Genetic control of flowering in spotted gum, Corymbia citriodora subsp. variegata and C. maculata

Genetically controlled asynchrony in anthesis is an effective barrier to gene flow between planted and native forests. We investigated the degree of genetically controlled variation in the timing of key floral developmental stages in a major plantation species in subtropical Australia, Corymbia citriodora subsp. variegata K.D. Hill and L.A.S Johnson, and its relative C. maculata K.D. Hill and L.A.S. Johnson. Flowering observations were made in a common garden planting at Bonalbo in northern New South Wales in spring on 1855 trees from eight regions over three consecutive years, and monthly on a subset of 208 trees for 12 months. Peak anthesis time was stable over years and observations from translocated trees tended to be congruent with the observations in native stands, suggesting strong genetic control of anthesis time. A cluster of early flowering provenances was identified from the north-east of the Great Dividing Range. The recognition of a distinct flowering race from this region accorded well with earlier evidence of adaptive differentiation of populations from this region and geographically-structured genetic groupings in C. citriodora subsp. variegata. The early flowering northern race was more fecund, probably associated with its disease tolerance and greater vigour. Bud abundance fluctuated extensively at the regional level across 3 years suggesting bud abundance was more environmentally labile than timing of anthesis. Overall the level of flowering in the planted stand (age 12 years) was low (8–12% of assessed trees with open flowers), and was far lower than in nearby native stands. Low levels of flowering and asynchrony in peak anthesis between flowering races of C. citriodora subsp. variegata may partially mitigate a high likelihood of gene flow where the northern race is planted in the south of the species range neighbouring native stands

Enhanced processing of SPOT multispectral satellite imagery for environmental monitoring and modelling

The Taita Hills in southeastern Kenya form the northernmost part of Africa’s Eastern Arc Mountains, which have been identified by Conservation International as one of the top ten biodiversity hotspots on Earth. As with many areas of the developing world, over recent decades the Taita Hills have experienced significant population growth leading to associated major changes in land use and land cover (LULC), as well as escalating land degradation, particularly soil erosion. Multi-temporal medium resolution multispectral optical satellite data, such as imagery from the SPOT HRV, HRVIR, and HRG sensors, provides a valuable source of information for environmental monitoring and modelling at a landscape level at local and regional scales. However, utilization of multi-temporal SPOT data in quantitative remote sensing studies requires the removal of atmospheric effects and the derivation of surface reflectance factor. Furthermore, for areas of rugged terrain, such as the Taita Hills, topographic correction is necessary to derive comparable reflectance throughout a SPOT scene. Reliable monitoring of LULC change over time and modelling of land degradation and human population distribution and abundance are of crucial importance to sustainable development, natural resource management, biodiversity conservation, and understanding and mitigating climate change and its impacts. The main purpose of this thesis was to develop and validate enhanced processing of SPOT satellite imagery for use in environmental monitoring and modelling at a landscape level, in regions of the developing world with limited ancillary data availability. The Taita Hills formed the application study site, whilst the Helsinki metropolitan region was used as a control site for validation and assessment of the applied atmospheric correction techniques, where multiangular reflectance field measurements were taken and where horizontal visibility meteorological data concurrent with image acquisition were available. The proposed historical empirical line method (HELM) for absolute atmospheric correction was found to be the only applied technique that could derive surface reflectance factor within an RMSE of < 0.02 ps in the SPOT visible and near-infrared bands; an accuracy level identified as a benchmark for successful atmospheric correction. A multi-scale segmentation/object relationship modelling (MSS/ORM) approach was applied to map LULC in the Taita Hills from the multi-temporal SPOT imagery. This object-based procedure was shown to derive significant improvements over a uni-scale maximum-likelihood technique. The derived LULC data was used in combination with low cost GIS geospatial layers describing elevation, rainfall and soil type, to model degradation in the Taita Hills in the form of potential soil loss, utilizing the simple universal soil loss equation (USLE). Furthermore, human population distribution and abundance were modelled with satisfactory results using only SPOT and GIS derived data and non-Gaussian predictive modelling techniques. The SPOT derived LULC data was found to be unnecessary as a predictor because the first and second order image texture measurements had greater power to explain variation in dwelling unit occurrence and abundance. The ability of the procedures to be implemented locally in the developing world using low-cost or freely available data and software was considered. The techniques discussed in this thesis are considered equally applicable to other medium- and high-resolution optical satellite imagery, as well the utilized SPOT data.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

