 model can reliably predict NO3-N leaching using a few easily accessible input variables (R2=0.75). According to the model estimation of NO3-N leaching, the global spatiotemporal pattern and hotspots were identified. The total NO3-N leaching in agroecosystems increased from 23.2 Tg N yr-1 in 1961 to 32.8 Tg N yr-1 in 2000 and 39.7 Tg N yr-1 in 2010. Hotspots of NO3-N leaching in agroecosystems expanded from Europe in 1961 to China, South Asia and Brazil in 2000 and 2010. The high spatiotemporal heterogeneity of NO3-N leaching was mainly driven by soil properties (soil TN, soil pH, soil texture), aridity index and farming practices (N fertilization and irrigation). Results of the present research demonstrate that the capacities of data mining in better understanding the complex N cycling in terrestrial ecosystems and informing potential mitigation strategies to reduce N loss. Data mining coupled with advanced machine learning methods could not only address the limitations of process-based models and improve model simulation performances, but also provide an alternative approach in predicting N dynamics at a larger scale.
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ItemEnhancing Environmental Benefits of Rainwater Harvesting Systems Using ‘Smart’ Real-Time Control Technology( 2021)Urban centres face numerous challenges related to the urban water cycle, including flooding, degradation of receiving waters, and scarcity of water resources. Among the stormwater control measures (SCMs) being increasingly adopted worldwide to improve the way stormwater is managed, rainwater harvesting (RWH) systems can potentially simultaneously address all of these issues. However, their performance has, until now, been limited by their passive and static nature, lacking the ability to adapt to changing conditions, such as rainfall variability, and climate and urban expansion. Recent advances in real-time control (RTC), so called “smart” technology, offer great promise to transform the conventional RWH systems into highly adaptive systems. To date however, little is known about the benefits of such technology in improving the performance of RWH systems. Understanding, testing and exploring this potential is the primary focus of my research. My thesis aims to develop and test RTC strategies that improve the simultaneous objectives of RWH systems related to water supply, flood mitigation and restoration of more natural flow regimes. This analysis is undertaken at a range of scales, given the potential for such technology to be applied to rainfall captured from individual buildings, or to networks of rainwater storages distributed throughout a catchment. This thesis comprised four major components. It first comprehensively reviewed the literature and examined the state-of-art of the application of RTC technology in a range of SCMs. Many studies have shown that the use of RTC can improve the performance of various type of SCMs at the site scale, in terms of both runoff quality and quantity (hydrology). On the other hand, there is a relatively untested potential to apply such technology at a mix of scales. The second component developed and modeled a range of RTC RWH systems that utilised a 7-day rainfall forecast to examine the impact of increasing rainfall forecast window on the performance of these systems in water supply, flood mitigation and restoration of more natural flow regimes. Using a relative long lead-time rainfall forecast was shown to enhance the ability of RTC in mitigating flood risks, while delivering an outflow regime that is close to reference streamflow. Such a design has also demonstrated to minimise the effect of forecast errors, given that the longer prediction window provides greater opportunity to adapt, before the forecast rainfall event occurs. Based on such RTC strategies, the network-scale impacts of RTC RWH systems on the behaviour of a stormwater network were also assessed through a modelling study. RTC was found to substantially reduce the risks of urban flooding in both current and future climates, while simultaneously providing a decentralised water supply. Applying RTC on a greater proportion of the RWH systems showed larger relative benefits than simply increasing the storage capacity, providing an important insight to guide investment in flood mitigation by storage. To advance the control strategy at the network scale, the final component developed and evaluated the performance of a centralised optimisation-based RTC model that enabled collaboration between multiple RWH systems. Modelling results have shown that such a strategy was able to deliver a synergy benefit in achieving better baseflow restoration, without any real detriment to the supply and flood mitigation performance of the integrated system. This is achieved by allowing larger storages to compensate for smaller, underperforming storages, thus achieving higher overall performance. More importantly, analysis across the three modelling components has shown that RTC-based rainwater harvesting systems can fundamentally modify the flow regime of stormwater runoff, leading to a promising potential to restore the natural flow regime in urban streams. While future work is required to address both technical and social-economic challenges, this research demonstrates the technical feasibility of using smart technology to better manage urban stormwater in a range of contexts and for a suite of environmental objectives. Its application has the potential to fundamentally transform the way rainwater harvesting—and stormwater management more broadly—are applied. Doing so will maximise the benefits to urban communities and to receiving environments.
