Most life forms, including plants, are more or less susceptible to infection by pathogens. Whereas plant-pathogen interactions are well studied in human-managed systems they are less known in natural ecosystems. In this thesis the interactions between the sterilising anther-smut fungus Microbotryum silenes-dioicae and the host plant Silene dioica were studied in natural habitats in the Skeppsvik archipelago in northern Sweden. The purpose was to study some population characteristics that can potentially influence the colonization of anther-smut (Microbotryum silenes-dioicae) in young Silene dioica populations. Specifically, it was tested whether the population age, floral-  and total density, population size and distances to nearest diseased populations affect incidence of disease (presence of disease) and prevalence of disease (proportion of diseased individuals in populations) in younger host populations. It was found that incidence and prevalence of disease increased with host population age and size. In addition, it was seen that distances to diseased populations could not explain incidence or prevalence of disease. These results can potentially be used to predict disease risk in similar plant-pathogen systems.

Population models are very often used and considered useful in the policy-making process and for planning purposes. In this research I have tried to illuminate the problem of analysing population evolution in space by using three models which cover a wide spectrum of complementary methodologies: a The Hotell.ing-Puu model b A multiregional demographic model c A synergetic model Hotelling's work and Puu's later generalization have produced theoretical continuous models treating population growth and dispersal in a combined logistic growth and diffusion equation. The multiregional model is a discrete model based on the Markovian assumption which simulates the population evolution disaggregated by age and region. It is further assumed that this population is governed by a given pattern of growth and interregional mobility. The synergetic model is also a discrete model based on the Markovian assumption incorporating a probabilistic framework with causal structure. The quantitative description of the population dynamics is treated in terms of trend parameters, which are correlated in turn with demo-economic factors. / <p>Diss. Umeå : Umeå universitet, 1988</p> / Digitalisering@umu

This diploma thesis summarises current approaches to age management, or human resources management taking in account the age and skills of employees in the Czech Republic. The theoretical part of this paper deals with the background of this concept, describes the present demographical development, its consequences in the labour field, and the problem of aging population which is visible in the need to adapt applied management strategies in organisations to this trend. There are mentioned several programmes, thoughts, and legislative measures on which the newest concepts and strategic plans in Europe and the Czech Republic are based. The empirical part of the thesis focuses on a specific level of organisations, and consists of two surveys. The first one is a comparative case study for which data were collected in two organisations which have recently implemented measures stemming from age management strategies. These measures are then specified and confronted with the statements of the employees who, in semi-structured interviews with the author, talked about the changes that were put into practice under the concept of age management, and about the discrimination of persons over 50 years of age on the labour market. The second survey was carried out by a questionnaire distributed online to...

The demographic transition led to an added productivity commonly referred to as the demographic divided, which resulted in high rates of economic growth in most of the world. The general consensus is that the increased pace of economic growth was attained largely thanks to changes in population age structure. However, the literature contains evidence that the population structure does not have a significant impact on economic growth and that improvements in education attainment have in fact been responsible for the high rates of economic growth. These claims are in contradiction with most of the literature and can have important implications for future research and policy making. Since these claims have not been, to the best of our knowledge, verified, this thesis aims to replicate the original research using newer and more suitable data for a higher number of countries. In addition to the original research, analysis is also performed on various subsamples based on governance and cultural indicators. The level and the change in education attainment did not appear statistically significant in most of the regressions, so the claims could not be proved or disproved. However, important insights about the role of not only population structure and labor force participation in explaining economic growth were...

Pension schemes are facing more difficulties on matching their underlying liabilities with assets, mainly due to faster mortality improvements for their underlying populations, better environments and medical treatments and historically low interest rates. Given most of the pension schemes are relatively much smaller than the national population, modelling and forecasting the small populations' longevity risk become urgent tasks for both the industrial practitioners and academic researchers. This thesis starts with a systematic analysis on the influence of population size on the uncertainties of mortality estimates and forecasts with a stochastic mortality model, based on a parametric bootstrap methodology with England and Wales males as our benchmark population. The population size has significant effect on the uncertainty of mortality estimates and forecasts. The volatilities of small populations are over-estimated by the maximum likelihood estimators. A Bayesian model is developed to improve the estimation of the volatilities and the predictions of mortality rates for the small populations by employing the information of larger population with informative prior distributions. The new model is validated with the simulated small death scenarios. The Bayesian methodologies generate smoothed estimations for the mortality rates. Moreover, a methodology is introduced to use the information of large population for obtaining unbiased volatilities estimations given the underlying prior settings. At last, an empirical study is carried out based on the Scotland mortality dataset.