Joint Regression and Association Models for Repeated Categorical Responses

The focus of this study is on statistical analysis of categorical responses, where the response values are dependent of each other. The most typical example of this kind of dependence is when repeated responses have been obtained from the same study unit. For example, in Paper I, the response of interest is the pneumococcal nasopharengyal carriage (yes/no) on 329 children. For each child, the carriage is measured nine times during the first 18 months of life, and thus repeated respones on each child cannot be assumed independent of each other. In the case of the above example, the interest typically lies in the carriage prevalence, and whether different risk factors affect the prevalence. Regression analysis is the established method for studying the effects of risk factors. In order to make correct inferences from the regression model, the associations between repeated responses need to be taken into account. The analysis of repeated categorical responses typically focus on regression modelling. However, further insights can also be gained by investigating the structure of the association. The central theme in this study is on the development of joint regression and association models. The analysis of repeated, or otherwise clustered, categorical responses is computationally difficult. Likelihood-based inference is often feasible only when the number of repeated responses for each study unit is small. In Paper IV, an algorithm is presented, which substantially facilitates maximum likelihood fitting, especially when the number of repeated responses increase. In addition, a notable result arising from this work is the freely available software for likelihood-based estimation of clustered categorical responses.

Flying-Fox Roost Disturbance and Hendra Virus Spillover Risk

Bats of the genus Pteropus (flying-foxes) are the natural host of Hendra virus (HeV) which periodically causes fatal disease in horses and humans in Australia. The increased urban presence of flying-foxes often provokes negative community sentiments because of reduced social amenity and concerns of HeV exposure risk, and has resulted in calls for the dispersal of urban flying-fox roosts. However, it has been hypothesised that disturbance of urban roosts may result in a stress-mediated increase in HeV infection in flying-foxes, and an increased spillover risk. We sought to examine the impact of roost modification and dispersal on HeV infection dynamics and cortisol concentration dynamics in flying-foxes. The data were analysed in generalised linear mixed models using restricted maximum likelihood (REML). The difference in mean HeV prevalence in samples collected before (4.9%), during (4.7%) and after (3.4%) roost disturbance was small and non-significant (P = 0.440). Similarly, the difference in mean urine specific gravity-corrected urinary cortisol concentrations was small and non-significant (before = 22.71 ng/mL, during = 27.17, after = 18.39) (P= 0.550). We did find an underlying association between cortisol concentration and season, and cortisol concentration and region, suggesting that other (plausibly biological or environmental) variables play a role in cortisol concentration dynamics. The effect of roost disturbance on cortisol concentration approached statistical significance for region, suggesting that the relationship is not fixed, and plausibly reflecting the nature and timing of disturbance. We also found a small positive statistical association between HeV excretion status and urinary cortisol concentration. Finally, we found that the level of flying-fox distress associated with roost disturbance reflected the nature and timing of the activity, highlighting the need for a ‘best practice’ approach to dispersal or roost modification activities. The findings usefully inform public discussion and policy development in relation to Hendra virus and flying-fox management.

Hazard Function Models to Estimate Mortality Rates Affecting Fish Populations with Application to the Sea Mullet (Mugil cephalus) Fishery on the Queensland Coast (Australia)

Fisheries management agencies around the world collect age data for the purpose of assessing the status of natural resources in their jurisdiction. Estimates of mortality rates represent a key information to assess the sustainability of fish stocks exploitation. Contrary to medical research or manufacturing where survival analysis is routinely applied to estimate failure rates, survival analysis has seldom been applied in fisheries stock assessment despite similar purposes between these fields of applied statistics. In this paper, we developed hazard functions to model the dynamic of an exploited fish population. These functions were used to estimate all parameters necessary for stock assessment (including natural and fishing mortality rates as well as gear selectivity) by maximum likelihood using age data from a sample of catch. This novel application of survival analysis to fisheries stock assessment was tested by Monte Carlo simulations to assert that it provided unbiased estimations of relevant quantities. The method was applied to the data from the Queensland (Australia) sea mullet (Mugil cephalus) commercial fishery collected between 2007 and 2014. It provided, for the first time, an estimate of natural mortality affecting this stock: 0.22±0.08 year −1 .

