Plant cell walls constitute one of the most abundant raw biomaterials on Earth. The synthesis of long-chain olysaccharides, the main components of plant cell walls starts ab ovo in the cytoplasm where most of the building blocks for polysaccharide synthesis, so-called nucleotide sugars, are produced. The monosaccharide moieties of nucleotide sugars are incorporated into growing polysaccharide chains either directly at the plasma membrane by lycosyltransferases (GTs) that form cellulose synthase complexes or by those residing in the Golgi apparatus. In the latter case, nucleotide sugars have to pass the Golgi membranes with the help of nucleotide sugar transporters (NSTs). Once inside, they are used by Golgi GTs which assemble polysaccharide chains and decorate proteins and lipids with sugar residues. Recent evidence suggests that in plants nucleotide sugars can be guided to specific polysaccharides and/or glycan decorations, yet the molecular mechanisms of these processes are not fully understood. This PhD research attempts to explore the phenomenon of the targeted substrate delivery by investigating two possible hypotheses: the spatiotemporal distribution of proteins within the Golgi apparatus and the occurrence of direct interactions between NSTs and GTs. The author of this dissertation has tested both of those hypotheses by investigating protein-protein interactions, localising the individual components to their specific sub-compartments within the cell and tracking changes in mutant plants where these processes are modulated. The bifunctional UDP-RHAMNOSE/UDP-GALACTOSE TRANSPORTER (URGT) family from the model plant Arabidopsis thaliana was selected for this study. While this family has six members which in vitro are capable of transporting the same substrates, plant mutant studies indicate substrate preference and targeted delivery to specific cell wall components in vivo. This thesis presents the first evidence that members of the URGT family localise to specific sub-Golgi compartments. The colocalisation studies undertaken as part of this thesis place URGT1 and URGT5 in the cis-Golgi, URGT2, URGT4 and URGT6 – in the medial Golgi, while URGT3 seems to localise to trans-Golgi stacks. Protein-protein interactions studies have identified multiple interaction partners for the six URGTs. Notably, many of those are known galactosyltransferases, which aligns with the transport function of the URGTs. It is therefore highly likely that the identified candidates are true interactors, which use the proximity of the transporter to increase the process efficiency by substrate channelling. This finding is further supported by the fact that observed interactions between URGT family members and GTs often localise to the same sub-Golgi compartment. The study identified new potential galactosyl- and rhamnosyltransferases, including two putative arabinogalactan protein galactosyltransferases. The data obtained during this project suggest, that URGTs may determine the flow of substrate through both spatial separation within the sub-Golgi stacks and direct interactions with GTs. The study presents new insight into the sugar substrate delivery processes in plants, suggests that similar processes may take place in other NST families and that their specificity may be similarly tuned by localisation and interactions.

The marine environment is heavily affected by fishing pressure and knowing how different management strategies affect the persistence of marine species is crucial for ensuring sustainable fishing. Models used within the fisheries management strategies evaluation context have been implemented in the past decades from traditional single species methods to an ecosystem-based approach, but there are still uncertainties on the effectiveness of these models. This thesis aims to understand the drivers of marine species persistence coupling network-based methods and spatially explicit population viability analyses (PVA). This thesis focuses on marine species of south-eastern Australian waters, a region characterised by rich biodiversity and oceanographic complexity, supporting important Australian commercial fisheries sectors. PVA is an approach not yet widely investigated in the context of fisheries management strategies evaluation, however understanding species viability and ensuring metapopulation persistence is fundamental to avoid overexploitation of the stocks. In this thesis is examined how spatially explicit PVA compares to other commonly used models, demonstrating that PVA is a powerful alternative, suitable to inform fisheries management. PVA is applied to estimate metapopulation persistence in a spatial context, analysing how persistence changes when modelling alternative fisheries management scenarios for important commercial fisheries species. The knowledge of species distribution is very important for any spatially explicit population modelling and is needed when studying population viability and dynamics. A recent challenge in understanding and predicting species’ distributions has been focused on the influence of population connectivity. This thesis explores how to integrate graphbased metrics, representative of seascape connectivity, into marine-based species distribution models (SDMs) to understand the contribution of connectivity to predict marine species spatial distribution. Connectivity is a key determinant of metapopulation persistence of species inhabiting fragmented habitats. Larval connectivity is quantified using a biophysical model. Connectivity is visualized as networks, where habitat patches are represented by nodes and dispersal connections are represented by linkages. In this thesis graph-based metrics are calculated because of their significant role as indicator of metapopulation persistence, identifying key habitat patches for the overall persistence of the species. The results of this thesis demonstrate how PVA is a valuable tool helping to inform fisheries managers on the effects of fishing on marine species. Habitat heterogeneity and movement ecology demonstrate to be critical model parameters, strongly influencing metapopulation persistence, suggesting that fisheries managers might benefit from better understanding of movement behaviour and habitat characteristics. This thesis results also provide insight on the role of connectivity to determine marine populations persistence and distribution. Hotspots of connectivity reveal to be key habitats, often enhancing habitat suitability, and strongly influencing metapopulation persistence. Managers and ecologists would benefit by employing similar approaches in making more efficient and more ecologically informed decisions and focusing more on local connectivity patterns to better understand and protect marine species.

