544 resultados para ENVIRONMENTAL STATISTICS


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The paper examines whether there was an excess of deaths and the relative role of temperature and ozone in a heatwave during 7–26 February 2004 in Brisbane, Australia, a subtropical city accustomed to warm weather. The data on daily counts of deaths from cardiovascular disease and non-external causes, meteorological conditions, and air pollution in Brisbane from 1 January 2001 to 31 October 2004 were supplied by the Australian Bureau of Statistics, Australian Bureau of Meteorology, and Queensland Environmental Protection Agency, respectively. The relationship between temperature and mortality was analysed using a Poisson time series regression model with smoothing splines to control for nonlinear effects of confounding factors. The highest temperature recorded in the 2004 heatwave was 42°C compared with the highest recorded temperature of 34°C during the same periods of 2001–2003. There was a significant relationship between exposure to heat and excess deaths in the 2004 heatwave estimated increase in non-external deaths: 75 [(95% confidence interval, CI: 11–138; cardiovascular deaths: 41 (95% CI: −2 to 84)]. There was no apparent evidence of substantial short-term mortality displacement. The excess deaths were mainly attributed to temperature but exposure to ozone also contributed to these deaths.

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Environmental education is a field which has only come of age since the late nineteen sixties. While its content and practice have been widely debated and researched, its leadership has been minimally studied and, therefore, is only partially understood. The role of mentoring in the development of leaders has been alluded to, but has attracted scant research. Therefore, this study explores the importance of mentoring during the personal and professional development of leaders in environmental education. Four major research questions were investigated. Firstly, have leaders been men to red during their involvement with environmental education? Secondly, when and how has that mentoring taken place? Thirdly, what was the personal and professional effectiveness of the mentoring relationship? Fourthly, is there any continuation of the mentoring process which might be appropriate for professional development within the field of environmental education? Leaders were solicited from a broad field of environmental educators including teachers, administrators, academics, natural resource personnel, business and community persons. They had to be recognized as active leaders across several environmental education networks. The research elicited qualitative and quantitative survey data from fifty seven persons in Queensland, Australia and Colorado, USA. Seventeen semi-structured interviews were subsequently conducted with selected leaders who had nominated their mentors. This led to a further thirteen 'linked interviews' with some of the mentors' mentors and new mentorees. The interview data is presented as four cases reflecting pairs, triads, chains and webs of relationships- a major finding of the research process. The analysis of the data from the interviews and the surveys was conducted according to a grounded theory approach and was facilitated by NUD.IST, a computer program for non-numerical text analysis. The findings of the study revealed many variations on the classical mentoring patterns found in the literature. Gender and age were not seen as mportant factors, as there were examples of contemporaries in age, older men to younger women, older women to younger men, and women to women. Personal compatibility, professional respect and philosophical congruence were critical. Mentoring was initiated from early, mid and late career stages with the average length of the relationship being fourteen years. There was seldom an example of the mentoree using the mentor for hierarchical career climbing, although frequent career changes were made. However, leadership actions were found to increase after the intervention of a mentoring relationship. Three major categories of informal mentoring were revealed - perceived,acknowledged and deliberate. Further analysis led to the evolution of the core concept, a 'cascade of influence'. The major finding of this study was that this sample of leaders, mentors and new mentorees moved from the perception of having been mentored to the acknowledgment of these relationships and an affirmation of their efficacy for both personal and professional growth. Hence, the participants were more likely to continue future mentoring, not as a serendipitous happening, but through a deliberate choice. Heightened awareness and more frequent 'cascading' of mentoring have positive implications for the professional development of future leaders in environmental education in both formal and informal settings. Effective mentoring in environmental education does not seek to create 'clones' of the mentors, but rather to foster the development of autonomous mentorees who share a philosophical grounding. It is a deliberate invitation to 'join the clan'.

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This dissertation is primarily an applied statistical modelling investigation, motivated by a case study comprising real data and real questions. Theoretical questions on modelling and computation of normalization constants arose from pursuit of these data analytic questions. The essence of the thesis can be described as follows. Consider binary data observed on a two-dimensional lattice. A common problem with such data is the ambiguity of zeroes recorded. These may represent zero response given some threshold (presence) or that the threshold has not been triggered (absence). Suppose that the researcher wishes to estimate the effects of covariates on the binary responses, whilst taking into account underlying spatial variation, which is itself of some interest. This situation arises in many contexts and the dingo, cypress and toad case studies described in the motivation chapter are examples of this. Two main approaches to modelling and inference are investigated in this thesis. The first is frequentist and based on generalized linear models, with spatial variation modelled by using a block structure or by smoothing the residuals spatially. The EM algorithm can be used to obtain point estimates, coupled with bootstrapping or asymptotic MLE estimates for standard errors. The second approach is Bayesian and based on a three- or four-tier hierarchical model, comprising a logistic regression with covariates for the data layer, a binary Markov Random field (MRF) for the underlying spatial process, and suitable priors for parameters in these main models. The three-parameter autologistic model is a particular MRF of interest. Markov chain Monte Carlo (MCMC) methods comprising hybrid Metropolis/Gibbs samplers is suitable for computation in this situation. Model performance can be gauged by MCMC diagnostics. Model choice can be assessed by incorporating another tier in the modelling hierarchy. This requires evaluation of a normalization constant, a notoriously difficult problem. Difficulty with estimating the normalization constant for the MRF can be overcome by using a path integral approach, although this is a highly computationally intensive method. Different methods of estimating ratios of normalization constants (N Cs) are investigated, including importance sampling Monte Carlo (ISMC), dependent Monte Carlo based on MCMC simulations (MCMC), and reverse logistic regression (RLR). I develop an idea present though not fully developed in the literature, and propose the Integrated mean canonical statistic (IMCS) method for estimating log NC ratios for binary MRFs. The IMCS method falls within the framework of the newly identified path sampling methods of Gelman & Meng (1998) and outperforms ISMC, MCMC and RLR. It also does not rely on simplifying assumptions, such as ignoring spatio-temporal dependence in the process. A thorough investigation is made of the application of IMCS to the three-parameter Autologistic model. This work introduces background computations required for the full implementation of the four-tier model in Chapter 7. Two different extensions of the three-tier model to a four-tier version are investigated. The first extension incorporates temporal dependence in the underlying spatio-temporal process. The second extensions allows the successes and failures in the data layer to depend on time. The MCMC computational method is extended to incorporate the extra layer. A major contribution of the thesis is the development of a fully Bayesian approach to inference for these hierarchical models for the first time. Note: The author of this thesis has agreed to make it open access but invites people downloading the thesis to send her an email via the 'Contact Author' function.

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Effective environmental governance is hampered by the continuing presumption of the state as central actor in the domestic and international political contexts. Over the last 20 years, the traditional 'Westphalian' conception of the sovereign state has come under increasing pressure not only in theory, but also in practice, as evidenced by the increasing importance attributed to the participation of quasi-government and non-government actors in decision-making in domestic and international political issues. This paper is a contribution to the on-going debate about the meaning of effective environmental governance by mapping out a post-Westphalian conception of governance. In particular, it defines governance in relation to the protection of biodiversity; highlights obstacles to effective governance in this area, and discusses forming environmental management plans and environmental governance regimes to implement them. The final section of the paper suggests seven directions for ensuring the realisation of effective environmental governance.