Population structure, effective population size and adverse effects of stocking in the endangered Australian eastern freshwater cod Maccullochella ikei

Microsatellite markers were used to examine spatio-temporal genetic variation in the endangered eastern freshwater cod Maccullochella ikei in the Clarence River system, eastern Australia. High levels of population structure were detected. A model-based clustering analysis of multilocus genotypes identified four populations that were highly differentiated by F-statistics (FST = 0· 09 − 0· 49; P < 0· 05), suggesting fragmentation and restricted dispersal particularly among upstream sites. Hatchery breeding programmes were used to re-establish locally extirpated populations and to supplement remnant populations. Bayesian and frequency-based analyses of hatchery fingerling samples provided evidence for population admixture in the hatchery, with the majority of parental stock sourced from distinct upstream sites. Comparison between historical and contemporary wild-caught samples showed a significant loss of heterozygosity (21%) and allelic richness (24%) in the Mann and Nymboida Rivers since the commencement of stocking. Fragmentation may have been a causative factor; however, temporal shifts in allele frequencies suggest swamping with hatchery-produced M. ikei has contributed to the genetic decline in the largest wild population. This study demonstrates the importance of using information on genetic variation and population structure in the management of breeding and stocking programmes, particularly for threatened species.

Kidney Induction: control by Notch, Wnt and GDNF/Ret signalling

The permanent mammalian kidney (metanephros) develops as a result of complex reciprocal tissue interactions between a ureteric epithelium and the renal mesenchyme. The overall goal of the research in this thesis was to gain data that will eventually help in elucidating the formation of congenital renal malformations. The experiments in my thesis aimed to reveal the mechanisms by which Notch, Wnt and GDNF/Ret signalling pathways regulate the development of functional kidney. The function of Notch pathway was studied by a transgenic mouse model, where it was shown that overactivation of Notch signalling disturbs kidney development and alters the expression of Gdnf and Ret/GFRa1. This indicates that Notch signalling interplays with GDNF/Ret in the regulation of the primary ureteric budding and its subsequent branching. The data also suggested that strict spatio-temporal regulation of these two pathways is required for determination of ureteric tip-identity, which appeared to be crucial for the branch formation. The function of Wnt signalling in the ureteric morphogenesis was studied by in vivo and in vitro methods to show that a canonical pathway is required for ureteric branching. Stabilisation and deletion of the canonical pathway mediator, b-catenin specifically in the ureteric epithelium result in renal aplasia/hypodysplasia. These defects originate from severe blockage of ureteric branching due to the disrupted Ret signalling. Consequently, ureteric tip specific markers are lost and ureteric stalk identity is expanded throughout the whole epithelium. Thus, the data demonstrates that the Wnt/b-catenin pathway plays an essential role in the patterning and branching of the ureteric epithelium. A novel in vitro method was generated and utilised in nephron induction studies to reveal the mechanisms through which nephrogenesis is induced. Transient GSK3 inhibition results in stabilisation of b-catenin in the isolated renal mesenchyme, which efficiently triggers nephron formation. Also genetic stabilisation of b-catenin specifically in the mesenchyme results in spontaneous nephrogenesis. The results show that activation of the canonical Wnt pathway is sufficient to initiate nephrogenesis, and suggest that this pathway mediates the nephron induction in murine kidney mesenchymes. Taken together, this thesis demonstrates Notch and Wnt signalling pathways as novel regulators of ureteric branching morphogenesis, and that activation of the canonical Wnt pathway is sufficient for nephron induction. The studies also indicate that the Notch and Wnt pathways cross-talk with GDNF/Ret signalling in the patterning of ureteric epithelium.

Soft Functional Materials Induced by Fibrillar Networks of Small Molecular Photochromic Gelators

Low-molecular-mass organogelators (LMOGs) based on photochromic molecules aggregate in selected solvents to form gels through various spatio-temporal interactions. The factors that control the mode of aggregation of the chromophoric core in the LMOGs during gelation, gelation-induced changes in fluorescence, the formation of stacked superstructures of extended pi-conjugated systems, and so forth are discussed with selected examples. Possible ways of generating various light-harvesting assemblies are proposed, and some unresolved questions, future challenges, and their possible solutions on this topic are presented.

