45 resultados para Authors, Australian -- South Australia -- Biography

em University of Queensland eSpace - Australia


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The normalised difference vegetation index (NDVI) has evolved as a primary tool for monitoring continental-scale vegetation changes and interpreting the impact of short to long-term climatic events on the biosphere. The objective of this research was to assess the nature of relationships between precipitation and vegetation condition, as measured by the satellite-derived NDVI within South Australia. The correlation, timing and magnitude of the NDVI response to precipitation were examined for different vegetation formations within the State (forest, scrubland, shrubland, woodland and grassland). Results from this study indicate that there are strong relationships between precipitation and NDVI both spatially and temporally within South Australia. Differences in the timing of the NDVI response to precipitation were evident among the five vegetation formations. The most significant relationship between rainfall and NDVI was within the forest formation. Negative correlations between NDVI and precipitation events indicated that vegetation green-up is a result of seasonal patterns in precipitation. Spatial patterns in the average NDVI over the study period closely resembled the boundaries of the five classified vegetation formations within South Australia. Spatial variability within the NDVI data set over the study period differed greatly between and within the vegetation formations examined depending on the location within the state. ACRONYMS AVHRR Advanced Very High Resolution Radiometer ENVSAEnvironments of South Australia EOS Terra-Earth Observing System EVIEnhanced Vegetation Index MODIS Moderate Resolution Imaging Spectro-radiometer MVC Maximum Value Composite NDVINormalised Difference Vegetation Index NIRNear Infra-Red NOAANational Oceanic and Atmospheric Administration SPOT Systeme Pour l’Observation de la Terre. [ABSTRACT FROM AUTHOR]

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Objective: To survey the use, cost, beliefs and quality of life of users of complementary and alternative medicine (CAM). Design: A representative population survey conducted in 2004 with longitudinal comparison to similar 1993 and 2000 surveys. Participants: 3015 South Australian respondents over the age of 15 years (71.7% participation). Results: In 2004, CAMs were used by 52.2% of the population. Greatest use was in women aged 25-34 years, with higher income and education levels. CAM therapists had been visited by 26.5% of the population. In those with children, 29.9% administered CAMs to them and 17.5% of the children had visited CAM therapists. The total extrapolated cost in Australia of CAMs and CAM therapists in 2004 was AUD$1.8 billion, which was a decrease from AUD$2.3 billion in 2000. CAMs were used mostly to maintain general health. The users of CAM had lower quality-of-life scores than non-users. Among CAM users, 49.7% used conventional medicines on the same day and 57.2% did not report the use of CAMs to their doctor. About half of the respondents assumed that CAMs were independently tested by a government agency; of these, 74.8% believed they were tested for quality and safety, 21.8% for what they claimed, and 17.9% for efficacy. Conclusions: Australians continue to use high levels of CAMs and CAM therapists. The public is often unaware that CAMs are not tested by the Therapeutic Goods Administration for efficacy or safety.

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To foster ongoing international cooperation beyond ACES (APEC Cooperation for Earthquake Simulation) on the simulation of solid earth phenomena, agreement was reached to work towards establishment of a frontier international research institute for simulating the solid earth: iSERVO = International Solid Earth Research Virtual Observatory institute (http://www.iservo.edu.au). This paper outlines a key Australian contribution towards the iSERVO institute seed project, this is the construction of: (1) a typical intraplate fault system model using practical fault system data of South Australia (i.e., SA interacting fault model), which includes data management and editing, geometrical modeling and mesh generation; and (2) a finite-element based software tool, which is built on our long-term and ongoing effort to develop the R-minimum strategy based finite-element computational algorithm and software tool for modelling three-dimensional nonlinear frictional contact behavior between multiple deformable bodies with the arbitrarily-shaped contact element strategy. A numerical simulation of the SA fault system is carried out using this software tool to demonstrate its capability and our efforts towards seeding the iSERVO Institute.