Biodiversity is declining globally, with habitat clearing playing a major role in perpetuating these declines. Offsets aim to achieve no net loss of biodiversity by implementing conservation actions that deliver equal biodiversity gains to those lost through development. Broad habitat-based biodiversity metrics are commonly used to quantify development impacts and assign offset requirements. However, it is unclear what reliance on habitat-based offset metrics means for biodiversity long-term. In this thesis I explore the current state of biodiversity metrics within the scientific literature and how these metrics are applied in policies around the world. I also quantitatively test nine biodiversity metrics and explore the long-term ramifications of their use in offsetting on species persistence. In a sample of 255 publications from ecology (n = 158), conservation planning (n = 54), and offsetting (n = 43), I identify 24 categories of metrics used to quantify biodiversity. The offsetting literature focused largely on habitat attributes and area-based approaches for measuring biodiversity. Similarly, consistent use of habitat attributes, habitat condition, and area in 21 offset policies demonstrates that offsets do not adequately capture individual species or communities. Many offset policies measure species presence, however, less than half of those I reviewed measured any species-specific attributes which could be used to help inform conservation actions for those species. These two reviews demonstrate that the metrics currently used to measure biodiversity don’t reflect some of the key biodiversity attributes offsets aim to protect. To understand the long-term consequences of relying on such habitat-based metrics for offsetting I developed a spatial simulation tool and present a methodological framework that quantitatively tests the effects of metric choice on long-term persistence. The R-based simulation tool uses raster data to simulate development impacts and restoration efforts. I tested nine biodiversity metrics spanning an axis of pattern versus process and capturing different levels of biodiversity: area of habitat, condition of habitat, vegetation area, vegetation condition, area * habitat suitability, condition * habitat suitability, abundance, metapopulation connectivity and rarity-weighted richness. The resulting raster outputs are used in population viability analyses for five species. Most metrics achieved no net loss or net gains in the metric values, species’ habitat suitability or abundance, but only when impacts avoided high suitability areas. When impacts cannot avoid high suitability areas, species-specific metrics deliver higher gains in abundance per hectare restored than habitat-based metrics alone. Failing to improve current offset practices ensures species will continue to decline under development-offset trading programs and should provide an incentive for policy makers to properly enforce impact avoidance measures where possible.

My approach in this thesis was to explore how to wring more information out of existing data to reduce uncertainty, improve decision-making and hope to generate better conservation outcomes. I explore and develop a range of quantitative tools to this end. I look at three key areas: dealing with uncertainty, structuring decision making, and improving the use of existing information. I consider these concepts over three thematic case studies: monitoring the abundance of three vulture species in Cambodia, trading-off the costs and benefits of releasing information publicly when a new species or population is discovered, and comparing use of optimisation and project prioritisation protocols to allocate funding to species conservation efforts. In the first case-study, I develop new Bayesian hierarchical model to estimate vulture abundance, and compare the inferences available from this approach with less specialised approaches previously used. In the second case-study I develop a decision-making framework to allow decision-makers to explicitly trade-off costs and benefits, and apply the method to data collected from informants who have made these types of decisions themselves. In the final section, I explore whether additional information can improve optimisation to allocate funding, and compare performance in terms of expected avoided extinctions of the optimisation approach with a project prioritisation protocol. I find that there is indeed much more we can learn from the information we have. But this is not a free lunch – work needs to be done to uncover opportunities, and technical skills are often needed to make best use of them, and assumptions must often be made to draw conclusions.