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

Variability in exposure to ambient ultrafine particles in urban schools: Comparative assessment between Australia and Spain

Ambient ultrafine particle number concentrations (PNC) have inhomogeneous spatio-temporal distributions and depend on a number of different urban factors, including background conditions and distant sources. This paper quantitatively compares exposure to ambient ultrafine particles at urban schools in two cities in developed countries, with high insolation climatic conditions, namely Brisbane (Australia) and Barcelona (Spain). The analysis used comprehensive indoor and outdoor air quality measurements at 25 schools in Brisbane and 39 schools in Barcelona. PNC modes were analysed with respect to ambient temperature, land use and urban characteristics, combined with the measured elemental carbon concentrations, NOx (Brisbane) and NO2 (Barcelona). The trends and modes of the quantified weekday average daily cycles of ambient PNC exhibited significant differences between the two cities. PNC increases were observed during traffic rush hours in both cases. However, the mid-day peak was dominant in Brisbane schools and had the highest contribution to total PNC for both indoors and outdoors. In Barcelona, the contribution from traffic was highest for ambient PNC, while the mid-day peak had a slightly higher contribution for indoor concentrations. Analysis of the relationships between PNC and land use characteristics in Barcelona schools showed a moderate correlation with the percentage of road network area and an anti-correlation with the percentage of green area. No statistically significant correlations were found for Brisbane. Overall, despite many similarities between the two cities, school-based exposure patterns were different. The main source of ambient PNC at schools was shown to be traffic in Barcelona and mid-day new particle formation in Brisbane. The mid-day PNC peak in Brisbane could have been driven by the combined effect of background and meteorological conditions, as well as other local/distant sources. The results have implications for urban development, especially in terms of air quality mitigation and management at schools.

Abundance indices for long-lived tropical snappers: estimating standardized catch rates from spatially and temporally coarse logbook data

The Northern Demersal Scalefish Fishery has historically comprised a small fleet (≤10 vessels year−1) operating over a relatively large area off the northwest coast of Australia. This multispecies fishery primarily harvests two species of snapper: goldband snapper, Pristipomoides multidens and red emperor, Lutjanus sebae. A key input to age-structured assessments of these stocks has been the annual time-series of the catch rate. We used an approach that combined Generalized Linear Models, spatio-temporal imputation, and computer-intensive methods to standardize the fishery catch rates and report uncertainty in the indices. These analyses, which represent one of the first attempts to standardize fish trap catch rates, were also augmented to gain additional insights into the effects of targeting, historical effort creep, and spatio-temporal resolution of catch and effort data on trap fishery dynamics. Results from monthly reported catches (i.e. 1993 on) were compared with those reported daily from more recently (i.e. 2008 on) enhanced catch and effort logbooks. Model effects of catches of one species on the catch rates of another became more conspicuous when the daily data were analysed and produced estimates with greater precision. The rate of putative effort creep estimated for standardized catch rates was much lower than estimated for nominal catch rates. These results therefore demonstrate how important additional insights into fishery and fish population dynamics can be elucidated from such “pre-assessment” analyses.

Multiple instance dictionary learning for activity representation

This paper presents an effective feature representation method in the context of activity recognition. Efficient and effective feature representation plays a crucial role not only in activity recognition, but also in a wide range of applications such as motion analysis, tracking, 3D scene understanding etc. In the context of activity recognition, local features are increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational requirements, their performance is still limited for real world applications due to a lack of contextual information and models not being tailored to specific activities. We propose a new activity representation framework to address the shortcomings of the popular, but simple bag-of-words approach. In our framework, first multiple instance SVM (mi-SVM) is used to identify positive features for each action category and the k-means algorithm is used to generate a codebook. Then locality-constrained linear coding is used to encode the features into the generated codebook, followed by spatio-temporal pyramid pooling to convey the spatio-temporal statistics. Finally, an SVM is used to classify the videos. Experiments carried out on two popular datasets with varying complexity demonstrate significant performance improvement over the base-line bag-of-feature method.

Flight directionality of Tribolium castaneum soon after take-off under glasshouse and field conditions

Flight directionality of the rust-red flour beetle, Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae), was investigated under glasshouse and field conditions using sticky traps placed around dense experimental infestations of T. castaneum derived from field-collected samples. Although beetles of this species are known to fly quite readily, information on flight of beetles away from grain resources is limited. Under still glasshouse conditions, T. castaneum does not demonstrate strong horizontal or vertical trajectories in their initial flight behaviour. Flight was significantly directional in half of the replicates, but trapped beetles were only weakly concentrated around the mean direction of flight. In the field, by contrast, emigration of T. castaneum was strongly directional soon after flight initiation. The mean vector lengths were generally >0.5 which indicates that trapped beetles were strongly concentrated around the calculated mean flight direction. A circular-circular regression of mean flight vs. mean downwind direction suggested that flight direction was generally correlated with downwind direction. The mean height at which T. castaneum individuals initially flew was 115.4 ± 7.0 cm, with 58.3% of beetles caught no more than 1 m above the ground. The height at which beetles were trapped did not correlate with wind speed at the time of sampling, but the data do indicate that wind speed significantly affected T. castaneum flight initiation, because no beetles (or very few; no more than three) were trapped in the field when the mean wind speed was above 3 m s−1. This study thus demonstrates that wind speed and direction are both important aspects of flight behaviour of T. castaneum, and therefore of the spatio-temporal dynamics of this species.