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ItemGenomic and Phenomic Indicators of Persistence in Perennial Ryegrass Cultivar Evaluation( 2021)Poor persistence of perennial ryegrass creates many challenges for livestock producers to use their arable lands more productively and intensively within sustainable limits. Therefore, the persistence of perennial ryegrass cultivars has become one of the primary objectives in pasture breeding. The expression of persistence in a perennial ryegrass sward may depend on a combination of the sowing environment (management and climate), host grass genetics, presence of endophyte and interactions between these factors. Hence, pasture persistence has proven to be challenging to define and measure during pasture cultivar evaluation. The most commonly used techniques to evaluate persistence of perennial ryegrass in pasture breeding are laborious, time-consuming, and may require special training. Long-term grazing along with environmental stresses could change phenomic and genomic variation within a sward as an adaptive mechanism to maintain survival and productivity. In this selection process, less fit genotypes can be eliminated from a population, whereas well-adapted genotypes may become dominant in a sward. Understanding this adaptive process may be important for handling genetic resources, cultivar improvement, and pasture management. With the rapid technology development in recent years, high-throughput phenotyping and advanced molecular techniques to evaluate plant traits have increased in agriculture research. High throughput phenotyping platforms detect reflectance from plants and reliably generate phenomic data representing plant development, architecture, growth or biomass productivity of single plants or populations. However, the implementation of high throughput approaches in perennial ryegrass breeding has received limited attention compared to crop species. Therefore, this thesis aimed to develop and implement tools to predict the persistence of perennial ryegrass cultivars suited for growing in dairy environments of Australia. Fractional plant ground cover may provide information to understand the relationship of the plant resistance to abiotic and biotic stresses. Therefore, the first objective of the thesis was to develop a phenomic tool to assess pasture ground cover in field plots. In this experiment, data acquisition was conducted over three years after sowing using aerial-based and ground-based image sensors. Object-based and pixel-based image analysis techniques were implemented to extract phenomic features from images. The experimental results indicated a strong positive relationship between ground truth data and sensor-based estimates (p<0.001). Therefore, subsequent image analysis and image sensors may have a potential to accurately and efficiently estimate pasture persistence in large-scale breeding programs. Pasture senescence may indicate changes in plant growth, development and resistance to abiotic and biotic stresses. Therefore, the thesis further investigated the feasibility of existing HTP (High-Throughput Phenotyping) approaches for pasture senescence estimation. Aerial-based multispectral images, ground-based RGB (Red, Green and Blue) images, and ground-based hyperspectral data were acquired from a three-year-old perennial ryegrass trial. Software packages and machine learning scripts were used to develop a phenomic pipeline for high-throughput data acquisitions and phenomic feature extraction. Based on the results of this study, it was confirmed that high-resolution images and machine learning scripts offer a precision tool to assess perennial ryegrass senescence in pasture breeding programs. The study was further extended to compare phenomic and genomic variation of surviving populations following multiple years of grazing by dairy cattle with that present within the original populations. Phenomic and genomic data were collected from a field experiment in three subsequent growing periods (2018-2020) using advanced phenotyping and pioneering molecular tools. The results of this experiment indicated that morphological characters of the original cultivar can be influenced and changed due to environmental stress, such as grazing and heat stress. However, the magnitude of these changes may depend on the growing season and cultivar. Plant survival percentage and productivity of a perennial ryegrass population are associated with infected endophyte strains and directional selection due to long-term environmental effects. This study also showed that persistence of perennial ryegrass was accounted for in the three-way interactions among host grass, endophyte and environmental factors. Based on the observations of the experiment, the thesis identified agronomically elite host grass-endophyte interaction (commercial cultivars) for the Southwest region of Victoria. Advanced phenotyping and pioneering molecular tools used in this thesis may offer a potential to develop novel cultivars with prolonged pasture persistence more quickly than ever before. The research findings of this thesis (indicators of persistence) may support seed companies and the wider industries to suggest a novel definition of persistence, which includes farmers expectations such as increased productivity and later heading date.