Cereal crops are exposed to different abiotic stresses thus impacting agricultural productivity, but soil beneficial microorganisms have the potential to improve the adaptation of crops to suboptimal environments. This study resolves the time-specific dynamics between the plant growth promoting bacteria Azospirillum brasilense and the model cereal species Brachypodium distachyon grown under suboptimal temperatures and low P availability. Results contribute to our current understanding of the phenotypic and biochemical adaptative rearrangements occurring in plants during interaction with beneficial bacteria.

Aphids (Hemiptera: Aphididae) can be particularly devastating to grain crops, with their economic importance weighted on their ability to cause significant yield losses through a variety of methods. From feeding damage alone in 2012, cereal aphids caused an average annual loss of $14 million in Australian wheat crops. For over a century, growers have relied upon host plant resistance and chemical treatments to control invertebrate pests, however suppression of beneficial organisms and increased resistance within targeted species has created an ongoing battle with pest control. For example, the polyphagous green peach aphid (Myzus persicae (Sulzer)), often a pest of canola crops, has developed resistance to over 74 insecticides including carbamates, pyrethroids, and organophosphates around the world. Due to these issues, control of agricultural pests is now focussed on Integrated Pest Management (IPM) strategies, within which natural enemies can play a role as biological controls. Parasitoid wasps have had the most success as biological control organisms in the past, likely due to their host specificity. I spent three years collecting data on grain aphid pests and their associated natural enemies, paying particular attention to the hymenopteran parasitoids. I determined the distribution of grain aphids and their associated Aphidiinae within grain production landscapes around Australia, utilising historic data and citizen science. Additionally, I determined how aphid abundance and diversity, along with their associated parasitoids changed throughout the growing seasons. I created a key of aphid parasitoids (Hymenoptera: Aphidiinae) parasitizing aphids in Australian grain production landscapes. Finally, I determined the effects of seed treatments on specific natural enemies associated with M. persicae, identifying the difference between parasitoid and predator effects. My findings are informative for developing strategies to conserve those Aphidiinae species of particular importance in controlling aphid pests. Additionally, these results can assist with pest management decisions, enabling growers to implement IPM based on a greater breadth of knowledge.

Ecotoxicology studies the fate and effect of chemicals in the ecosystem using scientific approaches. Laboratory tests (e.g. acute and chronic tests) establish dose response relationships between toxicants and the test species. Although laboratory tests provide essential data to understand the potential impact of toxicants in the aquatic environment, they lack environmental realism. In situ tests provide environmental realism by exposing the test organism to toxicants in the aquatic environment. Test species are central in ecotoxicity assays. Molluscs are commonly used in ecotoxicological tests and they are the second largest phylum, have a global distribution, widely abundant in freshwaters, and ecological importance (e.g. as a food source, provides habitat and protection) makes them useful in ecotoxicity tests. This thesis used a freshwater snail, Potamopyrgus antipodarum (J.E. Gray, 1843), for laboratory and field testing. Although native to New Zealand, it is a successful invasive species in many parts of the world, including Australia and has been successfully used as a test species for ecotoxicity tests and as a bioindicator in some countries (e.g. in Europe, and the USA). A few Australian studies have used it in laboratory assays and field studies. There is still less knowledge and information of P. antipodarum as a test species and bioindicator in Australia. Therefore, the overall aim of the thesis is to assess the potential of P. antipodarum as a bioindicator of freshwater pollution in Australia. In Chapter 2, adult P. antipodarum were exposed (96 h) to environmentally relevant concentrations (ERCs) of metals (copper and zinc) and a pesticide (imidacloprid) in water. Mortality (LC50) and behavioural responses (EC50) were assessed to investigate the sensitivity of the snail and the potential use of its behavioural response in the environmental risk assessment of toxicants. The Chapter 3 was an extension of the Chapter 2 to assess their sensitivity in chronic toxicity tests. Adult snails were exposed for 28-d to ERCs of several chemicals (Cu, Zn, bifenthrin, and 17 a-ethynylestradiol), physico-chemical conditions (salinity and temperature), and food limitation in water and sediment bioassays. Endpoints including reproduction, growth, and mortality were measured. This study evaluated the sensitivity of this species during chronic exposure and compared the response of these Australian cultures to those abroad. In Chapter 4, adult snails were deployed in cages in the field for 28-d at 9 sites (i.e. 7 impact sites, and 2 reference sites) in Merri Creek and an additional reference