979 resultados para horned Senmurvs, roundels, trees


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Determining the ecologically relevant spatial scales for predicting species occurrences is an important concept when determining species–environment relationships. Therefore species distribution modelling should consider all ecologically relevant spatial scales. While several recent studies have addressed this problem in artificially fragmented landscapes, few studies have researched relevant ecological scales for organisms that also live in naturally fragmented landscapes. This situation is exemplified by the Australian rock-wallabies’ preference for rugged terrain and we addressed the issue of scale using the threatened brush-tailed rock-wallaby (Petrogale penicillata) in eastern Australia. We surveyed for brush-tailed rock-wallabies at 200 sites in southeast Queensland, collecting potentially influential site level and landscape level variables. We applied classification trees at either scale to capture a hierarchy of relationships between the explanatory variables and brush-tailed rock-wallaby presence/absence. Habitat complexity at the site level and geology at the landscape level were the best predictors of where we observed brush-tailed rock-wallabies. Our study showed that the distribution of the species is affected by both site scale and landscape scale factors, reinforcing the need for a multi-scale approach to understanding the relationship between a species and its environment. We demonstrate that careful design of data collection, using coarse scale spatial datasets and finer scale field data, can provide useful information for identifying the ecologically relevant scales for studying species–environment relationships. Our study highlights the need to determine patterns of environmental influence at multiple scales to conserve specialist species such as the brush-tailed rock-wallaby in naturally fragmented landscapes.

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The following paper presents an evaluation of airborne sensors for use in vegetation management in powerline corridors. Three integral stages in the management process are addressed including, the detection of trees, relative positioning with respect to the nearest powerline and vegetation height estimation. Image data, including multi-spectral and high resolution, are analyzed along with LiDAR data captured from fixed wing aircraft. Ground truth data is then used to establish the accuracy and reliability of each sensor thus providing a quantitative comparison of sensor options. Tree detection was achieved through crown delineation using a Pulse-Coupled Neural Network (PCNN) and morphologic reconstruction applied to multi-spectral imagery. Through testing it was shown to achieve a detection rate of 96%, while the accuracy in segmenting groups of trees and single trees correctly was shown to be 75%. Relative positioning using LiDAR achieved a RMSE of 1.4m and 2.1m for cross track distance and along track position respectively, while Direct Georeferencing achieved RMSE of 3.1m in both instances. The estimation of pole and tree heights measured with LiDAR had a RMSE of 0.4m and 0.9m respectively, while Stereo Matching achieved 1.5m and 2.9m. Overall a small number of poles were missed with detection rates of 98% and 95% for LiDAR and Stereo Matching.

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In Pollard v Trude [2008] QSC 119 (20 May 2008) the plaintiff claimed for personal injuries suffered when he was struck by a golf ball during the course of a tournament. The plaintiff was a member of a group of four, playing in a two-day tournament at Indooroopilly Golf Club. All four players had teed off at the second hole of the course and when the defendant took his second shot; his ball struck one of the trees bordering the fairway and deflected, hitting the plaintiff who was waiting to take his third stroke. As the ball was in flight, the defendant had called out "Watch out Errol", or words to that effect, to the plaintiff. The plaintiff suffered injury to his eye, leaving his vision impaired. The plaintiff sued in negligence, alleging that by failing to shout "fore" as is traditionally done in golf, the defendant had failed to warn the appellant and this was a breach of their duty. The claim in negligence was dismissed by the Queensland Supreme Court, holding that there had been no breach of the duty.

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Objectives: The objectives of this study were to specifically investigate the differences in culture, attitudes and social networks between Australian and Taiwanese men and women and identify the factors that predict midlife men and women’s quality of life in both countries. Methods: A stratified random sample strategy based on probability proportional sampling (PPS) was conducted to investigate 278 Australian and 398 Taiwanese midlife men and women’s quality of life. Multiple regression modelling and classification and regression trees (CARTs) were performed to examine the potential differences on culture, attitude, social networks, social demographic factors and religion/spirituality in midlife men and women’s quality of life in both Australia and Taiwan. Results: The results of this study suggest that culture involves multiple functions and interacts with attitudes, social networks and individual factors to influence a person’s quality of life. Significant relationships were found between the interaction between cultural circumstances and a person’s internal and external factors. The research found that good social support networks and a healthy optimistic disposition may significantly enhance midlife men and women’s quality of life. Conclusion: The study indicated that there is a significant relationship between culture, attitude, social networks and quality of life in midlife Australian and Taiwanese men and women. People who had higher levels of horizontal individualism and collectivism, positive attitudes and better social support had better psychological, social, physical and environmental health, while it emerged that vertical individualists with competitive characteristics would experience a lower quality of life. This study has highlighted areas where opportunities exist to further reflect upon contemporary social health policies for Australian and Taiwanese societies and also within the global perspective, in order to provide enhanced quality care for growing midlife populations.

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Habitat models are widely used in ecology, however there are relatively few studies of rare species, primarily because of a paucity of survey records and lack of robust means of assessing accuracy of modelled spatial predictions. We investigated the potential of compiled ecological data in developing habitat models for Macadamia integrifolia, a vulnerable mid-stratum tree endemic to lowland subtropical rainforests of southeast Queensland, Australia. We compared performance of two binomial models—Classification and Regression Trees (CART) and Generalised Additive Models (GAM)—with Maximum Entropy (MAXENT) models developed from (i) presence records and available absence data and (ii) developed using presence records and background data. The GAM model was the best performer across the range of evaluation measures employed, however all models were assessed as potentially useful for informing in situ conservation of M. integrifolia, A significant loss in the amount of M. integrifolia habitat has occurred (p < 0.05), with only 37% of former habitat (pre-clearing) remaining in 2003. Remnant patches are significantly smaller, have larger edge-to-area ratios and are more isolated from each other compared to pre-clearing configurations (p < 0.05). Whilst the network of suitable habitat patches is still largely intact, there are numerous smaller patches that are more isolated in the contemporary landscape compared with their connectedness before clearing. These results suggest that in situ conservation of M. integrifolia may be best achieved through a landscape approach that considers the relative contribution of small remnant habitat fragments to the species as a whole, as facilitating connectivity among the entire network of habitat patches.

