A cultivated environment: Exploring the global distribution of plants in gardens, parks and streetscapes

Plants cultivated in gardens, parks and streetscapes are becoming increasingly important to peoples?? experience of biological life, and have been the recent focus of research in ecology, invasion biology, human geography and sociology. However patterns of distribution have not previously been explored at a global scale. In this study, global patterns in the distribution of cultivated floras were explored to determine the significance of biophysical and social factors driving species distributions. The taxonomic similarity of 72 published species lists was examined, covering a wide geographic and climatic range and a variety of land uses. Cultivated floras across urban and rural settlements were found to be very different and unsurprisingly to be strongly filtered by temperature. However we found that human behaviour may overcome other physical drivers of plant distribution such as rainfall in some instances. Social factors were also found to be important. Having a different dominant language (a proxy for cultural background) and difference in GDP per person (a proxy for household income) were also related to the dissimilarity of cultivated floras. Differences in both the social and physical environment are related to floristic differences between cities. However, we recognise that other factors identified in the literature but unsuited to meta-analysis, may also influence the composition of cultivated landscapes. These include changes in policy relating to the provision of street and park vegetation, the availability of plants from nurseries and the preferences of influential gardeners and landscape designers. The significance of the relationship between temperature and species composition suggests that cultivated floras are likely to change in response to climate change. The high level of dissimilarity observed between settlements suggests that patterns of potential naturalisation of cultivated plants are likely to be more complex than currently accepted.     

Linking Advertising,Materialism, and Life Satisfaction

This paper develops theory related to advertising, materialism, and life satisfaction by formally testing explanations related to the antecedents and consequences of materialism. Survey data were collected from seven major cities each in a different country (Australia, Bosnia/Herzegovina, Germany, Egypt, Korea, Turkey, and the USA) using a probability sample (cluster sampling method involving income stratification). The results showed that the extent to which advertising is perceived to be materialistic contributes to materialism. Materialism, in turn, leads to the frequent use of various standards of comparison in making judgments about standard of living. As judgments about standard of living increase, standard of living is evaluated more negatively. In turn, negative self-evaluations contribute significantly to dissatisfaction with life.     

Live supervision in the same room

Following a brief explanation of live supervision, its advantages as a practice teaching method are outlined. The main part of the article focusses on detailed and practical suggestions for the preparation and conduct of live supervision sessions. Discussion then centres around some of the pitfalls and ethical issues which need to be considered. The article concludes by advocating that live supervision can make an important contribution to the current drive to improve practice competence in social work.     

Platonic Forehand versus Aristotelian Smash - the use of computers as macroscopes in knowing the social world

This paper draws on Desrosie ¤ res, Hayles and Tukey in arguing for an exploratory approach to the use of numerical taxonomy and related approaches in quantitative social research. It asserts that rather than trying to develop algorithm (either in the form of equation sets or game rules) based representations which abstract 'variables' as analogies of Newtonian forces, we should centre on cases and deal with classifications. Then trajectories can be explored in terms of changes both in the classification location of particular cases and changes in the actual form of the classification sets themselves. This approach seems to correspond with Aristotle's notion of intuitive induction with computing technology understood as extending the cognitive capacities of the taxonomist.     

Tracking national and regional spatial-temporal mortality risk associated with NO2 concentrations in Canada: a Bayesian hierarchical two-level model

The association between daily variations in urban air quality and mortality has been well documented using time series statistical methods. This approach assumes a constant association over time. We develop a space-time dynamic model that relaxes this assumption, thus more directly examining the hypothesis that improvements in air quality translate into improvements in public health. We postulate a Bayesian hierarchical two-level model to estimate annual mortality risks at regional and national levels and to track both risk and heterogeneity of risk within and between regions over time. We illustrate our methods using daily nitrogen dioxide concentrations (NO2) and nonaccidental mortality data collected for 1984-2004 in 24 Canadian cities. Estimates of risk and heterogeneity are compared by cause of mortality (cardio-pulmonary [CP] versus non-CP) and season, respectively. Over the entire period, the NO2 risk for CP mortality was slightly lower but with a narrower credible interval than that for non-CP mortality, mainly due to an unusually low risk for a single year (1998). Warm season NO2 risk was higher than cold season risk for both CP and non-CP mortality. For 21 years overall there were no significant differences detected among the four regional NO2 risks. We found overall that there was no strong evidence for time trends in NO2 risk at national or regional levels. However, an increasing linear time trend in the annual between-region heterogeneities was detected, which suggests the differences in risk among the four regions are getting larger, and further studies are necessary to understand the increasing heterogeneity.     