site in Cardinia Creek to evaluate the performance of snails at various points along Merri Creek with different land use. Various endpoints were measured at the organism level (growth, mortality and reproduction), and the sub-organism level (glutathione Stransferase, GST; lipid peroxidation, LPO; and catalase, CAT). The biological response of the snails at each impact site were compared to the 2 reference sites on Merri Creek to show the potential impact of land use on the snails. The additional reference site at Cardiana Creek was compared with the reference sites on Merri Creek to identify any difference in response in a different catchment. This project shows that P. antipodarum is a suitable and sensitive species for acute and chronic assays because it responded to ERCs of toxicants, the response is like populations abroad, it showed a similar response to other test species and LC50 and EC50 value was within the range of other test species in use. There is potential to use acute tests (LC50) and behavioural responses (EC50) in the rapid risk assessment of environmental pollutants. Field data also revealed that P. antipodarum is a suitable bioindicator for Australian environmental conditions because the response of this population was similar to the populations abroad, and other test species used in in situ tests and showed a high tolerance to environmental variations. This research also shows that although laboratory tests can provide us with essential data to understand the potential impact of toxicants in the aquatic environment, they lack environmental realism. And we can achieve environmental realism by exposing the species to toxicants in the aquatic environment during in situ tests.

Fire is a key disturbance process in >50% of terrestrial ecosystems where species are often adapted to specific fire regimes. However, ongoing changes to fire regimes now represent a considerable threat to biodiversity, including mammals and reptiles in Australia. Despite this, there are large knowledge gaps around how different types of fire – or ‘pyrodiversity’ – affect biodiversity and how fire interacts with other key drivers of animal populations. This thesis explored the drivers of mammal and reptile distributions in fire-prone mallee woodlands, to answer key questions of wider relevance to fire-prone ecosystems. First, I explored the influence of daily meteorological conditions on small mammal capture rates during field surveys. I built regression models of the daily capture rates of different species and families against six meteorological variables to determine favourable conditions for ecological surveys. Capture rates of all species were influenced by a least one meteorological variable, although responses to specific conditions varied between taxa. Small mammal surveys should be conducted in a variety of weather conditions to ensure a representative sample of the local community and my results can be used to determine conditions favourable to a single species or family. Second, I explored how pyrodiversity influences the distributions of whole animal assemblages in conjunction with other environmental gradients. I built species distribution models for 17 mammals and 54 reptiles against different measures of fire and mapped the distribution of each species across a >100 000 km2 region. Native mammals showed a variety of responses. Microbats were more likely to occur as time since fire increased, whereas rodent occurrence was positively correlated with recently burned areas. Occurrence of small dasyurid marsupials was positively correlated with the area and configuration of older post-fire age classes, showing the importance of spatial context in understanding the fire responses of animals. Reptile responses to pyrodiversity were more consistent, however there was variation within taxonomic groups regarding the importance of different fire elements. Many reptiles occurred most frequently between 0-50 years post-fire, coinciding with peaks in hummock grass growth. However, configuration of this key habitat component was important to reptiles, and planning for appropriate configurations of fire-derived habitat should be incorporated into fire management for reptile conservation. Maps of species distributions can be used to better incorporate the needs of individual species into fire and conservation planning. Lastly, I used a field experiment to test different mechanisms for how fine-scale patterns of fire influence animal populations in recently burnt environments. Small mammal, reptile and invasive predator activity was monitored in the year following a large planned burn to explore how the amount and configuration of burnt and unburnt habitat affects recovery. Reptile assemblages varied between burnt and unburnt sites, and reptile species richness increased at sites with higher amounts and connectivity of unburnt vegetation. Mammals did not have clear relationships with spatial patterns of planned fire, however fox activity increased after the fire at all sites. Small mammals appear resilient to this scale of planned fire and retaining well-connected unburnt refuges is important for maintaining reptile diversity. Overall, my work helps to define the types of fire that benefit mallee mammal and reptile assemblages, and this thesis highlights how this knowledge can be used to improve fire management for biodiversity conservation.