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Greenhouse gas markets, where invisible gases are traded, must seem like black boxes to most people. Farmers can make money on these markets, such as the Chicago Climate Exchange, by installing methane capture technologies in animal-based systems, no-till farming, establishing grasslands, and planting trees.

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Fault tree analysis (FTA) is presented to model the reliability of a railway traction power system in this paper. First, the construction of fault tree is introduced to integrate components in traction power systems into a fault tree; then the binary decision diagram (BDD) method is used to evaluate fault trees qualitatively and quantitatively. The components contributing to the reliability of overall system are identified with their relative importance through sensitivity analysis. Finally, an AC traction power system is evaluated by the proposed methods.

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Various countries have been introducing sustainable assessment tools for real estate design to produce integrated sustainability components not just for the building, but also the landscape component of the development. This paper aims to present the comparison between international and local assessment tools of landscape design for housing estate developments in Bangkok Metropolitan Region (BMR), Thailand. The methodologies used are to review, then compare and identify discrepancy indicators among the tools. This paper will examine four international tools; LEED for Neighbourhood Development (LEED – ND) of United State of America (USA), EnviroDevelopment standards of Australia, Residential Landscape Sustainability of United Kingdom (UK) and Green Mark for Infrastructure of Singapore; and three BMR’s existing tools; Land Subdivision Act B.E. 2543, Environmental Impact Assessment Monitoring Awards (EIA-MA) and Thai’s Rating for Energy and Environmental Sustainability of New construction and major renovation (TREES-NC). The findings show that there are twenty two elements of three categories which are neighbourhood design, community management, and environmental condition. Moreover, only one element in neighbourhood designs different between the international and local tools. The sustainable assessment tools have existed in BMR but they are not complete in only one assessment tool. Thus, the development of new comprehensive assessment tool will be necessary in BMR; however, it should meet the specific environment and climate condition for housing estate development at BMR.

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Background For CAM to feature prominently in health care decision-making there is a need to expand the evidence-base and to further incorporate economic evaluation into research priorities. In a world of scarce health care resources and an emphasis on efficiency and clinical efficacy, CAM, as indeed do all other treatments, requires rigorous evaluation to be considered in budget decision-making. Methods Economic evaluation provides the tools to measure the costs and health consequences of CAM interventions and thereby inform decision making. This article offers CAM researchers an introductory framework for understanding, undertaking and disseminating economic evaluation. The types of economic evaluation available for the study of CAM are discussed, and decision modelling is introduced as a method for economic evaluation with much potential for use in CAM. Two types of decision models are introduced, decision trees and Markov models, along with a worked example of how each method is used to examine costs and health consequences. This is followed by a discussion of how this information is used by decision makers. Conclusions Undoubtedly, economic evaluation methods form an important part of health care decision making. Without formal training it can seem a daunting task to consider economic evaluation, however, multidisciplinary teams provide an opportunity for health economists, CAM practitioners and other interested researchers, to work together to further develop the economic evaluation of CAM.

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This study examined the distribution of major mosquito species and their roles in the transmission of Ross River virus (RRV) infection for coastline and inland areas in Brisbane, Australia (27°28′ S, 153°2′ E). We obtained data on the monthly counts of RRV cases in Brisbane between November 1998 and December 2001 by statistical local areas from the Queensland Department of Health and the monthly mosquito abundance from the Brisbane City Council. Correlation analysis was used to assess the pairwise relationships between mosquito density and the incidence of RRV disease. This study showed that the mosquito abundance of Aedes vigilax (Skuse), Culex annulirostris (Skuse), and Aedes vittiger (Skuse) were significantly associated with the monthly incidence of RRV in the coastline area, whereas Aedes vigilax, Culex annulirostris, and Aedes notoscriptus (Skuse) were significantly associated with the monthly incidence of RRV in the inland area. The results of the classification and regression tree (CART) analysis show that both occurrence and incidence of RRV were influenced by interactions between species in both coastal and inland regions. We found that there was an 89% chance for an occurrence of RRV if the abundance of Ae. vigifax was between 64 and 90 in the coastline region. There was an 80% chance for an occurrence of RRV if the density of Cx. annulirostris was between 53 and 74 in the inland area. The results of this study may have applications as a decision support tool in planning disease control of RRV and other mosquito-borne diseases.

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Developing safe and sustainable road systems is a common goal in all countries. Applications to assist with road asset management and crash minimization are sought universally. This paper presents a data mining methodology using decision trees for modeling the crash proneness of road segments using available road and crash attributes. The models quantify the concept of crash proneness and demonstrate that road segments with only a few crashes have more in common with non-crash roads than roads with higher crash counts. This paper also examines ways of dealing with highly unbalanced data sets encountered in the study.

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Road crashes cost world and Australian society a significant proportion of GDP, affecting productivity and causing significant suffering for communities and individuals. This paper presents a case study that generates data mining models that contribute to understanding of road crashes by allowing examination of the role of skid resistance (F60) and other road attributes in road crashes. Predictive data mining algorithms, primarily regression trees, were used to produce road segment crash count models from the road and traffic attributes of crash scenarios. The rules derived from the regression trees provide evidence of the significance of road attributes in contributing to crash, with a focus on the evaluation of skid resistance.