Computing the Stochastic Complexity of Simple Probabilistic Graphical Models

Minimum Description Length (MDL) is an information-theoretic principle that can be used for model selection and other statistical inference tasks. There are various ways to use the principle in practice. One theoretically valid way is to use the normalized maximum likelihood (NML) criterion. Due to computational difficulties, this approach has not been used very often. This thesis presents efficient floating-point algorithms that make it possible to compute the NML for multinomial, Naive Bayes and Bayesian forest models. None of the presented algorithms rely on asymptotic analysis and with the first two model classes we also discuss how to compute exact rational number solutions.

Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering

The Minimum Description Length (MDL) principle is a general, well-founded theoretical formalization of statistical modeling. The most important notion of MDL is the stochastic complexity, which can be interpreted as the shortest description length of a given sample of data relative to a model class. The exact definition of the stochastic complexity has gone through several evolutionary steps. The latest instantation is based on the so-called Normalized Maximum Likelihood (NML) distribution which has been shown to possess several important theoretical properties. However, the applications of this modern version of the MDL have been quite rare because of computational complexity problems, i.e., for discrete data, the definition of NML involves an exponential sum, and in the case of continuous data, a multi-dimensional integral usually infeasible to evaluate or even approximate accurately. In this doctoral dissertation, we present mathematical techniques for computing NML efficiently for some model families involving discrete data. We also show how these techniques can be used to apply MDL in two practical applications: histogram density estimation and clustering of multi-dimensional data.

Quantification of the inevitable: the influence of soil macrofauna on soil water movement in rehabilitated open-cut mined lands

Recolonisation of soil by macrofauna (especially ants, termites and earthworms) in rehabilitated open-cut mine sites is inevitable and, in terms of habitat restoration and function, typically of great value. In these highly disturbed landscapes, soil invertebrates play a major role in soil development (macropore configuration, nutrient cycling, bioturbation, etc.) and can influence hydrological processes such as infiltration, seepage, runoff generation and soil erosion. Understanding and quantifying these ecosystem processes is important in rehabilitation design, establishment and subsequent management to ensure progress to the desired end goal, especially in waste cover systems designed to prevent water reaching and transporting underlying hazardous waste materials. However, the soil macrofauna is typically overlooked during hydrological modelling, possibly due to uncertainties on the extent of their influence, which can lead to failure of waste cover systems or rehabilitation activities. We propose that scientific experiments under controlled conditions and field trials on post-mining lands are required to quantify (i) macrofauna–soil structure interactions, (ii) functional dynamics of macrofauna taxa,and (iii) their effects on macrofauna and soil development over time. Such knowledge would provide crucial information for soil water models, which would increase confidence in mine waste cover design recommendations and eventually lead to higher likelihood of rehabilitation success of open-cut mining land.

Co2 emissions and income trajectory in Australia: The role of technological change

This study investigates the relationship between per capita carbon dioxide (CO2) emissions and per capita GDP in Australia, while controlling for technological state as measured by multifactor productivity and export of black coal. Although technological progress seems to play a critical role in achieving long term goals of CO2 reduction and economic growth, empirical studies have often considered time trend to proxy technological change. However, as discoveries and diffusion of new technologies may not progress smoothly with time, the assumption of a deterministic technological progress may be incorrect in the long run. The use of multifactor productivity as a measure of technological state, therefore, overcomes the limitations and provides practical policy directions. This study uses recently developed bound-testing approach, which is complemented by Johansen- Juselius maximum likelihood approach and a reasonably large sample size to investigate the cointegration relationship. Both of the techniques suggest that cointegration relationship exists among the variables. The long-run and short-run coefficients of CO2 emissions function is estimated using ARDL approach. The empirical findings in the study show evidence of the existence of Environmental Kuznets Curve type relationship for per capita CO2 emissions in the Australian context. The technology as measured by the multifactor productivity, however, is not found as an influencing variable in emissionsincome trajectory.

