932 resultados para environmental problem


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Long-term systematic population monitoring data sets are rare but are essential in identifying changes in species abundance. In contrast, community groups and natural history organizations have collected many species lists. These represent a large, untapped source of information on changes in abundance but are generally considered of little value. The major problem with using species lists to detect population changes is that the amount of effort used to obtain the list is often uncontrolled and usually unknown. It has been suggested that using the number of species on the list, the "list length," can be a measure of effort. This paper significantly extends the utility of Franklin's approach using Bayesian logistic regression. We demonstrate the value of List Length Analysis to model changes in species prevalence (i.e., the proportion of lists on which the species occurs) using bird lists collected by a local bird club over 40 years around Brisbane, southeast Queensland, Australia. We estimate the magnitude and certainty of change for 269 bird species and calculate the probabilities that there have been declines and increases of given magnitudes. List Length Analysis confirmed suspected species declines and increases. This method is an important complement to systematically designed intensive monitoring schemes and provides a means of utilizing data that may otherwise be deemed useless. The results of List Length Analysis can be used for targeting species of conservation concern for listing purposes or for more intensive monitoring. While Bayesian methods are not essential for List Length Analysis, they can offer more flexibility in interrogating the data and are able to provide a range of parameters that are easy to interpret and can facilitate conservation listing and prioritization. © 2010 by the Ecological Society of America.

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It is becoming increasingly popular to consider species interactions when managing ecological foodwebs. Such an approach is useful in determining how management can affect multiple species, with either beneficial or detrimental consequences. Identifying such actions is particularly valuable in the context of conservation decision making as funding is severely limited. This paper outlines a new approach that simplifies the resource allocation problem in a two species system for a range of species interactions: independent, mutualism, predator-prey, and competitive exclusion. We assume that both species are endangered and we do not account for decisions over time. We find that optimal funding allocation is to the conservation of the species with the highest marginal gain in expected probability of survival and that, across all except mutualist interaction types, optimal conservation funding allocation differs between species. Loss in efficiency from ignoring species interactions was most severe in predator-prey systems. The funding problem we address, where an ecosystem includes multiple threatened species, will only become more commonplace as increasing numbers of species worldwide become threatened. © 2011 Elsevier B.V.

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Threatened species often exist in a small number of isolated subpopulations. Given limitations on conservation spending, managers must choose from strategies that range from managing just one subpopulation and risking all other subpopulations to managing all subpopulations equally and poorly, thereby risking the loss of all subpopulations. We took an economic approach to this problem in an effort to discover a simple rule of thumb for optimally allocating conservation effort among subpopulations. This rule was derived by maximizing the expected number of extant subpopulations remaining given n subpopulations are actually managed. We also derived a spatiotemporally optimized strategy through stochastic dynamic programming. The rule of thumb suggested that more subpopulations should be managed if the budget increases or if the cost of reducing local extinction probabilities decreases. The rule performed well against the exact optimal strategy that was the result of the stochastic dynamic program and much better than other simple strategies (e.g., always manage one extant subpopulation or half of the remaining subpopulation). We applied our approach to the allocation of funds in 2 contrasting case studies: reduction of poaching of Sumatran tigers (Panthera tigris sumatrae) and habitat acquisition for San Joaquin kit foxes (Vulpes macrotis mutica). For our estimated annual budget for Sumatran tiger management, the mean time to extinction was about 32 years. For our estimated annual management budget for kit foxes in the San Joaquin Valley, the mean time to extinction was approximately 24 years. Our framework allows managers to deal with the important question of how to allocate scarce conservation resources among subpopulations of any threatened species. © 2008 Society for Conservation Biology.

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A number of online algorithms have been developed that have small additional loss (regret) compared to the best “shifting expert”. In this model, there is a set of experts and the comparator is the best partition of the trial sequence into a small number of segments, where the expert of smallest loss is chosen in each segment. The regret is typically defined for worst-case data / loss sequences. There has been a recent surge of interest in online algorithms that combine good worst-case guarantees with much improved performance on easy data. A practically relevant class of easy data is the case when the loss of each expert is iid and the best and second best experts have a gap between their mean loss. In the full information setting, the FlipFlop algorithm by De Rooij et al. (2014) combines the best of the iid optimal Follow-The-Leader (FL) and the worst-case-safe Hedge algorithms, whereas in the bandit information case SAO by Bubeck and Slivkins (2012) competes with the iid optimal UCB and the worst-case-safe EXP3. We ask the same question for the shifting expert problem. First, we ask what are the simple and efficient algorithms for the shifting experts problem when the loss sequence in each segment is iid with respect to a fixed but unknown distribution. Second, we ask how to efficiently unite the performance of such algorithms on easy data with worst-case robustness. A particular intriguing open problem is the case when the comparator shifts within a small subset of experts from a large set under the assumption that the losses in each segment are iid.