Fine-tuning of unmanned aerial surveillance for ecological systems

Much of our understanding and management of ecological processes requires knowledge of the distribution and abundance of species. Reliable abundance or density estimates are essential for managing both threatened and invasive populations, yet are often challenging to obtain. Recent and emerging technological advances, particularly in unmanned aerial vehicles (UAVs), provide exciting opportunities to overcome these challenges in ecological surveillance. UAVs can provide automated, cost-effective surveillance and offer repeat surveys for pest incursions at an invasion front. They can capitalise on manoeuvrability and advanced imagery options to detect species that are cryptic due to behaviour, life-history or inaccessible habitat. UAVs may also cause less disturbance, in magnitude and duration, for sensitive fauna than other survey methods such as transect counting by humans or sniffer dogs. The surveillance approach depends upon the particular ecological context and the objective. For example, animal, plant and microbial target species differ in their movement, spread and observability. Lag-times may exist between a pest species presence at a site and its detectability, prompting a need for repeat surveys. Operationally, however, the frequency and coverage of UAV surveys may be limited by financial and other constraints, leading to errors in estimating species occurrence or density. We use simulation modelling to investigate how movement ecology should influence fine-scale decisions regarding ecological surveillance using UAVs. Movement and dispersal parameter choices allow contrasts between locally mobile but slow-dispersing populations, and species that are locally more static but invasive at the landscape scale. We find that low and slow UAV flights may offer the best monitoring strategy to predict local population densities in transects, but that the consequent reduction in overall area sampled may sacrifice the ability to reliably predict regional population density. Alternative flight plans may perform better, but this is also dependent on movement ecology and the magnitude of relative detection errors for different flight choices. Simulated investigations such as this will become increasingly useful to reveal how spatio-temporal extent and resolution of UAV monitoring should be adjusted to reduce observation errors and thus provide better population estimates, maximising the efficacy and efficiency of unmanned aerial surveys.

Co-distribution and co-infection of chikungunya and dengue viruses

BACKGROUND Chikungunya and dengue infections are spatio-temporally related. The current review aims to determine the geographic limits of chikungunya, dengue and the principal mosquito vectors for both viruses and to synthesise current epidemiological understanding of their co-distribution. METHODS Three biomedical databases (PubMed, Scopus and Web of Science) were searched from their inception until May 2015 for studies that reported concurrent detection of chikungunya and dengue viruses in the same patient. Additionally, data from WHO, CDC and Healthmap alerts were extracted to create up-to-date global distribution maps for both dengue and chikungunya. RESULTS Evidence for chikungunya-dengue co-infection has been found in Angola, Gabon, India, Madagascar, Malaysia, Myanmar, Nigeria, Saint Martin, Singapore, Sri Lanka, Tanzania, Thailand and Yemen; these constitute only 13 out of the 98 countries/territories where both chikungunya and dengue epidemic/endemic transmission have been reported. CONCLUSIONS Understanding the true extent of chikungunya-dengue co-infection is hampered by current diagnosis largely based on their similar symptoms. Heightened awareness of chikungunya among the public and public health practitioners in the advent of the ongoing outbreak in the Americas can be expected to improve diagnostic rigour. Maps generated from the newly compiled lists of the geographic distribution of both pathogens and vectors represent the current geographical limits of chikungunya and dengue, as well as the countries/territories at risk of future incursion by both viruses. These describe regions of co-endemicity in which lab-based diagnosis of suspected cases is of higher priority.

Human action recognition from video sequences

This PhD research has proposed new machine learning techniques to improve human action recognition based on local features. Several novel video representation and classification techniques have been proposed to increase the performance with lower computational complexity. The major contributions are the construction of new feature representation techniques, based on advanced machine learning techniques such as multiple instance dictionary learning, Latent Dirichlet Allocation (LDA) and Sparse coding. A Binary-tree based classification technique was also proposed to deal with large amounts of action categories. These techniques are not only improving the classification accuracy with constrained computational resources but are also robust to challenging environmental conditions. These developed techniques can be easily extended to a wide range of video applications to provide near real-time performance.