Head motion and Inattention/Hyperactivity share common genetic influences: Implications for fMRI studies of ADHD

Head motion (HM) is a well known confound in analyses of functional MRI (fMRI) data. Neuroimaging researchers therefore typically treat HM as a nuisance covariate in their analyses. Even so, it is possible that HM shares a common genetic influence with the trait of interest. Here we investigate the extent to which this relationship is due to shared genetic factors, using HM extracted from resting-state fMRI and maternal and self report measures of Inattention and Hyperactivity-Impulsivity from the Strengths and Weaknesses of ADHD Symptoms and Normal Behaviour (SWAN) scales. Our sample consisted of healthy young adult twins (N = 627 (63% females) including 95 MZ and 144 DZ twin pairs, mean age 22, who had mother-reported SWAN; N = 725 (58% females) including 101 MZ and 156 DZ pairs, mean age 25, with self reported SWAN). This design enabled us to distinguish genetic from environmental factors in the association between head movement and ADHD scales. HM was moderately correlated with maternal reports of Inattention (r = 0.17, p-value = 7.4E-5) and Hyperactivity-Impulsivity (r = 0.16, p-value = 2.9E-4), and these associations were mainly due to pleiotropic genetic factors with genetic correlations [95% CIs] of rg = 0.24 [0.02, 0.43] and rg = 0.23 [0.07, 0.39]. Correlations between self-reports and HM were not significant, due largely to increased measurement error. These results indicate that treating HM as a nuisance covariate in neuroimaging studies of ADHD will likely reduce power to detect between-group effects, as the implicit assumption of independence between HM and Inattention or Hyperactivity-Impulsivity is not warranted. The implications of this finding are problematic for fMRI studies of ADHD, as failing to apply HM correction is known to increase the likelihood of false positives. We discuss two ways to circumvent this problem: censoring the motion contaminated frames of the RS-fMRI scan or explicitly modeling the relationship between HM and Inattention or Hyperactivity-Impulsivity

Making and changing wills: Prevalence, predictors, and triggers

Wills are important social, economic, and legal documents. Yet little is known about current will making practices and intentions. A comprehensive national database on the prevalence of will making in Australia was developed to identify who is or is not most likely to draw up a will and triggers for making and changing wills. A national survey of 2,405 adults aged above 18 years was administered by telephone in August and September 2012. Fifty-nine percent of the Australian adult population has a valid will, and the likelihood of will making increases with age and estate value. Efforts to get organized, especially in combination with life stage and asset changes trigger will making; procrastination, rather than a strong resistance, appears to explain not making a will. Understanding will making is timely in the context of predicted significant intergenerational transfers of wealth, changing demographics, and a renewed emphasis on retirement planning.

Kuka on potilas? : Suomalaisen sikiöseulontakäytännön sosiaalieettistä tarkastelua

Who is the patient? A social-ethical study of the Finnish practice of prenatal screening. The aim of this study is to examine the Finnish practice of prenatal screening from a social-ethical perspective. Analyzing ethical problems in medicine and medical practice only on a general scale may conceal relevant ethical dilemmas. Previous studies have suggested that many pregnant women view the prenatal screening practices customary in the Finnish maternal care system as intimidating and oppressive. This study analyzes the ethical questions of prenatal screening by focusing on the experiences and decision-making of a pregnant woman. Finnish women s experiences of and decision-making on the most common prenatal screening methods are reflected in the basic principles of biomedical ethics described by Tom L. Beauchamp and James F. Childress in Principles of Biomedical Ethics. To concretize women s experiences I refer to studies of Finnish women s experiences of prenatal screenings. This study shows that the principles of autonomy, non-maleficence and beneficence seem to materialize rather poorly in the Finnish practice of prenatal screening. The main ethical problem with prenatal screening is that the likelihood of a foetal cure is very limited and, upon detection of an affected foetus, the choice is usually whether to continue with the pregnancy or to undergo an abortion. Although informed consent should be required, women s participation in prenatal testing is, in many cases at least, not based on their active decision. Many women experience severe anxiety when they receive a positive screening result and must wait for the final results. Medical studies indicate that long- term anxiety may negatively influence the foetus and the mother-child relationship. This study shows that the practice of prenatal screening as such may cause more harm than benefit to many pregnant women and their foetuses. This study examines the decision-making process of a pregnant woman by using the theory of medical casuistry described in Jonsen, Siegler and Winslade s Clinical Ethics. This study focuses on each of the four points of view recommended by the theory. The main problem seems to be the question of whom the patient of prenatal screening is and whom the practice is intended to benefit: the mother, the foetus, the family or society? This study shows that the concepts of health in Finnish maternal care in general, and of the prenatal screening system in particular, differ considerably. It also demonstrates that the purpose and the aims of prenatal screening, aside from the woman s right to choose, has been expressed neither in Finnish public health programmes nor in the public recommendations of prenatal screening. This study suggests that the practice of prenatal screening is a statement, though unexpressed, of public health policy and as such comprises part of the policy of disability. This study further demonstrates that through a single explicit aim (the woman s right to choose) society actually evades its obligation to women by saddling pregnant women with the entire moral responsibility as well as the possible negative consequences of her choice, such as sorrow, regrets and moral balancing. The study reveals several ethical problems in the Finnish practice of prenatal screening. Such problems should be dealt with as the Finnish practice of prenatal screening advances.