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Staffing rural and remote schools is an important policy issue for the public good. This paper examines the private issues it also poses for teachers with families working in these communities, as they seek to reconcile careers with educational choices for children. The paper first considers historical responses to staffing rural and remote schools in Australia, and the emergence of neoliberal policy encouraging marketisation of the education sector. We report on interviews about considerations motivating household mobility with 11 teachers across regional, rural and remote communities in Queensland. Like other middle-class parents, these teachers prioritised their children’s educational opportunities over career opportunities. The analysis demonstrates how teachers in rural and remote communities constitute a special group of educational consumers with insider knowledge and unique dilemmas around school choice. Their heightened anxieties around school choice under neoliberal policy are shown to contribute to the public issue of staffing rural and remote schools.

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Changing environments pose a serious problem to current robotic systems aiming at long term operation under varying seasons or local weather conditions. This paper is built on our previous work where we propose to learn to predict the changes in an environment. Our key insight is that the occurring scene changes are in part systematic, repeatable and therefore predictable. The goal of our work is to support existing approaches to place recognition by learning how the visual appearance of an environment changes over time and by using this learned knowledge to predict its appearance under different environmental conditions. We describe the general idea of appearance change prediction (ACP) and investigate properties of our novel implementation based on vocabularies of superpixels (SP-ACP). Our previous work showed that the proposed approach significantly improves the performance of SeqSLAM and BRIEF-Gist for place recognition on a subset of the Nordland dataset under extremely different environmental conditions in summer and winter. This paper deepens the understanding of the proposed SP-ACP system and evaluates the influence of its parameters. We present the results of a large-scale experiment on the complete 10 h Nordland dataset and appearance change predictions between different combinations of seasons.

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A sizeable (and growing) proportion of the public in Western democracies deny the existence of anthropogenic climate change. It is commonly assumed that convincing deniers that climate change is real is necessary for them to act pro-environmentally. However, the likelihood of ‘conversion’ using scientific evidence is limited because these attitudes increasingly reflect ideological positions. An alternative approach is to identify outcomes of mitigation efforts that deniers find important. People have strong interests in the welfare of their society, so deniers may act in ways supporting mitigation efforts where they believe these efforts will have positive societal effects. In Study 1, climate change deniers (N D 155) intended to act more pro-environmentally where they thought climate change action would create a society where people are more considerate and caring, and where there is greater economic/technological development. Study 2 (ND347) replicated this experimentally, showing that framing climate change action as increasing consideration for others, or improving economic/technological development, led to greater pro-environmental action intentions than a frame emphasizing avoiding the risks of climate change. To motivate deniers’ pro-environmental actions, communication should focus on how mitigation efforts can promote a better society, rather than focusing on the reality of climate change and averting its risks.

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There is often a gap between teaching beliefs and actual practice, between ‘what is valued and what is taught’ (Jones, 2009, p. 175). This may be particularly true when it comes to teaching creatively and teaching for creativity in higher education. This lack of congruence is not necessarily due to a lack of awareness about what is possible, or the desire to enact change in this domain. It may, however, be due to a mix of less easily manipulated contextual factors (environmental, socio-cultural, political and economic), and a lack of discourse (Jackson, 2006) around the problem...

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GVHD remains the major complication of allo-HSCT. Murine models are the primary system used to understand GVHD, and to develop potential therapies. Several factors are critical for GVHD in these models; including histo- compatibility, conditioning regimen, and T-cell number. We serendipitously found that environmental factors such as the caging system and bedding also significantly impact the kinetics of GVHD in these models. This is important because such factors may influence the experimental conditions required to cause GVHD and how mice respond to various treatments. Consequently, this is likely to alter interpretation of results between research groups, and the perceived effectiveness of experimental therapies.