Significance: The rapid evolution of herbicide resistance in weeds provides a tractable system to study adaptive evolution. Investigations into the dynamics of herbicide resistance development in agroecosystems will advance our understanding of evolutionary biology, as well as guide the formulation of recommendations to control herbicide-resistant weeds. Materials and Methods: Accurate and efficient strategies to characterise and monitor weed populations are required. Populations can be monitored directly by gathering phenotype and genotype data; as well as indirectly by predicting phenotypes using genomic prediction. This thesis investigated the adaptive evolution of weed populations with respect to herbicides. We used Lolium rigidum (rigid/annual ryegrass) as the model weed species because of its ability to evolve resistance to many herbicides with different modes of action. The herbicides used were clethodim (fatty acid biosynthesis inhibitor), glyphosate (aromatic amino acid biosynthesis inhibitor), sulfometuron (branched-chain amino acid biosynthesis inhibitor), terbuthylazine (photosystem II disruptor), and trifluralin (tubulin disruptor). Results: The results of this research can be summarised as: 1. Characterising a landscape by sampling more populations using low-resolution low-cost pool sequencing (Pool-seq) will yield better QTL detection and genomic prediction accuracies than sampling less populations with high-resolution high-cost individual sequencing. 2. L. rigidum populations were collected across South-East Australia, and a colorimetric phenotyping method (instaGraminoid) was developed to cost-effectively quantify herbicide resistance using photographs. 3. Pool-sequencing coupled with genome complexity reduction (Pool-ddRADseq) with MseI and NsiI restriction enzymes, followed by filtering at 99% read and mapping accuracies, 227X minimum depth, and 0.001 minor allele frequency were predicted to result in accurate allele frequency estimates while retaining 600,000 SNPs. 4. Genome-wide association experiments using instaGraminoid-derived phenotype data and Pool-seq-derived genotype data show evidence of highly polygenic herbicide resistance traits and the genetic basis of cross-resistance. 5. The putative resistance alleles are more likely to have originated from standing genetic variation than from de novo mutations. 6. Genomic prediction using population-level data can be useful in herbicide resistance monitoring and management by identifying potentially resistant populations at the early stages of resistance evolution. Conclusion and recommendations: Herbicide resistance is a polygenic trait with many loci conferring cross-resistance. It is rapidly evolving from the rich reservoir of standing genetic variation. Herbicide application remains to be a cost-effective approach to control weeds, but it will inevitably become ineffective with the evolution of cross-resistance. I propose a genomically-informed rotation of chemical and non-chemical control strategies. This involves using genomic prediction to cost-effectively and rapidly monitor herbicide resistances. Depending on the predicted levels of resistance, different herbicide mixtures or non-chemical weed control methods can be recommended.

Many thousands of gene families across the tree of life still lack robust functional characterisation, and thousands more may be under-characterised, with additional unknown functions not represented in official annotations. Here, I aim to characterise the evolution and functions of the poorly characterised ecdysteroid kinase-like (EcKL) gene family, which has a peculiar taxonomic distribution and is largely known for containing an ecdysteroid 22-kinase gene in the silkworm, Bombyx mori. I hypothesised that EcKLs may also be responsible for insect-specific ‘detoxification-by-phosphorylation’, as well as ecdysteroid hormone metabolism. My first approach was to explore the evolution of the EcKLs in the genus Drosophila (Diptera: Drosophilidae), which contains the well-studied model insect Drosophila melanogaster. Drosophila EcKLs have evolutionary and transcriptional similarities to the cytochrome P450s, a classical detoxification family, and an integrative ‘detoxification score’, benchmarked against the known functions of P450 genes, predicted nearly half of D. melanogaster EcKLs are candidate detoxification genes. A targeted PheWAS approach in D. melanogaster also identified novel toxic stress phenotypes associated with genomic and transcriptomic variation in EcKL and P450 genes. These results suggest many Drosophila EcKLs function in detoxification, or at least have key functions in the metabolism of xenobiotics, and additionally identify a number of novel P450 detoxification candidate genes in D. melanogaster. I then broadened the phylogenomic analysis of EcKLs to a manually annotated dataset containing an