Regional resilience: Pre-service teacher preparation to teach in the bush

This paper reports on the outcomes of a two year ALTC Competitive Research and Development Project that aimed to "Develop Strategies at the Pre-Service Level to Address Critical Teacher Attraction and Retention Issues in Australian Rural, Regional and Remote Schools". As well as developing a ‘training framework’ and teaching guides to increase the capacity and credibility of four universities to prepare educators who might venture out of the metropolitan area to teach, data were gathered from pre-service and graduate teachers to analyse regional resilience. It was found that there was a strong likelihood to participate in a regional practicum and stay in a non-metropolitan community once they graduated from university if they had a positive attitude to regional Western Australia either through a family connection or previous experience. Recommendations from this study emphasise the importance of having pre-service students participate in positive regional experiences early in their university study.

Essays on Banking Crises

This thesis aims at finding the role of deposit insurance scheme and central bank (CB) in keeping the banking system safe. The thesis also studies the factors associated with long-lasting banking crises. The first essay analyzes the effect of using explicit deposit insurance scheme (EDIS), instead of using implicit deposit insurance scheme (IDIS), on banking crises. The panel data for the period of 1980-2003 includes all countries for which the data on EDIS or IDIS exist. 70% of the countries in the sample are less developed countries (LDCs). About 55% of the countries adopting EDIS also come from LDCs. The major finding is that the using of EDIS increases the crisis probability at a strong significance level. This probability is greater if the EDIS is inefficiently designed allowing higher scope of moral hazard problem. Specifically, the probability is greater if the EDIS provides higher coverage to deposits and if it is less powerful from the legal point of view. This study also finds that the less developed a country is to handle EDIS, the higher the chance of banking crisis. Once the underdevelopment of an economy handling the EDIS is controlled, the EDIS separately is no longer a significant factor of banking crises. The second essay aims at determining whether a country s powerful CB can lessen the instability of the banking sector by minimizing the likelihood of a banking crisis. The data used include indicators of the CB s autonomy for a set of countries over the period of 1980-89. The study finds that in aggregate a more powerful CB lessens the probability of banking crisis. When the CB s authority is disentangled with respect to its responsibilities, the study finds that the longer tenure of CB s chief executive officer and the greater power of CB in assigning interest rate on government loans are necessary for reducing the probability of banking crisis. The study also finds that the probability of crisis reduces more if an autonomous CB can perform its duties in a country with stronger law and order tradition. The costs of long-lasting banking crises are high because both the depositors and the investors lose confidence in the banking system. For a rapid recovery of a crisis, the government very often undertakes one or more crisis resolution policy (CRP) measures. The third essay examines the CRP and other explanatory variables correlated with the durations of banking crises. The major finding is that the CRP measure allowing the regulation forbearance to keep the insolvent banks operative and the public debt relief program are respectively strongly and weakly significant to increase the durations of crises. Some other explanatory variables, which were found by previous studies to be related with the probability of crises to occur, are also correlated with the durations of crises.