Sterilizing the "Feeble-minded": Eugenics in Alberta, Canada, 1929–1972

Abstract Between 1929 and 1972, the Alberta Eugenics Board recommended that 4739 residents of the province be sterilized. However, only 60% of these individuals, 2834 in total, were ultimately sterilized since the legislation under which the Eugenics Board operated required patient consent to be obtained unless the individual recommended for sterilization was diagnosed as "mentally defective." Women, teenagers and young adults, and Aboriginals were particularly targeted by the Alberta Eugenics Board. The Board pursued its sterilization mandate extremely aggressively and, because of a unique set of social, political and economic circumstances in the province, continued to operate long after other political jurisdictions in North America had set aside their involuntary sterilization programs.     

Using the Summed Rank Cusum for monitoring environmental data from industrial processes

Environmental issues have become a hot topic recently, especially those surrounding industrial outputs. Effluents, emissions, outflows, by-products, waste materials, product de-commissioning, land reclamation and energy consumption are all the subject of monitoring, either under new legislation or through economic necessity. Many types of environmental data are often difficult to understand or measure because of their unusual distribution of values however. Standard methods of monitoring these data types often fail or are unwieldy. The scarcity of events, small volume measurements and the unusual time scales sometimes involved add to the complexity of the task. One recently developed monitoring technique is the Summed Rank Cusum (SRC) that applies non-parametric methods to a standard chart. The SRC can be used diagnostically and this paper describes the application of this new tool to three data sets, each derived from a different problem area. These are measuring industrial effluent, assessing the levels of potentially harmful proteins produced by an industrial process and industrial land reclamation in the face of harmful waste materials. The use of the SRC to spot change points in time retrospectively is described. The paper also shows the use of SRC in the significant-difference testing mode, which is applied via the use of spreadsheets. Links to other similar methods described in the literature are given and formulae describing the statistical nature of the transformation are shown. These practical demonstrations illustrate that the graphical interpretation of the method appears to help considerably in practice when trying to find time-series change points. The charts are an effective graphical retrospective monitoring technique when dealing with non-normal data. The method is easy to apply and may help considerably in dealing with environmental data in the industrial setting when standard methods are not appropriate. Further work is continuing on the more theoretical aspects of the method.     

The dangers posed by saddle points,and other problems,when using central composite designs

This paper discusses two problems, which can occur when using central composite designs (CCDs), that are not generally covered in the literature but can lead to wrong decisions-and therefore incorrect models-if they are ignored. Most industrialbased experimental designs are sequential. This usually involves running as few initial tests as possible, while getting enough information as is needed to provide a reasonable approximation to reality (the screening stage). The CCD design strategy generally requires the running of a full or fractional factorial design (the cube or hypercube) with one or more additional centre points. The cube is augmented, if deemed necessary, by additional experiments known as star-points. The major problems highlighted here concern the decision to run the star points or not. If the difference between the average response at the centre of the design and the average of the cube results is significant, there is probably a need for one or more quadratic terms in the predictive model. If not, then a simpler model that includes only main effects and interactions is usually considered sufficient. This test for 'curvature' in a main effect will often fail if the design space contains or surrounds a saddle-point. Such a point may disguise the need for a quadratic term. This paper describes the occurrence of a real saddle-point from an industrial project and how this was overcome. The second problem occurs because the cube and star point portions of a CCD are sometimes run as orthogonal blocks. Indeed, theory would suggest that this is the correct procedure. However in the industrial context, where minimizing the total number of tests is at a premium, this can lead to designs with star points a long way from the cube. In such a situation, were the curvature test to be found non-significant, we could end with a model that predicted well within the cube portion of the design space but that would be unreliable in the balance of the total area of investigation. The paper discusses just such a design, one that disguised the real need for a quadratic term.