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ItemUnderstanding the Determinants of Environmental Resistomes in Urban and Natural Ecosystems( 2021)The spread of antibiotic resistance genes (ARGs) is a great public health threat faced by humanity in the 21st century. However, our understanding of the abiotic and biotic factors determining the distribution of ARGs in the environment is lacking. This knowledge gap hampers our ability to design efficient management strategies to mitigate the dissemination of environmental ARGs. Soil and plant phyllosphere are the two largest environmental habitats of microorganisms and the most important reservoirs of environmental ARGs. In urban ecosystems, soil and plants in green spaces are major interfaces between environmental microbiome and human microbiome, which are closely related to the welling being of urban residents. In this study, we investigated resistome profiles and bacterial community assemblies in soil and plant phyllosphere samples collected from 40 urban parks across Melbourne, Australia. A total of 218 and 217 unique ARGs, which confer resistance to all major classes of antibiotics commonly used in humans and animals, were identified in soil and plant phyllosphere samples, respectively suggesting that urban green spaces were important reservoirs of ARGs. The results of correlation analyses indicated that the abundance of ARGs was significantly (P < 0.001) positively correlated with industrial factors (represented by the numbers of industries in a region). Structural equation model revealed that industrial distribution was one of the most important factors that contributed to the variations in resistome profiles in urban green spaces after accounting for multiple drivers. We further explored the main factors influencing the assemblies of bacterial communities in urban green spaces. Industrial development was also identified as a key factor in shaping bacterial communities as variation partitioning analysis results revealed that industrial factors could explain 20% and 28% of the variations in soil and grass phyllosphere bacterial communities, respectively. In natural ecosystems, ARGs are considered as an important proxy of ecosystem multifunctionality. To explore the biogeographic patterns of ARGs in natural ecosystems, we constructed ARG abundance atlas for plant phyllosphere and soil from an over 4,000 km transect across eastern and northern Australia. The results revealed that plant phyllosphere and soil resistomes exhibited opposite biogeographic patterns. The results of Spearman’s correlation analysis and structural equation model revealed that ARG abundance in plant phyllosphere was mainly related to the community assemblies of co-occurring bacterial, fungal, and protistan communities. However, ARG abundance in soil was mainly correlated with mean annual temperature, mean annual precipitation and soil nutrition content. These results indicated the distinct roles of biotic and abiotic factors in shaping resistomes in plant phyllosphere and soil and could potentially explain the observed contrasting biogeographic patterns of ARG abundance in these two different environmental habitats. Given the profound roles of soil fauna on the evolution and spreading of ARGs, we also profiled the resistomes in termite mounds, which is a unique habitat for diverse microorganisms. By collecting termite mound and soil samples from an over 1,500 km transect in northern Australia, we found that both the abundance and diversity of ARGs in termite mounds were significantly (P < 0.001) lower than that in surrounding bulk soils. Further analyses revealed that the differences between termite mound and bulk soil resistomes might result from the substantial increases in pH and nutrient availability due to termite mound formation. These results provided valuable implications for utilizing soil faunal activity for the regulating of the dissemination of environmental ARGs. Taken together, this thesis provided important evidence that both urban and natural environments are critical reservoirs of ARGs. In urban environments, changes in ARGs were more impacted by anthropogenic factors, particularly industrial development. In natural environments, climatic and edaphic factors were the main predictors of resistome profile. We also found that the resistome profiles in soil and plant phyllosphere were distinct from each other suggesting the important roles of habitat properties in influencing resistome profiles. These findings advance our understanding of the biogeographical distribution patterns of ARGs in the environmental settings and provide important scientific data for refining the management strategies to combat the spreading of environmental ARGs, a potential major threat to the public health.