additional 128 insect genomes and three other arthropod genomes, as well as a number of transcriptome assemblies. Phylogenetic inference suggested insect EcKLs can be grouped into 13 subfamilies that are differentially conserved between insect lineages, and order-specific analyses for Diptera, Lepidoptera and Hymenoptera revealed both highly conserved and highly variable EcKL clades within these taxa. Using phylogenetic comparative methods, EcKL gene family size was found to vary with detoxification-related traits, such as the sizes of classical detoxification gene families, insect diet, and two estimations of ‘detoxification breadth’ (DB), one qualitative and one quantitative. Additionally, the rate of EcKL duplication was found to be low in lineages with small DB—bees and tsetse flies. These results suggest the EcKL gene family functions in detoxification across insects. Building on my previous ‘detoxification score’ analysis, I used the powerful genetic toolkit in D. melanogaster and developmental toxicology assays to test the hypothesis that EcKL genes in the highly dynamic Dro5 clade are involved in the detoxification of selected plant and fungal toxins. Knockout or misexpression of Dro5 genes, particularly CG13659 (Dro5-7), modulated susceptibility to the methylxanthine alkaloid caffeine, and Dro5 knockout also increased susceptibility to kojic acid, a fungal secondary metabolite. These results validate my evolutionary and integrative analyses, and provide the first experimental evidence for the involvement of EcKLs in detoxification processes. Finally, I aimed to find genes encoding ecdysteroid kinases in D. melanogaster, focusing on Wallflower (Wall/CG13813) and Pinkman (pkm/CG1561), orthologs of a known ecdysteroid 22-kinase gene. Wall and pkm null mutant animals developed normally, but misexpression of Wall caused tissue-specific developmental defects, albeit not those consistent with inactivation of the main ecdysteroid hormones, ecdysone and 20-hydroxyecdysone. In addition, my hypothesis that Wall encodes an ecdysteroid 26-kinase was not supported by hypostasis experiments with a loss-of-function allele of the ecdysteroid 26-hydroxylase/carboxylase gene Cyp18a1. Combined with existing expression and regulatory data, these results suggest Wall encodes an ecdysteroid kinase with an unknown substrate, and hint at previously unknown complexity in ecdysteroid signalling and metabolism in D. melanogaster. Overall, this thesis provides a detailed exploration of the functions of the EcKL gene family in insects, showing that these genes comprise a novel detoxification gene family in multiple taxa, and that they may also contribute to understudied aspects of ecdysteroid metabolism in a model insect. This work also demonstrates the power and potential of integrating evolutionary, genomic, transcriptomic and experimental data when characterising genes of unknown function.

All organisms on Earth engage in microbial symbioses. These alliances between animals and microbes are situated along a continuum of benefits versus costs with mutualism at one end and parasitism at the other. Even within one group of microbes—sub-Kingdom Alveolata—we find classic mutualists such as the Symbiodiniaceae (Dinoflagellata) that are endosymbionts of reef-building corals, and the parasitic Apicomplexa such as the malaria-causing Plasmodium. Both Symbiodiniaceae and Plasmodium are intracellular symbionts. Contact, recognition and ingress of the symbionts into their host cells are pivotal for commencement of their symbioses. These mechanisms are mediated by the innate immune system, and eukaryotic pattern recognition receptors (PRRs) recognize microbial-associated molecular patterns (MAMPs). These molecules, traditionally known to trigger an inflammatory response during microbial infections, also mediate the cross-talk between host and symbiont. Glycan-lectin interaction is a common MAMP-PRR pathway that apparently acts as a lock-and-key mechanism in both mutualistic and parasitic symbioses. The mechanism used by Plasmodium to invade the host is well understood, whereas the ingress of dinoflagellates into their cnidarian hosts remains enigmatic. In Chapter 2, I compare our knowledge of the Plasmodium-human parasitism to explore whether it could perhaps inform the understanding of how cnidarian Symbiodiniaceae mutualisms are initially established. To explore establishment of symbiosis between corals and their symbiotic algae (Chapter 3), I created a matrix of symbiotic compatibilities between a wide range of Symbiodiniaceae and three genotypes of Exaiptasia diaphana—a model organism for the cnidarian dinoflagellate symbiosis—from the Great Barrier Reef. This study permitted the selection of Symbiodiniaceae types with various level of affinity to the cnidarian host: Breviolum minutum is the homologous species (i.e., native), Cladocopium