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Background The impact of socio-environmental factors on suicide has been examined in many studies. Few of them, however, have explored these associations from a spatial perspective, especially in assessing the association between meteorological factors and suicide. This study examined the association of meteorological and socio-demographic factors with suicide across small areas over different time periods. Methods Suicide, population and socio-demographic data (e.g., population of Aboriginal and Torres Strait Islanders (ATSI), and unemployment rate (UNE) at the Local Government Area (LGA) level were obtained from the Australian Bureau of Statistics for the period of 1986 to 2005. Information on meteorological factors (rainfall, temperature and humidity) was supplied by Australian Bureau of Meteorology. A Bayesian Conditional Autoregressive (CAR) Model was applied to explore the association of socio-demographic and meteorological factors with suicide across LGAs. Results In Model I (socio-demographic factors), proportion of ATSI and UNE were positively associated with suicide from 1996 to 2000 (Relative Risk (RR)ATSI = 1.0107, 95% Credible Interval (CI): 1.0062-1.0151; RRUNE = 1.0187, 95% CI: 1.0060-1.0315), and from 2001 to 2005 (RRATSI = 1.0126, 95% CI: 1.0076-1.0176; RRUNE = 1.0198, 95% CI: 1.0041-1.0354). Socio-Economic Index for Area (SEIFA) and IND, however, had negative associations with suicide between 1986 and 1990 (RRSEIFA = 0.9983, 95% CI: 0.9971-0.9995; RRATSI = 0.9914, 95% CI: 0.9848-0.9980). Model II (meteorological factors): a 1°C higher yearly mean temperature across LGAs increased the suicide rate by an average by 2.27% (95% CI: 0.73%, 3.82%) in 1996–2000, and 3.24% (95% CI: 1.26%, 5.21%) in 2001–2005. The associations between socio-demographic factors and suicide in Model III (socio-demographic and meteorological factors) were similar to those in Model I; but, there is no substantive association between climate and suicide in Model III. Conclusions Proportion of Aboriginal and Torres Strait Islanders, unemployment and temperature appeared to be statistically associated with of suicide incidence across LGAs among all selected variables, especially in recent years. The results indicated that socio-demographic factors played more important roles than meteorological factors in the spatial pattern of suicide incidence.

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The Australian water sector needs to adapt to effectively deal with the impacts of climate change on its systems. Challenges as a result of climate change include increasingly extreme occurrences of weather events including flooding and droughts (Pittock, 2011). In response to such challenges, the National Water Commission in Australia has identified the need for the water sector to transition towards being readily adaptable and able to respond to complex needs for a variety of supply and demand scenarios (National Water Commission, 2013). To successfully make this transition, the sector will need to move away from business as usual, and proactively pursue and adopt innovative approaches and technologies as a means to successfully address the impacts of climate change on the Australian water sector. In order to effectively respond to specific innovation challenges related to the sector, including climate change, it is first necessary to possess a foundational understanding about the key elements related to innovation in the sector. This paper presents this base level understanding, identifying the key barriers, drivers and enablers, and elements for innovative practise in the water sector. After initially inspecting the literature around the challenges stemming from climate change faced by the sector, the paper then examines the findings from the initial two rounds of a modified Delphi study, conducted with experts from the Australian water sector, including participants from research, government and industry backgrounds. The key barriers, drivers and enablers for innovation in the sector identified during the initial phase of the study formed the basis for the remainder of the investigation. Key elements investigated were: barriers – scepticism, regulation systems, inconsistent policy; drivers – influence of policy, resource scarcity, thought leadership; enablers – framing the problem, effective regulations, community acceptance. There is a convincing argument for the water sector transitioning to a more flexible, adaptive and responsive system in the face of challenges resulting from climate change. However, without first understanding the challenges and opportunities around making this transition, the likelihood of success is limited. For that reason, this paper takes the first step in understanding the elements surrounding innovation in the Australian water sector.