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For purposes of interstate and international fruit trade, it is necessary to demonstrate that in areas in which fruit fly species have not previously established permanent populations, but which are subject to introductions of fruit flies from outside the area, the introduced population once detected, has not become established. In this paper, we apply methodology suggested mainly by Carey (1991, 1995) to introductions of Mediterranean fruit fly (Medfly), Ceratitis capitata Weid., and Queensland fruit fly (QFF) Bactrocera tryoni Froggatt (Diptera: Tephritidae) to South Australia, a state in which these species do not occur naturally and in which introductions, once detected, are actively treated. By analysing historical data associated with fruit fly outbreaks in South Australia, we demonstrate that: (i) fruit flies occur seasonally, as would occur in established populations, except there is no evidence of the critical spring generation of either species; (ii) there is no evidence of increasing frequency of outbreaks, trapped flies or larval occurrences over 29 years; (iii) there is no evidence of decreasing time between catches of adult flies as the years progress; (iv) there is no decrease in the mean number of years between outbreaks in the same locations; (v) there is no statistically significant recurrence of outbreaks in the same locations in successive years; (vi) there is no evidence of spread of outbreaks outwards from a central location; (vii) the likelihood of outbreaks in a city or town is related to the size of the human population; (viii) introduction pathways by road from Western Australia (for Medfly) and eastern Australia (for QFF) are shown to exist and to illegally or accidentally carry considerable amounts of fruit into South Australia; and (ix) there was no association between the numbers of either Queensland fruit fly or Medfly and the spatial pattern of either loquat or cumquat trees as sources of larval food in spring. This analysis supports the hypothesis that most fruit fly outbreaks in South Australia have been the result of separate introductions of infested fruit by vehicular traffic and that most of the resultant fly outbreaks were detected and died out within a few weeks of the application of eradication procedures. An alternative hypothesis, that populations of fruit flies are established in South Australia at below detectable levels, is impossible to disprove with conventional technology, but the likelihood of it being true is minimised by our analysis. Both hypotheses could be tested soon with newly developed genetic techniques.

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Demonstrating the existence of trends in monitoring data is of increasing practical importance to conservation managers wishing to preserve threatened species or reduce the impact of pest species. However, the ability to do so can be compromised if the species in question has low detectability and the true occupancy level or abundance of the species is thus obscured. Zero-inflated models that explicitly model detectability improve the ability to make sound ecological inference in such situations. In this paper we apply an occupancy model including detectability to data from the initial stages of a fox-monitoring program on the Eyre Peninsula, South Australia. We find that detectability is extremely low (< 18%) and varies according to season and the presence or absence of roadside vegetation. We show that simple methods of using monitoring data to inform management, such as plotting the raw data or performing logistic regression, fail to accurately diagnose either the status of the fox population or its trajectory over time. We use the results of the detectability model to consider how future monitoring could be redesigned to achieve efficiency gains. A wide range of monitoring programs could benefit from similar analyses, as part of an active adaptive approach to improving monitoring and management.

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The abundance and activity of the prothrombin activator (pseutarin C) within the venom of the Eastern brown snake (Pseudonaja textilis textilis) is the primary determinant of its coagulation potency. Textilinin-1, also in this venom, is a plasmin inhibitor which is thought to exert its toxic effects through the slowing of fibrinolysis. The aim of this report is to determine if there are differences in the potency of the venom from Eastern brown snakes collected from South Australia (SA) compared to those from Queensland (QLD). A concentration of 0.4 mu g/ml venom protein from six QLD specimens clotted citrated plasma in an average time of 21.4 +/- 3.3 s compared to 68.7 +/- 2.4 s for the same amount of SA venom (averaged for six individuals). The more potent procoagulant activity of the QLD venom was measured between 0.4 and 94 mu g/ml venom protein in plasma. The anti-plasmin activity of textilinin was also greater in the venom of the snakes collected from QLD, causing full inhibition of plasmin at approximately 1.88 mu g/ml of venom protein compared to approximately 7.5 mu g/ml for the SA venoms. It is concluded that geographic differentiation of the Eastern brown snakes results in significant differences venom potency.

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Objective: To determine whether mental illness is associated with accessibility and remoteness. Design: A cross-sectional, population-based, computer-assisted telephone interview survey, stratified by Accessibility and Remoteness Index of Australia (ARIA) categories. Setting: Secondary analysis of data collected from 2545 South Australian adults in October and November 2000. Outcome measures: Psychological distress and depression as determined by the Kessler 10 Psychological Distress Scale, the SF-12 measure of health status, and self-reported mental illness diagnosed by a doctor in the previous 12 months. Results: Overall, mental illness prevalence estimates were similar using the three measures of psychological distress (10.5%), clinical depression (12.9%) and self-reported mental health problem (12.7%). For each measure, there was no statistically significant variation in prevalence across ARIA categories, except for a lower than expected prevalence of depression (7.7%) in the accessible category. There was no trend suggesting higher levels of mental illness among residents of rural and remote regions. Conclusions: The prevalence rates of psychological distress, depression and self-reported mental illness are high. However, we found no evidence that the prevalence of these conditions varies substantially across ARIA categories in South Australia. This finding may challenge existing stereotypes about higher levels of mental illness outside metropolitan Australia.