goreaui is the compatible heterologous species (i.e., non-native), and Fugacium kawagutii is the heterologous-incompatible species. Symbiont species and host genotype influenced colonization dynamics, which is consistent with selectivity roles for both host and symbiont at the onset of symbiosis. This matrix of different host–symbiont compatibilities was used in Chapter 4 to explore the molecular mechanisms of recognition and establishment of the cnidarian Symbiodiniaceae symbiosis. I used anion-exchange chromatography, lectin array technology and confocal microscopy to develop an inventory of sugars potentially acting as MAMPS on the dinoflagellate surface. The Symbiodiniaceae cell surface glycome was diverse and varied among algal species. By comparing the glycan inventories of the homologous symbiont B. minutum, the heterologous, compatible symbiont C. goreaui, and the incompatible species (F. kawagutii), I was able to focus on selected sugars implicated in recognition and then attempt to perturb recognition by modifying or masking epitopes on either the host or symbiont. D-galactose (especially methyl-b-D-galactose), xylose and fucose seem to regulate the host invasion by homologous or heterologous algae. In Chapter 5, I further explored Symbiodiniaceae cell surface with a proteomic analysis of algal cell wall. Several proteins with transmembrane translocating activity were identified, and a large proportion of the amino acid residues are still uncharacterized. Intriguingly, the reticulocyte-binding-like (RBL) protein was identified on the surface of Symbiodiniaceae used here. RBL proteins are involved in the recognition of sialic acid-containing receptors of host cells during malaria infection. This thesis describes in detail the Symbiodiniaceae cell surface and contributes to the knowledge of how this structure could mediate the symbiosis with cnidarians. Furthermore, my work highlights important similarities between Symbiodiniaceae and their relatives in the Phylum Apicomplexa. If, in the Alveolata, mutualism did lead to parasitism, Symbiodiniaceae and Plasmodium may have conserved symbiont/host recognition mechanisms, perhaps sialic acid mediated, to access the host and start symbioses.

Recent advances in microscopy have led to an improved visualization of different cell processes. Yet, this also leads to a higher demand of tools which can process images in an automated and quantitative fashion. Here, we present two applications that were developed to quantify different processes in eukaryotic cells which rely on the organization and dynamics of the cytoskeleton. In plant cells, microtubules and actin filaments form the backbone of the cytoskeleton. These structures support cytoplasmic streaming, cell wall organization and tracking of cellular material to and from the plasma membrane. To better understand the underlying mechanisms of cytoskeletal organization, dynamics and coordination, frameworks for the quantification are needed. While this is fairly well established for the microtubules, the actin cytoskeleton has remained difficult to study due to its highly dynamic behaviour. One aim of this thesis was therefore to provide an automated framework to quantify and describe actin organization and dynamics. We used the framework to represent actin structures as networks and examined the transport efficiency in Arabidopsis thaliana hypocotyl cells. Furthermore, we applied the framework to determine the growth mode of cotton fibers and compared the actin organization in wild-type and mutant cells of rice. Finally, we developed a graphical user interface for easy usage. Microtubules and the actin cytoskeleton also play a major role in the morphogenesis of epidermal leaf pavement cells. These cells have highly complex and interdigitated shapes which are hard to describe in a quantitative way. While the relationship between microtubules, the actin cytoskeleton and shape formation is the object of many studies, it is still not clear how and if the cytoskeletal components predefine indentations and protrusions in pavement cell shapes. To understand the underlying cell processes which coordinate cell morphogenesis, a quantitative shape descriptor is needed. Therefore, the second aim of this thesis was the development of a network-based shape descriptor which captures global and local shape features, facilitates shape comparison and can be used to evaluate shape complexity. We demonstrated that our framework can be used to describe and compare shapes from various domains. In addition, we showed that the framework accurately detects local shape features of pavement cells and outperform contending approaches. In the third part of the thesis, we extended the shape description framework to describe pavement cell shape features on tissue-level by proposing different network representations of the underlying imaging data.