Neuronal K-Cl Cotransporter : Transcriptional Mechanisms of KCC2 Gene Regulation

K-Cl cotransporter 2 (KCC2) maintains a low intracellular Cl concentration required for fast hyperpolarizing responses of neurons to classical inhibitory neurotransmitters γ-aminobutyric acid (GABA) and glycine. Decreased Cl extrusion observed in genetically modified KCC2-deficient mice leads to depolarizing GABA responses, impaired brain inhibition, and as a consequence to epileptic seizures. Identification of mechanisms regulating activity of the SLC12A5 gene, which encodes the KCC2 cotransporter, in normal and pathological conditions is, thus, of extreme importance. Multiple reports have previously elucidated in details a spatio-temporal pattern of KCC2 expression. Among the characteristic features are an exclusive neuronal specificity, a dramatic upregulation during embryonic and early postnatal development, and a significant downregulation by neuronal trauma. Numerous studies confirmed these expressional features, however transcriptional mechanisms predetermining the SLC12A5 gene behaviour are still unknown. The aim of the presented thesis is to recognize such transcriptional mechanisms and, on their basis, to create a transcriptional model that would explain the established SLC12A5 gene behaviour. Up to recently, only one KCC2 transcript has been thought to exist. A particular novelty of the presented work is the identification of two SLC12A5 gene promoters (SLC12A5-1a and SLC12A5-1b) that produce at least two KCC2 isoforms (KCC2a and KCC2b) differing by their N-terminal parts. Even though a functional 86Rb+ assay reveals no significant difference between transport activities of the isoforms, consensus sites for several protein kinases, found in KCC2a but not in KCC2b, imply a distinct kinetic regulation. As a logical continuation, the current work presents a detailed analysis of the KCC2a and KCC2b expression patterns. This analysis shows an exclusively neuron-specific pattern and similar expression levels for both isoforms during embryonic and neonatal development in rodents. During subsequent postnatal development, the KCC2b expression dramatically increases, while KCC2a expression, depending on central nervous system (CNS) area, either remains at the same level or moderately decreases. In an attempt to explain both the neuronal specificity and the distinct expressional kinetics of the KCC2a and KCC2b isoforms during postnatal development, the corresponding SLC12A5-1a and SLC12A5-1b promoters have been subjected to a comprehensive bioinformatical analysis. Binding sites of several transcription factors (TFs), conserved in the mammalian SLC12A5 gene orthologs, have been identified that might shed light on the observed behaviour of the SLC12A5 gene. Possible roles of these TFs in the regulating of the SLC12A5 gene expression have been elucidated in subsequent experiments and are discussed in the current thesis.

Cellular and molecular regulation of mammalian blastocyst hatching

In mammals including humans, failure in blastocyst hatching and implantation leads to early embryonic loss and infertility. Prior to implantation, the blastocyst must hatch out of its acellular glycoprotein coat, the zona pellucida (ZP). The phenomenon of blastocyst hatching is believed to be regulated by (i) dynamic cellular components such as actin-based trophectodermal projections (TEPs), and (ii) a variety of autocrine and paracrine molecules such as growth factors, cytokines and proteases. The spatio-temporal regulation of zona lysis by blastocyst-derived cellular and molecular signaling factors is being keenly investigated. Our studies show that hamster blastocyst hatching is acelerated by growth factors such as heparin binding-epidermal growth factor and leukemia inhibitory factor and that embryo-derived, cysteine proteases including cathepsins are responsible for blastocyst hatching. Additionally, we believe that cyclooxygenase-generated prostaglandins, estradiol-17 beta mediated estrogen receptor-alpha signaling and possibly NF kappa B could be involved in peri-hatching development. Moreover, we show that TEPs are intimately involved with lysing ZP and that the TEPs potentially enrich and harbor hatching-enabling factors. These observations provide new insights into our understanding of the key cellular and molecular regulators involved in the phenomenon of mammalian blastocyst hatching, which is essential for the establishment of early pregnancy.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

Spatial and vertical heterogeneities in aerosol properties over oceanic regions around India: Implications for radiative forcing

The influence of atmospheric aerosols on Earth's radiation budget and hence climate, though well recognized and extensively investigated in recent years, remains largely uncertain mainly because of the large spatio-temporal heterogeneity and the lack of data with adequate resolution. To characterize this diversity, a major multi-platform field campaign ICARB (Integrated Campaign for Aerosols, gases and Radiation Budget) was carried out during the pre-monsoon period of 2006 over the Indian landmass and surrounding oceans, which was the biggest such campaign ever conducted over this region. Based on the extensive and concurrent measurements of the optical and physical properties of atmospheric aerosols during ICARB, the spatial distribution of aerosol radiative forcing was estimated over the entire Bay of Bengal (BoB), northern Indian Ocean and Arabian Sea (AS) as well as large spatial variations within these regions. Besides being considerably lower than the mean values reported earlier for this region, our studies have revealed large differences in the forcing components between the BoB and the AS. While the regionally averaged aerosol-induced atmospheric forcing efficiency was 31 +/- 6 W m(-2) tau(-1) for the BoB, it was only similar to 18 +/- 7 W m(-2) tau(-1) for the AS. Airborne measurements revealed the presence of strong, elevated aerosol layers even over the oceans, leading to vertical structures in the atmospheric forcing, resulting in significant warming in the lower troposphere. These observations suggest serious climate implications and raise issues ranging from the impact of aerosols on vertical thermal structure of the atmospheric and hence cloud formation processes to monsoon circulation.