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This project investigates the integration of Information Communication Technologies (ICTs) into educational settings by closely looking at the uptake of the perceived affordances offered by ICTs by students enrolled in a French language course at Queensland University of Technology. This cross-disciplinary research uses the theoretical concepts of: Ecological Psychology (Gibson, 1979; Good, 2007; Reed, 1996); Ecological Linguistics (Greeno, 1994; Leather & van Dam, 2003; van Lier 2000, 2003, 2004a, 2004b); Design (Norman, 1988, 1999); Software Design/ Human-Computer Interaction (Hartson, 2003; McGrenere & Ho, 2000); Learning Design (Conole & Dyke, 2004a, 2004b; Laurillard et al. 2000;); Education (Kirschner, 2002; Salomon, 1993; Wijekumar et al., 2006) and Educational Psychology (Greeno, 1994). In order to investigate this subject, the following research questions, rooted in the theoretical foundations of the thesis, were formulated: (1) What are the learners’ attitudes towards the ICT tools used in the project?; (2) What are the affordances offered by ICTs used in a specific French language course at university level from the perspective of the teacher and from the perspective of language learners?; (3) What affordances offered by ICT tools used by the teacher within the specific teaching and learning environment have been taken up by learners?; and (4) What factors influence the uptake by learners of the affordances created by ICT tools used by the teacher within the specific teaching and learning environment? The teaching phase of this project, conducted between 2006 and 2008, used Action Research procedures (Hopkins, 2002; McNiff & Whitehead, 2002; van Lier 1994) as a research framework. The data were collected using the following combination of qualitative and quantitative methods: (1) questionnaires administered to students (Hopkins, 2002; McNiff & Whitehead, 2002) using Likert-scale questions, open questions, yes/no questions; (2) partnership classroom observations of research participants conducted by Research Participant Advocates (Hopkins, 2002; McNiff & Whitehead, 2002); and (3) a focus group with volunteering students who participated in the unit (semi-structured interview) (Hopkins, 2002; McNiff & Whitehead, 2002). The data analysis confirms the importance of a careful examination of the teaching and learning environment and reveals differences in the ways in which the opportunities for an action offered by the ICTs were perceived by teacher and students, which impacted on the uptake of affordances. The author applied the model of affordance, as described by Good (2007), to explain these differences and to investigate their consequences. In conclusion, the teacher-researcher considers that the discrepancies in perceiving the affordances result from the disparities between the frames of reference and the functional contexts of the teacher-researcher and students. Based on the results of the data analysis, a series of recommendations is formulated supporting calls for careful analysis of frames of reference and the functional contexts of all participants in the learning and teaching process. The author also suggests a modified model of affordance, outlining the important characteristics of its constituents.

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There is an ongoing debate about the reasons for and factors contributing to healthcare-associated infection (HAI). Different solutions have been proposed over time to control the spread of HAI, with more focus on hand hygiene than on other aspects such as preventing the aerial dissemination of bacteria. Yet, it emerges that there is a need for a more pluralistic approach to infection control; one that reflects the complexity of the systems associated with HAI and involves multidisciplinary teams including hospital doctors, infection control nurses, microbiologists, architects, and engineers with expertise in building design and facilities management. This study reviews the knowledge base on the role that environmental contamination plays in the transmission of HAI, with the aim of raising awareness regarding infection control issues that are frequently overlooked. From the discussion presented in the study, it is clear that many unknowns persist regarding aerial dissemination of bacteria, and its control via cleaning and disinfection of the clinical environment. There is a paucity of good-quality epidemiological data, making it difficult for healthcare authorities to develop evidence-based policies. Consequently, there is a strong need for carefully designed studies to determine the impact of environmental contamination on the spread of HAI.

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Pebble matrix filtration (PMF) is a water treatment technology that can remove suspended solids in highly turbid surface water during heavy storms. PMF typically uses sand and natural pebbles as filter media. Hand-made clay pebbles (balls) can be used as alternatives to natural pebbles in PMF treatment plants, where natural pebbles are not readily available. Since the high turbidity is a seasonal problem that occurs during heavy rains, the use of newly developed composite clay balls instead of pure clay balls have the advantage of removing other pollutants such as natural organic matter (NOM) during other times. Only the strength properties of composite clay balls are described here as the pollutant removal is beyond the scope of this paper. These new composite clay balls must be able to withstand dead and live loads under dry and saturated conditions in a filter assembly. Absence of a standard ball preparation process and expected strength properties of composite clay balls were the main reasons behind the present study. Five different raw materials from industry wastes: Red Mud (RM), Water Treatment Alum Sludge (S), Shredded Paper (SP), Saw Dust (SD), and Sugar Mulch (SM) were added to common clay brick mix (BM) in different proportions. In an effort to minimize costs, in this study clay balls were fired to 1100 0C at a local brick factory together with their bricks. A comprehensive experimental program was performed to evaluate crushing strength of composite hand-made clay balls, using uniaxial compression test to establish the best material combination on the basis of strength properties for designing sustainable filter media for water treatment plants. Performance at both construction and operating stages were considered by analyzing both strength properties under fully dry conditions and strength degradation after saturation in a water bath. The BM-75% as the main component produced optimum combination in terms of workability and strength. With the material combination of BM-75% and additives-25%, the use of Red Mud and water treatment sludge as additives produced the highest and lowest strength of composite clay balls, with a failure load of 5.4 kN and 1.4 kN respectively. However, this lower value of 1.4 kN is much higher than the effective load on each clay ball of 0.04 kN in a typical filter assembly (safety factor of 35), therefore, can still be used as a suitable filter material for enhanced pollutant removal.