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ItemUnderstanding the contribution of comammox bacteria to nitrification in terrestrial ecosystems( 2021)The discovery of complete ammonia oxidizers, comammox Nitrospira, represents a breakthrough in the history of nitrification research. Nitrospira inopinata, which was obtained from the aquatic ecosystem, is the only pure comammox bacterial isolate reported so far. Ammonia oxidation kinetics of N. inopinata revealed that they prefer an oligotrophic lifestyle, but such evidence in terrestrial ecosystems is lacking. The niche differentiation between comammox Nitrospira and canonical ammonia oxidizers, and the relative contribution of comammox Nitrospira to soils are largely unknown. Here, the responses of comammox Nitrospira to nitrogen (N) fertilizers and nitrification inhibitors (NIs) in agricultural and forest soils, and metabolic activity and community composition of comammox Nitrospira involved in soil nitrification process, and the biogeographical distribution and ecological preference of comammox Nitrospira in large-scale soil surveys were studied in order to improve our understanding of the potential role of comammox Nitrospira in terrestrial ecosystems. The microcosm incubations treated with different N fertilizers (ammonium sulfate and urea) in agricultural and forest soils demonstrated that nitrogen applications significantly increased the abundance of comammox Nitrospira clade A over time. Besides, six NIs, including acetylene (C2H2), 2-chloro-6-(trichloromethyl) pyridine (nitrapyrin), 3,4-dimethylpyrazole phosphate (DMPP), allylthiourea (ATU), dicyandiamide (DCD) and 1-octyne (C8H14) were applied in two agricultural soils, including arable and pasture soils. The results revealed that the amendment of all the six NIs significantly decreased soil nitrate concentrations, but to varying degrees throughout the incubations. Except for C8H14, the other five NIs effectively inhibited the growth of comammox Nitrospira clade A in the pasture soil. 13CO2-DNA-stable isotope probing (SIP) revealed that comammox Nitrospira clade A incorporated 13CO2 into their genomes in fertilized soils during the microcosm incubations, indicating that comammox Nitrospira clade A may play an active role in the soils with high nutrient inputs. Phylogenetic analyses revealed that the majority of 13C-labelled comammox Nitrospira clade A belonged to a distinct cluster separated from most sequences obtained from aquatic and engineering systems. The community structure and evolutionary adaptation of soil comammox bacteria may have a strong influence on their niche specialization. These comammox Nitrospira species in the terrestrial ecosystems may be less oligotrophic than their aquatic counterparts. The large-scale field investigations further explored the biogeographic distributions of comammox Nitrospira and ecological niches of individual comammox Nitrospira phylotypes in a range of Australian soils. A total of 295 soil samples were collected from the regions over 4000 km in eastern Australia. Among all the tested edaphic and climatic parameters, mean annual precipitation (MAP) was the strongest driver affecting the abundance, richness and community structure of comammox Nitrospira clade A. Four phylogenetic clusters were identified in these soil habitats, and two of them were the dominant clusters. MAP was consistently the best predictor correlated with the relative abundances of the dominant clusters. Notably, these two dominant clusters had contrasting correlations with the environmental factors, including MAP, mean annual temperature, soil nitrate and total nitrogen. Taken together, a comprehensive understanding of the ecological characteristics of comammox Nitrospira in terrestrial ecosystems was conducted at various levels from laboratory microcosm incubations in representative agricultural and forest soils to large-scale field investigations in a wide range of Australian soils. This research provides novel evidence that the growth and activity of comammox Nitrospira clade A can be stimulated by some soil management practices, and the distribution of comammox Nitrospira clade A might be not strictly oligotrophic and instead have a broader ecological niche breadth than previously considered. These findings have profoundly expanded our knowledge of the environmental niches of comammox Nitrospira and their relative contribution to nitrification in soils.
