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In recent years there has been an oft-held assumption as to the decline of traditions as well as folk belief amidst the technological modern age. The current thesis seeks to bring to light the various rituals, traditions and beliefs surrounding pregnancy in Japanese society, arguing that, although changed, they are still very much alive and a large part of the pregnancy experience. Current perception and ideas were gathered through a series of in depth interviews with 31 Japanese females of varying ages and socio-cultural backgrounds. These current perceptions were then compared to and contrasted with historical data of a folkloristic nature, seeking to highlight developments and seek out continuities. This was done within the theoretical framework of the liminal nature of that which is betwixt and between as set forth by Victor Turner, as well as theories set forth by Mary Douglas and her ideas of the polluting element of the liminal. It quickly became obvious that the beliefs were still strong having though developed from a person-to-person communication and into a set of knowledge acquired by the mother largely from books, magazines and or offline.

The purpose of this thesis is to explore how useful a classificatory research approach can be to researching mortality patterns. This is conducted through creating an area classification of small area mortality patterns for England and Wales (2006 to 2009). The resulting area classification is then applied to research the existence of area effects on health, to assess how useful it is as an analytical tool. To successfully achieve this, the thesis begins through reviewing the literature to examine the importance of taking an area perspective to researching mortality. This was extended to assess the extent of which an area classification could build upon past research. Data and methodology issues were discussed, to evaluate the best approach required to building a high quality and relevant area classification. The area classification was built and statistical testing was conducted to assess the stability of it. The area classification was then interpreted to examine the main mortality patterns that dominant England and Wales. Explanations for the clusters were derived from demographic, social and geographical factors. The area classification was then analysed to explore the existence of area effects through a multi-level analysis. This was extended to examine the impact on health as people migrated between the clusters, exploring whether area effects were observed. Benchmarking of these results was performed, comparing it to using GORs instead to group the data, to evaluate how useful the results were.

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Demography is the study of population dynamics. Populations can be considered as groups of individuals living within a given region. These simple statements encompass highly disparate systems, which respond to demographic and environmental stochasticity in predictable and unpredictable ways. The responses depend on the structure of the population, since individuals can have vastly different survival and recruitment, which, with dispersal, determine population abundance. Whilst some variation is inter-st(age) – increases in reproductive performance with age, for example – substantial intra-st(age) variation is not uncommon. Using longterm individual-based data on two disparate vertebrate populations, the focus of this thesis is the interaction between structure and stochasticity in demographic models, and consequences on resultant aspects of population growth. Structured models that incorporated variation in demographic rates detected marked differences within, between and across diverse habitats for different age-classes in both populations. These results were consistent for a wide range of scaling and definition to account for mathematical dependence. Spatial structure was more influential than age-structure in responses to stochastic predation. Despite significant changes in performance and phenotype with age, individual heterogeneity within ageclasses was vast. These results are of importance for conservation and management action, as well as predictors of evolutionary change. The population is a fundamental force in ecology and evolution. This work adds weight to the argument that characteristics of individual performance in response to variability in their environments are pivotal to increased understanding of changes in population abundance. These individual responses are dependent upon the opportunity generated by population structure. A failure to incorporate either structure or stochasticity neglects crucial aspects in population regulation, and therefore ecological and evolutionary change.

This thesis assesses approaches to population surface modeling by pulling together the benefits of reference gridded population data with local regression procedures and geographically weighted regression. This study provides a more detailed assessment of surface modelling accuracy than was achieved in any previous studies to assess factors which explain errors in the predictions. The primary aim of this thesis is to evaluate Martin’s (1989) population surface modeling approach and also design and implement a method using secondary data, suitable for application in England and Wales. This research is based on the idea that population data presented for a single zone could be redistributed in the zone using local parameters such as housing density. A weighted sum performs the spatial redistribution. The thesis also aims to make use of remote sensing (RS) data and image processing techniques such as maximum likelihood classification and normalised difference vegetation index to identify (un) populated cells. The potential of Landsat images and RS data analysis is assessed particularly for countries where high quality land use data are not readily obtainable, and their generation is not feasible in the near future. This thesis focuses on the identification of unpopulated cells, rather than populated units, using RS data. Case studies make use of data from Northern Ireland (NI), and Jonkoping in southern Sweden. The outcomes indicate the impact of population density, population variance, and resolution of source zones on the accuracy of population allocation to grid cells using Martin’s (1989) model. The results show significant accuracy in prediction to 100m cells using an alternative approach based on settlement data for NI and this is recommended as an alternative method for England and Wales. It also concluded that there the potential to generate population surfaces using Landsat data for areas where local residential data are not easily accessible.