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ItemThe influence of land-use change on soil microbial communities in riparian ecosystems( 2021)Riparian ecosystems are areas with elevated soil fertility due to nutrient rich sediment deposition, topography, and high water availability, all of which result in high biomass productivity. The increased availability of ecosystem services makes riparian ecosystems vulnerable to land clearing, where the native riparian forest is converted to agricultural pastures. Efforts to revert this land-use change and restore native riparian vegetation focus on revegetation with native plant species. To what extent these concatenated land-use changes influence soil microbial communities is still uncertain, despite the key role that soil microbiota play in the biogeochemical cycles and vegetation dynamics. This thesis addresses that knowledge gap and pursues three main aims: - To assess how the spatial distribution of soil microbial communities varies in relation to the spatial structure of vegetation and soil properties, thus informing sampling strategies (Chapter 2). - To identify how taxonomic and functional composition of soil bacterial community change through the conversion from a remnant native riparian forest to agricultural pasture, that is later revegetated with native species, and whether this change is related to vegetation, soil properties, and/or soil depth (Chapter 3). - To identify how taxonomic and functional composition of soil fungal community change with the land-use conversion mentioned above, and whether this change is related to vegetation, soil properties, and/or soil depth (Chapter 4). In Chapter 2 I found that variation in the taxonomic composition of soil microbial communities (fungi, bacteria, archaea) was related to vegetation properties, particularly sub-canopy composition, and to a lesser extent soil chemical properties. Relationships between microbial communities and vegetation composition were stronger in top-soil than sub-soil. The exception was phylum Glomeromycota, where the relationship was stronger with ground cover composition and only for top-soil. In contrast to the taxonomic composition, the functional composition of the soil microbial community showed no relationships with vegetation properties or soil physical and chemical properties. I conclude that soil microbial communities within areas with similar vegetation communities show little variation, therefore a small sampling effort would be needed to adequately describe the characteristics of such soil communities. In Chapter 3 I found that taxonomic and functional composition of soil bacterial community varied across land uses, with cleared riparian forest converted to agricultural pastures being different from remnant forest and revegetated areas. Land-use differences were phylum-specific. For instance, Acidobacteria were more abundant in remnant soils whereas Actinobacteria were more abundant in pasture soils. Overall, bacterial metabolic activity and soil carbon and nitrogen content decreased with soil depth, while bacterial metabolic diversity and evenness increased with soil depth. Soil bacterial taxonomic composition was related to soil texture and soil chemical properties, but the functional composition was only related to soil texture. My results suggest that the conversion of riparian forests to pasture is associated with significant changes in the soil bacterial community, and that revegetation contributes to reversing such changes. Nevertheless, the observed changes in bacterial community composition (taxonomic and functional) were not directly related to changes in vegetation but were more closely related to soil properties. In Chapter 4 I found that taxonomic and functional composition of soil fungi infrequently varied with land-use change or depth, with differences only observed for a few taxa. In contrast, fungal community composition was strongly related to soil chemical properties in both top-soil and sub-soil. My results indicate Ascomycota and Basidiomycota were more abundant in areas with low relative soil fertility (N, P, K and Ca) and little ground cover, whereas the opposite was true for Glomeromycota. Sites with high clay content, low sub-canopy cover, and high tree basal area tended to harbour more plant pathogens, dung saprotrophs, and arbuscular mycorrhizae. In contrast, areas with high sub-canopy cover and less tree basal area encompassed a greater abundance of animal pathogens, wood saprotrophs, and ectomycorrhizae. In conclusion land-use change had little effect on taxonomic and functional composition of soil fungal communities. In conclusion, I found that soil bacterial communities were more responsive to land-use change and depth than soil fungal communities. Relationships with vegetation were complex: within a community of soil microbes, I found relationships with sub-canopy vegetation; however, across multiple communities, bacteria showed no relationship to vegetation, and fungi were related to ground cover vegetation and canopy, not sub-canopy vegetation. My research suggests that the impact of land-use change on soil microbial communities is related to the extent that it influences soil physical and chemical properties. Therefore, monitoring or quantifying the extent land-use change alters soil physical and chemical properties may indicate the impact of land-use change on soil microbial communities.